"Inoculation prompts the immune system to make antibodies to the virus, but as mutations change its shape, the virus can become more resistant to those antibodies. In the worst case, failing to stop the spread of the virus globally would allow more mutations that could make existing vaccines less effective, leaving even inoculated populations vulnerable.

“This idea that no one is safe until everyone is safe is not just an adage, it is really true,” said Andrea Taylor, the assistant director at Duke Global Health Innovation Center.

Even in the most optimistic scenarios, Ms. Taylor said, at the current pace of production, there will not be enough vaccines for true global coverage until 2023. The current rollout plans across Africa are expected to vaccinate only 20 to 35 percent of the population this year if everything goes right."

The New York Times

As Virus Variants Spread, ‘No One Is Safe Until Everyone Is Safe’

By Lynsey Chutel and Marc Santora

Jan. 31, 2021
Updated 11:16 a.m. ET

“The urgency of vaccination applies to everyone on the planet, disease experts point out. A mutation in any location will likely spread everywhere — something that happened earlier in the pandemic with a mutation called D614G that appears to have enhanced transmission.

“Vaccine nationalism is very clearly a problem,” said Maria Sundaram, an epidemiologist at the University of Toronto.

“The allure of being vaccinated and getting to normal is not quite reality because of the new variants and the underserved communities of the world not getting them.”

Collins, the NIH director, said he sees best-case and worst-case scenarios.

Best case, he said, is that “people roll up their sleeves as quickly as possible to get to that 80 to 85 percent [vaccination rate] and no other strains emerge that are more resistant.”

The worst case is that if people “continue to be irresponsible,” more transmissible variants will rip across the country and potentially escape vaccines, treatments and naturally acquired immunity.

And then, he said, “we’d have to redesign a completely new vaccine all over again.”

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Washington Post

Coronavirus mutations add urgency to vaccination effort as experts warn of long battle ahead

Ariana Eunjung Cha

1. DEFINING SYNDEMICS

"Merrill Singer and colleagues (Singer, 1994, 1996; Singer & Snipes, 1992) developed the concept of syndemics in the early 1990s, in the context of research on the HIV epidemic, which was then ravaging poor, Black, and other communities of color in urban North America. Singer built on the long‐standing observation that communities most impacted by new epidemics often are already facing other threats to their health. In the case of HIV among marginalized people in the U.S., those threats included “a set of closely interrelated endemic and epidemic conditions (eg, HIV, TB, STDs, hepatitis, cirrhosis, infant mortality, drug abuse, suicide, homicide, etc.), all of which are strongly influenced and sustained by a broader set of political‐economic and social factors” (Singer, 1996). The crucial point, Singer argued, was that these conditions did not merely co‐occur; the synergy among epidemics made each worse.

Syndemic theory, then, integrates two concepts: disease concentration and disease interaction (Mendenhall & Singer, 2020; Tsai & Venkataramani, 2015). Disease concentration refers to the co‐occurrence or clustering of multiple epidemics as a result of large‐scale, political‐economic forces and adverse social conditions. Disease interaction refers to the ways that overlapping epidemics exacerbate the health effects of adverse social conditions, either through biological interactions between disease states or through interactions between biological and social processes.

Neither disease concentration nor disease interaction is unique to syndemic thinking; the uniqueness lies in their integration. Attention to disease concentration is a common feature of most frameworks for population health, including fundamental cause theory (Link & Phelan, 1995), ecosocial theory (Krieger, 2001), and the concepts of structural violence (Farmer, 2003) and structural vulnerability (Leatherman, 2005; Quesada, Hart, & Bourgois, 2011). Indeed, more than half a century ago, Cassel (1964) argued for the relevance of social‐science theory to epidemiology by highlighting social processes that lead to the clustering of seemingly unrelated diseases (in his case, tuberculosis and schizophrenia). However, like Cassel, most models of population health frame the co‐occurrence of epidemics in terms of the cumulative burden of disease. What the syndemic framework adds is the prediction that overlapping epidemics are more than the sum of the parts. Both (a) biological interactions between epidemics and (b) biosocial ones between epidemics and the social conditions that shape them can result in more suffering and death than would be expected in models that treat each disease in isolation.

The focus on disease interaction also has deep, historical roots, stretching back at least to Scrimshaw, Taylor, and Gordon's (1959) work on synergism and antagonism between nutrition and infection (see also Scrimshaw, 2003). Disease interaction is usually described in terms of comorbidity and multimorbidity (van den Akker, Buntinx, & Knottnerus, 1996). These concepts, which have gained wider currency in the context of COVID‐19, draw attention to common etiological pathways across disease states and to the complexity of care for patients with more than one chronic disease. Comorbidity and multimorbidity are most salient in clinical medicine but are also relevant to epidemiology and health services research (Valderas, Starfield, Sibbald, Salisbury, & Roland, 2009). Even when invoked in epidemiology, however, the focus is on the distribution of comorbid conditions (and predisposing social conditions or risk factors) at the level of the individual (Barnett et al., 2012). If syndemic theory were concerned only with biological interactions at the individual level (eg, for people who were infected with both HIV and TB), it is not clear what value it would add beyond the framework of multimorbidity. The promise of the theory lies in raising questions across levels of analysis about interactions among clustered epidemics and the underlying social conditions that drive them. This unique perspective is what makes syndemic theory relevant to the COVID‐19 pandemic.

2. RELEVANCE TO COVID‐19

The core tenets of syndemic theory, then, are that:

large‐scale, political‐economic forces, which play out over generations, result in deep‐seated social, economic, and power inequities;
these inequities shape the distribution of risks and resources for health, resulting in the social and spatial clustering of epidemic diseases (disease concentration); and
some overlapping epidemics have synergistic effects due to (a) biological interactions between disease states or (b) interactions between biological processes and the social, economic, and power inequities that shape the distribution of health to begin with (disease interaction).

COVID‐19 has made these ideas feel urgent from the start. In early March, for example, the New York Times highlighted the intersection of social factors that increase the risk of infection in impoverished communities, such as housing density and reliance on public transportation, and “disproportionately high rates of disease and illness” that make infection more deadly (Eligon, 2020). Days later Time predicted that people with low incomes—disproportionately Black, Indigenous, or other people of color—would face higher exposure to the virus (because they are less likely to be able to work from home, more likely to work in service sectors where contact with strangers is routine, more likely to live in multi‐family apartment buildings) and had less access to sick leave and medical care if they did become sick (Vesoulis, 2020). In mid‐May, when the New York City Health Department first released data on COVID‐19 deaths by ZIP code, the prediction had borne out: the highest death rates were in low‐income neighborhoods with disproportionate numbers of Black and Latinx people (Schwirtz & Cook, 2020).

The spatial concentration of COVID‐19 death manifests on a broader scale, too. In early April, The Atlantic ran a story about the demographic distinctiveness of COVID‐19 mortality in the American South (Newkirk, 2020), suggesting that younger people were dying there at higher rates than in other hard‐hit regions because of the legacy of slavery and Jim Crow. The suspected pathway was a higher burden of chronic diseases like hypertension and diabetes, which followed from social and political‐economic factors such as poverty, limited government investment in health care, and mass incarceration, among others.¹

These accounts by journalists and others paint a compelling picture. The challenge for researchers is to incorporate such observations into a theory that generates testable propositions about the links between systemic racism, chronic disease, and risk of mortality from COVID‐19. That work has already begun. Social scientists and public health researchers have drawn attention to the structural conditions that shape the concentration of COVID‐19 in communities already facing higher burdens of poverty, racial inequity, and disease (Khazanchi et al., 2020; Laster Pirtle, 2020; Williams & Cooper, 2020). Medical scientists and clinicians have emphasized the interactions among comorbid conditions that are overrepresented among COVID‐19 hospitalizations and deaths—particularly hypertension (Pranata, Lim, Huang, Raharjo, & Lukito, 2020), diabetes (Kreutz et al., 2020), and obesity (Akoumianakis & Filippatos, 2020). Syndemic theory draws together both approaches, bridging the population‐ and individual‐level perspectives of the social and medical sciences, and it adds new questions about possible interactions between COVID‐19 and pre‐existing social inequities that may exacerbate suffering from chronic diseases like hypertension and diabetes.

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