Person: Kiang, Mathew
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Kiang
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Mathew
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Kiang, Mathew
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Publication U.S. county-level characteristics to inform equitable COVID-19 response(Cold Spring Harbor Laboratory, 2020-04-11) Chin, Taylor; Kahn, Rebecca; Li, Ruoran; Chen, Jarvis; Krieger, Nancy; Buckee, Caroline; Balsari, Satchit; Kiang, MathewBackground: The spread of Coronavirus Disease 2019 (COVID-19) across the United States confirms that not all Americans are equally at risk of infection, severe disease, or mortality. A range of intersecting biological, demographic, and socioeconomic factors are likely to determine an individual’s susceptibility to COVID-19. These factors vary significantly across counties in the United States, and often reflect the structural inequities in our society. Recognizing this vast inter-county variation in risks will be critical to mounting an adequate response strategy. Methods and Findings: Using publicly available county-specific data we identified key biological, demographic, and socioeconomic factors influencing susceptibility to COVID-19, guided by international experiences and consideration of epidemiological parameters of importance. We created bivariate county-level maps to summarize examples of key relationships across these categories, grouping age and poverty; comorbidities and lack of health insurance; proximity, density and bed capacity; and race and ethnicity, and premature death. We have also made available an interactive online tool that allows public health officials to query risk factors most relevant to their local context. Our data demonstrate significant inter-county variation in key epidemiological risk factors, with a clustering of counties in certain states, which will result in an increased demand on their public health system. While the East and West coast cities are particularly vulnerable owing to their densities (and travel routes), a large number of counties in the Southeastern states have a high proportion of at-risk populations, with high levels of poverty, comorbidities, and premature death at baseline, and low levels of health insurance coverage. The list of variables we have examined is by no means comprehensive, and several of them are interrelated and magnify underlying vulnerabilities. The online tool allows readers to explore additional combinations of risk factors, set categorical thresholds for each covariate, and filter counties above different population thresholds. Conclusion: COVID-19 responses and decision making in the United States remain decentralized. Both the federal and state governments will benefit from recognizing high intra-state, inter-county variation in population risks and response capacity. Many of the factors that are likely to exacerbate the burden of COVID-19 and the demand on healthcare systems are the compounded result of long-standing structural inequalities in US society. Strategies to protect those in the most vulnerable counties will require urgent measures to better support communities’ attempts at social distancing and to accelerate cooperation across jurisdictions to supply personnel and equipment to counties that will experience high demand.Publication Every Body Counts: Measuring Mortality From the COVID-19 Pandemic(American College of Physicians, 2020-09-11) Kiang, Mathew; Irizarry, Rafael; Buckee, Caroline; Balsari, SatchitAs of mid-August 2020, more than 170 000 U.S. residents have died of coronavirus disease 2019 (COVID-19); however, the true number of deaths resulting from COVID-19, both directly and indirectly, is likely to be much higher. The proper attribution of deaths to this pandemic has a range of societal, legal, mortuary, and public health consequences. This article discusses the current difficulties of disaster death attribution and describes the strengths and limitations of relying on death counts from death certificates, estimations of indirect deaths, and estimations of excess mortality. Improving the tabulation of direct and indirect deaths on death certificates will require concerted efforts and consensus across medical institutions and public health agencies. In addition, actionable estimates of excess mortality will require timely access to standardized and structured vital registry data, which should be shared directly at the state level to ensure rapid response for local governments. Correct attribution of direct and indirect deaths and estimation of excess mortality are complementary goals that are critical to our understanding of the pandemic and its effect on human life.Publication Mortality in Puerto Rico after Hurricane Maria(New England Journal of Medicine (NEJM/MMS), 2018) Kishore, Nishant; Marqués, Domingo; Mahmud, Ayesha; Kiang, Mathew; Rodriguez, Irmary; Fuller, Arlan; Ebner, Peggy; Sorensen, Cecilia; Racy, Fabio De Castro Jorge; Lemery, Jay; Maas, Leslie; Leaning, Jennifer; Irizarry, Rafael; Balsari, Satchit; Buckee, CarolineBACKGROUND Quantifying the effect of natural disasters on society is critical for recovery of public health services and infrastructure. The death toll can be difficult to assess in the aftermath of a major disaster. In September 2017, Hurricane Maria caused massive infrastructural damage to Puerto Rico, but its effect on mortality remains contentious. The official death count is 64. METHODS Using a representative, stratified sample, we surveyed 3299 randomly chosen households across Puerto Rico to produce an independent estimate of all-cause mortality after the hurricane. Respondents were asked about displacement, infrastructure loss, and causes of death. We calculated excess deaths by comparing our estimated post-hurricane mortality rate with official rates for the same period in 2016. RESULTS From the survey data, we estimated a mortality rate of 14.3 deaths (95% confidence interval [CI], 9.8 to 18.9) per 1000 persons from September 20 through December 31, 2017. This rate yielded a total of 4645 excess deaths during this period (95% CI, 793 to 8498), equivalent to a 62% increase in the mortality rate as compared with the same period in 2016. However, this number is likely to be an underestimate because of survivor bias. The mortality rate remained high through the end of December 2017, and one third of the deaths were attributed to delayed or interrupted health care. Hurricane-related migration was substantial. CONCLUSIONS This household-based survey suggests that the number of excess deaths related to Hurricane Maria in Puerto Rico is more than 70 times the official estimate. (Funded by the Harvard T.H. Chan School of Public Health and others.)Publication Police Killings and Police Deaths Are Public Health Data and Can Be Counted(Public Library of Science, 2015) Krieger, Nancy; Chen, Jarvis; Waterman, Pamela; Kiang, Mathew; Feldman, Justin MichaelNancy Krieger and colleagues argue that law-enforcement–related deaths in the United States should be treated as notifiable conditions, which would allow public health departments to report these data in real-time.Publication Data in Crisis — Rethinking Disaster Preparedness in the United States(Massachusetts Medical Society, 2021-10-14) Balsari, Satchit; Kiang, Mathew; Buckee, CarolineTo protect our most vulnerable communities from increasingly frequent climate-related extreme weather events, public health agencies and hospitals need to know — before, during, and after a disaster — who and where these vulnerable people are, their hazard-specific risks, and whether they have been displaced from their networks of care. We have all the necessary building blocks in place to ensure that this information gets where it needs to go, but sustained commitment and investment in the necessary data systems, methodologic tools, and translational pipelines will be required to prepare for the natural disasters facing us.