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1. Excess mortality in the United States during the first three months of the COVID-19 pandemic

   https://doi.org/10.1017/S0950268820002617  

   Rivera, R.; Rosenbaum, J. E.; Quispe, W. (January 2020, Epidemiology and Infection)

   null (Ed.)

   Abstract Deaths are frequently under-estimated during emergencies, times when accurate mortality estimates are crucial for emergency response. This study estimates excess all-cause, pneumonia and influenza mortality during the coronavirus disease 2019 (COVID-19) pandemic using the 11 September 2020 release of weekly mortality data from the United States (U.S.) Mortality Surveillance System (MSS) from 27 September 2015 to 9 May 2020, using semiparametric and conventional time-series models in 13 states with high reported COVID-19 deaths and apparently complete mortality data: California, Colorado, Connecticut, Florida, Illinois, Indiana, Louisiana, Massachusetts, Michigan, New Jersey, New York, Pennsylvania and Washington. We estimated greater excess mortality than official COVID-19 mortality in the U.S. (excess mortality 95% confidence interval (CI) 100 013–127 501 vs. 78 834 COVID-19 deaths) and 9 states: California (excess mortality 95% CI 3338–6344) vs. 2849 COVID-19 deaths); Connecticut (excess mortality 95% CI 3095–3952) vs. 2932 COVID-19 deaths); Illinois (95% CI 4646–6111) vs. 3525 COVID-19 deaths); Louisiana (excess mortality 95% CI 2341–3183 vs. 2267 COVID-19 deaths); Massachusetts (95% CI 5562–7201 vs. 5050 COVID-19 deaths); New Jersey (95% CI 13 170–16 058 vs. 10 465 COVID-19 deaths); New York (95% CI 32 538–39 960 vs. 26 584 COVID-19 deaths); and Pennsylvania (95% CI 5125–6560 vs. 3793 COVID-19 deaths). Conventional model results were consistent with semiparametric results but less precise. Significant excess pneumonia deaths were also found for all locations and we estimated hundreds of excess influenza deaths in New York. We find that official COVID-19 mortality substantially understates actual mortality, excess deaths cannot be explained entirely by official COVID-19 death counts. Mortality reporting lags appeared to worsen during the pandemic, when timeliness in surveillance systems was most crucial for improving pandemic response. 

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2. Excess mortality in Ukraine during the course of COVID-19 pandemic in 2020–2021

   https://doi.org/10.1038/s41598-023-33113-2  

   Shishkin, Aleksandr; Lhewa, Pema; Yang, Chen; Gankin, Yuriy; Chowell, Gerardo; Norris, Michael; Skums, Pavel; Kirpich, Alexander (April 2023, Scientific Reports)

   Abstract In this work, the COVID-19 pandemic burden in Ukraine is investigated retrospectively using the excess mortality measures during 2020–2021. In particular, the epidemic impact on the Ukrainian population is studied via the standardized both all-cause and cause-specific mortality scores before and during the epidemic. The excess mortality counts during the pandemic were predicted based on historic data using parametric and nonparametric modeling and then compared with the actual reported counts to quantify the excess. The corresponding standardized mortalityP-score metrics were also compared with the neighboring countries. In summary, there were three “waves” of excess all-cause mortality in Ukraine in December 2020, April 2021 and November 2021 with excess of 32%, 43% and 83% above the expected mortality. Each new “wave” of the all-cause mortality was higher than the previous one and the mortality “peaks” corresponded in time to three “waves” of lab-confirmed COVID-19 mortality. The lab-confirmed COVID-19 mortality constituted 9% to 24% of the all-cause mortality during those three peak months. Overall, the mortality trends in Ukraine over time were similar to neighboring countries where vaccination coverage was similar to that in Ukraine. For cause-specific mortality, the excess observed was due to pneumonia as well as circulatory system disease categories that peaked at the same times as the all-cause and lab-confirmed COVID-19 mortality, which was expected. The pneumonias as well as circulatory system disease categories constituted the majority of all cases during those peak times. The seasonality in mortality due to the infectious and parasitic disease category became less pronounced during the pandemic. While the reported numbers were always relatively low, alcohol-related mortality also declined during the pandemic. 

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3. Excess mortality in U.S. prisons during the COVID-19 pandemic

   https://doi.org/10.1126/sciadv.adj8104  

   Sugie, Naomi F.; Turney, Kristin; Reiter, Keramet; Tublitz, Rebecca; Kaiser, Daniela; Goodsell, Rebecca; Secrist, Erin; Patil, Ankita; Jiménez, Monik (December 2023, Science Advances)

   U.S. prisons were especially susceptible to COVID-19 infection and death; however, data limitations have precluded a national accounting of prison mortality (including but not limited to COVID-19 mortality) during the pandemic. Our analysis of mortality data collected from public records requests (supplemented with publicly available data) from 48 Departments of Corrections provides the most comprehensive understanding to date of in-custody mortality during 2020. We find that total mortality increased by 77% in 2020 relative to 2019, corresponding to 3.4 times the mortality increase in the general population, and that mortality in prisons increased across all age groups (49 and under, 50 to 64, and 65 and older). COVID-19 was the primary driver for increases in mortality due to natural causes; some states also experienced substantial increases due to unnatural causes. These findings provide critical information about the pandemic’s toll on some of the country’s most vulnerable individuals while underscoring the need for data transparency and standardized reporting in carceral settings. 

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4. Designing for Researcher Access in the U.S. Mortality Data Ecosystem

   https://doi.org/10.1145/3687032  

   Doyle, Dylan Thomas; Fiesler, Casey; Pater, Jessica; Brubaker, Jed R (November 2024, Proceedings of the ACM on Human-Computer Interaction)

   Access to mortality data is critical for researchers for various reasons, including the development of life-saving medical interventions. However, high-quality mortality data is typically unavailable for researchers to access in a timely manner due to bottlenecks and inefficiencies in the coordination of managing mortality data across a vast information ecosystem. To identify opportunities to improve access to mortality data, we conducted a qualitative interview study with 20 experts with direct knowledge and experience with mortality data systems. From these interviews, we mapped the mortality data ecosystem and found that policy constraints are the main underlying cause of bottlenecks and inefficiencies. We argue that policy intervention is required to optimize the coordination of mortality data between databases and between organizations. To support researcher access to mortality data, we present guiding principles for designers seeking to improve the mortality data ecosystem. These principles contribute to CSCW scholarship focused on the challenges of coordination across large information ecosystems and the tradeoffs between technology and policy when designing such systems. 

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5. Sex bias in mortality risk changes over the lifespan of bottlenose dolphins

   https://doi.org/10.1098/rspb.2023.0675  

   McEntee, Molly H.; Foroughirad, Vivienne; Krzyszczyk, Ewa; Mann, Janet (July 2023, Proceedings of the Royal Society B: Biological Sciences)

   Research on sex biases in longevity in mammals often assumes that male investment in competition results in a female survival advantage that is constant throughout life. We use 35 years of longitudinal data on 1003 wild bottlenose dolphins ( Tursiops aduncus ) to examine age-specific mortality, demonstrating a time-varying effect of sex on mortality hazard over the five-decade lifespan of a social mammal. Males are at higher risk of mortality than females during the juvenile period, but the gap between male and female mortality hazard closes in the mid-teens, coincident with the onset of female reproduction. Female mortality hazard is non-significantly higher than male mortality hazard in adulthood, resulting in a moderate male bias in the oldest age class. Bottlenose dolphins have an intensely male-competitive mating system, and juvenile male mortality has been linked to social competition. Contrary to predictions from sexual selection theory, however, male–male competition does not result in sustained male-biased mortality. As female dolphins experience high costs of sexual coercion in addition to long and energetically expensive periods of gestation and lactation, this suggests that substantial female investment in reproduction can elevate female mortality risk and impact sex biases in lifespan. 

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