Analyses of academician cohorts generate biased pandemic excess death estimates.

OBJECTIVE: Death data from cohorts of academicians have been used to estimate pandemic excess deaths. We aimed to evaluate the validity of this approach. STUDY DESIGN AND SETTING: Data were analyzed from living and deceased member lists from Mainland China, UK and Greece academies; and Nobel laureates (and US subset thereof). Samples of early elected academicians were probed for unrecorded deaths; datasets overtly missing deaths were excluded from further analyses. Actuarial risks were compared against the general population in the same country in respective age strata. Relative incidence risk increases in death in active pandemic periods were compared to population-wide pandemic excess death estimates for the same country. RESULTS: Royal Society and Academy of Athens datasets overtly missed deaths. Prepandemic death rates were 4- to 12-fold lower in the Chinese Academy of Engineering (CAE) vs respective age strata of the Mainland China population. A +158% relative increase in death risk was seen in CAE data during the first 12-month of wide viral spread. Both increases (+34% in British Academy) and decreases (-27% in US Nobel laureates) in death rates occurred in pandemic (2020-22) vs prepandemic (2017-19) years; point estimates were far from known excess deaths in the respective countries (+6% and +14%, respectively). Published excess death estimates for urban-dwelling Mainland China selectively analyzed CAE that had double the pandemic death rates than another Chinese academy (Chinese Academy of Sciences). CONCLUSION: Missingness, lack of representativeness, large uncertainty, and selective analysis reporting make data from academy rosters unreliable for estimating general population excess deaths.

Assessing the impact of short-term ozone exposure on excess deaths from cardiovascular disease: a multi-pollutant model in Nanjing, China's Yangtze River Delta.

Background: Ozone pollution is associated with cardiovascular disease mortality, and there is a high correlation between different pollutants. This study aimed to assess the association between ozone and cardiovascular disease deaths and the resulting disease burden in Nanjing, China. Methods: A total of 151,609 deaths from cardiovascular disease were included in Nanjing, China from 2013 to 2021. Daily data on meteorological and air pollution were collected to apply a generalized additional model with multiple pollutants to perform exposure-response analyses, stratification analysis, and evaluation of excess deaths using various standards. Results: In the multi-pollutant model, an increase of 10 µg/m3 in O3 was significantly associated with a 0.81% (95%CI: 0.49, 1.12%) increase in cardiovascular disease deaths in lag05. The correlation weakened in both the single-pollutant model and two-pollutant models, but remained more pronounced in females, the older group, and during warm seasons. From 2013 to 2021, the number of excess deaths attributed to ozone exposure in cardiovascular disease continued to rise with an increase in ozone concentration in Nanjing. If the ozone concentration were to be reduced to the WHO standard and the minimum level, the number of deaths would decrease by 1,736 and 10,882, respectively. Conclusion: The risk of death and excess deaths from cardiovascular disease due to ozone exposure increases with higher ozone concentration. Reducing ozone concentration to meet WHO standards or lower can provide greater cardiovascular disease health benefits.

A Research Note on Community Resilience Estimates: New U.S. Census Bureau Data With an Application to Excess Deaths From COVID-19.

In this research note, we describe the results of the first validation study of the U.S. Census Bureau's new Community Resilience Estimates (CRE), which uses Census microdata to develop a tract-level vulnerability index for the United States. By employing administrative microdata to link Social Security Administration mortality records to CRE, we show that CRE quartiles provide more stable predictions of COVID-19 excess deaths than single demographic categorizations such as race or age, as well as other vulnerability measures including the U.S. Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) and the Federal Emergency Management Agency's National Risk Index (NRI). We also use machine learning techniques to show that CRE provides more predictive power of COVID-19 excess deaths than standard socioeconomic predictors of vulnerability such as poverty and unemployment, as well as SVI and NRI. We find that a 10-percentage-point increase in a key CRE risk measure is associated with one additional death per neighborhood during the initial outbreak of COVID-19 in the United States. We conclude that, compared with alternative measures, CRE provides a more accurate predictor of community vulnerability to a disaster such as a pandemic.

A proposed analytical approach to estimate excess daily mortality rates in Ecuador.

Background: The COVID-19 pandemic has proved deadly all over the globe; however, one of the most lethal outbreaks occurred in Ecuador. Aims: This study aims to highlight the pandemic's impact on the most affected countries worldwide in terms of excess deaths per capita and per day. Methods: An ecological study of all-cause mortality recorded in Ecuador was performed. To calculate the excess deaths relative to the historical average for the same dates in 2017, 2018, and 2019, we developed a bootstrap method based on the central tendency measure of mean. A Poisson fitting analysis was used to identify trends on officially recorded all-cause deaths and COVID-19 deaths. A bootstrapping technique was used to emulate the sampling distribution of our expected deaths estimator µâŒ¢deaths by simulating the data generation and model fitting processes daily since the first confirmed case. Results: In Ecuador, during 2020, 115,070 deaths were reported and 42,453 were cataloged as excess mortality when compared to 2017-2019 period. Ecuador is the country with the highest recorded excess mortality in the world within the shortest timespan. In one single day, Ecuador recorded 1,120 deaths (6/100,000), which represents an additional 408% of the expected fatalities. Conclusion: Adjusting for population size and time, the hardest-hit country due to the COVID-19 pandemic was Ecuador. The mortality excess rate shows that the SARS-CoV-2 virus spread rapidly in Ecuador, especially in the coastal region. Our results and the proposed new methodology could help to address the real situation of the number of deaths during the initial phase of pandemics.

"The Graves Cannot Be Dug Fast Enough": Excess Deaths Among US Amish and Mennonites During the 1918 Flu Pandemic.

Estimating the lethal impact of a pandemic on a religious community with significant barriers to outsiders can be exceedingly difficult. Nevertheless, Stein and colleagues (2021) developed an innovative means of arriving at such an estimate for the lethal impact of COVID-19 on the Amish community in 2020 by counting user-generated death reports in the widely circulated Amish periodical The Budget. By comparing monthly averages of reported deaths before and during the COVID-19 pandemic, Stein and colleagues were able to arrive at a rough estimate of "excess deaths" during the first year of the pandemic. Our research extends the same research method, applying it to the years during and immediately preceding the global influenza pandemic of 1918. Results show similarly robust findings, including three notable "waves" of excess deaths among Amish and conservative Mennonites in the USA in 1918, 1919, and 1920. Such results point to the promise of utilizing religious periodicals like The Budget as a relatively untapped trove of user-generated data on public health outcomes among religious minorities more than a century in the past.

Do vaccines increase or decrease susceptibility to diseases other than those they protect against?

Contrary to the long-held belief that the effects of vaccines are specific for the disease they were created; compelling evidence has demonstrated that vaccines can exert positive or deleterious non-specific effects (NSEs). In this review, we compiled research reports from the last 40 years, which were found based on the PubMed search for the epidemiological and immunological studies on the non-specific effects (NSEs) of the most common human vaccines. Analysis of information showed that live vaccines induce positive NSEs, whereas non-live vaccines induce several negative NSEs, including increased female mortality associated with enhanced susceptibility to other infectious diseases, especially in developing countries. These negative NSEs are determined by the vaccination sequence, the antigen concentration in vaccines, the type of vaccine used (live vs. non-live), and also by repeated vaccination. We do not recommend stopping using non-live vaccines, as they have demonstrated to protect against their target disease, so the suggestion is that their detrimental NSEs can be minimized simply by changing the current vaccination sequence. High IgG4 antibody levels generated in response to repeated inoculation with mRNA COVID-19 vaccines could be associated with a higher mortality rate from unrelated diseases and infections by suppressing the immune system. Since most COVID-19 vaccinated countries are reporting high percentages of excess mortality not directly attributable to deaths from such disease, the NSEs of mRNA vaccines on overall mortality should be studied in depth.

Excess Deaths Associated with Rheumatic Heart Disease, Australia, 2013-2017.

During 2013-2017, the mortality rate ratio for rheumatic heart disease among Indigenous versus non-Indigenous persons in Australia was 15.9, reflecting health inequity. Using excess mortality methods, we found that deaths associated with rheumatic heart disease among Indigenous Australians were probably substantially undercounted, affecting accuracy of calculations based solely on Australian Bureau of Statistics data.

A comprehensive analysis of all-cause and cause-specific excess deaths in 30 countries during 2020.

The impact of COVID-19 on mortality from specific causes of death remains poorly understood. This study analysed cause-of-death data provided by the World Health Organization from 2011 to 2019 to estimate excess deaths in 2020 in 30 countries. Over-dispersed Poisson regression models were used to estimate the number of deaths that would have been expected if the pandemic had not occurred, separately for men and women. The models included year and age categories to account for temporal trends and changes in size and age structure of the populations. Excess deaths were calculated by subtracting observed deaths from expected ones. Our analysis revealed significant excess deaths from ischemic heart diseases (IHD) (in 10 countries), cerebrovascular diseases (CVD) (in 10 countries), and diabetes (in 19 countries). The majority of countries experienced excess mortality greater than 10%, including Mexico (+ 38·8% for IHD, + 34·9% for diabetes), Guatemala (+ 30·0% for IHD, + 10·2% for CVD, + 39·7% for diabetes), Cuba (+ 18·8% for diabetes), Brazil (+ 12·9% for diabetes), the USA (+ 15·1% for diabetes), Slovenia (+ 33·8% for diabetes), Poland (+ 30·2% for IHD, + 19·5% for CVD, + 26 1% for diabetes), Estonia (+ 26·9% for CVD, + 34·7% for diabetes), Bulgaria (+ 22·8% for IHD, + 11·4% for diabetes), Spain (+ 19·7% for diabetes), Italy (+ 18·0% for diabetes), Lithuania (+ 17·6% for diabetes), Finland (+ 13·2% for diabetes) and Georgia (+ 10·7% for IHD, + 19·0% for diabetes). In 2020, 22 out of 30 countries had a significant increase in total mortality. Some of this excess was attributed to COVID-19, but a substantial increase was also observed in deaths attributed to cardiovascular diseases and diabetes.

COVID-19 Excess Deaths in Peru's 25 States in 2020: Nationwide Trends, Confounding Factors, and Correlations With the Extent of Ivermectin Treatment by State.

Introduction In 2020, nations hastened to contain an emerging COVID-19 pandemic by deploying diverse public health approaches, but conclusive appraisals of the efficacy of these approaches are elusive in most cases. One of the medicines deployed, ivermectin (IVM), a macrocyclic lactone having biochemical activity against SARS-CoV-2 through competitive binding to its spike protein, has yielded mixed results in randomized clinical trials (RCTs) for COVID-19 treatments. In Peru, an opportunity to track the efficacy of IVM with a close consideration of confounding factors was provided through data for excess deaths as correlated with IVM use in 2020, under semi-autonomous policies in its 25 states. Methods To evaluate possible IVM treatment effects, excess deaths as determined from Peruvian national health data were analyzed by state for ages ≥60 in Peru's 25 states. These data were compared with monthly summary data for excess deaths in Peru for the period 2020-2021 as published by the WHO in 2022. To identify potential confounding factors, Google mobility data, population densities, SARS-CoV-2 genetic variations, and seropositivity rates were also examined. Results Reductions in excess deaths over a period of 30 days after peak deaths averaged 74% in the 10 states with the most intensive IVM use. As determined across all 25 states, these reductions in excess deaths correlated closely with the extent of IVM use (p<0.002). During four months of IVM use in 2020, before a new president of Peru restricted its use, there was a 14-fold reduction in nationwide excess deaths and then a 13-fold increase in the two months following the restriction of IVM use. Notably, these trends in nationwide excess deaths align with WHO summary data for the same period in Peru. Conclusions The natural experiment that was put into motion with the authorization of IVM use for COVID-19 in Peru in May 2020, as analyzed using data on excess deaths by locality and by state from Peruvian national health sources, resulted in strong evidence for the drug's effectiveness. Several potential confounding factors, including effects of a social isolation mandate imposed in May 2020, variations in the genetic makeup of the SARS-CoV-2 virus, and differences in seropositivity rates and population densities across the 25 states, were considered but did not appear to have significantly influenced these outcomes.

Reports of deaths are an exaggeration: all-cause and NAA-test-conditional mortality in Germany during the SARS-CoV-2 era.

Counts of SARS-CoV-2-related deaths have been key numbers for justifying severe political, social and economical measures imposed by authorities world-wide. A particular focus thereby was the concomitant excess mortality (EM), i.e. fatalities above the expected all-cause mortality (AM). Recent studies, inter alia by the WHO, estimated the SARS-CoV-2-related EM in Germany between 2020 and 2021 as high as 200 000. In this study, we attempt to scrutinize these numbers by putting them into the context of German AM since the year 2000. We propose two straightforward, age-cohort-dependent models to estimate German AM for the 'Corona pandemic' years, as well as the corresponding flu seasons, out of historic data. For Germany, we find overall negative EM of about -18 500 persons for the year 2020, and a minor positive EM of about 7000 for 2021, unveiling that officially reported EM counts are an exaggeration. In 2022, the EM count is about 41 200. Further, based on NAA-test-positive related death counts, we are able to estimate how many Germans have died due to rather than with CoViD-19; an analysis not provided by the appropriate authority, the RKI. Through 2020 and 2021 combined, our due estimate is at no more than 59 500. Varying NAA test strategies heavily obscured SARS-CoV-2-related EM, particularly within the second year of the proclaimed pandemic. We compensated changes in test strategies by assuming that age-cohort-specific NAA-conditional mortality rates during the first pandemic year reflected SARS-CoV-2-characteristic constants.

Impacts of the COVID-19 pandemic on life expectancy at birth in Asia.

OBJECTIVE: To investigate the impact of the COVID-19 pandemic on life expectancy at birth (e0) for 51 Asian countries and territories from January 1, 2020 to December 31, 2021. METHOD: Based on age-sex-specific mortality used for estimating the changes in e0 for years 2019, 2020, and 2021 from the 2022 revision of the World Population Prospects, we employed Arriaga's discrete method to decompose changes in e0 into both absolute and relative contributions of changes in age-specific death rate, and further obtained the age-sex-specific contribution to changes in e0 by country/territory and period (i.e., 2019-2020 and 2020-2021) for Asia. FINDINGS: The COVID-19 pandemic reduced 1.66 years in e0 of the Asian population from 2019 to 2021, slightly lower than the world average of 1.74 years. South Asia had a high loss of 3.01 years, whereas Eastern Asia had almost no changes. Oman, Lebanon, India, Armenia, Azerbaijan, Indonesia, and the Philippines experienced a high loss of above 2.5 years in e0. Despite significant national and territorial variations, the decline of e0 in Asia was mostly from the age group of 60-79 years, followed by age groups of 80 + and 45-59 years; and age groups of children contributed little (i.e., 0-4 and 5-14 years old). Males suffered more losses than females in this pandemic. Asian nations saw less loss in e0 in the second year of the pandemic, i.e., 2020-2021, than in the first year, i.e., 2019-2020, but this recovery trend was not observed in Southern Asia and South-Eastern Asia. Countries from Central Asia and Western Asia, such as Kazakhstan, Armenia, Azerbaijan, Lebanon, and Oman, had extraordinarily more losses in e0 in the first year at ages around 70. CONCLUSION: The COVID-19 pandemic had significantly affected e0 of Asian populations, and most contribution to the reduction of e0 came from the three older age groups, 60-79 years, 80 + years, and 45-59 years, with great variations across countries/territories. Our findings could have important implications for development of more resilient public health systems in Asian societies with better policy interventions for vulnerable demographic groups.

Incidence and outcome of patients with difficulty in hospital acceptance during COVID-19 pandemic in Osaka Prefecture, Japan: A population-based descriptive study.

Aim: The impact of the coronavirus disease (COVID-19) pandemic on the emergency medical service system in Japan has not been fully revealed. The purpose of this study was to determine the impact of the COVID-19 pandemic in 2021 on the difficulty in hospital acceptance of patients and patient outcome in Osaka Prefecture. Methods: This study was a descriptive epidemiological study with a 3-year study period from January 2019 to December 2021. We included patients who were transported by ambulance and had registered in the Osaka Emergency Information Research Intelligent Operation Network (ORION) system. The primary end-point of this study was the difficulty in hospital acceptance by month, and the secondary outcome was the mortality of patients who experience difficulty in hospital acceptance in each year. Results: We included 1,302,646 cases in this study. The proportion of cases with difficulty in hospital acceptance was 2.74% (12,829/468,709) in 2019, 3.74% (15,527/414,987) in 2020, and 5.09% (21,311/418,950) in 2021. The crude odds ratio for 2020 was 1.38 (95% confidence interval, 1.35-1.41) and for 2021 was 1.90 (95% confidence interval, 1.86-1.95). In 2019, 218 patients with difficulty in hospital acceptance had died by 21 days after hospitalization, whereas the number increased to 405 in 2020 and 750 in 2021. Conclusion: The number of patients experiencing difficulty in hospital acceptance during the COVID-19 pandemic in Osaka Prefecture increased, and patient outcomes were worse than before the pandemic.

The impact of COVID-19 shelter-in-place policy responses on excess mortality.

As a way of slowing COVID-19 transmission, many countries and U.S. states implemented shelter-in-place (SIP) policies. However, the effects of SIP policies on public health are a priori ambiguous. Using an event study approach and data from 43 countries and all U.S. states, we measure changes in excess deaths following the implementation of COVID-19 shelter-in-place (SIP) policies. We do not find that countries or U.S. states that implemented SIP policies earlier had lower excess deaths. We do not observe differences in excess deaths before and after the implementation of SIP policies, even when accounting for pre-SIP COVID-19 death rates.

Missing Americans: Early death in the United States-1933-2021.

We assessed how many US deaths would have been averted each year, 1933-2021, if US age-specific mortality rates had equaled the average of 21 other wealthy nations. We refer to these excess US deaths as "missing Americans." The United States had lower mortality rates than peer countries in the 1930s-1950s and similar mortality in the 1960s and 1970s. Beginning in the 1980s, however, the United States began experiencing a steady increase in the number of missing Americans, reaching 622,534 in 2019 alone. Excess US deaths surged during the COVID-19 pandemic, reaching 1,009,467 in 2020 and 1,090,103 in 2021. Excess US mortality was particularly pronounced for persons under 65 years. In 2020 and 2021, half of all US deaths under 65 years and 90% of the increase in under-65 mortality from 2019 to 2021 would have been avoided if the United States had the mortality rates of its peers. In 2021, there were 26.4 million years of life lost due to excess US mortality relative to peer nations, and 49% of all missing Americans died before age 65. Black and Native Americans made up a disproportionate share of excess US deaths, although the majority of missing Americans were White.

Assessment of Suspected COVID-19 Deaths in Nonhealthcare Settings in Côte d'Ivoire, March 11 to July 31, 2020.

According to hospital records, 5 months after reporting its first case of COVID-19, Côte d'Ivoire reported only 102 deaths. We conducted a community mortality survey in the 13 districts where 95% of COVID-19 cases were reported to assess COVID-19 mortality in nonhealthcare settings. To identify suspected COVID-19 deaths in communities, we used data from social and administrative institutions, such as police and fire departments, funeral homes, and places of worship, whose functions include providing services related to deaths. Our survey identified 54 (17.6%) suspected COVID-19 deaths, which is more than half of the official reported number. Our study showed that in areas with low access to healthcare and poorly functioning death notification and registration systems, community-based data sources could be used to identify suspected COVID-19 deaths outside of the health sector. They can provide early warning data on events, such as an unusual number of community deaths or diseases.

Evaluation of concordance in estimation of excess mortality due to COVID-19 pandemic.

BACKGROUND: The World Health Organization (WHO) kept track of COVID-19 data at country level daily during the pandemic that included the number of tests, infected cases and fatalities. This daily record was susceptible to change depending on the time and place and impacted by underreporting. In addition to reporting cases of excess COVID-19-related deaths, the WHO also provided estimates of excess mortality based on mathematical models. OBJECTIVE: To evaluate the WHO reported and model-based estimate of excess deaths to determine the degree of agreement and universality. METHODOLOGY: Epidemiological data gathered from nine different countries between April 2020 and December 2021 are used in this study. These countries are India, Indonesia, Italy, Russia, United Kingdom, Mexico, the United States, Brazil and Peru and each of them recorded more than 1.5 million deaths from COVID-19 during these months. Statistical tools including correlation, linear regression, intraclass correlation and Bland-Altman plots are used to assess the degree of agreement between reported and model-based estimates of excess deaths. RESULTS: The WHO-derived mathematical model for estimating excess deaths due to COVID-19 was found to be appropriate for only four of the nine chosen countries, namely Italy, United Kingdom, the United States and Brazil. The other countries showed proportional biases and significantly high regression coefficients. CONCLUSION: The study revealed that, for some of the chosen nations, the mathematical model proposed by the WHO is practical and capable of estimating the number of excess deaths brought on by COVID-19. However, the derived approach cannot be applied globally.

Variability in excess deaths across countries with different vulnerability during 2020-2023.

Excess deaths provide total impact estimates of major crises, such as the COVID-19 pandemic. We evaluated excess death's trajectories during 2020-2023 across countries with accurate death registration and population age structure data; and assessed relationships with economic indicators of vulnerability. Using the Human Mortality Database on 34 countries, excess deaths were calculated for 2020-2023 (to week 29, 2023) using 2017-2019 as reference, with weekly expected death calculations and adjustment for 5 age strata. Countries were divided into less and more vulnerable; the latter had per capita nominal GDP<$30,000, Gini>0.35 for income inequality and/or at least 2.5% of their population living in poverty. Excess deaths (as proportion of expected deaths, p%) were inversely correlated with per capita GDP (r=-0.60), correlated with proportion living in poverty (r=0.66) and modestly correlated with income inequality (r=0.45). Incidence rate ratio for deaths was 1.06 (95% confidence interval, 1.04-1.08) in the more versus less vulnerable countries. Excess deaths started deviating in the two groups after the first wave. Between-country heterogeneity diminished over time within each of the two groups. Less vulnerable countries had mean p%=-0.8% and 0.4% in 0-64 and >65 year-old strata while more vulnerable countries had mean p%=7.0% and 7.2%, respectively. Usually lower death rates were seen in children 0-14 years old during 2020-2023 versus pre-pandemic years. While the pandemic hit some countries earlier than others, country vulnerability dominated eventually the cumulative impact. Half of the analyzed countries witnessed no substantial excess deaths versus pre-pandemic levels, while the other half suffered major death tolls.

The Evolution of Excess Deaths in the United States During the First 2 Years of the COVID-19 Pandemic.

Understanding consequences of the COVID-19 pandemic requires information on the excess mortality resulting from it. Multiple studies have examined excess deaths during the pandemic's initial stages, but how these have changed over time is unclear. National- and state-level death counts and population data from 2009 to 2022 were used in this analysis to evaluate excess fatalities from March 2020 to February 2021 and March 2021 to February 2022, with deaths from earlier years used to project baseline counts. The outcomes were total, group-specific, cause-specific, and age-by-cause excess fatalities, and numbers and percentages directly involving COVID-19. Excess deaths declined from 655,735 (95% confidence interval: 619,028, 691,980) during the first pandemic year to 586,505 (95% confidence interval: 532,823, 639,205) in the second. The reductions were particularly large for Hispanics, Blacks, Asians, seniors, and residents of states with high vaccination rates. Excess deaths increased from the first to second year for persons younger than 65 years and in low-vaccination states. Excess mortality from some diseases declined, but those from alcohol, drug, vehicle, and homicide causes likely increased between the first and second pandemic year, especially for prime-age and younger individuals. The share of excess fatalities involving COVID-19 decreased modestly over time, with little change in its role as an underlying versus contributing cause of death.

Undiagnosed Pulmonary Tuberculosis (TB) and Coronavirus Disease 2019 (COVID-19) in Adults Dying at Home in a High-TB-Burden Setting, Before and During Pandemic COVID-19: An Autopsy Study.

BACKGROUND: Missing or undiagnosed patients with tuberculosis (TB) or coronavirus disease 2019 (COVID-19) are of concern. Identifying both infections in patients with no diagnosis prior to death contributes to understanding the burden of disease. To confirm reports of global reduction in TB incidence, a 2012 autopsy study of adults dying at home of natural causes in a high-TB-burden setting was repeated, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) assessments after the first COVID-19 surge in South Africa. METHODS: Adult decedents who died at home with insufficient information to determine cause of death, no recent hospitalization, and no current antemortem TB or COVID-19 diagnosis were identified between March 2019 and October 2020 with a 4-month halt during lockdown. A standardized verbal autopsy followed by minimally invasive needle autopsy (MIA) was performed. Biopsies were taken for histopathology from liver, bilateral brain and lung; bronchoalveolar lavage fluid was collected for Xpert (MTB/RIF) and mycobacterial culture, and blood for human immunodeficiency virus (HIV) polymerase chain reaction (PCR) testing. After the start of the COVID-19 pandemic, a nasopharyngeal swab and lung tissue were subjected to SARS-CoV-2 PCR testing. RESULTS: Sixty-six MIAs were completed in 25 men and 41 women (median age, 60 years); 68.2% had antemortem respiratory symptoms and 30.3% were people with HIV. Overall, TB was diagnosed in 11 of 66 (16.7%) decedents, and 14 of 41 (34.1%) in the COVID-19 pandemic were SARS-CoV-2 positive. CONCLUSIONS: Undiagnosed TB in adults dying at home has decreased but remains unacceptably high. Forty percent of decedents had undiagnosed COVID-19, suggesting that estimates of excess deaths may underestimate the impact of SARS-CoV-2 on mortality.