student essay the disproportional impact of covid

STUDENT ESSAY The Disproportional Impact of COVID-19 on African Americans

Volume 22/2, December 2020, pp 299-307

Maritza Vasquez Reyes

Introduction

We all have been affected by the current COVID-19 pandemic. However, the impact of the pandemic and its consequences are felt differently depending on our status as individuals and as members of society. While some try to adapt to working online, homeschooling their children and ordering food via Instacart, others have no choice but to be exposed to the virus while keeping society functioning. Our different social identities and the social groups we belong to determine our inclusion within society and, by extension, our vulnerability to epidemics.

COVID-19 is killing people on a large scale. As of October 10, 2020, more than 7.7 million people across every state in the United States and its four territories had tested positive for COVID-19. According to the New York Times database, at least 213,876 people with the virus have died in the United States. [1] However, these alarming numbers give us only half of the picture; a closer look at data by different social identities (such as class, gender, age, race, and medical history) shows that minorities have been disproportionally affected by the pandemic. These minorities in the United States are not having their right to health fulfilled.

According to the World Health Organization’s report Closing the Gap in a Generation: Health Equity through Action on the Social Determinants of Health , “poor and unequal living conditions are the consequences of deeper structural conditions that together fashion the way societies are organized—poor social policies and programs, unfair economic arrangements, and bad politics.” [2] This toxic combination of factors as they play out during this time of crisis, and as early news on the effect of the COVID-19 pandemic pointed out, is disproportionately affecting African American communities in the United States. I recognize that the pandemic has had and is having devastating effects on other minorities as well, but space does not permit this essay to explore the impact on other minority groups.

Employing a human rights lens in this analysis helps us translate needs and social problems into rights, focusing our attention on the broader sociopolitical structural context as the cause of the social problems. Human rights highlight the inherent dignity and worth of all people, who are the primary rights-holders. [3] Governments (and other social actors, such as corporations) are the duty-bearers, and as such have the obligation to respect, protect, and fulfill human rights. [4] Human rights cannot be separated from the societal contexts in which they are recognized, claimed, enforced, and fulfilled. Specifically, social rights, which include the right to health, can become important tools for advancing people’s citizenship and enhancing their ability to participate as active members of society. [5] Such an understanding of social rights calls our attention to the concept of equality, which requires that we place a greater emphasis on “solidarity” and the “collective.” [6] Furthermore, in order to generate equality, solidarity, and social integration, the fulfillment of social rights is not optional. [7] In order to fulfill social integration, social policies need to reflect a commitment to respect and protect the most vulnerable individuals and to create the conditions for the fulfillment of economic and social rights for all.

Disproportional impact of COVID-19 on African Americans

As noted by Samuel Dickman et al.:

economic inequality in the US has been increasing for decades and is now among the highest in developed countries … As economic inequality in the US has deepened, so too has inequality in health. Both overall and government health spending are higher in the US than in other countries, yet inadequate insurance coverage, high-cost sharing by patients, and geographical barriers restrict access to care for many. [8]

For instance, according to the Kaiser Family Foundation, in 2018, 11.7% of African Americans in the United States had no health insurance, compared to 7.5% of whites. [9]

Prior to the Affordable Care Act—enacted into law in 2010—about 20% of African Americans were uninsured. This act helped lower the uninsured rate among nonelderly African Americans by more than one-third between 2013 and 2016, from 18.9% to 11.7%. However, even after the law’s passage, African Americans have higher uninsured rates than whites (7.5%) and Asian Americans (6.3%). [10] The uninsured are far more likely than the insured to forgo needed medical visits, tests, treatments, and medications because of cost.

As the COVID-19 virus made its way throughout the United States, testing kits were distributed equally among labs across the 50 states, without consideration of population density or actual needs for testing in those states. An opportunity to stop the spread of the virus during its early stages was missed, with serious consequences for many Americans. Although there is a dearth of race-disaggregated data on the number of people tested, the data that are available highlight African Americans’ overall lack of access to testing. For example, in Kansas, as of June 27, according to the COVID Racial Data Tracker, out of 94,780 tests, only 4,854 were from black Americans and 50,070 were from whites. However, blacks make up almost a third of the state’s COVID-19 deaths (59 of 208). And while in Illinois the total numbers of confirmed cases among blacks and whites were almost even, the test numbers show a different picture: 220,968 whites were tested, compared to only 78,650 blacks. [11]

Similarly, American Public Media reported on the COVID-19 mortality rate by race/ethnicity through July 21, 2020, including Washington, DC, and 45 states (see figure 1). These data, while showing an alarming death rate for all races, demonstrate how minorities are hit harder and how, among minority groups, the African American population in many states bears the brunt of the pandemic’s health impact.

Approximately 97.9 out of every 100,000 African Americans have died from COVID-19, a mortality rate that is a third higher than that for Latinos (64.7 per 100,000), and more than double than that for whites (46.6 per 100,000) and Asians (40.4 per 100,000). The overrepresentation of African Americans among confirmed COVID-19 cases and number of deaths underscores the fact that the coronavirus pandemic, far from being an equalizer, is amplifying or even worsening existing social inequalities tied to race, class, and access to the health care system.

Considering how African Americans and other minorities are overrepresented among those getting infected and dying from COVID-19, experts recommend that more testing be done in minority communities and that more medical services be provided. [12] Although the law requires insurers to cover testing for patients who go to their doctor’s office or who visit urgent care or emergency rooms, patients are fearful of ending up with a bill if their visit does not result in a COVID test. Furthermore, minority patients who lack insurance or are underinsured are less likely to be tested for COVID-19, even when experiencing alarming symptoms. These inequitable outcomes suggest the importance of increasing the number of testing centers and contact tracing in communities where African Americans and other minorities reside; providing testing beyond symptomatic individuals; ensuring that high-risk communities receive more health care workers; strengthening social provision programs to address the immediate needs of this population (such as food security, housing, and access to medicines); and providing financial protection for currently uninsured workers.

Social determinants of health and the pandemic’s impact on African Americans’ health outcomes

In international human rights law, the right to health is a claim to a set of social arrangements—norms, institutions, laws, and enabling environment—that can best secure the enjoyment of this right. The International Covenant on Economic, Social and Cultural Rights sets out the core provision relating to the right to health under international law (article 12). [13] The United Nations Committee on Economic, Social and Cultural Rights is the body responsible for interpreting the covenant. [14] In 2000, the committee adopted a general comment on the right to health recognizing that the right to health is closely related to and dependent on the realization of other human rights. [15] In addition, this general comment interprets the right to health as an inclusive right extending not only to timely and appropriate health care but also to the determinants of health. [16] I will reflect on four determinants of health—racism and discrimination, poverty, residential segregation, and underlying medical conditions—that have a significant impact on the health outcomes of African Americans.

Racism and discrimination

In spite of growing interest in understanding the association between the social determinants of health and health outcomes, for a long time many academics, policy makers, elected officials, and others were reluctant to identify racism as one of the root causes of racial health inequities. [17] To date, many of the studies conducted to investigate the effect of racism on health have focused mainly on interpersonal racial and ethnic discrimination, with comparatively less emphasis on investigating the health outcomes of structural racism. [18] The latter involves interconnected institutions whose linkages are historically rooted and culturally reinforced. [19] In the context of the COVID-19 pandemic, acts of discrimination are taking place in a variety of contexts (for example, social, political, and historical). In some ways, the pandemic has exposed existing racism and discrimination.

Poverty (low-wage jobs, insurance coverage, homelessness, and jails and prisons)

Data drawn from the 2018 Current Population Survey to assess the characteristics of low-income families by race and ethnicity shows that of the 7.5 million low-income families with children in the United States, 20.8% were black or African American (while their percentage of the population in 2018 was only 13.4%). [20] Low-income racial and ethnic minorities tend to live in densely populated areas and multigenerational households. These living conditions make it difficult for low-income families to take necessary precautions for their safety and the safety of their loved ones on a regular basis. [21] This fact becomes even more crucial during a pandemic.

Low-wage jobs: The types of work where people in some racial and ethnic groups are overrepresented can also contribute to their risk of getting sick with COVID-19. Nearly 40% of African American workers, more than seven million, are low-wage workers and have jobs that deny them even a single paid sick day. Workers without paid sick leave might be more likely to continue to work even when they are sick. [22] This can increase workers’ exposure to other workers who may be infected with the COVID-19 virus.

Similarly, the Centers for Disease Control has noted that many African Americans who hold low-wage but essential jobs (such as food service, public transit, and health care) are required to continue to interact with the public, despite outbreaks in their communities, which exposes them to higher risks of COVID-19 infection. According to the Centers for Disease Control, nearly a quarter of employed Hispanic and black or African American workers are employed in service industry jobs, compared to 16% of non-Hispanic whites. Blacks or African Americans make up 12% of all employed workers but account for 30% of licensed practical and licensed vocational nurses, who face significant exposure to the coronavirus. [23]

In 2018, 45% of low-wage workers relied on an employer for health insurance. This situation forces low-wage workers to continue to go to work even when they are not feeling well. Some employers allow their workers to be absent only when they test positive for COVID-19. Given the way the virus spreads, by the time a person knows they are infected, they have likely already infected many others in close contact with them both at home and at work. [24]

Homelessness : Staying home is not an option for the homeless. African Americans, despite making up just 13% of the US population, account for about 40% of the nation’s homeless population, according to the Annual Homeless Assessment Report to Congress. [25] Given that people experiencing homelessness often live in close quarters, have compromised immune systems, and are aging, they are exceptionally vulnerable to communicable diseases—including the coronavirus that causes COVID-19.

Jails and prisons : Nearly 2.2 million people are in US jails and prisons, the highest rate in the world. According to the US Bureau of Justice, in 2018, the imprisonment rate among black men was 5.8 times that of white men, while the imprisonment rate among black women was 1.8 times the rate among white women. [26] This overrepresentation of African Americans in US jails and prisons is another indicator of the social and economic inequality affecting this population.

According to the Committee on Economic, Social and Cultural Rights’ General Comment 14, “states are under the obligation to respect the right to health by, inter alia , refraining from denying or limiting equal access for all persons—including prisoners or detainees, minorities, asylum seekers and illegal immigrants—to preventive, curative, and palliative health services.” [27] Moreover, “states have an obligation to ensure medical care for prisoners at least equivalent to that available to the general population.” [28] However, there has been a very limited response to preventing transmission of the virus within detention facilities, which cannot achieve the physical distancing needed to effectively prevent the spread of COVID-19. [29]

Residential segregation

Segregation affects people’s access to healthy foods and green space. It can also increase excess exposure to pollution and environmental hazards, which in turn increases the risk for diabetes and heart and kidney diseases. [30] African Americans living in impoverished, segregated neighborhoods may live farther away from grocery stores, hospitals, and other medical facilities. [31] These and other social and economic inequalities, more so than any genetic or biological predisposition, have also led to higher rates of African Americans contracting the coronavirus. To this effect, sociologist Robert Sampson states that the coronavirus is exposing class and race-based vulnerabilities. He refers to this factor as “toxic inequality,” especially the clustering of COVID-19 cases by community, and reminds us that African Americans, even if they are at the same level of income or poverty as white Americans or Latino Americans, are much more likely to live in neighborhoods that have concentrated poverty, polluted environments, lead exposure, higher rates of incarceration, and higher rates of violence. [32]

Many of these factors lead to long-term health consequences. The pandemic is concentrating in urban areas with high population density, which are, for the most part, neighborhoods where marginalized and minority individuals live. In times of COVID-19, these concentrations place a high burden on the residents and on already stressed hospitals in these regions. Strategies most recommended to control the spread of COVID-19—social distancing and frequent hand washing—are not always practical for those who are incarcerated or for the millions who live in highly dense communities with precarious or insecure housing, poor sanitation, and limited access to clean water.

Underlying health conditions

African Americans have historically been disproportionately diagnosed with chronic diseases such as asthma, hypertension and diabetes—underlying conditions that may make COVID-19 more lethal. Perhaps there has never been a pandemic that has brought these disparities so vividly into focus.

Doctor Anthony Fauci, an immunologist who has been the director of the National Institute of Allergy and Infectious Diseases since 1984, has noted that “it is not that [African Americans] are getting infected more often. It’s that when they do get infected, their underlying medical conditions … wind them up in the ICU and ultimately give them a higher death rate.” [33]

One of the highest risk factors for COVID-19-related death among African Americans is hypertension. A recent study by Khansa Ahmad et al. analyzed the correlation between poverty and cardiovascular diseases, an indicator of why so many black lives are lost in the current health crisis. The authors note that the American health care system has not yet been able to address the higher propensity of lower socioeconomic classes to suffer from cardiovascular disease. [34] Besides having higher prevalence of chronic conditions compared to whites, African Americans experience higher death rates. These trends existed prior to COVID-19, but this pandemic has made them more visible and worrisome.

Addressing the impact of COVID-19 on African Americans: A human rights-based approach

The racially disparate death rate and socioeconomic impact of the COVID-19 pandemic and the discriminatory enforcement of pandemic-related restrictions stand in stark contrast to the United States’ commitment to eliminate all forms of racial discrimination. In 1965, the United States signed the International Convention on the Elimination of All Forms of Racial Discrimination, which it ratified in 1994. Article 2 of the convention contains fundamental obligations of state parties, which are further elaborated in articles 5, 6, and 7. [35] Article 2 of the convention stipulates that “each State Party shall take effective measures to review governmental, national and local policies, and to amend, rescind or nullify any laws and regulations which have the effect of creating or perpetuating racial discrimination wherever it exists” and that “each State Party shall prohibit and bring to an end, by all appropriate means, including legislation as required by circumstances, racial discrimination by any persons, group or organization.” [36]

Perhaps this crisis will not only greatly affect the health of our most vulnerable community members but also focus public attention on their rights and safety—or lack thereof. Disparate COVID-19 mortality rates among the African American population reflect longstanding inequalities rooted in systemic and pervasive problems in the United States (for example, racism and the inadequacy of the country’s health care system). As noted by Audrey Chapman, “the purpose of a human right is to frame public policies and private behaviors so as to protect and promote the human dignity and welfare of all members and groups within society, particularly those who are vulnerable and poor, and to effectively implement them.” [37] A deeper awareness of inequity and the role of social determinants demonstrates the importance of using right to health paradigms in response to the pandemic.

The Committee on Economic, Social and Cultural Rights has proposed some guidelines regarding states’ obligation to fulfill economic and social rights: availability, accessibility, acceptability, and quality. These four interrelated elements are essential to the right to health. They serve as a framework to evaluate states’ performance in relation to their obligation to fulfill these rights. In the context of this pandemic, it is worthwhile to raise the following questions: What can governments and nonstate actors do to avoid further marginalizing or stigmatizing this and other vulnerable populations? How can health justice and human rights-based approaches ground an effective response to the pandemic now and build a better world afterward? What can be done to ensure that responses to COVID-19 are respectful of the rights of African Americans? These questions demand targeted responses not just in treatment but also in prevention. The following are just some initial reflections:

First, we need to keep in mind that treating people with respect and human dignity is a fundamental obligation, and the first step in a health crisis. This includes the recognition of the inherent dignity of people, the right to self-determination, and equality for all individuals. A commitment to cure and prevent COVID-19 infections must be accompanied by a renewed commitment to restore justice and equity.

Second, we need to strike a balance between mitigation strategies and the protection of civil liberties, without destroying the economy and material supports of society, especially as they relate to minorities and vulnerable populations. As stated in the Siracusa Principles, “[state restrictions] are only justified when they support a legitimate aim and are: provided for by law, strictly necessary, proportionate, of limited duration, and subject to review against abusive applications.” [38] Therefore, decisions about individual and collective isolation and quarantine must follow standards of fair and equal treatment and avoid stigma and discrimination against individuals or groups. Vulnerable populations require direct consideration with regard to the development of policies that can also protect and secure their inalienable rights.

Third, long-term solutions require properly identifying and addressing the underlying obstacles to the fulfillment of the right to health, particularly as they affect the most vulnerable. For example, we need to design policies aimed at providing universal health coverage, paid family leave, and sick leave. We need to reduce food insecurity, provide housing, and ensure that our actions protect the climate. Moreover, we need to strengthen mental health and substance abuse services, since this pandemic is affecting people’s mental health and exacerbating ongoing issues with mental health and chemical dependency. As noted earlier, violations of the human rights principles of equality and nondiscrimination were already present in US society prior to the pandemic. However, the pandemic has caused “an unprecedented combination of adversities which presents a serious threat to the mental health of entire populations, and especially to groups in vulnerable situations.” [39] As Dainius Pūras has noted, “the best way to promote good mental health is to invest in protective environments in all settings.” [40] These actions should take place as we engage in thoughtful conversations that allow us to assess the situation, to plan and implement necessary interventions, and to evaluate their effectiveness.

Finally, it is important that we collect meaningful, systematic, and disaggregated data by race, age, gender, and class. Such data are useful not only for promoting public trust but for understanding the full impact of this pandemic and how different systems of inequality intersect, affecting the lived experiences of minority groups and beyond. It is also important that such data be made widely available, so as to enhance public awareness of the problem and inform interventions and public policies.

In 1966, Dr. Martin Luther King Jr. said, “Of all forms of inequality, injustice in health is the most shocking and inhuman.” [41] More than 54 years later, African Americans still suffer from injustices that are at the basis of income and health disparities. We know from previous experiences that epidemics place increased demands on scarce resources and enormous stress on social and economic systems.

A deeper understanding of the social determinants of health in the context of the current crisis, and of the role that these factors play in mediating the impact of the COVID-19 pandemic on African Americans’ health outcomes, increases our awareness of the indivisibility of all human rights and the collective dimension of the right to health. We need a more explicit equity agenda that encompasses both formal and substantive equality. [42] Besides nondiscrimination and equality, participation and accountability are equally crucial.

Unfortunately, as suggested by the limited available data, African American communities and other minorities in the United States are bearing the brunt of the current pandemic. The COVID-19 crisis has served to unmask higher vulnerabilities and exposure among people of color. A thorough reflection on how to close this gap needs to start immediately. Given that the COVID-19 pandemic is more than just a health crisis—it is disrupting and affecting every aspect of life (including family life, education, finances, and agricultural production)—it requires a multisectoral approach. We need to build stronger partnerships among the health care sector and other social and economic sectors. Working collaboratively to address the many interconnected issues that have emerged or become visible during this pandemic—particularly as they affect marginalized and vulnerable populations—offers a more effective strategy.

Moreover, as Delan Devakumar et al. have noted:

the strength of a healthcare system is inseparable from broader social systems that surround it. Health protection relies not only on a well-functioning health system with universal coverage, which the US could highly benefit from, but also on social inclusion, justice, and solidarity. In the absence of these factors, inequalities are magnified and scapegoating persists, with discrimination remaining long after. [43]

This current public health crisis demonstrates that we are all interconnected and that our well-being is contingent on that of others. A renewed and healthy society is possible only if governments and public authorities commit to reducing vulnerability and the impact of ill-health by taking steps to respect, protect, and fulfill the right to health. [44] It requires that government and nongovernment actors establish policies and programs that promote the right to health in practice. [45] It calls for a shared commitment to justice and equality for all.

Maritza Vasquez Reyes, MA, LCSW, CCM, is a PhD student and Research and Teaching Assistant at the UConn School of Social Work, University of Connecticut, Hartford, USA.

Please address correspondence to the author. Email: [email protected].

Competing interests: None declared.

Copyright © 2020 Vasquez Reyes. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

[1] “Coronavirus in the U.S.: Latest map and case count,” New York Times (October 10, 2020). Available at https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html.

[2] World Health Organization Commission on the Social Determinants of Health, Closing the gap in a generation: Health equity through action on the social determinants of health (Geneva: World Health Organization, 2008), p. 1.

[3] S. Hertel and L. Minkler, Economic rights: Conceptual, measurement, and policy issues (New York: Cambridge University Press, 2007); S. Hertel and K. Libal, Human rights in the United States: Beyond exceptionalism (Cambridge: Cambridge University Press, 2011); D. Forsythe, Human rights in international relations , 2nd edition (Cambridge: Cambridge University Press, 2006).

[4] Danish Institute for Human Rights, National action plans on business and human rights (Copenhagen: Danish Institute for Human Rights, 2014).

[5] J. R. Blau and A. Moncada, Human rights: Beyond the liberal vision (Lanham, MD: Rowman and Littlefield, 2005).

[6] J. R. Blau. “Human rights: What the United States might learn from the rest of the world and, yes, from American sociology,” Sociological Forum 31/4 (2016), pp. 1126–1139; K. G. Young and A. Sen, The future of economic and social rights (New York: Cambridge University Press, 2019).

[7] Young and Sen (see note 6).

[8] S. Dickman, D. Himmelstein, and S. Woolhandler, “Inequality and the health-care system in the USA,” Lancet , 389/10077 (2017), p. 1431.

[9] S. Artega, K. Orgera, and A. Damico, “Changes in health insurance coverage and health status by race and ethnicity, 2010–2018 since the ACA,” KFF (March 5, 2020). Available at https://www.kff.org/disparities-policy/issue-brief/changes-in-health-coverage-by-race-and-ethnicity-since-the-aca-2010-2018/.

[10] H. Sohn, “Racial and ethnic disparities in health insurance coverage: Dynamics of gaining and losing coverage over the life-course,” Population Research and Policy Review 36/2 (2017), pp. 181–201.

[11] Atlantic Monthly Group, COVID tracking project . Available at https://covidtracking.com . 

[12] “Why the African American community is being hit hard by COVID-19,” Healthline (April 13, 2020). Available at https://www.healthline.com/health-news/covid-19-affecting-people-of-color#What-can-be-done?.

[13] World Health Organization, 25 questions and answers on health and human rights (Albany: World Health Organization, 2002).

[14] Ibid; Hertel and Libal (see note 3).

[17] Z. Bailey, N. Krieger, M. Agénor et al., “Structural racism and health inequities in the USA: Evidence and interventions,” Lancet 389/10077 (2017), pp. 1453–1463.

[20] US Census. Available at https://www.census.gov/library/publications/2019/demo/p60-266.html.

[21] M. Simms, K. Fortuny, and E. Henderson, Racial and ethnic disparities among low-income families (Washington, D.C.: Urban Institute Publications, 2009).

[23] Centers for Disease Control and Prevention, Health Equity Considerations and Racial and Ethnic Minority Groups (2020). Available at https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.

[24] Artega et al. (see note 9).

[25] K. Allen, “More than 50% of homeless families are black, government report finds,” ABC News (January 22, 2020). Available at https://abcnews.go.com/US/50-homeless-families-black-government-report-finds/story?id=68433643.

[26] A. Carson, Prisoners in 2018 (US Department of Justice, 2020). Available at https://www.bjs.gov/content/pub/pdf/p18.pdf.

[27] United Nations Committee on Economic, Social and Cultural Rights, General Comment No. 14, The Right to the Highest Attainable Standard of Health, UN Doc. E/C.12/2000/4 (2000).

[28] J. J. Amon, “COVID-19 and detention,” Health and Human Rights 22/1 (2020), pp. 367–370.

[30] L. Pirtle and N. Whitney, “Racial capitalism: A fundamental cause of novel coronavirus (COVID-19) pandemic inequities in the United States,” Health Education and Behavior 47/4 (2020), pp. 504–508.

[31] Ibid; R. Sampson, “The neighborhood context of well-being,” Perspectives in Biology and Medicine 46/3 (2003), pp. S53–S64.

[32] C. Walsh, “Covid-19 targets communities of color,” Harvard Gazette (April 14, 2020). Available at https://news.harvard.edu/gazette/story/2020/04/health-care-disparities-in-the-age-of-coronavirus/.

[33] B. Lovelace Jr., “White House officials worry the coronavirus is hitting African Americans worse than others,” CNBC News (April 7, 2020). Available at https://www.cnbc.com/2020/04/07/white-house-officials-worry-the-coronavirus-is-hitting-african-americans-worse-than-others.html.

[34] K. Ahmad, E. W. Chen, U. Nazir, et al., “Regional variation in the association of poverty and heart failure mortality in the 3135 counties of the United States,” Journal of the American Heart Association 8/18 (2019).

[35] D. Desierto, “We can’t breathe: UN OHCHR experts issue joint statement and call for reparations” (EJIL Talk), Blog of the European Journal of International Law (June 5, 2020). Available at https://www.ejiltalk.org/we-cant-breathe-un-ohchr-experts-issue-joint-statement-and-call-for-reparations/.

[36] International Convention on the Elimination of All Forms of Racial Discrimination, G. A. Res. 2106 (XX) (1965), art. 2.

[37] A. Chapman, Global health, human rights and the challenge of neoliberal policies (Cambridge: Cambridge University Press, 2016), p. 17.

[38] N. Sun, “Applying Siracusa: A call for a general comment on public health emergencies,” Health and Human Rights Journal (April 23, 2020).

[39] D. Pūras, “COVID-19 and mental health: Challenges ahead demand changes,” Health and Human Rights Journal (May 14, 2020).

[41] M. Luther King Jr, “Presentation at the Second National Convention of the Medical Committee for Human Rights,” Chicago, March 25, 1966.

[42] Chapman (see note 35).

[43] D. Devakumar, G. Shannon, S. Bhopal, and I. Abubakar, “Racism and discrimination in COVID-19 responses,” Lancet 395/10231 (2020), p. 1194.

[44] World Health Organization (see note 12).

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COVID-19 and the Disproportionate Impact on Black Americans

Q&A with Enrique Neblett

Professor of health behavior and health education.

July 1, 2020

Why is the coronavirus pandemic causing Black Americans to be disproportionately affected by COVID-19 and what can we do at the individual and community level to dismantle the systemic racism at the root of these health disparities? We spoke to Enrique Neblett, professor of Health Behavior and Health Education, to learn more. 

In what ways has the Black population in the United States been uniquely affected by COVID-19?

There are a few ways in which people have talked about how Black Americans have been affected by the pandemic.

One has to do with higher rates of hospitalization, infections and mortality rates. From very early on in the pandemic, we were appalled by data that showed Black Americans disproportionately represented for these outcomes relative to their percentage of the population. 

Milwaukee and Chicago are two examples that come to mind. African Americans in these cities are about a third of the population, but represented over 70% of the deaths. Similarly, in Georgia, African Americans make up a third of the population but represented 80% of hospitalizations. Unfortunately, we see the same things here in Michigan, where African Americans are roughly 14% of the population, yet they represent 33% of the cases, and 41% of deaths.

The second area is the psychological impact of the pandemic. The Black population is among a large group of the essential workers, and many have to make tough decisions with regard to staying home if they get sick or risking lost wages—or even unemployment—in addition to situations such as having to deal with the loss of family members or taking care of family who may be sick. A recent poll found that Black Americans are nearly three times as likely to personally know someone who has died from the virus than white Americans. In some cases, we’re talking about the emotional toll of having to make excruciating decisions about whether to risk getting sick or work while sick and other financial considerations, while also coping with premature and unexpected death and loss. 

Why is COVID-19 impacting the Black population disportionately? 

There are a complex set of factors that account for why the pandemic is disproportionately affecting Black Americans, but it is important that we name structural and systemic racism as drivers of COVID-19 disparities. There was speculation early on in the pandemic about chronic underlying conditions and how some are more likely to succumb to COVID-19 when they have diabetes or other underlying conditions. Unfortunately, we know that Black Americans are more likely to have high rates of cardiovascular disease and other chronic conditions than whites, in part, due to structural inequities in access to critical resources necessary to maintain health.

Another factor is occupational vulnerability. Black Americans are more likely than white Americans to hold jobs that are essential to the function of critical infrastructure. These are jobs that require continuous interaction with the public and, in some cases, don’t offer benefits such as paid vacation or the option to work from home.

Availability and access to testing is another important factor. In the initial stages of the pandemic, there were many places where testing was limited or unavailable, or there were significant delays in processing the test results. Lack of access to adequate testing and timely results can both be liabilities in getting urgent and needed medical care.

Poverty is another social determinant of health, structured by institutional and systemic racism, that has played a role in COVID-19 disparities. Lack of access to medical care to seek treatment, quality health insurance, healthy food, standard housing, and clean water are all factors that can indirectly contribute to heightened vulnerability to exposure and infection and lead to negative COVID-19 outcomes.

It is critical that we take a close look at how racism and longstanding structural inequities and practices—past and present—shape these factors and contribute to negative COVID-19 outcomes. 

If systemic racism is the root cause of COVID-19 related and other health disparities, how do we need to work together to end it?

There are several strategies that can be mobilized in working against systemic racism and, in turn, the impact of COVID-19 on Black Americans. A multi-pronged approach must inform the action steps that we can take as individuals and communities.

Listening to one another, self-educating, reading, and learning about systemic racism and how it operates are a great start. At the individual level, I’ve also seen people using their voices and privilege to raise awareness and propose concrete actions for eradicating racism by writing op-eds, letters, and making phone calls to lawmakers. Community groups and organizations possess valuable knowledge and expertise, represent critical assets, and are also well positioned to write letters and make calls.

Other strategies for mobilizing include investing in capacity building and helping communities to build their infrastructure in order to be able to respond to disasters like COVID-19. 

I've been really fortunate in my role as associate director of the Detroit Community-Academic Urban Research Center (Detroit URC) to discuss mobilization efforts with community partners in Detroit. It’s important that we work together to share resources and information with the residents who need them most. Also, it is important to remember that eradicating racism and promoting health equity will require the execution of concrete, specific and measurable actions that will lead to lasting systemic and structural change.

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Middle School High School    |    Daily Do

What Causes the Disproportionate Impact of COVID-19 on Racial and Ethnic Minority Groups?

By Todd Campbell and Okhee Lee

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Biology Crosscutting Concepts Disciplinary Core Ideas Is Lesson Plan Life Science NGSS Phenomena Science and Engineering Practices Three-Dimensional Learning Middle School High School

Sensemaking Checklist

Teachers and families across the country are facing a new reality of providing opportunities for students to do science through distance and home learning. The Daily Do is one of the ways NSTA is supporting teachers and families with this endeavor. Each weekday, NSTA will share a sensemaking task teachers and families can use to engage their students in authentic, relevant science learning. We encourage families to make time for family science learning (science is a social process!) and are dedicated to helping students and their families find balance between learning science and the day-to-day responsibilities they have to stay healthy and safe.

Interested in learning about other ways NSTA is supporting teachers and families? Visit the NSTA homepage .

Sensemaking is actively trying to figure out how the world works (science) or how to design solutions to problems (engineering). Students do science and engineering through the science and engineering practices . Engaging in these practices necessitates that students be part of a learning community to be able to share ideas, evaluate competing ideas, give and receive critique, and reach consensus. Whether this community of learners is made up of classmates or family members, students and adults build and refine science and engineering knowledge together.

Introduction

In today’s task, students answer the following questions: What are the causes of the disproportionate impact of COVID-19 on racial and ethnic minority groups? Why is the Centers for Disease Control (CDC) and Prevention guidance for how to slow the spread of COVID-19 necessary, but insufficient? What kinds of system-level solutions can our society implement to address the disproportionate impact of COVID-19 on racial and ethnic minority groups?

Students use science and engineering practices alongside disciplinary core ideas and crosscutting concepts to identify and explain the causes of the disproportionate impact of COVID-19 on racial and ethnic minority groups. Then they consider why the CDC guidance for slowing the spread of COVID-19 is necessary, but insufficient to address the causes that have led to the disproportionate impact of COVID-19. Finally, they propose system-level solutions for addressing the disproportionate impact of COVID-19.

Today’s task builds on ideas introduced in the following Daily Dos: How Can We Make Informed Decisions to Keep Ourselves and Our Communities Safe During the COVID-19 Pandemic? by Todd Campbell and Okhee Lee, and Are There Differences in How People Are Affected by the COVID-19 Pandemic in the United States? If So, Why Are There Differences, and What Should We Do About the Disproportionate Impact of COVID-19? by Todd Campbell, Okhee Lee, Eileen Murray, and John Russell.

Daily Do Playlist: Tracking COVID-19 in the United States

What causes the disproportionate impact of COVID-19 on racial and ethnic minority groups? is a stand-alone task. However, it can be taught as part of an instructional sequence in which students are provided authentic opportunities to develop and employ the science and engineering practice Using Mathematics and Computational Thinking to make sense of the spread of COVID-19 through the U.S. population and the disproportionate number of cases and deaths in non-white communities. Students further use data to support them in identifying actions they can take to keep their families and communities safe and in implementing their proposed solutions to ending health disparities.

View Playlist

Part 1. What are the indicators of the disproportionate impact of COVID-19 on racial and ethnic minority groups? [Data Science and Critical Consciousness]

The purpose of Part 1 is to help students see the evidence for the disproportionate impact of COVID-19 on racial and ethnic minority groups. Share the accompanying Student Journal with students before you begin.

What do you notice and wonder? What questions or comments do you have? Figure 1 presents the CDC data on the disproportionate impact of COVID-19 cases, hospitalizations, and deaths by race and ethnicity on certain racial and ethnic populations in the United States.

To begin, in small groups of 2–3 or individually, students share their noticings and wonderings about Figure 1.

Note: From Risk for COVID-19 Infection, Hospitalization, and Death by Race/Ethnicity, by Centers for Disease Control and Prevention, 2021 ( https://www.cdc.gov/coronavirus/2019-ncov/covid-data/investigations-discovery/hospitalization-death-by-race-ethnicity.html ).

Next, students write the following in their journals:

• Write an argument about which racial and ethnic groups have been most affected by COVID-19.
• Provide evidence for this argument by using the data in Figure 1.

Part 2. What is the CDC guidance for slowing the spread of COVID-19? What are the scientific explanations for the CDC guidance? [Simulations/Computer Science]

The purpose of Part 2 is to help students understand the scientific explanations behind the CDC guidance for slowing the spread of COVID-19. The CDC guidance is presented at the bottom of Figure 1 and explored in more depth through the activities below.

Activity A: Wear a Mask. In this activity, students learn about the role that masks play in slowing the spread of COVID-19.

Students explore this simulation, published by Live Science: To Mask or Not to Mask: This Simulation Shows Why It’s a Good Idea to Wear a Mask . [To play the simulation, scroll down to the last video embedded in the article and click on the white arrow in the middle of the black box.] In their journals, students write a scientific explanation for how masks slow the spread of COVID-19.

Activity B: Stay 6 Feet Apart. In this activity, students learn about the role that staying 6 feet apart plays in slowing the spread of COVID-19.

Students explore this simulation, published in The Washington Post article “ Military-Grade Camera Shows Risks of Airborne Coronavirus Spread .” In their journals, students write a scientific explanation for how staying 6 feet apart slows the spread of COVID-19.

Activity C: Wash Your Hands. In this activity, students learn about the role that handwashing plays in slowing the spread of COVID-19.

Students watch the following video, available at the Health Matters website:  How Soap Suds Kill the Coronavirus .  In their journals, students write a scientific explanation for how handwashing slows the spread of COVID-19.

Part 3. What are the societal causes of the disproportionate impact of COVID-19 on racial and ethnic minority groups? How are these societal causes connected to the CDC guidance for slowing the spread of COVID-19? [Critical Consciousness]

The purpose of Part 3 is twofold. First, students recognize societal causes of the disproportionate impact of COVID-19 on racial and ethnic minority groups (e.g., individuals from certain racial and ethnic minority groups are overrepresented in the populations of essential workers and those who are incarcerated). Second, students connect these causes to challenges these groups might experience when trying to follow the CDC guidance (e.g., staying 6 feet apart).

Students read four news articles:

• Article 1. " Coronavirus Infection by Race: What’s Behind the Health Disparities? "
• Article 2. " How COVID-19 Is Highlighting Racial Disparities in Americans’ Health "
• Article 3. " In California, the Pandemic Hits Latinos Hard "
• Article 4. “ Exclusive: Indigenous Americans Dying From Covid at Twice the Rate of White Americans ”

After reading each article, students answer these questions in their journals:

• Identify the racial and ethnic minority groups referenced in the article.
• List societal causes identified in the article.
• Connect these societal causes to the CDC guidance that the identified racial and ethnic minority groups might not be able to follow.

Part 4. How does the CDC guidance for slowing COVID-19's spread (wearing a mask, staying 6 feet apart, washing your hands), which is based on science, fail to address how systemic racism is causing inequities related to COVID-19 for racial and ethnic minority groups? [Critical Conciousness]

The purpose of Part 4 is to help students recognize that while following the CDC guidance for slowing the spread of COVID-19 is essential, not all citizens are able to follow this guidance due to the impact of systemic racism in the United States, which has resulted in significant differences among racial and ethnic groups regarding employment opportunities, wages, living arrangements, access to medical care, access to running water, and incarceration rates.

Students combine what they have learned in Part 1 (to what extent racial and ethnic minority groups are disproportionately impacted by COVID-19), Part 2 (scientific explanations in the CDC guidance for slowing the spread of COVID-19), and Part 3 (societal causes that have led to the disproportionate impact of COVID-19 on racial and ethnic minority groups).

In their journals, students write an essay to answer this question:

How does the CDC guidance for slowing the spread of COVID-19 (wearing a mask, staying 6 feet apart, washing your hands), which is based on science, fail to address systemic racism that has created inequities for racial and ethnic minority groups?

Part 5. Beyond individual decision-making related to CDC guidance, what system-level solutions can our society implement to address the disproportionate impact of COVID-19 on racial and ethnic minority groups? [Critical Consciousness, Media Literacy]

The purpose of Part 5 is to help students recognize that beyond following the CDC guidance for slowing the spread of COVID-19, system-level solutions are necessary if the United States is to address the disproportionate impact of COVID-19 on racial and ethnic minority groups. While students should understand the need for individual action to slow the spread of COVID-19 in their communities, they should also understand that without equitable access to resources in society, ethnic and racial minority groups will continue to be disproportionately harmed by COVID-19.

Students watch two videos and explore a website that describe different approaches to addressing systemic racism in the United States.

• Video 1. Inside California Politics: Former Stockton Mayor, Oakland Mayor Talk Guaranteed Income for Residents
• Video 2. Biden Signs Four Executive Actions Focused on Racial Equity
• Website. Racial Equity Tools (Students select one additional system-level solution they believe could help address systemic racism.)

After each activity, students return to their journals to identify (1) what approach is proposed/implemented, (2) how this approach addresses systemic racism, and (3) how this approach could reduce the disproportionate impact of COVID-19 on racial and ethnic minority groups.

Part 6. What system-level solutions can we propose to local, state, or national leaders to address the disproportionate impact of COVID-19 on racial and ethnic minority groups? [Critical Consciousness and Civic Engagement]

Working in groups of 2–3, students propose system-level solutions to the disproportionate impact of COVID-19 on racial and ethnic minority groups and share their ideas with local, state, or national leaders.

Using the Common Cause: Find Your Representatives website, students identify a local, state, or national leader with whom to share their system-level solutions.

( Note: To identify leaders, the site asks for a local address. Students can enter their own address, or the teacher can provide the school's address. After students enter an address, national, state, and local leaders are identified and links to their homepages are provided. Each homepage contains that leader’s contact information [e.g., e-mail and mailing address]. )

Students write a letter proposing one or two approaches for mitigating the disproportionate impact of COVID-19 on racial and ethnic minority groups. Students use this resource for helpful guidance on writing a letter to political leaders: Guidelines: How to Write a Letter to a Politician .

NSTA has created a What causes the disproportionate impact of COVID-19 on racial and ethnic minority groups? collection of resources to support teachers and families using this task. If you're an NSTA member, you can add this collection to your library by clicking on Add to My Library (near top of page).

The NSTA Daily Do is an open educational resource (OER) and can be used by educators and families providing students distance and home science learning. Access the entire collection of NSTA Daily Dos .

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COVID Hurt Student Learning: Key Findings From a Year of Research

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Dozens of studies have come out over the past months concluding that the pandemic had a negative—and uneven—effect on student learning.

National analyses have shown that students who were already struggling fell further behind than their peers, and that Black and Latino students experienced greater declines in test scores than their peers.

But taken together, what implications do they have for school and district leaders looking for a path forward?

Here are four questions and answers, based on what we’ve learned from the most salient studies, that dig into the evidence.

Did students who stayed in remote learning longer fare worse than those who learned in person?

Generally, yes—but not in every single instance.

School buildings shut down in spring 2020 . By fall 2021, most students were back learning in person. But schools took a variety of different approaches in the middle, during the 2020-21 school year.

Several studies have attempted to examine the effects of the choices that districts made during that time period. And they found that students who were mostly in-person fared better than students who were mostly remote.

An analysis of 2021 spring state test data across 12 states found that districts that offered more access to in-person options saw smaller declines in math and reading scores than districts that offered less access. In reading, the effect was much larger in districts with a higher share of Black and Hispanic students.

Assessment experts, as well as the researchers, have urged caution about these results, noting that it’s hard to draw conclusions from results on spring 2021 state tests, given low rates of participation and other factors that affected how the tests were administered.

But it wasn’t just state test scores that were affected. Interim test scores—the more-frequent assessments that schools give throughout the year—saw declines too.

Another study examined scores on the Measures of Academic Progress assessment, or MAP , an interim test developed by NWEA, a nonprofit assessment provider. Researchers at NWEA, the American Institutes for Research, and Harvard examined data from 2.1 million students during the 2020-21 school year.

Students in districts that were remote during this period had lower achievement growth than students in districts that offered in-person learning. The effects were most substantial for high-poverty schools in remote learning districts.

Still, other research introduces some caveats.

The Education Recovery Scorecard, a collaboration between researchers at Stanford and Harvard, analyzed states’ scores on the 2022 National Assessment of Educational Progress. They compared these scores to the average amount of time that a district in the state spent in remote learning.

For the most part, this analysis confirmed the findings of previous research: In states where districts were remote longer, student achievement was worse. But there were also some outliers, like California. There, students saw smaller declines in math than average, even though the state had the highest closure rates on average. The researchers also noted that even among districts that spent the same amount of time in 2020-21 in remote learning, there were differences in achievement declines.

Are there other factors that could have contributed to these declines?

It’s probable. Remote learning didn’t take place in a vacuum, as educators and experts have repeatedly pointed out. But there’s not a lot of empirical evidence on this question just yet.

Children switched to virtual instruction as the pandemic unfolded around them—parents lost jobs, family members fell sick and died. In many cases, the school districts that chose remote learning served communities that also suffered some of the highest mortality rates from COVID.

The NWEA, AIR, and Harvard researchers—the group that looked at interim test data—note this. “It is possible that the relationships we have observed are not entirely causal, that family stress in the districts that remained remote both caused the decline in achievement and drove school officials to keep school buildings closed,” they wrote.

The Education Recovery Scorecard team plans to investigate the effects of other factors in future research, “such as COVID death rates, broadband connectivity, the predominant industries of employment and occupations for parents in the school district.”

Most of this data is from the 2020-21 school year. What’s happening now? Are students making progress?

They are—but it’s unevenly distributed.

NWEA, the interim assessment provider, recently analyzed test data from spring 2022 . They found that student academic progress during the 2021-22 school did start to rebound.

But even though students at both ends of the distribution are making academic progress, lower-scoring students are making gains at a slower rate than higher-scoring students.

“It’s kind of a double whammy. Lower-achieving students were harder hit in that initial phase of the pandemic, and they’re not achieving as steadily,” Karyn Lewis, the lead author of the brief, said earlier in November .

What should schools do in response? How can they know where to focus their efforts?

That depends on what your own data show—though it’s a good bet that focusing on math, especially for kids who were already struggling, is a good place to start.

Test results across the board, from the NAEP to interim assessment data, show that declines have been larger in math than in reading . And kids who were already struggling fell further behind than their peers, widening gaps with higher-achieving students.

But these sweeping analyses don’t tell individual teachers, or even districts, what their specific students need. That may look different from school to school.

“One of the things we found is that even within a district, there is variability,” Sean Reardon, a professor of poverty and inequality in education at Stanford University and a researcher on the Education Recovery Scorecard, said in a statement.

“School districts are the first line of action to help children catch up. The better they know about the patterns of learning loss, the more they’re going to be able to target their resources effectively to reduce educational inequality of opportunity and help children and communities thrive,” he said.

Experts have emphasized two main suggestions in interviews with Education Week.

• Figure out where students are. Teachers and school leaders can examine interim test data from classrooms or, for a more real-time analysis, samples of student work. These classroom-level data are more useful for targeting instruction than top-line state test results or NAEP scores, experts say.
• Districts should make sure that the students who have been disproportionately affected by pandemic disruptions are prioritized for support.

“The implication for district leaders isn’t just, ‘am I offering the right kinds of opportunities [for academic recovery]?’” Lewis said earlier this month. “But also, ‘am I offering them to the students who have been harmed most?’”

A version of this article appeared in the December 14, 2022 edition of Education Week as COVID Hurt Student Learning: Four Key Findings from A Year of Research

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Writing about COVID-19 in a college admission essay

by: Venkates Swaminathan | Updated: September 14, 2020

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For students applying to college using the CommonApp, there are several different places where students and counselors can address the pandemic’s impact. The different sections have differing goals. You must understand how to use each section for its appropriate use.

The CommonApp COVID-19 question

First, the CommonApp this year has an additional question specifically about COVID-19 :

Community disruptions such as COVID-19 and natural disasters can have deep and long-lasting impacts. If you need it, this space is yours to describe those impacts. Colleges care about the effects on your health and well-being, safety, family circumstances, future plans, and education, including access to reliable technology and quiet study spaces. Please use this space to describe how these events have impacted you.

This question seeks to understand the adversity that students may have had to face due to the pandemic, the move to online education, or the shelter-in-place rules. You don’t have to answer this question if the impact on you wasn’t particularly severe. Some examples of things students should discuss include:

• The student or a family member had COVID-19 or suffered other illnesses due to confinement during the pandemic.
• The candidate had to deal with personal or family issues, such as abusive living situations or other safety concerns
• The student suffered from a lack of internet access and other online learning challenges.
• Students who dealt with problems registering for or taking standardized tests and AP exams.

Jeff Schiffman of the Tulane University admissions office has a blog about this section. He recommends students ask themselves several questions as they go about answering this section:

• Are my experiences different from others’?
• Are there noticeable changes on my transcript?
• Am I aware of my privilege?
• Am I specific? Am I explaining rather than complaining?
• Is this information being included elsewhere on my application?

If you do answer this section, be brief and to-the-point.

Counselor recommendations and school profiles

Second, counselors will, in their counselor forms and school profiles on the CommonApp, address how the school handled the pandemic and how it might have affected students, specifically as it relates to:

• Grading scales and policies
• Graduation requirements
• Instructional methods
• Schedules and course offerings
• Testing requirements
• Your academic calendar
• Other extenuating circumstances

Students don’t have to mention these matters in their application unless something unusual happened.

Writing about COVID-19 in your main essay

Write about your experiences during the pandemic in your main college essay if your experience is personal, relevant, and the most important thing to discuss in your college admission essay. That you had to stay home and study online isn’t sufficient, as millions of other students faced the same situation. But sometimes, it can be appropriate and helpful to write about something related to the pandemic in your essay. For example:

• One student developed a website for a local comic book store. The store might not have survived without the ability for people to order comic books online. The student had a long-standing relationship with the store, and it was an institution that created a community for students who otherwise felt left out.
• One student started a YouTube channel to help other students with academic subjects he was very familiar with and began tutoring others.
• Some students used their extra time that was the result of the stay-at-home orders to take online courses pursuing topics they are genuinely interested in or developing new interests, like a foreign language or music.

Experiences like this can be good topics for the CommonApp essay as long as they reflect something genuinely important about the student. For many students whose lives have been shaped by this pandemic, it can be a critical part of their college application.

Want more? Read 6 ways to improve a college essay , What the &%$! should I write about in my college essay , and Just how important is a college admissions essay? .

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Home > Honors College > Honors Theses > 1912

Honors Theses

An analysis of the effects of covid-19 on students at the university of mississippi: family, careers, mental health.

Hannah Newbold Follow

Date of Award

Spring 5-1-2021

Document Type

Undergraduate Thesis

Integrated Marketing Communication

First Advisor

Second advisor.

Cynthia Joyce

Third Advisor

Marquita Smith

Relational Format

Dissertation/Thesis

This study analyzes the effects of COVID-19 on students at the University of Mississippi. For students, COVID-19 changed the landscape of education, with classes and jobs going online. Students who graduated in May 2020 entered a poor job market and many ended up going to graduate school instead of finding a job. Access to medical and professional help was limited at the very beginning, with offices not taking patients or moving appointments to virtual only. This would require that each student needing help had to have access to quality internet service, which wasn’t always guaranteed, thus producing additional challenges.

These chapters, including a robust literature review of relevant sources, as well as a personal essay, consist further of interviews with students and mental health counselors conducted over the span of several months. These interviews were conducted and recorded over Zoom. The interviews were conducted with individuals who traveled in similar social circles as me. These previously existing relationships allowed the conversation to go deeper than before and allowed new levels of relationship. Emerging from these conversations were six overlapping themes: the importance of family, the need for health over career, the challenge of isolation, struggles with virtual education, assessing mental health, and facing the reality of a bright future not promised. Their revelations of deep academic challenges and fears about the future amid stories of devastating personal loss, produces a striking and complex picture of emerging strength.

Recommended Citation

Newbold, Hannah, "An Analysis Of The Effects Of COVID-19 On Students At The University of Mississippi: Family, Careers, Mental Health" (2021). Honors Theses . 1912. https://egrove.olemiss.edu/hon_thesis/1912

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Disproportionate Impact of COVID-19 Pandemic on Racial and Ethnic Minorities

Affiliations.

• 1 Department of Surgery, Division of Trauma and Surgical Critical Care, 14506Kendall Regional Medical Center, Miami, FL, USA.
• 2 Department of Surgery, University of South Florida, Tampa, FL, USA.
• PMID: 33231496
• PMCID: PMC7691116
• DOI: 10.1177/0003134820973356

Background: Health disparities are prevalent in many areas of medicine. We aimed to investigate the impact of the COVID-19 pandemic on racial/ethnic groups in the United States (US) and to assess the effects of social distancing, social vulnerability metrics, and medical disparities.

Methods: A cross-sectional study was conducted utilizing data from the COVID-19 Tracking Project and the Centers for Disease Control and Prevention (CDC). Demographic data were obtained from the US Census Bureau, social vulnerability data were obtained from the CDC, social distancing data were obtained from Unacast, and medical disparities data from the Center for Medicare and Medicaid Services. A comparison of proportions by Fisher's exact test was used to evaluate differences between death rates stratified by age. Negative binomial regression analysis was used to predict COVID-19 deaths based on social distancing scores, social vulnerability metrics, and medical disparities.

Results: COVID-19 cumulative infection and death rates were higher among minority racial/ethnic groups than whites across many states. Older age was also associated with increased cumulative death rates across all racial/ethnic groups on a national level, and many minority racial/ethnic groups experienced significantly greater cumulative death rates than whites within age groups ≥ 35 years. All studied racial/ethnic groups experienced higher hospitalization rates than whites. Older persons (≥ 65 years) also experienced more COVID-19 deaths associated with comorbidities than younger individuals. Social distancing factors, several measures of social vulnerability, and select medical disparities were identified as being predictive of county-level COVID-19 deaths.

Conclusion: COVID-19 has disproportionately impacted many racial/ethnic minority communities across the country, warranting further research and intervention.

Keywords: COVID-19; health disparities; racial disparities; social determinants of health.

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• Published: 23 September 2023

Unraveling the controversial effect of Covid-19 on college students’ performance

• Luca Bonacini 1 ,
• Giovanni Gallo 2 &
• Fabrizio Patriarca 2  

Scientific Reports volume  13 , Article number:  15912 ( 2023 ) Cite this article

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• Epidemiology
• Health care economics
• Social evolution

We disentangle the channels through which Covid-19 has affected the performance of university students by setting up an econometric strategy to identify separately changes in both teaching and evaluation modes, and the short and long term effects of mobility restrictions. We exploit full and detailed information from the administrative archives of one among the first universities to be shut down since the virus spread from Wuhan. The results help solving the inconsistencies in the literature by providing evidence of a composite picture where negative effects such as those caused by the sudden shift to remote learning and by the exposure to mobility restrictions, overlap to opposite effects due to a change in evaluation methods and home confinement during the exam’s preparation. Such overlap of conflicting effects, weakening the signaling role of tertiary education, would add to the learning loss by further exacerbating future consequences on the “Covid” generation.

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Introduction.

There is a wide and varied literature stressing how the pandemic crisis has harmed the accumulation of human capital. In this article we focus on tertiary education and in particular on students’ performance. While in the case of primary and secondary education the literature converges on the emergence of a consistent learning deficit 1 , in the case of tertiary education the picture is much more controversial. To untangle the knot it is important to consider the variety of channels through which the pandemic might have affected students’ outcomes. Indeed, together with channels that affected all the population, both directly on health and indirectly through containment and lockdown measures, in the case of college education there are specific channels related to the shutdown of in presence activities as the sudden shift to remote learning, the temporary return of students to their places of origin and the change in student assessment methods that also shifted to online mode. Each channel has had impacts on different aspects of students’ careers, with different intensities and even in opposite directions. In our opinion, this composite picture helps explaining the lack of uniqueness of the evidence provided by the related literature developed so far.

Separating the overall effects between different channels requires very detailed data as to implement satisfactory econometric strategies to go beyond the identification of the overall effect based on simple comparison of pre- and post-pandemic values. For this purpose, we use the administrative data of one among the first Universities directly involved in the spread of the virus outside China: the University of Modena and Reggio Emilia. We can track between 2018 and 2021 a total of about 38,000 students, who have taken about 400,000 exams, with high-level details on the characteristics of examinations, study paths, background of students and teachers fixed effects.

By exploiting this rich dataset, we build an econometric strategy based on difference-in-differences estimations 2 to analyze the exams marks by distinguishing between the contrasting effects of the change in teaching and in assessment modes, and then consider separately the effects of exposure to lockdown measures.

On the one hand, while the transition to distance learning may have had a negative impact on learning, as confirmed by the literature on lower levels of education 3 , 4 , the need to change the assessment method may have had an opposite effect on measured performance. Indeed, since the shift to online exams made more difficult to avoid plagiarism or other misconduct 5 , this might have incentivized students to cheat. Furthermore, the exams mode itself (e.g. alone or in the classroom, with interviews or quizzes) may have affected students’ performance during the exams, and finally also teachers evaluation attitudes could have become less stringent. To solve the possible overlap of contrasting effects and correct for the possible divergent dynamics of actual and measured students’ performance, we exploit the pre-existence of courses where classes were already given, though partially, in remote mode even before the pandemic, although exams mode were the same as for the other courses. In this way we can build a difference-in-differences identification strategy exploiting the heterogeneity related to the fact that the extent shift of teaching mode has been different though the change in assessment mode has been the same.

On the other one hand, we use the information on the exam date as to take into account the effect of lockdown measures. This information allows us to build a proxy of exposure to restriction which is both time and space varying, by matching the data on the pattern of restrictions in Italian regions. Indeed, the prolonged closure of a university with a supra-regional students pool, located in an area with a relatively high cost of living, has led the majority of students to return to their homes. This led to (exogenous) different exposures to containment measures, since they had a predominantly regional character.

The results also give us a composite evidence that help us explain the puzzled results found in the literature about the effects of lockdown measures: while the overall exposure to containment measures appears to have a significant negative impact on students, being confined at home during the preparation of the exams turns out instead to have had a positive effect.

In the next sections, after a review of the related literature, we lay out a description of the case study and of the data used. Next, we present the econometric strategy and then discuss the results. Before concluding, in the final session we also perform some robustness checks.

Tertiary education and the pandemic

While the socio-economic consequences of the Covid-19 have been already studied in deep from many points of views, papers focused on the impact of the pandemic on higher education are still few and provide contradictory results. We can split this branch of literature into two groups of studies: those using pupils’ surveys 6 , 7 , 8 and those considering data on students’ actual outcomes 9 , 10 , 11 , 12 . Overall, the first ones find negative effects of the pandemic, while the second ones mostly agree on the contrary.

A pioneering contribution is provided by 6 , which surveyed approximately 1500 students at one of the largest public institutions in the United States. To our knowledge, their analysis is the first trying to get the impact of the pandemic on students’ outcomes. Results show large negative effects. Due to Covid-19, 13% of students have delayed graduation, 40% have lost a job, internship, or job offer, and 29% expect to earn less at age 35. Moreover, these effects have been highly heterogeneous: one quarter of students increased their study time by more than 4 weekly hours due to Covid-19, while another quarter decreased their study time by more than 5 h per week. This heterogeneity often followed existing socioeconomic divides. Lower-income students are 55% more likely than their higher-income peers to have delayed graduation due to Covid-19.

In the same spirit 8 , conducted an online survey on 3163 Queens College students during the summer 2020. She analyses the effect of the Covid-19 outbreak on current and expected outcomes through an estimation of individual-level subjective treatment effects. She finds that due to the pandemic, between 14 and 34% of students considered to drop-out, as they think to lose their financial assistance, or to postpone their graduation. The pandemic also deprived 39% of students of their jobs and reduced their earnings by 35%. Finally, her analysis also reveals that the effect of the pandemic on social insecurity has been different on the basis of the students’ well-being as it has been deeper for students with a federal Pell grant than their peers.

Hu et al. 7 make a contribution to the analysis on students’ self-perception as they differentiate their analysis to the previous ones asking about students’ conditions two years later since the outbreak of the pandemic, in the period between January 17 to February 25, 2022. They surveyed 151 college students in Northern Michigan asking how much their learning quality is influenced by the Covid-19 and they conclude that respondents’ education was severely affected by the pandemic, averaging a score of 7.58 on a scale of 10. These results suggest that the negative impact of Covid-19 on students’ self-perception is not limited to the short run.

Contrasting results are provided instead by the second stream of literature as in 10 , 11 , 12 . Gonzalez et al. 10 analyze the effects of Covid-19 confinement on the autonomous learning performance of students in higher education through a sort of randomized control experiment. Their study relies on a field experiment with 458 students at Universidad Autonoma de Madrid. The control group corresponds to academic years 2017/2018 and 2018/2019. The experimental group comprehends students from 2019/2020. The results show a significant positive effect of the Covid-19 confinement on students’ performance as they changed their learning strategies to a more continuous habit. Similar results hold in 11 . They estimate the effects of online education during the Covid-19 lockdown on student performance through a difference-in-differences approach using administrative data from Chinese Middle Schools. They consider three schools in the same county in Baise City before and after the Covid-19 onset. School A is the control group, as it did not provide any online educational support to its students. School B and C (treatment group) used an online platform. They point out a positive effect of online education by 0.22 of a standard deviation on student academic results. They also found that the results are homogeneous between rural and urban students.

Other contributions mainly focus on the heterogeneity of the effect across groups, but even in none of these we can find an evidence of a decrease in overall performance. Rodríguez-Planas 8 uses an event study approach to compare the gap between low-income students and their peers in the same University. She concludes that lower-income students with a lower performance during the pre-pandemic period outperformed their higher-income peers thanks to the different use of the flexible grading policy based on their financial and academic needs. In contrast, in the absence of the flexible grading policy, lower-income top-performing students would have underperformed relative to their higher-income counterparts. Engelhardt et al. 13 compare university students’ performance in the first semester affected by Covid-19 to that of the previous three ones. They do not find significant differences in performance across periods. These results are confirmed also for low-income, first-generation, and minority students. Castellanos-Serrano et al. 14 focus on the academic consequences of the Covid-19 in gender inequalities by several education performances. They consider 7477 students enrolled in just one faculty from the 2016/2017 to 2020/2021 academic years. Using a basic pre-post identification strategy, they find heterogeneous effects of the pandemic by sex since women’s results worsened in comparison to those of the pre-covid-19 period to a greater extent than for men. Besides, all sex slightly improved their results over the pandemic period. Maldonado and De Witte 15 consider the last year of primary schools in the Dutch-speaking Flemish region of Belgium. Using a 6-year panel, they perform a linear regression model with a pre-post Covid variable and find that, on average, students of the 2020 cohort experienced significant learning losses. Moreover, inequality within and across schools increased as a result of the Covid-19 crisis. Altindag et al. 16 leverage data from 15,000 students enrolled in a U.S. public university to investigate the performance of students in in-person compared to online courses during the pandemic. Using a student fixed effects model, the authors find that students in in-person courses fared better than online students with respect to their grades, the propensity to withdraw from the course, and the likelihood of receiving a passing grade. Agostinelli et al. 17 decompose the potential channels operating through the online learning, peers interactions, and the time spent with the parents. They conclude that each of these channels contribute to higher educational inequality during the pandemic.

All these studies target at the overall impact of Covid-19. Differently, Bird et al. 9 focus on the specific impact of the pandemic-triggered shift to online education. To do that they use data on students attending Virginia’s community colleges and set up an econometric strategy partially similar to that of part of our analysis: they use a difference-in-differences strategy in which the treatment groups is composed by the students enrolled in an in-person course and the control group is composed by the students which the course was provided online also before the Covid-19 widespread. Differently to the present contribution, their primary outcome of interest is the course completion, namely a binary variable equal to one whether the student received any grade sufficient (A, B, C, D, P + , or P), zero otherwise. The authors find that the shift to the online modality led to a modest decrease in course completion between 3 and 6%. This reduction in course completion is primarily driven by a large increase in course withdrawals (37% or + 2.7 percentage points in absolute terms) and, more narrowly, by an increase in course failure (10.8% or + 1.3 percentage points).

It is thus worth to notice that by focusing on a specific channel of the impact of the Covid-19 period, results shows a different picture than the one offered by the aggregate evidence. Delving deeper in this direction, in this paper we will try to solve the apparent puzzle. Our basic hypothesis is that the coexistence of negative effects reported subjectively or detected in the analysis of specific channels, together with positive effects resulting from the analysis of the overall outcomes is mainly due to the coexistence of positive effects on reported performance due to a change in evaluation standards, and negative effects on actual performance.

The case study

The case study is the University of Modena and Reggio Emilia. Unimore is a medium-sized Italian university, with a wide range of fields organized in 12 departments, ranked in the middle among Italian high education institutions, with a predominantly regional and national enrollment pool. As we will see in the econometric strategy session, this last characteristic together with the peculiarities of the relationship with pandemic events will be valuable for the purpose of the identification strategy we will use in this study. A final feature of the case study, that we will exploit in “ Econometric strategy ” section, is that a significant share of Unimore’s departments, before the pandemic, already offered degree programs where each single course provides mixed in-presence and remote classes.

At the same time, the university has recently undertaken a process of integrating all micro-data from administrative sources or interviews into a single database, Unimoredata, which enable us to analyze with a very high level of detail the performance trends of its students along the period of interest.

The pandemic at Unimore

On 21 February 2020 the Coronavirus had just begun to spread outside China and the first outbreaks of the virus were detected in the North-East of Italy. Two days later, on February 23, due to the dynamics of the virus in the neighborhood, the Emilia-Romagna Region imposed a four days closure of the activities to all the universities in its territory, thus including Unimore. This has been the first restrictive measure involving educational institutions, which will anticipate all other restrictive measures, including the first large-scale red zone, the one that the following week was imposed to the territory of the Modena province (i.e. the Italian name for the NUTS-3 region level). Indeed, since the virus spread over, the next week lessons did not turn back to in presence and the closing measures were instead extended to all Italian Universities as early as March 4, according to restrictive measures that will last until the summer.

In the Italian university system, the yearly activity is divided into two semesters, with lessons taking place from late September to December for the first semester and from late February up to the end of May in the second one. Consequently, the closure of the in-presence activities at Unimore, coincides exactly with the beginning of the second semester of the academic year 2019/2020. As a result, the shift toward remote learning at Unimore, unlike in the case of the other universities, has completely covered the semester affected by the first stage of the pandemic.

After the first wave of the virus, most Italian universities opted for solutions allowing at least a partial resumption of in-presence activities for the following semester. Unimore, instead, adopted a very restrictive policy announcing already in May 2020 that the activities would have remained in remote for all the first semester of the following academic year (i.e. 2020/2021) and that it would have been possible to attend the lessons remotely in the second semester of the following academic year independently from the evolution of the pandemic. The lessons turned back in presence only at the end of the second semester of the academic year 2020/2021and only for the first-year students. The latter decision, taken in December 2020, was driven by the fact that a second wave of Covid-19 contagions was in place during that period and a third wave was largely expected for the successive months. In Italy, to be noted, the first wave of Covid-19 contagions took roughly place from February to May 2020, the second wave from October to December 2020, and the third wave from February to April 2021.

Following the timing of the main waves of coronavirus contagions, the pandemic period can be split in three different sub-periods in the Unimore context. The first one arrives up to September 2020 and corresponds to the first wave of contagions, the complete shift of the University activities to remote mode, and to the national restrictive measures. The second period, from October 2020 to March 2021, was characterized by the fact that Unimore was still closed and lockdown measures took a regional level dimension using a four colors classification. According to this new mechanism, the tightening of restrictive measures was based on a set of indicators at the regional level—mostly related to pressures of Covid-19 contagions on the healthcare system—which distinguished white, yellow, orange and red zones.. The third period, from April 2021 onwards, was instead characterized by a partial return to in-presence activities at Unimore thanks to a progressive loosening of social distancing measures and the massive vaccination campaign.

As for the scheduling of exams, whose grades are the outcome variable we are going to consider, in line with the other Italian universities, Unimore provides three regular sessions of exams: the winter session, from the beginning of January up to the end of February; the summer session, spanning from the half of May to the end of July; and the fall session, from the end of August to the end of September. According to the specific course, there are also a number of cases where exams are held in extra-ordinary sessions (April to May and October to December). The first exams in the Covid-19 period are thus the ones in April 2020, the last exams of the first sub-period ends with the exams of the fall 2020 regular session, the second sub-period starts with the extra-ordinary sessions of October and December 2020, includes the 2021 winter session end finishes with the exams of the extraordinary session in spring 2021, the last period covers the regular sessions of summer and fall 2022.

The Unimore dataset

This study relies on Unimoredata, a database created with a specific Unimore project integrating all students’ individual information from administrative records and many large scale surveys (e.g. the Almalaurea post-degree surveys on early access to the labour market) since 2001.

Specifically, for the purpose of the presented analysis, we refer to a dataset merging together detailed information from the following administrative archives: (1) the register containing demographic characteristics of each student; (2) the archive reporting yearly information on each Unimore course attended by each student; and (3) the archive collecting all exams passed by each student attending Unimore. The latter dataset is particularly important for our analysis, as it contains full information about students’ passed exams, like the obtained mark, the date of notification, the subject, the teaching period, and teachers’ characteristics. According to the administrative data collection policies in Italian public Universities, failed exams are instead not recorded. Further investigation, however, have shown that during the pandemic the dynamics of passed exams had very a similar path to those of average exams marks which, as we will see below, have slightly increased. At same time, drop out rates increased by 2.1 percentage points, showing thus very similar patterns as those record elsewhere as in 9 .

The analysis focuses on the grades of passed exams held in the period ranging from January 2018 to September 2021, thus our reference period starts from more than two years before the pandemic and then covers all the period characterized by the first three and major waves of Covid-19. We decide to restrict the sample of analysis considering only students aged 18–36 years old. Despite students being 37 years old or more represent a clear minority group (about 2% of the sample), we choose to exclude them from the analysis because their peculiar characteristics makes overall unclear their condition during the pandemic (e.g. they may be employed in remote working or in layoff/furlough period). Due to similar reasons, we also drop from the sample those students who still haven’t held any exam one year after the standard end of the course (about 5% of the sample). We also drop the exams for which we miss information about the teacher since they correspond to courses taught by teachers who are recruited on annual contracts and thus normally change from year to year (about 9.5% of the sample). In conclusion, our analysis relies on a sample of 371.000 exams held and passed by about 38,000 students. A detailed description of all variables used in the analyses and main descriptive statistics on the sample of students are presented in the Supplementary Material (Supplementary Table S1 and Table S2 respectively).

In the second part of the analysis, we build a difference-in-differences (DID henceforth) identification strategy exploiting also the information about the courses held with mix modality of teaching. However, as the provision of such kind of courses is not common to all departments, we exclude from the sample of analysis all observations referring to departments where these course are not supplied. With this last sample restriction the second part of the analysis relies on about 230 thousand exams. Also the main descriptive statistics on this reduced sample of students are presented in the Supplementary Material (Supplementary Table S3 ).

Econometric strategy

The performance of students exams is analyzed by looking at the mark of each single exam as resulting from the administrative archives.

The benchmark model uses the following linear specification:

where \({y}_{j,i,t}\) is the mark obtained at the j exam of the student i at time t (if the student attends and passes the exam); \({X}_{i,t}\) and \({Z}_{j,t}\) are two vectors respectively of student level and exam level controls (some of them are time varying); \({m}_{t}\) is the month of the exam; \({C}_{t}\) is the dummy variable for the Covid-19 period, that is set alternatively as a single dummy or a set of dummies distinct by the 3 sub-periods outlined above, and \({\varepsilon }_{j,i,t}\) is the error term. The equation is estimated with linear OLS and errors are clustered at student level. The set of controls at student level \({X}_{i,t}\) includes: students’ demographic characteristics as gender, age, NUTS-3 region level region of birth and region of residence; the kind of upper secondary school attended before university (11 different categories); a dummy variable for being a sophomore or junior student and the number of exams already passed by the student at each exam date (i.e. proxies of students’ tenure and quality). The set of controls at the exam level \({Z}_{j,t}\) includes: the specific department of the degree program; a dummy for master degree courses (vs bachelor ones); the number of university credits (CFU) related to the exam; the exam month. To be clear, in the Italian system each exam correspond to an amount of credits varying from 3 to 12, and usually equal to 6 and 9; the greater is the number of credits the higher is the complexity and somewhat the difficulty of the exam. Formally, a CFU represents about 25 studying hours (in general assuming 7/8 h of lessons attendance and 17/18 h of ‘study at home’). A bachelor degree is generally reached after the completion of 180 CFU, while master degree courses count 120 CFU. Furthermore, we include in \({Z}_{j,t}\) also teachers individual fixed effects to account for this important source of heterogeneity, corresponding to 1160 dummy variables in the benchmark case.

In this benchmark model we thus focus on the coefficient \(\theta\) representing the overall impact of the pandemic, similarly to what most of the literature outlined above does. As we discussed above, this approach would catch the effect on measured performance rather than to actual one. Thus, once set up this base model, we move to assess an identification strategy aimed to disentangle the effect of the changing teaching (and thus learning) methodologies first, and then the effects of the exposure to restrictive measures.

Identifying the impact of (suddenly) changing teaching models

In this section we set up an econometric strategy to identify the impact of the shift from in-presence to remote learning brought about by social distancing measures. Thus, we are not going to evaluate the effectiveness of different teaching methodologies in normal times, we are instead analyzing the impact of a forced sudden shift that has also often caught unprepared teachers and technical staff.

As we have anticipated in previous sessions, possible negative effects on students’ actual performance could be overshadowed by opposing changes in measured performance related to changing examination modes. To avoid student misconduct, and in compliance with the general directives of the Italian Ministry of Education, Unimore adopted a set of arrangements to the remote examination modes that included student room control systems, software to control the activities of the personal computers used for examination tests (Safe Exam Browser), and limits to the ratio of examining students to teachers assigned to video surveillance. Such arrangements have reduced possible misbehavior however surely not eliminated it. At same time, the same shifts of exams modes with this related arrangements might have impacted on students’ performance during the exam. An analysis of the impacts on actual student performance, therefore, cannot disregard all this performance measurement problems. To this end, we will set up a DID identification strategy relying on the fact that while the shift in exams mode, with the related performance measuring biases, has equally concerned all courses, the change in teaching modalities has not been equal for all. Indeed, many Departments at Unimore, before the pandemic, already included in their supply degree programs with an hybrid online and in presence learning. In these programs all courses have only a share of teaching using traditional face to face methodology, and this share corresponds on average to the half of the course teaching activities with very little variation among courses. At same time, this courses have all same in-presence evaluation modes independently from the teaching modality. Thus, the shut off of in-presence activities had different consequences in terms of intensity in changing teaching modes among hybrid and standard courses but same consequences in terms of changes in evaluation modes and then also in performance measuring standards. In particular, we can argue without loss of generality that the impact in terms of changing teaching methodologies was double in the case of standard in-presence programs respect to hybrid ones.

We exploit this option in a DID approach by adding to the base specification in Eq. ( 1 ) the course modality variable and its interaction term with the Covid-19 variable:

where the variable \({D}_{j}\) is a dummy representing the course modality in normal times: in-presence ( \({D}_{j}=1\) ) or hybrid one. A negative sign of the interaction coefficient \(\pi\) would evidence a relatively worst performance for exams in traditional programs respect to those in hybrid ones and thus, according to the DID strategy interpretation of causal inference, supporting for a negative impact of the shift to distance teaching. Moreover, since the teaching modality shift is double for courses in standard programs respect to those in hybrid programs, in terms of magnitude we can state that the impact estimated is a lower bound estimation that should correspond to half of the actual impact.

In the sample of analysis, these hybrid courses represent around 19% of the students and the online teaching usually represent half of the classes for each exam. As students and exams could have different features in the two kind of programs, we correct for possible composition biases by using an Inverse Probability Weighting (IPW) strategy with the hybrid mode variable D as treatment variable. The IPW estimate relies on the following set of covariates: students’ demographic characteristics (i.e. gender, age, and NUTS-3 level region of birth and residence); the kind of upper secondary school; the year of enrollment; the specific department; and a dummy for master degree courses (vs bachelor ones). Finally, to properly isolate the effect of changing in teaching modes, we restrict the sample to the exams corresponding to classes taught in the immediately preceding teaching period (i.e. about 161 out of 223 thousand of exams). In fact, exams can be attended either in the months immediately following the end of classes but also in next semesters, several months after. We limit our analysis to the former case of ‘on-schedule’ exams. With this sample restriction we narrow the analysis on exams prepared by students attending courses taught according the modalities corresponding to the same specific period (before and after Covid-19 and also, in case, to the specific sub-periods). Moreover, by doing so, we can focus on exams whose preparation is more strictly related to the classes attendance rather than to the use of supplementary materials, such as handbooks or slides.

Identifying the impact of the exposure to restrictions

To identify the effect of exposure to restrictive and lockdown measures, we exploit the consequences of the very prudential policy implemented by Unimore about the recovery of normal activity described above.

As elsewhere, the closure of universities led to the return to their origin places of a large part of students being not resident in the neighborhood of the University. Suggestive is the case of Milan, where the news of the regional lockdown for the following day, circulated in advance because of a communication mistake, caused an exodus of students from North to South Italy so massive as to strongly impact on the spread of the virus in the southern regions of the Country while it was still concentrated only in the Northern regions.

During summer 2020, while Covid-19 related restrictions had been loosened by the national government, the universities were allowed to decide autonomously whether to re-start in presence activities for the next year. The decision in most campus or university cities contexts to reactivate in-presence activities, with the need to bear the cost of new infrastructure needed to respect legal prescriptions for social distancing, have also been driven by the economic interests of the neighborhood, for which the closure of the university leads to significant losses, like in the case of the owners of rental properties, commercial activities, and so on.

This was not actually the case for Unimore. In this area, the university has indeed a significant impact on its territory, but the economic vocation is another, ranging from automotive (Ferrari, Maserati, etc.) to food processing (e.g. Parmigiano Reggiano, Modena’s Balsamico), via robotics and ceramics. Moreover, the Modena city hospital, which was among those most put under pressure since the first waves of the pandemic, is part of the same university and has significant political weight even in the managerial offices (the same chancellor was a professor of the department of Medicine). As a consequence, the subjective experiences of professors and other civil servants grounded in departments operating within the Modena hospital understandably had a weight on their attitudes on the level of precautions to take.

As a result, Unimore adopted different decision respect to most universities, as the neighboring University of Bologna, which guaranteed a reopening of activities also through ad hoc investments for mixed teaching and the intervention of public institutions providing housing supports for students. Just before the end of the second semester of 2020, Unimore finally announced that the activities of the first semester of the following academic year—starting in September 2020—would have kept the distance mode. This exacerbates the emptying of the cities of Modena and Reggio Emilia, as evidenced by the attention given by the local press. Indeed, since then, also for the contribution of the very high living costs characterizing the cities of Modena and Reggio Emilia, most students returned to their homes and freshmen did not come in Modena and Reggio Emilia to find a new accommodation. This depletion is also confirmed by the fact that at the end of the second semester of the 2021/2022 academic year, when in-person attendance was reopened for a number of courses, despite the announcement made well in advance, only a minority share of students actually returned physically to the classroom while the rest continued to attend remotely. This decision did not turn out to be so wrong if one considers that the arrival of the second and third waves of the virus also induced the other universities to close down again.

At the same time, restrictive measures took a regional articulation from October 2020, following the four-color classification mentioned above. This induced a strong heterogeneity in students exposure to restrictions. The restrictions adopted in the case of red classification are similar to the lockdown implemented nationwide from March to May 2020, thus an overall home confinement. Accordingly, the time-varying restrictions in place at the residence of each student are a reliable proxy of the restrictions to which she has been subjected having a relevant time and space varying dimension. Figure  1 gives evidence of the regional heterogeneity of the cumulated restrictions from the beginning of the pandemic to September 2021, but the time-varying dimension of restrictions is relevant as well. To be noted, for the sake of the analysis, the national level lockdown imposed during the first wave of the virus, which lasted 70 days, is considered as a red zone and included on each regions’ records.

Cumulated number of days in red classified regional conditions.

We exploit this peculiarity to analyze two different aspects of the exposure to the restrictive measures. First, we consider the impact of cumulated exposition to restrictive measures since the start of pandemic. Second, we consider the effect of exposure to restrictive measures during the exam preparation period. To do all this, we add to the benchmark model in Eq. ( 1 ) one variable in two different cases. For each date of exam, in the first case we compute the cumulated number of days that the region of residence has passed under red zone restrictions while in the second one we compute the share of days in red zone over the 14 days before the exam. As we count among the days spent in a red zone also those related to the national level lockdown, when these variables still have a time-varying dimension and then allow for some heterogeneity, we can use all the data period from May 2020 onwards.

In detailing our findings, we start by providing an overall picture of students’ performance after and before the Covid-19 pandemic in Table 1 . In the first column we report estimates of the model specification presented in Eq. ( 1 ) and, in particular, the coefficient of the Covid-19 dummy variable being 1 for the whole period ranging from April 2020 to September 2021. The coefficient is positive and significant at 1% level.

In terms of magnitude, considering that exam marks at the Italian universities are expressed over 30 points with 18 being the minimum of passed exams and the standard deviation in the sample is 3.7 points, the value of 0.186 reported in the first column of Table 1 is not negligible although low. When we look at the three sub-periods of pandemic discussed in “ The pandemic at Unimore ” section separately, the coefficient is still positive and significant for each sub-period (second column of Table 1 ). The positive effect is concentrated in the first two periods of the pandemic, where the coefficient is a bit greater than 0.2. In the third period (i.e. April-September 2021), the coefficient becomes much lower but it remains still significant. The lower magnitude of the coefficient in the last period is consistent with the partial reopening of in-presence activities, which could blur the pandemic influence on the students’ performances. To account for this possible confounding factor, in the third column of Table 1 , we report the estimate of the overall impact limited to the first year of the pandemic only, thus limiting the reference period to April 2021 rather than September 2021. In this case the coefficient of the Covid-19 dummy variable has a value close to those reported in the first two sub-periods of pandemic.

In conclusion, the evidence provided in Table 1 would suggest that in relation to the sample of passed exams, students’ performance has slightly benefited from the pandemic, consistently with other studies of the literature surveyed above which use the same Covid-19 period dummy variable approach or else rely on some descriptive evidence. Our explanatory hypothesis, that we attempt to confirm in what follows, is that this unexpected outcome is mainly driven by a misalignment between the reported performance and the actual one. Indeed, because of the shut off of all in-presence activities, not only classes but also the exam evaluation shift to remote, becoming more slack. (To be clear, we are not able to assess whether these changes in the evaluation standards are due to a change in the kind of exams made—which also shifted from in-presence to remote—or to the adoption of magnanimous criteria by teachers.) This hypothesis could also fit with the partial different behavior of the last period, when time elapsed and experience cumulated could have impact on the effectiveness of assessment modes.

In what follows, we go beyond the analysis of the overall effect on reported performance to explore the two main different channels through which the pandemic may have negatively impacted actual performances: the sudden shift to remote teaching and the home confinement.

The impact of (suddenly) changing teaching models

Table 2 shows the estimation results of the model specification presented in Eq. ( 2 ) and corresponding to the identification strategy outlined in “ Identifying the impact of (suddenly) changing teaching models ” section. This strategy is aimed at disentangling the effect of the sudden shift to remote teaching on students’ performances. To do that, as anticipated in “ Identifying the impact of (suddenly) changing teaching models ” section, we first restrict the sample to the departments having both in-presence and hybrid courses (see “ The Unimore dataset ” section), then consider only the exams corresponding to classes taught in the immediately preceding teaching period, and then estimate the IPW weights using the course modality as treatment variable.

Column 1, 3 and 5 of Table 2 presents the same base model shown in the previous section restricted to departments providing at least one hybrid course and with the addition of a control variable for the course modality (1 if in-person and 0 otherwise) and using the IPW correction (see Supplementary Table S4 for the first stage estimations). To be noted, Supplementary Table S5 , which is the equivalent of Table 1 in the subsample used in this IPW case, highlights that the pandemic-related coefficient does not change much with respect to the one presented in Table 1 . This evidence confirms that the sample restrictions here adopted, as well as the bias on the coefficient of variables not related to the IPW treatment variable due the application of the IPW correction, does not affect significantly our results. In column 2, 4 and 6 of the same table we use the DID specification presented in “ Identifying the impact of (suddenly) changing teaching models ” section.

In the baseline case, exam marks of students attending in-presence courses are lower if compared to those reported by students attending hybrid courses. When we consider the DID model which adds the interaction term, however, the effect of attending in-presence courses is not significant anymore while the coefficient of the interaction term is negative and strongly significant. Columns 3 and 4 of Table 2 present the same analysis shown in Columns 1 and 2 limiting the reference period to the first year of pandemic (i.e. up to May 2021), thus focusing on the period during which all classes were attended remotely. Clearly, in this case, the magnitude of the interaction term is much larger than before (1.0 vs 0.6 points), as well as the one of the Covid-19 dummy (1.2 vs 0.3 points).

Summing up, the hypothesis according to which the sudden shift to remote teaching had negatively affected students’ performance finds evidence in our results. As hybrid courses generally have half of lessons in presence, we can estimate the total impact of the change in teaching modality by doubling the coefficient of the interaction term, and thus obtaining a value of about 2 points out of 30. To better understand the extent of the estimated effect related to the pandemic, it should be considered that this value represents more than half of the standard deviation of exam marks and 6.6% of the overall marks range. Our estimated value of the losses related to the shift to remote teaching is close to the upper threshold of the results provided by 9 although obtained with different econometric set-up, unit level analysis, performance outcome and in a case study of another country (US vs Italy).

At same time we also confirm the hypothesis that changes in assessment modes are prominent drivers of the increase in student reported outcomes evidenced in the literature. This effect has offset the negative impact of the pandemic period misaligning the effective performance of students from the measured one. Indeed, when we shift from the base to the DID specifications the coefficient of the Covid-19 variable increases substantially and to an extent close to the absolute value of the coefficients of the interactions included.

The impact of the exposure to restrictions

We move now to the analysis of the impact of the exposure to mobility restrictions on students’ performances described in “ Identifying the impact of the exposure to restrictions ” section. To do this purpose, we slightly restricts the sample of the benchmark case (see Table 1 ) as we exclude the exams held by students who are not resident in Italy (they represent less than 2% of the full sample of exams). The second column of Table 3 adds to the base model—whose results are reported in column 1—the overall number of days each student spent under red zone restrictions, while the third column adds the variable reporting the share of days spent under red zone restrictions over the 14 days before the exam. As explained above, in the former case we focus on the cumulated impact of restrictions, while in the latter we assess the impact of being confined at home in the days just before the exam’s session, corresponding to the period of exams’ preparation.

Table 3 highlights that the number of days spent under red zone restrictions decreases the exam marks. One day more spent under lockdown restrictions corresponds to a reduction of 0.003 points. Considering that at the end of the reference period the average value of this variable is 105 days, we can estimate the average effect on students’ exam marks at the end of the pandemic to be about one third of point. At same time, as also in the previous section, when we take into account this negatively impacting channel, the estimated coefficient of the Covid-19 dummy increases.

While the results shows a negative long run effect of home confinement, that can be ascribed to mental stress issues, when we look at the effect in the short run, things substantially change. Our results show that a greater number of days spent under red zone restrictions during the two weeks preceding the exam (i.e. probably those on which the preparation to the exam is mainly concentrated) engenders an increase of students’ exam marks. In this case, the Covid-19 dummy coefficient does not report any relevant variation, confirming the change of examination modality to represent the main explanation of the positive impact on measured performance.

In conclusion, the results of our analysis suggest a composite effect of mobility restrictions. On the one hand, consistently with the results provided by 6 , they might have increased the amount of time allocated to study for exams thus improving performances in the short run. On the one other hand, however, in the long run the protracted exposure to the restrictions clearly reduced the students’ outcomes.

Robustness checks

In this session we present two different robustness checks, one for each of the two channels we considered in main analysis: the change in teaching modalities and the exposure to mobility restrictions.

As for the change in teaching methods, we perform a placebo test analysis. Instead of restricting the sample to on-schedule exams only, we consider the other exams: those made during the pandemic but related to courses attended in the pre-Covid-19 semesters. This test should therefore be considered as valid if two conditions hold. The first one is that the coefficients of the baseline model of the Covid variables are still positive and significant. This would confirm the increase in exams grade is due to the change in exams modality and not to change in teaching modes. The second condition requires that in the DID specification the coefficients of the interaction term between the Covid-19 dummy and the in-presence course one are found to be insignificant or to have very small magnitude. Results of the placebo test, presented in Table 4 , confirm the robustness of our results. In fact, while in the baseline model the coefficients of the covid variables confirm the baseline specification results, the coefficients of the interaction terms in the DID specification are always insignificant and their magnitude is strongly reduced if not even with opposite sign if compared to those reported in Table 2 .

As for the effect of restrictions on students’ performances, one possible weakness of our strategy is the fact that some students may not have returned back to their households and thus the restrictions in place in the region of origin may not correspond to the actual restrictions to which these students where subject to. This would affect our estimates but only partially since in the first stage of pandemic, the variables of interest have only a time variation, not spatial, because restrictions had national dimension. As to the following period, the option of not coming back home does not apply to freshmen students since the decision to keep university activities in remote mode for all the first semester, and to allow in any case to attend classes in remote for all the rest of the year, was communicated well before the opening of course registration. Besides, for the same reasons the case of not coming back home even after the first Covid-19 wave is less likely to have occurred for non-freshmen students because of the rent costs that could be saved. To be noted, house rent costs in Modena and Reggio Emilia are indeed particularly high if compared to other university cities as recorded by the yearly official statistics on living costs performed by the Italian Institute of Statistics, which places the two cities among the highest in Italy for living costs. Finally, it is likely that the climate of fear and concern that had spread in the early stages of the pandemic pushed most of people returning to their household of origin just before the end of the first national lockdown in May 2020 independently from the high economic incentives.

Anyway, to account for this possible source of bias we perform a sensitivity analysis by restricting the sample to students resident out of the Modena and Reggio Emilia provinces. We consider only students who faced the same decisions about where to spend the periods of suspension of university in-person activities, thus the bias would affect randomly all kind of students. Table 5 highlights that the coefficients of variables regarding the effect of restrictive measures do not change substantially with respect to those reported in Table 3 , overall confirming the robustness of our main results.

In the Supplementary Material we also report a heterogeneity analysis of our main results (i.e. those in Table 1 and Table 2 ) to assess whether they present any relevant change when distinguishing departments by ERC sector or teachers by age group (aged 59 or younger vs aged 60 or older). Specifically, Supplementary Table S6 and Table S8 show the heterogeneity of the Covid-19 impact on students’ exam marks by ERC sectors, while Supplementary Table S7 and Table S9 do the same by teachers’ age group.

Supplementary Table S6 points out that coefficients in the first column and the last column always have the same statistically significance and direction. As for the magnitude, departments in the Life Sciences sector (e.g. Medicine and Nursing) seem the most affected by Covid-19, while coefficients of Social Sciences and Humanities and STEM sectors are very similar each other. These results are overall confirmed in the analysis by pandemic period with the exception of Social Sciences and Humanities departments, where the coefficient for the Covid III period is positive but insignificant (in line with results in Table 2 though). Moreover, while the in-presence students appear to have different performances by ERC sector, Supplementary Table S8 highlights that the Covid-19 effect related to the change of teaching modality is negative and significant in all departments except for those in Life Sciences. As for the heterogeneous effects by teachers’ age group, Supplementary Table S7 shows that coefficients are very similar, then suggesting that older teachers have not behaved differently from others. Nonetheless, the DID analysis in Supplementary Table S9 points out a heterogeneous causal effect of Covid-19, which is significant only for the subgroup of older teachers when considering the full period (column 2). This evidence seems to suggest that teachers’ reaction to pandemic-related changes was similar during the first year of pandemic, but the effect has lasted longer among older teachers. All in all, they were more vulnerable to the COVID disease and probably have had a harder time to adapt to the online modality.

Finally, Supplementary Table S10 presents a robustness check on the overall effect of the time spent in a regional red zone during the two weeks preceding the exam (see Table 3 ). First, we provide an estimation where Covid-19 period dummies are included. Second, we provide an estimation focusing on the first year of pandemic only, to assess whether the effect estimated for the full period is stable or not over time. Supplementary Table S10 clearly shows that the effect of the variable of interest here is slightly lower than the one presented in Table 3 (differences are not significant at 10 percent level though), but still strongly positive and significant. This evidence confirms the effect of being forced at home during the two weeks before the exam is actually quite stable over the analyzed period.

Conclusions

In this study, we have focused on the effect of the pandemic on the performance of university students. By exploiting the opportunities provided by an administrative dataset containing very detailed information on the University of Modena and Reggio Emilia (Unimore), one of the forerunners of the restrictions imposed worldwide to universities during Covid-19 early stages, we have tried to solve some inconsistencies in the literature and to unbundle the two main channels through which the pandemic changed university students’ pathways: the shift to remote lessons and the exposure to lockdown measures.

On the one hand, the results of the DID estimations based on the distinction between full in-presence programs and hybrid ones suggests a mismatch between actual performance and measured performance related to the change in assessment methods and/or parameters. In the standard design that uses the Covid-19 period as treatment, the evidence is that of an overall albeit slight improvement in average marks: in the context of a grading system with marks expressed in thirtieths, with 18 as the minimum grade of passed exams and a variance of 3.6, during the pandemic the score of passed the exams increased by one sixth of point, a result substantially in line with that of the literature which also shows slightly positive overall effects in a number of different outcomes of students’ performance. Besides, to a more detailed insight, the pandemic still appears to have had negative effects on student performance. The evidence gathered allows us to estimate the impact of the sudden change in lecture modes in nearly two thirtieths. This result is in line with the literature focusing on specific aspects of the Covid-19 impact and also coherent with the studies on students’ subjective evaluations. Despite this channel seems to have been more relevant, also the psychological effects due to exposure to lockdown measures result as significant: at the end of the period considered, the cumulative impact of exposure to home confinement amounting to about one third of point. At the same time, being confined at home in the two weeks prior to the examination date appears to have had a positive impact: being forced to stay at home during all the two weeks before the exams increase the average grade by nearly one sixth of point. Nonetheless, the driver of the overall positive effect on students’ grades seems to be the change in evaluation standard, that result in having increased student grades by a value in the range of 2–2.5 thirtieths.

As a result, if we look at the effect on student’s actual performance, and thus on their process of human capital accumulation, we can support the evidence of an appreciable negative impact that has been, however, offset on the surface by an average more slack assessment systems. This gives rise to two different kind of problems. The first concerns the most well-known and direct aspect: the loss in terms of human capital accumulation, a significant loss that might have long-term effects. There is however also a further aspect. This generation of students will turn out to be less prepared compared to the others, regardless their similar average marks. This, over time, could produce a stigma effect by fostering a widespread perception that those who studied in the pandemic years are less capable if compared with other ones with same degree or marks. While this may be true for some, in particular for those who have benefited most from the different assessment modes, it is not true for all. Anyway, the signaling role of their degree on job applicants would be weakened. This could result in a process of statistical discrimination: an efficient practice for those who implement it, the employers, but as unfair for an already hard-hit generation of students.

Data availability

The datasets generated and analyzed during the current study uses the information coming from the administrative archives of the University of Modena and Reggio Emilia. They are not publicly available due restrictions related to data ownership but they are available together with all do files from the corresponding author on reasonable request by remote connection to a dedicated server. The research did not rely on any kind of experiments on humans and/or the use of human tissue samples. The whole research was performed in accordance with relevant guidelines/regulations, in particular with all requirements imposed by the Italian Data Protection Authority (GDPR) in its November 27, 2008 Requirements (Gazzetta Ufficiale No. 300, December 24, 2008) and subsequent and possible adjustments and amendments. In compliance with Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016, Legislative Decrees August 10, 2018 No. 101 and May 18, 2018 No. 51 of the Italian Government, the study did not required ethics approval and/or individual consent of the involved persons (the students of Unimore), who, in any case, at the time of matriculation at Unimore were informed about the processing of personal data also for purposes that respond to and are aimed at implementing the exercise of institutional powers vested in the university, including research.

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Bonacini, L., Gallo, G. & Patriarca, F. Unraveling the controversial effect of Covid-19 on college students’ performance. Sci Rep 13 , 15912 (2023). https://doi.org/10.1038/s41598-023-42814-7

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DOI : https://doi.org/10.1038/s41598-023-42814-7

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• v.16(2); 2024 Feb
• PMC10859553

Effects of the COVID-19 Pandemic on University Students' Mental Health: A Literature Review

Beatta zarowski.

1 Research, Oceania University of Medicine, Pago Pago, WSM

Demetrios Giokaris

2 Internal Medicine, Procare Med, Northbrook, USA

3 Mental Health, Procare Med, Northbrook, USA

This review aims to focus on the effects of COVID-19 on university students' mental health and deepen our understanding of it. The conclusions are based on the review of 32 studies conducted during the pandemic. This review confirms that university students were at high risk for mental health disorders, heightened stress, and increased sleep comorbidities both pre-pandemic and during the pandemic. This literature review confirmed a few universal trends, i.e., increased stress, anxiety, and depression, during the pandemic. The rates of insomnia, obsessive-compulsive disorder, and suicidal ideation also went up. Overall, female students are at a disadvantage in the development of mental health issues. Male students coped better but may be at higher risk for lethality in suicidal ideation. Students with a history of mental health issues and other comorbidities prior to the pandemic had worse outcomes compared to healthy individuals. The study points to a strong positive correlation between fear and increased rates of stress, anxiety, and insomnia. There is also a positive correlation between declining mental health and online learning. A strong negative correlation was present between physical activity and depressive symptoms. These findings are universal across many countries and regions where the studies occurred.

Introduction and background

The COVID-19 pandemic began in March 2020 and profoundly impacted university students' mental, emotional, academic, social, and other aspects of life. Mid-pandemic studies [ 1 - 5 ] and pre-pandemic publications, including 2017 WHO mental health estimates, place university students at high risk for mental health dysfunction, with a higher prevalence of psychiatric morbidity compared to the general global population, with 4.4% for anxiety and 3.6% for depression [ 5 ]. Unexpected and sudden restrictions, isolation policies, and lockdowns in many countries were meant to protect communities and society at large but had a lot of unintended negative consequences. This review aims to present evidence of the disruptive trends uniquely amplified globally within the university student population and identified in the literature published in 2020-2023 on this topic. The review will analyze 32 peer-reviewed sources focusing on the pandemic's mental, psychological, academic, social, and other effects on university students.

Methodology

This literature review utilized several scientific literature databases, including Science Direct, Google Scholar, Web of Science, and PubMed, to identify articles that include the search criteria, such as those related to the prevalence of anxiety, stress, depression, obsessive-compulsive disorder (OCD), sleep disorders, and suicidal ideation and other symptoms in students in university settings. For cross-reference, the review includes topics identified in scientific literature across different geographical regions and comprises the most prevalent mental health issues. The sources originated from different countries, including the United States, Denmark, UK, Turkey, Saudi Arabia, Serbia, UAE, Italy, Jordan, India, Lebanon, Egypt, Germany, Bangladesh, Iraq, Switzerland, Canada, Australia, and China, offering an international viewpoint on the mental health impact of the pandemic on university students. Each article was published following a scientific peer-review process, ensuring the reliability and validity of the data presented.

Inclusion/exclusion criteria

Specific inclusion and exclusion criteria were put together to preserve focus and relevance. The review included only peer-reviewed literature published between January 2020 and December 2023. The timeframe included research completed during and after the COVID-19 pandemic. Only the publications written in English were studied for inclusion. Studies on the mental health issues and consequences of the COVID-19 epidemic on university students were included, while studies on other populations or unrelated issues were discarded. Inclusion and exclusion criteria are shown in Table ​ Table1 1 .

Stress and anxiety

The WHO estimates that the most prevalent mental health disorder is anxiety, affecting up to 1/3 of adults in their lifetime [ 4 ]. Following the implementation of quarantines, lockdowns, and suspension of face-to-face teaching, universities and colleges switched to online remote learning modes. This sudden change altered students' functioning, primarily evidenced by increased stress and anxiety. The review demonstrated several trends directly resulting from the COVID-19 pandemic, such as fear of contamination, a rise in OCD, a decline in personal interactions, and long hours pursuing online learning. The review also identified several indirect stressors caused by COVID-19: financial hardships, decreased sleep quality, rise in pre-existing anxiety, depression, and stress. According to pre-pandemic data, direct and indirect stressors have contributed significantly to an overall spike in stress and anxiety. Female gender emerged as an additional factor for increased symptoms and comorbidities during COVID-19.

The most apparent stressor was the danger of contamination [ 3 , 6 - 10 ]. In the first few months of the pandemic, the university academic population in Turkey cited danger and fear of infection as the most significant stressors affecting their day-to-day lives [ 3 ]. American students echoed the same fear of infection among their family members and themselves [ 10 ]. Researchers concluded that prolonged exposure to fear positively correlated with increased anxiety [ 6 ]. The announcements of the pandemic often came with the government's policies of mandatory lockdowns to reduce the spread of COVID-19 infections. The restrictions considerably changed lifestyles and social relationships. For the first time in their lives, students experienced home quarantine. The research on increased stress and the adverse effects of at-home isolation was conducted during other pandemics and during COVID-19 [ 2 , 11 ]. The magnitude of the COVID-19 pandemic multiplied stress and other adverse effects and eliminated most of the social person-to-person interaction [ 2 , 12 , 13 ]. Researchers consistently show the harmful effects of social distancing and decreased social interactions during COVID-19 closures [ 10 ]. All those elements contributed to psychological dysfunction, increased stress, anxiety symptoms [ 14 ], and changes in sleeping patterns [ 15 , 16 ]. Other studies show a link between COVID-19-induced home isolation and changed sleep patterns [ 2 ], COVID-19 and stress, and poor academic performance [ 2 , 17 ].

Following announcements of public restrictions, colleges and universities rushed to implement online-only learning models [ 2 , 7 - 9 , 18 , 19 ]. Preventing academic loss and adopting digital learning allowed students to continue their education under home quarantine. Before the COVID-19 pandemic, Brooks et al. [ 11 ] analyzed the effects of home quarantine during other outbreaks. Brooks et al. hypothesize that education, when conducted under home quarantine, is a cause of increased frustration, stress, anger, and anxiety. The dominance of technology-driven college education associated with long online hours and possible internet addiction leads to a significant increase in anxiety levels [ 20 ]. The shift from in-person to digital education among university students contributed to increased anxiety prevalence [ 18 , 20 ]. A positive correlation between declining mental health and online learning was noted among Asian students, as observed by Islam et al. [ 21 ]. The constant fear, online presence, the enormous volume of information consumed, endless searches, and associated behaviors amplified anxiety and stress [ 8 , 22 ] and were a reason for the rise in anxiety [ 6 ] and were labeled as "cyberchondria" [ 7 ].

As the closures and lockdowns continued, students suffered financial hardships, causing anxiety [ 7 , 8 , 22 , 23 ]. College students reported adverse events such as declining family income, food and housing insecurity, and inadequate financial resources [ 23 ] to afford food, housing, and technology for effective learning. These indirect stressors disrupted the lives of low-income students more significantly and caused higher rates of stress and anxiety than those of high-income students [ 23 ]. Pandemic-generated unemployment caused working students to exhibit additional anxiety. Asian students were also reporting rising anxiety levels during the pandemic, particularly those who did not have access to resources [ 21 ], such as reliable internet, inability to purchase subscriptions, technology, or supplies, and who suffered from economic instability.

The long-term effects of the pandemic-related students' stress did not end with the first vaccination. This elevated stress trend continued for months after the initial impact [ 8 , 24 - 26 ], and even as of April 2021, 71% of Asian students were still reporting mild anxiety symptoms [ 26 ]. This finding contrasts with pre-pandemic anxiety levels recorded at about 15.7% and rising to 18.86% in March 2020 and to 32.68% in September 2020, respectively [ 26 ]. Al-Kumaim et al. [ 24 ] indicated that the pandemic had a considerable influence on students' psychological well-being, with anxiety being one of the most reported symptoms. The length of the pandemic hurt the mental health of university students. Students' anxiety levels continued at elevated levels. This observation is congruent with increased anxiety (60.8%) for students surveyed in 2021 [ 27 ]. The length of the pandemic was also detrimental to the deterioration of the mental health of the students.

Studies consistently found that female students were more at risk for increased anxiety during the pandemic. The research does not firmly establish why the female gender appears at significant risk for developing anxiety and increased stress [ 8 , 9 , 14 - 16 , 18 , 20 , 28 - 32 ]. This female factor could be due to the multifaceted nature of biological, psychosocial, cultural, and behavioral differences before and during the pandemic [ 29 ]. The exact calculations on how wide the gap is between male and female students' stress levels during the pandemic vary from paper to paper. The levels of pre-pandemic anxiety in female vs. male students were established in a Chinese longitudinal study showing anxiety for female students at 22%, while male students scored at 19% [ 29 ]. The study of students in Turkey [ 3 ] mid-COVID-19 demonstrates that the trend continues at almost twice the rate of anxiety, with 63% in females vs. 36% in male students. A systemic review by Liyanage et al. [ 4 ] quotes global differences in stress and anxiety for university students with mid-pandemic symptoms at 43% for females and 39% for males.

Several scholarly papers discuss the presence of a few well-established protective factors that reduce the levels of stress and anxiety experienced by students during the pandemic. The researchers zeroed in on the male gender [ 9 , 29 - 31 , 33 ], the presence of physical health [ 31 ], participation in exercise [ 34 ], student seniority, and urban residence [ 12 ]. Pre and mid-pandemic literature suggests that male students have shown consistently lower stress and anxiety symptoms than their female counterparts. This review shows strong mid-pandemic consistency for gender differences across many authors [ 3 , 6 - 9 , 13 , 28 , 29 , 31 , 32 ]. The articles reviewed do not explain why the male gender appears less affected by mental health challenges during the pandemic.

Academic stress is a part of a typical student learning cycle. Students who had senior student status experienced less stress [ 16 , 28 , 32 ]. Wang et al. [ 33 ] confirmed that increased stress and anxiety are more prevalent in junior student populations. The differences between the junior and senior students can be explained by older age, more independence, and autonomy contributing to frustrations. Undergraduate students need time to develop psychological and emotional skills to handle stress better [ 33 ].

Families of students residing in rural areas are more vulnerable to socioeconomic downturn. Rural areas experience higher rates of poverty, and students tend to be poorer than their urban colleagues who reside in urban settings [ 8 , 12 , 33 ]. Living in an urban setting with more access to resources, including high-speed internet, protects students from developing higher stress and anxiety levels [ 12 ]. Students who returned home and lived with supportive family members also reported decreased stress and anxiety levels compared to students who lived alone [ 8 , 12 ]. Students who lived with families had lower anxiety levels. Living with supportive parents had a protective effect on rising anxiety levels [ 12 ].

The extensive use of home confinement and prolonged self-quarantine began the COVID-19 pandemic. The disruption of students' daily regimens and increasing lack of physical health resulted in decreased motivation and academic/social involvement [ 31 ]. Xiang et al. [ 34 ] describe the relationship between anxiety levels among Chinese students who engaged in consistent physical activity during the pandemic vs. inactive students. Physically active students experienced better mental health [ 27 , 34 ]. Exercise stimulates endorphin production. Students who exercised regularly experienced decreased stress levels compared to non-active students [ 27 , 34 ]. Regular physical activity is a protective factor against increased anxiety levels. Pandemic time research showed an inverse association between resistance training and anxiety levels [ 34 ].

Together, these studies confirm the negative impact of the COVID-19 crisis on mental health, especially concerning anxiety and stress. Considering the challenges associated with the transition to adulthood, university students are particularly vulnerable to mental health problems.

Very few sources compare rates of depression pre- and post-pandemic. The studies that capture this information come from the United Arab Emirates (UAE) [ 28 ] and China [ 2 ]. They indicate the pre-pandemic level of depressive symptoms at 22% in UAE [ 28 ] and 16.9% [ 2 ] in China and post-pandemic depressive symptoms at 40% and 30.6%, respectively. The authors of both studies suggest that the rates of depression during the COVID-19 pandemic almost doubled. They link the increased rates of depression to family stress [ 2 ] and academic demands. High rates of depression at 64% among university medical students who lived with family during COVID-19 are also echoed by Serbian researchers [ 32 ]. Increased rates of depression in the student population, as compared to other age groups, before the pandemic continued the same trend post-pandemic [ 1 ].

Chinese university students who participated in the research were 18 to 24 years old [ 1 ]. This "post-adolescent" period [ 1 ] is one of the most challenging periods in life, characterized by difficulties managing emotions and inadequate capabilities and skills to manage psychological and academic needs. Research conducted during similar periods of confinement [ 2 ] shows that students, when in prolonged home isolation, are a vulnerable population to increased stress, anxiety, and, ultimately, depression. The studies on Jordanian students [ 2 ] link home confinement to COVID-19-related issues, including increased stress, anxiety, sleep and eating disturbances, feelings of loneliness, dissatisfaction with distance learning, and the presence of home quarantine as a possible precursor to the pandemic time increase in depression. Fawaz et al. [ 18 ] show a significant positive correlation between students' dissatisfaction and depressive symptoms. The analysis of the source of UK-based doctoral students' study [ 35 ] lists pre-existing cumulative stress, pre-pandemic depression, and anxiety as possible reasons for developing six times higher than the general population's depression tendencies, reporting clinical levels of depressive and anxiety symptoms at 28.3% and 79.4%, respectively. Researchers show a direct relationship between the COVID-19 home quarantine period and an increase in mental health difficulties represented by the following findings: 78% depression, 67.9% anxiety, and 58.7% stress [ 2 ].

Other studies show that during the COVID-19 pandemic, students feared and suffered academic decline [ 2 , 18 , 23 , 26 , 28 , 31 ]. The decrease in students' satisfaction during COVID-19 inherently influenced the increased prevalence of depressive symptoms [ 18 , 26 ]. Factors such as the perception of an overwhelming school workload also contributed to the increase in depressive symptoms [ 18 , 28 ]. Study participants felt overwhelmed by too many online tasks [ 18 , 24 ]. Students who are depressed are more likely to avoid classes, tests, and assignments [ 1 ], causing a slide to poor academic performance. Fawaz et al. [ 18 ] discovered an association between an abrupt shift to e-learning and an increase in perceived increase in workload that also produced depression symptoms.

Increasing depression during the COVID-19 pandemic was exacerbated among the students with feelings of loneliness and isolation [ 2 , 7 , 13 , 27 ]. Wang et al. [ 33 ] concluded that epidemic-related factors, such as the impact of isolation, increased anxiety, and fear of contagion, are associated with higher risk of depressive symptoms. Additional factors contributing to the increase in depressive symptoms include a family history of chronic illness [ 2 , 12 ].

Researchers show an increased prevalence of depressive symptoms in female students [ 2 , 29 ]. A Serbian study of university students [ 32 ] puts the rate of increased depression of female students at almost 2.5 times higher than men. Mirilovic et al. [ 32 ] also show more severe rates of depressive symptoms among junior first and second-year students as compared to senior students.

Despite many issues contributing to an increase in depressive symptoms, Xiang et al. [ 34 ] point to specific forms of physical activity, such as stretching and resistance training, which were negatively correlated with both anxiety and depression. Participating in house chores was negatively correlated with depression.

Quoted studies provide evidence of overall increased depressive symptoms in the university student population during the COVID-19 pandemic. The researchers point to several factors that play a role in the increased depression prevalence pre-pandemic baseline and increased mid-pandemic levels compared to the general population. This finding is a specific aspect of the mental health picture of the university student population.

Obsessive-compulsive disorder (OCD)

OCD is a chronic psychiatric disorder characterized by unwanted thoughts and repetitive behaviors. The global prevalence is at about 2.3% [ 36 ]. During the COVID-19 pandemic, government recommendations for increased handwashing efforts and other preventative measures provided a cognitive justification for excessive compulsion to take a firm root and spread [ 17 , 37 , 38 ]. Those prevention tools became a direct trigger and stressor for about 3.8% of medical students who struggled with OCD symptoms before the pandemic [ 36 ]. Medical students exhibit increased prevalence because the onset and peak of OCD happen in late teens and early adulthood. The average onset is 19-20 years old [ 21 ]. Munk et al. [ 38 ], in a German study, listed an increase in OCD symptoms from 3.6% before the pandemic to 21.4% in March 2020 in the general population. In late 2021, researchers in Iraq pointed to OCD symptoms in about 43% of surveyed university subjects [ 37 ], demonstrating a massive increase with symptoms spread as follows: unpleasant thoughts (58.1%), washing (14%), contamination scales (19.4%), and repetition of numbers (8%). These symptoms seem to affect the younger students more and the students in earlier years of study [ 37 ]. In addition, Zheng et al. [ 19 ] identified in their research that just becoming a student puts university students at 2.169 times the increased risk of having an OCD diagnosis compared to healthcare workers. Other variables as predictors for OCD in the general population may also apply to university students: being single places people at 1.836 times increased risk of having OCD, the presence of an increase in sleep latency is an independent predictor for OCD, and a history of psychiatric comorbidity. Mazhar et al. [ 39 ] observed that female medical students in junior preclinical years are more likely to suffer symptoms of OCD at increased rates in contrast to male students. Fears, depression, eating disorders, and other stress-inducing factors had a magnifying effect that contributed to increased OCD prevalence in students during the pandemic [ 37 ].

Suicidal ideation

Suicide claims over 800,000 lives every year worldwide [ 40 ], with more than half occurring before the age of 50. The estimated global mortality rate is about 16/100,000, with males at over four times the rate of females. It is the second leading cause of death among 10 to 34-year-old adults, according to the Centers for Disease Control and Prevention (CDC) [ 40 ]. Multiple authors talk about experiences of increased suicidal ideation among university students during the COVID-19 pandemic [ 16 , 30 , 41 , 42 ]. A study of younger students conducted before the COVID-19 pandemic by Lewinsohn et al. [ 43 ] found that female adolescents are at significantly higher risk of suicide attempts compared to male counterparts. The differences between genders diminished as participants increased with age. Gender was found to predict the lethality in suicide attempts as more males than females made attempts with high perceived lethality and medical lethality [ 43 ]. The study on Chinese university students during the COVID-19 pandemic [ 42 ] points to the male gender as well as a risk factor for increased suicidal ideation along with other factors like anxiety and depressive symptoms. Becoming a senior student decreases the risk of suicidal ideation [ 42 ].

A comparison between male and female students demonstrated that suicidal ideation is more prevalent among students with heightened depression and anxiety levels [ 30 , 41 , 42 ]. The pandemic disrupted daily structures and sleep-wake cycles. An increase in suicidal ideation was linked by AlHadi et al. [ 16 ] to students with insomnia symptoms. AlHadi et al. [ 16 ] suggest that insomnia could be the "mediator" between COVID-19 anxiety and suicide. They demonstrate a direct link between increased insomnia levels and an increase in suicidal thoughts [ 16 ]. Building on the analysis presented by Lewinsohn et al. [ 43 ], the research on Saudi students also finds junior female students have more experiences with an increased prevalence of suicidal thoughts. The theme of mental and medical health issues before the pandemic as a risk factor for developing suicidal ideation before and during the pandemic was brought up consistently as a risk factor for greater prevalence of suicidal ideation [ 30 , 40 - 44 ]. Scientists from multiple sources quoted by the CDC point out that at any age, suicidal behavior is a complex process. Experts agree that a single event does not cause suicide. It involves various risk factors, such as individual, relationships, community, and societal levels [ 40 ]. During the COVID-19 pandemic, university students were experiencing pressures and stress involving all aspects of life, increasing the possibility of the development of suicidal ideation, and advancing from ideation to suicidal attempts and suicide completion [ 40 , 42 , 44 ].

Canadian researchers [ 41 ] demonstrated that university students also remained vulnerable to the increased risk of developing suicidal ideation when additional risk factors were present: identifying as Chinese or as another ethnic minority, experiencing depression or anxiety, having a history of suicidal planning or attempts, and being overwhelmed but unable to get help [ 4 ].

The COVID-19 pandemic triggered an increase in uncertainty and fear. The elevated prevalence of suicidal ideation and other psychiatric disorders coincided with anti-pandemic measures such as lockdowns, social isolation, heightened levels of stress and psychological strain, and other factors beyond this review.

Sleeping disorders and insomnia

Most authors agree that sleeping disorders among university students have worsened during the COVID-19 pandemic, with increased stress and anxiety playing a significant role in sleep disruptions [ 8 , 10 , 14 - 16 , 19 , 20 , 45 , 46 ]. Students' negative perceptions during the COVID-19 pandemic were also reflected in decreased sleep quality [ 8 , 15 , 46 ]. The combination of social restrictions, physical isolation, and stress of distance learning resulted in interrupted sleep and wake cycles [ 8 , 15 , 20 , 22 ]. Over 52% of the students reported difficulties falling asleep and 43% reported not getting enough sleep with self-reported stress and anxiety in 78% of the student population [ 46 ], causing declining mental health [ 25 ].

Pre-COVID-19 sleep disorders increased their prevalence during the COVID-19 pandemic [ 15 , 46 ]. Dongol et al. analyzed data from smartwatches and surveys to measure sleep duration and light and deep sleep, and demonstrated that almost 80% of the students were found to be experiencing high-level sleeping disturbance; most significantly, about 27% of males and 33% of females had clinical insomnia [ 15 ]. These findings are in sharp contrast to insomnia presence before the pandemic at 9.5% [ 47 ]. The authors offer a list of predisposing factors that included the following: female gender, chronic health issues, being an older student, sleep disorder before the COVID-19 pandemic, increased caffeine consumption, and changes in daily routines that include sleeping patterns [ 15 ]. Dongol et al. attributed increased stress, poor sleep quality, and fear during COVID-19 to the elevated presence of clinical insomnia symptoms. On the other hand, the conclusion of the Italian study [ 14 ] discusses how the lockdowns affected the students' psycho-emotional well-being, changes in sleep patterns, and heightened insomnia rates from 15% before COVID-19 to 42% during the pandemic. Students identified different aspects associated with this difficulty: 52% reported increased problems falling asleep, 43% were not getting enough sleep, and almost 70% reported various disturbances ranging from having vivid dreams and not having a fixed sleep schedule to overwhelming stress and anxiety [ 14 ].

The fear of contracting COVID-19 has been found to correlate with heightened stress levels, clinical insomnia, and diminished sleep quality [ 10 , 15 ]. Pre-pandemic studies link insomnia in college students to poor academic performance [ 45 ]. Mid-pandemic research by Son et al. [ 10 ] suggested insomnia contributes to difficulties with concentration.

There has been a notable rise in the prevalence of insomnia, a decline in sleep quality, and elevated stress levels among college students, regardless of country of origin. This increased prevalence is particularly pronounced among female students [ 14 , 20 ], older students, and those with chronic illnesses and pre-existing sleep disorders [ 15 , 16 ].

Research gaps

This review addresses only college students as they are a particular population with many challenges. The scholarly papers examined the mental health difficulties, stressors, sleeping difficulties, selected psychiatric prevalence, coping methods, and potential short-term psychological impacts of the pandemic on higher education students. This review identifies opportunities for further research in this area by identifying gaps in existing literature.

More research should be conducted on the psychological influence of the coronavirus pandemic on university students with different backgrounds. The studies presented in this paper originated from the West, China, India, and a few Middle Eastern countries. It is essential to recognize how this pandemic has affected individuals from different backgrounds and how many factors may have influenced their experiences. Most studies have primarily focused on a narrow range of short-term effects. It is crucial to consider the wide-ranging consequences and lasting impact. Further research is necessary to fully comprehend the long-term mental health implications of the pandemic on university students.

Additionally, more research is needed to determine the most effective interventions/solutions for supporting university students continuously. Although most studies have primarily examined the adverse psychological effects, data are available on protective factors that can assist institutions and students. The research on the role of resilience and protective factors could provide helpful and practical information when facing COVID-19 or any other adverse event. This type of research allows the universities' governing bodies and administrators to comprehend students' mental health struggles and create effective strategies to support student well-being when facing personal, national, or global disasters such as COVID-19.

Future directions

To manage mental health needs during future outbreaks of COVID-19 or other pandemics, measurable, science-based, uniform intervention and support for university students are required. Most support should be deployed on a smaller scale and within the academic community to support individual students' needs. These services can be expanded and scaled up as needed during times of need. The literature suggests different models of examination of the interventional landscape [ 24 ]: (1) screenings and education: institutional and community-level regular screenings, broad education with outreach and follow-up, and access to tailored interventions and information for at-risk individuals. (2) Personal development: opportunities to examine and improve self-determination, self-efficacy, self-regulation, and other qualities [ 24 ]. Research out of Germany brings up a somewhat elusive concept of resilience [ 31 ] linked to a perception of control, a positive development that allows students to flourish under pressure and strengthen personal bonds. Researchers believe [ 31 ] that academic success is reinforced by the notion of "belonging" as a protective factor for mental health. Based on these findings, incorporating the teaching of resilience could become a valuable tool for university students. (3) Technical fluency: ongoing training and exposure to new technologies, digital fluency, mobile interactive learning, and intuitive design of online learning experiences [ 24 ]. (4) Environmental support: this area includes a broad category of socioeconomic factors like family support, university support, and emotional engagement [ 23 , 24 ]. Each category has its variables, and students' well-being depends on the sum of improvements in all four areas.

Finally, implementing a structured program of longitudinal studies to capture and measure the adequate representation of the mental health status of university students is the preferred practice in higher educational settings [ 4 ]. Taking a continuous pulse of the students' mental health through regular health screenings and hopefully accessible intervention seems like a logical solution. As those new interventions, studies, and programs are instituted, we need to measure what is changing and what is effective [ 25 ].

Recommendations

The COVID-19 pandemic caused school and university closures and changes in daily schedules, teaching methods, and other aspects of daily life. These changes dramatically impacted university students and highly affected young adults, leading to many mental health trends discussed above. The disadvantaged factors emerge among different student profiles analyzed: social isolation, female, history of comorbidities, poor, and rural background. The advantage factors were good health, male gender, resilience, supportive family and plenty of social connections, affluent urban background, and regular physical activity. The pandemic has intensified the significant increase in the number and type of disorders across the mental health spectrum and the rapid emergence of psychiatric conditions. This review finds that the COVID-19 pandemic negatively affected the mental health of university students, and the following trends have been identified: (1) decreased mental health: these psychological trends include increased stress, anxiety, self-reported decreased well-being, constant worry, etc. [ 1 , 3 , 4 , 6 , 9 , 10 , 12 - 23 , 26 - 28 , 30 , 31 , 33 , 34 , 46 ]; (2) psychiatric trends include the presence of depression, substance abuse, and increased psychiatric morbidity, including an increase in OCD occurrence as well as suicidal ideation [ 1 , 16 - 19 , 23 , 24 , 26 , 28 , 30 - 37 , 39 , 41 , 42 , 48 ]; (3) disruption of the circadian cycle trends, sleep disorders, and insomnia [ 10 , 14 - 16 , 19 , 20 , 46 ]; (4) the disproportional detrimental effect of COVID-19 on female students in all areas reviewed [ 3 , 6 , 9 , 13 - 16 , 20 , 28 - 31 ].

Conclusions

The COVID-19 pandemic is the most significant public health threat to generational mental health. Anxiety and stress were cited as the most prevalent conditions among the student population during the COVID-19 pandemic. Higher education institutions and governments were reactive in their response to the COVID-19 pandemic. Young intellectuals suffered at increased rates from stress, anxiety, sleep-related issues, depression, and suicidal ideation. A firm action to protect the students' safety and physical, social, and mental well-being must be taken in partnership with their communities, students, and higher education institutions.

The authors have declared that no competing interests exist.

Author Contributions

Concept and design:   Beatta Zarowski, Demetrios Giokaris, Olga Green

Acquisition, analysis, or interpretation of data:   Beatta Zarowski, Demetrios Giokaris, Olga Green

Drafting of the manuscript:   Beatta Zarowski, Demetrios Giokaris, Olga Green

Critical review of the manuscript for important intellectual content:   Beatta Zarowski, Demetrios Giokaris, Olga Green

Supervision:   Demetrios Giokaris