ABSTRACT
Background. Seroprevalence studies are important tools to estimate the prevalence of prior or recent SARS-CoV-2 infections. This information is critical for identifying hotspots and high-risk groups and informing public health responses to the COVID-19 pandemic. We conducted a city-level seroprevalence study in Holyoke, Massachusetts to estimate the seroprevalence of SARS-CoV-2 antibodies and risk factors for seropositivity. Methods. We invited inhabitants of 2,000 randomly sampled addresses to participate between November 5 and December 31, 2020. Participants completed questionnaires measuring sociodemographic and health characteristics, and COVID-19 exposure history, and provided dried blood spots for measurement of SARS-CoV-2 IgG and IgM antibodies. To calculate total and group seroprevalence estimates, inverse probability of response weights were constructed based on age, gender, race/ethnicity and census tract to ensure estimates represented the city's population. Results. We enrolled 280 households including 472 individuals. 328 underwent antibody testing. The citywide weighted seroprevalence of SARS-CoV-2 IgG or IgM was 13.9% (95%CI 7.8 - 21.8) compared to 9.8% based on publicly reported case counts. Seroprevalence was 16.8% (95%CI 5.7 - 28.0) among individuals identifying as Hispanic compared to 8.9% (95%CI 3.0 - 14.7) among those identifying as White. Seroprevalence was 20.7% (95%CI 2.2 - 39.2) for ages 0-19;13.8% (95%CI 5.6 - 22) for ages 20 - 44;9.6% (95%CI 0 - 20.5) for ages 45 - 59;4.8% (95%CI 0 - 10.2) for ages 60 - 84;and 42.9% (95%CI 0 - 100) for ages >85. Conclusion. The measured SARS-CoV-2 seroprevalence in Holyoke was only 13.9% during the second surge of SARS-CoV-2 in this region, far from accepted thresholds for "herd immunity" and highlighting the need for expanding vaccination. Individuals identifying as Hispanic were at high risk of prior infection. Subsequent community-level serosurveys are necessary to guide local responses to the SARSCoV-2 pandemic.
ABSTRACT
On 16 March 2021, the Teach311 + COVID-19 Collective (www.teach311.org) hosted a virtual roundtable discussion entitled "Sources of Disaster: New Epistemic Perspectives in Post-3.11 Japan." The event brought together scholars and students researching the history and anthropology of Japan to explore how the earthquake, tsunami, and nuclear power plant disaster of 11 March 2011 (3.11) changed our ways of knowing the world. The roundtable focused on the idea of the "source" to get at these epistemic shifts in lived experience and practical knowledge as well as historiography, and to investigate ideas that range from what we can know about acceptable risk and safety to notions of home and belonging. "Source" is a way to think about origins, but also the materials-texts, media, or testimony-that we collect and analyze to give rise to new or better knowledge. Building upon previous Teach311 activities that explored the roots of 3.11 and genba, participants in this roundtable expanded upon the significance and meanings of the notion of a "source" relative to the politics of epistemology in their research and studies in order to examine what reconstruction means in history when it is conducted alongside recovery.
ABSTRACT
As a result of the COVID-19 worldwide pandemic, the United States instituted various non-pharmaceutical interventions (NPIs) in an effort to slow the spread of the disease. Although necessary for public safety, these NPIs can also have deleterious effects on the economy of a nation. State and federal leaders need tools that provide insight into which combination of NPIs will have the greatest impact on slowing the disease and at what point in time it is reasonably safe to start lifting these restrictions to everyday life. In the present work, we outline a modeling process that incorporates the parameters of the disease, the effects of NPIs, and the characteristics of individual communities to offer insight into when and to what degree certain NPIs should be instituted or lifted based on the progression of a given outbreak of COVID-19. We apply the model to the 24 county-equivalents of Maryland and illustrate that different NPI strategies can be employed in different parts of the state. Our objective is to outline a modeling process that combines the critical disease factors and factors relevant to decision-makers who must balance the health of the population with the health of the economy. © 2021, University of Surrey. All rights reserved.