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Ohio under COVID: Lessons from America's Heartland in Crisis
Katherine Sorrels, Vanessa Carbonell, Danielle Bessett, Lora Arduser, Edward V. Wallace, and Michelle L. McGowan, Editors
In early March of 2020, Americans watched with uncertain terror as the novel coronavirus pandemic unfolded. One week later, Ohio announced its first confirmed cases. Just one year later, the state had over a million cases and 18,000 Ohioans had died. What happened in that first pandemic year is not only a story of a public health disaster, but also a story of social disparities and moral dilemmas, of lives and livelihoods turned upside down, and of institutions and safety nets stretched to their limits.
Ohio under COVID tells the human story of COVID in Ohio, America's bellwether state. Scholars and practitioners examine the pandemic response from multiple angles, and contributors from numerous walks of life offer moving first-person reflections. Two themes emerge again and again: how the pandemic revealed a deep tension between individual autonomy and the collective good, and how it exacerbated social inequalities in a state divided along social, economic, and political lines. Chapters address topics such as mask mandates, ableism, prisons, food insecurity, access to reproductive health care, and the need for more Black doctors. The book concludes with an interview with Dr. Amy Acton, the state's top public health official at the time COVID hit Ohio. Ohio under COVID captures the devastating impact of the pandemic, both in the public discord it has unearthed and in the unfair burdens it has placed on the groups least equipped to bear them.
This book is freely available in an open access edition thanks to TOME—a collaboration of the Association of American Universities, the Association of University Presses, and the Association of Research Libraries—and the University of Cincinnati.
Fig. 9.1.Spatial distribution of COVID-19 in the world (map on top), in the United States (map on bottom left), and in Ohio (map on bottom right) as of July 2022.
Fig. 9.2.Disease mapping of malaria and HIV. A) Spatial distribution of malaria prevalence in Africa (Hay and Snow 2006). B) Spatial distribution of HIV in Africa (Dwyer-Lindgren et al. 2019).
Fig. 9.4.County-level distribution of intensive care unit (ICU) beds (map on the left), and the distribution of the counties in the different spatial risk groups (map on the right) in Ohio. Group 1: counties with airports; Group 2: counties surrounding the counties with airports; Group 3: counties with main highways crossing the county; and Group 4: counties not surrounding counties with airports or being crossed by main highways.
Fig. 9.5.Projected number of cumulative numbers of COVID-related hospitalizations (top) and deaths (bottom) in Ohio assuming no change in the intensity of the March 2020 social distancing intervention (orange line), 20 percent reduction (grey line), 50 percent reduction (yellow line), and 70 percent reduction of the intervention (blue line).
Fig. 9.6.Projection of the spatiotemporal dynamics of the intensive care unit (ICU) beds available (panel maps on the left) and cumulative number of COVID-related deaths (panel maps on the right) under different scenarios of relaxation of the March 2020 social distancing interventions in Ohio.
Fig. 9.7.Spatial distribution of the cumulative number of COVID-19-related deaths (left) and COVID-19-related mortality risk (right) in Ohio from March 1 to May 5, 2020. A mortality risk > 1 indicates a higher risk of COVID-19-related death than expected based on the state average.
Fig. 9.9.Bivariate map comparing COVID-19 incidence rates in both periods. The first time period was from April 1 to May 31, 2020. The second time period was from June 1 to July 31, 2020. Incidence rates were categorized in quantiles; dark green indicates counties with the highest incidence rate in the first period, whereas dark purple indicates counties with the highest incidence in the second period. Counties in black had high incidence rates in both periods.
Fig. 9.10.Bivariate map comparing COVID-19 mortality rates in both periods. The first time period was from April 1 to May 31, 2020. The second time period was from June 1 to July 31, 2020. Dark green indicates counties with the highest mortality rate in the first period, whereas dark purple indicates counties with the highest mortality in the second period. Counties in black had high mortality rates in both periods. States outlined in red are in the higher incidence rate group.
Fig. 9.11.Map on the top illustrates the distribution of the urban (blue) and rural (yellow) counties in Ohio. Map on the bottom illustrates a bivariate map comparing incidence rates of COVID-19 in both periods. The first time period was from April 1 to May 31, 2020. The second time period was from June 1 to July 31, 2020. Dark blue indicates counties with the highest incidence rate in the first period, whereas dark pink indicates counties with the highest mortality in the second period. Counties in dark purple had high incidence rates in both periods. Counties outlined in red are urban counties.