Monitoring Health Systems by Estimating Excess Mortality

Abstract Importance: Monitoring health systems during and after natural disasters, epidemics, or outbreaks is critical for guiding policy decisions and interventions. When the effects of an event are long-lasting and difficult to detect in the short term, the accumulated effects can be devastating. Objective: We aim to leverage the improved access to mortality data to develop data-driven approaches that can help monitor health systems and quantify the effects on mortality of natural disasters, epidemics, or outbreaks. Design, Setting, and Participants: To demonstrate the utility of our approach we conducted several retrospective time-series analyses of mortality assessment after natural disasters. We obtained individual-level mortality records from the Department of Health of Puerto Rico from January 1985 to May 2020 to study the effects of hurricanes Hugo, Georges, and Maria in September 1989, September 1998, and September 2017, respectively. Further, we obtained daily mortality counts from Florida, New Jersey, and Louisiana’s Vital Statistic systems from January 2015 to December 2018, January 2007 to December 2015, and January 2003 to December 2006, respectively, to study the effects of hurricanes Irma in 2017, Sandy in 2013, and Katrina in 2005. Finally, we obtained individual-level mortality data from the Cook county, IL, medical examiners office, and state-specific weekly mortality counts from the Center for Disease Control and Prevention to assess the effect of the COVID-19 pandemic on the US health system. Exposures: Hurricanes Maria, Georges, and Hugo in Puerto Rico, Irma in Florida, Sandy in New Jersey, and Katrina in Louisiana, the Chikungunya outbreak in Puerto Rico, and the COVID-19 pandemic in the United States. Main Outcomes: We estimate and provide uncertainty assessments for percent increase from expected mortality, estimated excess deaths, and difference across groups. Results: We found that the death rate increase in Puerto Rico after Maria and Georges was substantially higher than the other hurricanes we examined. Further, we find that excess mortality in the US was already above 100,000 on May 9, 2020, with over 58% of these occurred in New York, New Jersey, Massachusetts, and Pennsylvania, and that effects of this pandemic were worse for elderly black individuals compared to whites of the same age. Conclusions and Relevance: Our approach can be used to monitor or assess health systems by estimating increased mortality rates and excess deaths from mortality records. Key Points Question: Can we estimate excess mortality and provide accurate uncertainty assessments from vital statistics data? Findings: We developed statistical methodology that accounts for key sources of variability and provides accurate estimates and their standard errors for excess mortality. We applied the approach to datasets from several US states including periods affected by hurricanes and epidemics. We found an elevated and persistent increase in mortality after hurricanes in Puerto Rico that was substantially higher than in other US states. We also found that excess mortality in the US during the COVID-19 pandemic reached 100,000 by May 9, 2020. Finally, we found significant differences in the effects of this pandemic across racial groups in the US. Meaning: Data-driven approaches can help monitor health systems and quantify the effects on mortality of natural disasters, epidemics, or outbreaks.