Syndemics and Coronavirus: The Social Dimensions of Public Health Crises
By: Chris Puckett, Department of Sociology
In the September 26, 2020 edition of the Lancet medical journal, Editor-in-Chief Richard Horton submitted a comment regarding the ongoing rise in SARS-CoV-2 infections. He notes the interaction between COVID-19 and other non-communicable diseases, the clustering of these conditions within social groups according to patterns of structural inequality, and the compounding of disease effects against a backdrop of socioeconomic disparity. From this, he concludes that “COVID-19 is not a pandemic. It is a syndemic.” Dr. Horton’s comment came at a time in which countries like the US and UK were experiencing a renewed surge of cases among their most at-risk populations. He encourages readers to consider the social implications that complicate efforts to slow the spread of COVID-19 across the globe.
But what is a syndemic? How is a syndemic defined? Where else can syndemics be observed? In this edition of the Global Current blog, I seek to contextualize Dr. Horton’s claim by discussing the core components of a syndemic, as well some examples of syndemics as they are studied in the global health literature. From this understanding, I will look to COVID-19 data as well as commentary from syndemic researchers to understand how these ideas tie into the ongoing pandemic. As countries around the world begin the long process of vaccine rollout, it is important to understand how social circumstances exacerbate health disparities on a global scale.
The Syndemic Model in Public Health
Before exploring COVID-19 as a syndemic, let’s go over the basic components of a syndemic. The syndemic model in public health is a theoretical framework that allows researchers to study the biological and social factors that complicate disease at the population level. At the core of any syndemic model is the clustering of two or more disease or health conditions within a population, which are exacerbated by social factors and leading to preventable suffering among at-risk populations (Singer, Bulled, Ostrach, and Mendenhall: 2017). The goal of a syndemic researcher, therefore, is to explore the effects these conditions or diseases have on one another, as well as the social and environmental factors that expose populations to these clustered disease effects. These two components of a syndemic model are called the biological-biological (bio-bio) interface and the biological-social (bio-social) interface respectively (Singer, Bulled, and Ostrach: 2020). These two interfaces must be clearly demonstrated to prove a disease interaction as syndemic, and not a co-occurring epidemic or the coincidental occurrence of social factors that produce negative health outcomes.
The bio-bio interface refers to the interactions between clustered diseases within the human body. Beyond increased susceptibility to disease in an already-sick patient, the bio-bio interface seeks to account for an enhanced disease burden among patients with multiple illnesses. The interaction between Human Immunodeficiency Virus (HIV) and the disease-causing Mycobacterium tuberculosis is an example of this kind of enhanced disease burden. The strain HIV puts on the immune system not only makes patients more susceptible to an infectious disease, but also weakens their immune response to the illness itself. This results in quicker progression and more intense symptoms than an otherwise healthy tuberculosis patient (Singer, Bulled, Ostrach, and Mendenhall: 2017). Also relevant to the bio-bio interface is comorbidity, or the idea that co-occurring chronic health conditions can exacerbate one another. For example, because obesity, hypertension, and diabetes share a set of underlying risk factors, they are often found together and interact to worsen each other’s effects on the body. In this way, they incur a cumulative health disadvantage greater than that which they would have individually (Ventura and Lavie: 2016). Through the bio-bio interface, syndemics researchers contend with a holistic understanding of the biological circumstances that accompany disease.
The observation of clustered disease does not constitute a syndemic on its own, however. Without precipitation by social patterns, diseases can cluster as a result of co-occurring epidemics or similarly asocial factors. This is the central tenet of the bio-social interface, that the aggregation of multiple diseases must be precipitated by patterns of structural disadvantage in society. Returning to a previous example, there is a powerful statistical association between poverty and nutritional diseases like hypertension and diabetes. If access to healthy foods is limited for an individual, as is often the case in areas of concentrated poverty, then they are more likely to rely on less healthy alternatives or risk going hungry. This differentially exposes impoverished people to the cumulative effects of clustered nutritional disease relative to those with better access to nutritious food (Harrington, Lutomoski, Molcho, and Perry: 2009). It should be noted here that social factors can produce negative health outcomes without clustering multiple diseases in a population. In other words, the presence of social factors complicating on its own does not constitute a syndemic. The bio-bio AND bio-social interfaces must be satisfied to classify a problem as a syndemic.
Practical Application of the Syndemic Framework: Malnutrition, Infectious Disease, and War
Let’s put this understanding of syndemics into practice by breaking down an example from the public health literature. In their article “Syndemics of War: Malnutrition-Infectious Disease Interactions and the Unintended Health Consequences of Intentional War Policies,” Bayla Ostrach and Merrel Singer (2012) note the bidirectional interaction of malnutrition and infectious disease in war zones. Not only does malnutrition impede immune response to pathogenic illnesses, thereby increasing susceptibility and severity of disease in malnourished people, infection can interfere with the metabolism of nutrients from food. Not only are these two conditions clustered together, they can exacerbate one another when experienced together.
This interaction satisfies the bio-bio interface but, as previously established, this alone does not satisfy a syndemic model. Without a clearly defined bio-social interface, it is still unclear whether this particular disease clustering has been precipitated by social circumstances. In this regard, the authors discuss several specific examples of the interaction between malnutrition and infectious disease from the Spanish Civil War, Vietnam War, and Gulf War. From these examples, they identify a unifying thread shared across all accounts: the impact of intentional war policies on civilians living in zones of armed conflict. In some cases, civilians in war zones were intentionally deprived food and supplies as a result of these policies, as can be seen in the international sanctions prohibiting the sale of food to Spanish loyalists during the Spanish Civil War. In other cases, these policies resulted in the deliberate destruction of sanitation and nutrition infrastructure, as is seen in the bombing of Iraqi water stations during the Gulf War and the use of herbicides in targeted crop destruction in Vietnam. In each of these cases, the decline in food access among civilians incited outbreaks of infectious diseases such as malaria, diarrheal disease, and respiratory infections. By clustering malnutrition and infectious disease in populations according to external social circumstances (i.e. wartime policy), the bio-social interface is satisfied, completing the syndemic model.
Syndemics and COVID-19
To move toward a syndemic understanding of COVID-19, as with the previous example, it’s important to start from the observation of clustered disease in a population. Dr. Horton sites the interaction between COVID-19 and non-communicable diseases (NCDs), an interaction that is statistically verifiable. A systematic review of the prevalence of NCDs among confirmed COVID-19 patients found that 5.8% also suffered from cardiovascular disease, 11% were diabetic, and an astonishing 21% were hypertensive (Baradaran, Ebrahimzadeh, Baradaran, Kachooei: 2020). This is attributable to shared underlying risk factors, such as age, poverty, and obesity, meaning that COVID-19 prevalence is associated with NCD prevalence, which constitutes disease clustering.
Similarly, COVID-19 severity is strongly associated with the presence of NCDs in a patient. One study found that, among New Yorkers hospitalized with severe cases of COVID-19, 33.8% were diabetic, 41.7% were obese, and 56.6% were hypertensive (Richardson, Hirsch, and Narasimhan: 2020). Another study found that the presence of at least one NCD increased the likelihood of death by a statistically significant degree among COVID-19 patients in Mexico (Hernandez-Galdamez et al.: 2020). Studies like these demonstrate that the interaction between COVID-19 and NCDs imposes a cumulative disease burden greater than the sum of its parts, resulting in quicker progression and more intense COVID-19 symptoms than are seen in otherwise healthy COVID-19 patients. In this way, the bio-bio interface is satisfied, as the aggregation of these diseases results in health disadvantages greater than they have individually.
But, as stated previously, this interaction is incomplete on its own. The bio-social interface, which posits that social conditions can precipitate disease clustering, is not yet satisfied. Dr. Horton posits that, “these conditions are clustering within social groups according to patterns of inequality deeply embedded in our societies.” But what are the patterns he references? First, consider the previous example of bio-social interface, specifically the clustering of nutritional diseases (diabetes, hypertension, obesity, etc.) around areas of concentrated poverty. Food insecurity, or the inability of a household to provide an ample amount of nutritious food for each individual, is strongly associated with lower scores on the Healthy Eating Index and instances of overweight children (Bhattacharya, Currie, and Haider: 2004). Another study in the Journal of Epidemiology and Community Health found that those whose access to healthy foods was limited by inadequate income were twice as likely to score within the lower two quintiles of DASH, a dietary program designed to detect and prevent hypertension and cardiovascular disease (Harrington, Lutomoski, Molcho, and Perry: 2009). In this way, the food poor are differentially exposed to NCDs that present an increased risk of severe COVID-19 complications.
A similar dynamic can be seen in the relationship between COVID-19 severity and racial inequalities. According to official CDC statistics, compared to non-Hispanic White Americans, non-Hispanic Black Americans and Hispanic Americans are 1.4x and 1.7x more likely to contract COVID-19 respectively when adjusted for age. The CDC attributes these disparities to the disproportionate representation of racial minorities in “essential work settings”, as working outside of their home increases the likelihood of exposure to SARS-CoV-2, as well as documented disparities in healthcare access and housing. Moreover, non-Hispanic Back Americans and Hispanic Americans are disproportionately hospitalized with severe COVID-19 at respective rates of 3.7x and 4.1x, and die as a result of complications due to COVID-19 at a shared rate of 2.8x (again, compared to non-Hispanic White Americans and adjusted for age), attributable to the disproportionate levels of poverty and NCD among racial minority groups.
Is COVID-19 a Syndemic?
With this understanding of biological and social factors that cluster COVID-19 alongside non-communicable disease against a backdrop of structural inequality, it would certainly seem that Dr. Horton’s claim that COVID-19 is syndemic is verified by the data. It is here, however, that an important distinction must be made: though this data shows that there are biological and social factors complicating COVID-19 in many parts of the world, this does not mean that the COVID-19 syndemic is global. Emily Mendenhall, a syndemics researcher at Georgetown University and author of Syndemic Suffering: Social Distress, Depression, and Diabetes Among Mexican American Women, published a response to Dr. Horton’s (2020) comment in the October 22, 2020 edition of The Lancet (Mendenhall: 2020). In her correspondence, Dr. Mendenhall argues that the social factors that drive COVID-19 morbidity and mortality in the United States do not apply in other social contexts. America’s political failures and history of racial inequality do not apply, for example, to New Zealand, whose COVID-19 plan entailed swift government action designed to minimize mortality. Though Dr. Mendenhall agrees that COVID-19 is a syndemic in the US for the reasons Dr. Horton suggests, she argues that “By calling the COVID-19 syndemic global, we miss the point of the concept entirely.”
Let’s compare the United States pandemic response to that of New Zealand to see how, as Dr. Mendenhall puts forth, one produces a syndemic and the other does not. To start, New Zealand’s pandemic response benefitted greatly from the involvement of epidemiologists and public health officials at every stage of its development. This allowed the country to begin implementing its response in the weeks leading up to COVID-19 gaining its official pandemic status. Widespread testing and contact tracing allowed for targeted quarantines of potentially infected individuals before the onset of symptoms, halting viral transmission in its tracks. Early epidemiological models suggested that New Zealand’s native Maori population were at highest risk for viral proliferation, allowing public health authorities to target these areas for testing and other key resources, mitigating the bio-social interactions that could complicate disease susceptibility and severity in those areas. Through a strictly enforced series of national lockdowns and stay-at-home orders, New Zealand was able to transition quickly from preventing the virus from spreading to eliminating the virus entirely, with the country famously transitioning to the post-pandemic period of its plan after only 100 days of quarantine.
Comparatively, the Trump administration downplayed COVID-19 and encouraged the spread of misinformation regarding the disease in the months leading up to the pandemic, hindering the US’ ability to craft an early pandemic response. As cases began to rise, the nation’s decentralized approach placed the burden of implementation squarely on the shoulders of state health authorities who, through a combination of chronic underfunding and absence of federal support, were largely unequipped to handle necessary procedures like testing and contact tracing. As a result, COVID-19 became embedded in communities before public health authorities had the tools to intervene. Moreover, the legacy of Jim Crow segregation in the United States has, through a potent mixture of concentrated poverty and limited government investment in healthcare, enhanced the disease burden of COVID-19 in the nation’s black population (Gravlee: 2020). The clustering of NCDs like hypertension and cardiovascular disease increases COVID-19 susceptibility and severity among black Americans, while mass incarceration and residential segregation pack them into “superspreader” locations, dramatically increasing their chances of coming into contact with the virus.
This brings us to the most important provocation in Dr. Mendenhall’s response to Dr. Horton: local context matters when defining a syndemic. COVID-19 is being experienced on a global scale, it is not isolated in one community over another. As the New Zealand example demonstrates, the biological and social circumstances that complicate COVID-19 are not shared universally. Defining a problem as syndemic necessitates a complete understanding of the disease contexts specific to the populations or areas researchers are studying, and defining COVID-19 as a global syndemic detracts from our ability to recognize those contexts.
Conclusion
In this edition of the Global Currents Blog, I began by outlining the necessary components of a syndemic. Multiple diseases or chronic health issues are clustered in populations AND interact with one another to create a cumulative disease burden. This is the bio-bio interface. Clustering of diseases is precipitated by differences in social conditions and structural inequalities that increase susceptibility to and severity of disease in a population. This is the bio-social interface. In the case of COVID-19, non-communicable diseases such as hypertension and cardiovascular disease are associated with quicker progression and more intense symptoms than in an otherwise healthy patient. The clustering of COVID-19 and NCDs follows patterns of inequality in society in some cases, though this varies contextually across the globe. COVID-19 is a syndemic in some contexts, as Dr. Horton argues, but this variation in local contexts means that the COVID-19 syndemic is not global, as Dr. Mendenhall argues.
As vaccine rollouts begin in earnest, a syndemic understanding of COVID-19 allows public health researchers to recognize the social and biological factors that complicate pandemic responses. Such factors are already being considered to an extent, with frontline medical workers and assisted living facilities receiving the first round of vaccinations, but these measures alone do not ensure ready vaccination in communities at greatest risk of COVID-19. The aggregation of NCDs in vulnerable communities coupled with a decentralized rollout plan in the United States have created gaping holes in vaccine coverage, meaning that the areas of highest viral proliferation and disease severity will remain unvaccinated for longer. Even with widespread vaccination, however, it’s clear that COVID-19, like the flu before it, will remain in the public health ecosystem long after lockdowns have been lifted and daily life has returned to “normal”. Through a syndemic understanding of the biological and social components of COVID-19, public health researchers and policymakers can curtail the disproportionate harm inflicted on our most at-risk communities.
References
Baradaran, Ashkan, Mohammad H. Ebrahimzadeh, Aslan Baradaran, and Amir R. Kachooei. 2020. “Prevalence of Comorbidities in COVID:19 Patients: A Systemic Review and Meta-Analysis.” The Archives of Bone and Joint Surgery, 8:suppl. 1, 247-255.
Bhattacharya, J., J. Currie, and S. Hader. 2006. “Breakfast of Champions? The Nutritional Effects of the School Breakfast Program.” Journal of Human Resources, 41(3):445-66.
Gravlee, Clarence. 2020. “Systemic Racism, Chronic Health Inequities, and COVID-19: A Syndemic in the Making?” American Journal of Human Biology Special Issue: Human Biologists Confront the COVID-19 Pandemic, 32(5).
Harrington, J., J. Lutomoski, M. Molcho, and I. J. Perry. 2009. “Food Poverty and Dietary Quality, is there a Relationship?” Journal of Epidemiology and Public Health, 63:16.
Ostrach, Bayla, and Merril Singer. 2012. “Syndemics of War: Malnutrition-Infectious Disease Interactions and the Unintended Health Consequences of Intentional War Policy.” Annals of Anthropological Practice Special Issue: Syndemics and Global Health: Implications for Prevention, Education, and Training, 36(2): 257-73.
Richardson, Safiya, Jamie S. Hirsch, and Mangala Narasimhan. 2020. “Presenting Characteristics, Comorbidities, and Outcomes among 5700 Patients Hospitalized with COVID-19 in the New York City Area.” The Journal of the American Medical Association, 323(20): 2052-2059.
Singer, Merril, Nicola Bulled, and Bayla Ostrach. 2020. “Whither Syndemics?: Trends in Syndemics Research, a Review 2015-2019.” Global Public Health 15(7): 943-55.
Singer, Merril, Nicola Bulled, Bayla Ostrach, and Emily Mendenhall. 2017. “Syndemics and the Biosocial Conception of Health.” The Lancet, 389(10072): 941-950.
Ventura, Hector O., and Carl J. Lavie. 2016. “Impact of Comorbidities in Hypertension.” Current Opinion in Cardiology, 31(4): 374-75.
