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Ahrens KA, Rossen LM, Milkowski C, Gelsinger C, Ziller E. Excess deaths associated with COVID-19 by rurality and demographic factors in the United States. J Rural Health 2024; 40:491-499. [PMID: 38082546 PMCID: PMC11164822 DOI: 10.1111/jrh.12815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/21/2023] [Accepted: 11/30/2023] [Indexed: 06/12/2024]
Abstract
PURPOSE To estimate percent excess deaths during the COVID-19 pandemic by rural-urban residence in the United States and to describe rural-urban disparities by age, sex, and race/ethnicity. METHODS Using US mortality data, we used overdispersed Poisson regression models to estimate monthly expected death counts by rurality of residence, age group, sex, and race/ethnicity, and compared expected death counts with observed deaths. We then summarized excess deaths over 6 6-month time periods. FINDINGS There were 16.9% (95% confidence interval [CI]: 16.8, 17.0) more deaths than expected between March 2020 and February 2023. The percent excess varied by rurality (large central metro: 18.2% [18.1, 18.4], large fringe metro: 15.6% [15.5, 15.8], medium metro: 18.1% [18.0, 18.3], small metro: 15.5% [15.3, 15.7], micropolitan rural: 16.3% [16.1, 16.5], and noncore rural: 15.8% [15.6, 16.1]). The percent excess deaths were 20.2% (20.1, 20.3) for males and 13.6% (13.5, 13.7) for females, and highest for Hispanic persons (49% [49.0, 49.6]), followed by non-Hispanic Black persons (28% [27.5, 27.9]) and non-Hispanic White persons (12% [11.6, 11.8]). The 6-month time periods with the highest percent excess deaths for large central metro areas were March 2020-August 2020 and September 2020-February 2021; for all other areas, these time periods were September 2020-February 2021 and September 2021-February 2022. CONCLUSION Percent excess deaths varied by rurality, age group, sex, race/ethnicity, and time period. Monitoring excess deaths by rurality may be useful in assessing the impact of the pandemic over time, as rural-urban patterns appear to differ.
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Affiliation(s)
- Katherine A. Ahrens
- Muskie School of Public Service, University of Southern Maine, Portland, Maine, USA
| | - Lauren M. Rossen
- National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland, USA
| | - Carly Milkowski
- Muskie School of Public Service, University of Southern Maine, Portland, Maine, USA
| | - Catherine Gelsinger
- Muskie School of Public Service, University of Southern Maine, Portland, Maine, USA
| | - Erika Ziller
- Muskie School of Public Service, University of Southern Maine, Portland, Maine, USA
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Meyer D, Lowensen K, Perrin N, Moore A, Mehta SH, Himmelfarb CR, Inglesby TV, Jennings JM, Mueller AK, LaRicci JN, Gallo W, Bocek AP, Farley JE. An evaluation of the impact of social and structural determinants of health on forgone care during the COVID-19 pandemic in Baltimore, Maryland. PLoS One 2024; 19:e0302064. [PMID: 38739666 PMCID: PMC11090349 DOI: 10.1371/journal.pone.0302064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 03/27/2024] [Indexed: 05/16/2024] Open
Abstract
Evidence suggests that reductions in healthcare utilization, including forgone care, during the COVID-19 pandemic may be contributing towards excess morbidity and mortality. The objective of this study was to describe individual and community-level correlates of forgone care during the COVID-19 pandemic. We conducted a cross-sectional, secondary data analysis of participants (n = 2,003) who reported needing healthcare in two population-representative surveys conducted in Baltimore, MD in 2021 and 2021-2022. Abstracted data included the experience of forgone care, socio-demographic data, comorbidities, financial strain, and community of residence. Participant's community of residence were linked with data acquired from the Baltimore Neighborhood Indicators Alliance relevant to healthcare access and utilization, including walkability and internet access, among others. The data were analyzed using weighted random effects logistic regression. Individual-level factors found to be associated with increased odds for forgone care included individuals age 35-49 (compared to 18-34), female sex, experiencing housing insecurity during the pandemic, and the presence of functional limitations and mental illness. Black/African American individuals were found to have reduced odds of forgone care, compared to any other race. No community-level factors were significant in the multilevel analyses. Moving forward, it will be critical that health systems identify ways to address any barriers to care that populations might be experiencing, such as the use of mobile health services or telemedicine platforms. Additionally, public health emergency preparedness planning efforts must account for the unique needs of communities during future crises, to ensure that their health needs can continue to be met. Finally, additional research is needed to better understand how healthcare access and utilization practices have changed during versus before the pandemic.
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Affiliation(s)
- Diane Meyer
- Center for Infectious Disease and Nursing Innovation, Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America
- Center for Health Security, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Kelly Lowensen
- Center for Infectious Disease and Nursing Innovation, Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America
| | - Nancy Perrin
- Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America
| | - Ayana Moore
- FHI 360, Durham, NC, United States of America
| | - Shruti H. Mehta
- Department of Epidemiology, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Cheryl R. Himmelfarb
- Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America
| | - Thomas V. Inglesby
- Center for Health Security, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Jacky M. Jennings
- Department of Pediatrics, Johns Hopkins University, School of Medicine, Baltimore, MD, United States of America
| | - Alexandra K. Mueller
- Department of Pediatrics, Johns Hopkins University, School of Medicine, Baltimore, MD, United States of America
| | - Jessica N. LaRicci
- Center for Infectious Disease and Nursing Innovation, Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America
| | - Woudase Gallo
- Center for Infectious Disease and Nursing Innovation, Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America
| | - Adam P. Bocek
- Center for Infectious Disease and Nursing Innovation, Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America
| | - Jason E. Farley
- Center for Infectious Disease and Nursing Innovation, Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America
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Maduro G, Li W, Huynh M, Bernard-Davila B, Gould LH, Van Wye G. Descriptive study of causes of death and COVID-19-associated morbidities from the New York City electronic death record: first wave of the pandemic March-July 2020. BMJ Open 2024; 14:e072441. [PMID: 38569678 PMCID: PMC11146393 DOI: 10.1136/bmjopen-2023-072441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 02/27/2024] [Indexed: 04/05/2024] Open
Abstract
OBJECTIVE Assessing excess deaths from benchmarks across causes of death during the first wave of the COVID-19 pandemic and identifying morbidities most frequently mentioned alongside COVID-19 deaths in the death record. METHODS Descriptive study of death records between 11 March 2020 and 27 July 2020, from the New York City Bureau of Vital Statistics. Mortality counts and percentages were compared with the average for the same calendar period of the previous 2 years. Distributions of morbidities from among forty categories of conditions were generated citywide and by sex, race/ethnicity and four age groups. Causes of death were assumed to follow Poisson processes for Z-score construction. RESULTS Within the study period, 46 563 all-cause deaths were reported; 132.9% higher than the average for the same period of the previous 2 years (19 989). Of those 46 563 records, 19 789 (42.5%) report COVID-19 as underlying cause of death. COVID-19 was the most prevalent cause across all demographics, with respiratory conditions (prominently pneumonia), hypertension and diabetes frequently mentioned morbidities. Black non-Hispanics had greater proportions of mentions of pneumonia, hypertension, and diabetes. Hispanics had the largest proportion of COVID-19 deaths (52.9%). Non-COVID-19 excess deaths relative to the previous 2-year averages were widely reported. CONCLUSION Mortality directly due to COVID-19 was accompanied by significant increases across most other causes from their reference averages, potentially suggesting a sizable COVID-19 death undercount. Indirect effects due to COVID-19 may partially account for some increases, but findings are hardly dispositive. Unavailability of vaccines for the time period precludes any impact over excess deaths. Respiratory and cardiometabolic-related conditions were most frequently reported among COVID-19 deaths across demographic characteristics.
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Affiliation(s)
- Gil Maduro
- Bureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, New York, USA
| | - Wenhui Li
- Bureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, New York, USA
| | - Mary Huynh
- Institute for State and Local Governance, City University of New York, New York, New York, USA
| | - Blanca Bernard-Davila
- Bureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, New York, USA
| | - L Hannah Gould
- Bureau of Epidemiologic Services, New York City Department of Health and Mental Hygiene, New York, New York, USA
| | - Gretchen Van Wye
- Assistant Commissioner, Bureau of Vital Statistics, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, New York, USA
- Department of Sociomedical Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
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Paglino E, Lundberg DJ, Wrigley-Field E, Zhou Z, Wasserman JA, Raquib R, Chen YH, Hempstead K, Preston SH, Elo IT, Glymour MM, Stokes AC. Excess natural-cause mortality in US counties and its association with reported COVID-19 deaths. Proc Natl Acad Sci U S A 2024; 121:e2313661121. [PMID: 38300867 PMCID: PMC10861891 DOI: 10.1073/pnas.2313661121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 12/06/2023] [Indexed: 02/03/2024] Open
Abstract
In the United States, estimates of excess deaths attributable to the COVID-19 pandemic have consistently surpassed reported COVID-19 death counts. Excess deaths reported to non-COVID-19 natural causes may represent unrecognized COVID-19 deaths, deaths caused by pandemic health care interruptions, and/or deaths from the pandemic's socioeconomic impacts. The geographic and temporal distribution of these deaths may help to evaluate which explanation is most plausible. We developed a Bayesian hierarchical model to produce monthly estimates of excess natural-cause mortality for US counties over the first 30 mo of the pandemic. From March 2020 through August 2022, 1,194,610 excess natural-cause deaths occurred nationally [90% PI (Posterior Interval): 1,046,000 to 1,340,204]. A total of 162,886 of these excess natural-cause deaths (90% PI: 14,276 to 308,480) were not reported to COVID-19. Overall, 15.8 excess deaths were reported to non-COVID-19 natural causes for every 100 reported COVID-19 deaths. This number was greater in nonmetropolitan counties (36.0 deaths), the West (Rocky Mountain states: 31.6 deaths; Pacific states: 25.5 deaths), and the South (East South Central states: 26.0 deaths; South Atlantic states: 25.0 deaths; West South Central states: 24.2 deaths). In contrast, reported COVID-19 death counts surpassed estimates of excess natural-cause deaths in metropolitan counties in the New England and Middle Atlantic states. Increases in reported COVID-19 deaths correlated temporally with increases in excess deaths reported to non-COVID-19 natural causes in the same and/or prior month. This suggests that many excess deaths reported to non-COVID-19 natural causes during the first 30 mo of the pandemic in the United States were unrecognized COVID-19 deaths.
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Affiliation(s)
- Eugenio Paglino
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA19104
| | - Dielle J. Lundberg
- Department of Global Health, Boston University School of Public Health, Boston, MA02118
- Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA98195
| | - Elizabeth Wrigley-Field
- Department of Sociology and Minnesota Population Center, University of Minnesota, Minneapolis, MN55455
| | - Zhenwei Zhou
- Department of Biostatistics, Boston University School of Public Health, Boston, MA02118
| | | | - Rafeya Raquib
- Department of Global Health, Boston University School of Public Health, Boston, MA02118
| | - Yea-Hung Chen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA94158
| | | | - Samuel H. Preston
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA19104
| | - Irma T. Elo
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA19104
| | - M. Maria Glymour
- Department of Epidemiology, Boston University School of Public Health, Boston, MA02118
| | - Andrew C. Stokes
- Department of Global Health, Boston University School of Public Health, Boston, MA02118
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Pothisiri W, Prasitsiriphon O, Apakupakul J, Ploddi K. Gender differences in estimated excess mortality during the COVID-19 pandemic in Thailand. BMC Public Health 2023; 23:1900. [PMID: 37784059 PMCID: PMC10544589 DOI: 10.1186/s12889-023-16828-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 09/24/2023] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND There is a limited body of research specifically examining gender inequality in excess mortality and its variations across age groups and geographical locations during the COVID-19 pandemic. This study aims to fill this gap by analyzing the patterns of gender inequality in excess all-cause mortality in Thailand during the COVID-19 pandemic. METHODS Data pertaining to all-cause deaths and population between January 1, 2010, and December 31, 2021, were obtained from Thailand's Bureau of Registration Administration. A seasonal autoregressive integrated moving average (SARIMA) technique was used to estimate excess mortality during the pandemic between January 2020 to December 2021. Gender differential excess mortality was measured as the difference in age-standardized mortality rates between men and women. RESULTS Our SARIMA-based estimate of all-cause mortality in Thailand during the COVID-19 pandemic amounted to 1,032,921 deaths, with COVID-19-related fatalities surpassing official figures by 1.64 times. The analysis revealed fluctuating patterns of excess and deficit in all-cause mortality rates across different phases of the pandemic, as well as among various age groups and regions. In 2020, the most pronounced gender disparity in excess all-cause mortality emerged in April, with 4.28 additional female deaths per 100,000, whereas in 2021, the peak gender gap transpired in August, with 7.52 more male deaths per 100,000. Individuals in the 80 + age group exhibited the largest gender gap for most of the observed period. Gender differences in excess mortality were uniform across regions and over the period observed. Bangkok showed the highest gender disparity during the peak of the fourth wave, with 24.18 more male deaths per 100,000. CONCLUSION The findings indicate an overall presence of gender inequality in excess mortality during the COVID-19 pandemic in Thailand, observed across age groups and regions. These findings highlight the need for further attention to be paid to gender disparities in mortality and call for targeted interventions to address these disparities.
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Affiliation(s)
- Wiraporn Pothisiri
- College of Population Studies, Chulalongkorn University, Bangkok, Thailand
| | | | - Jutarat Apakupakul
- Division of Epidemiology, Department of Disease Control, Ministry of Public Health, Nontaburi, Thailand
| | - Kritchavat Ploddi
- Division of Epidemiology, Department of Disease Control, Ministry of Public Health, Nontaburi, Thailand
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Chen R, Charpignon ML, Raquib RV, Wang J, Meza E, Aschmann HE, DeVost MA, Mooney A, Bibbins-Domingo K, Riley AR, Kiang MV, Chen YH, Stokes AC, Glymour MM. Excess Mortality With Alzheimer Disease and Related Dementias as an Underlying or Contributing Cause During the COVID-19 Pandemic in the US. JAMA Neurol 2023; 80:919-928. [PMID: 37459088 PMCID: PMC10352932 DOI: 10.1001/jamaneurol.2023.2226] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Accepted: 04/27/2023] [Indexed: 07/20/2023]
Abstract
Importance Adults with Alzheimer disease and related dementias (ADRD) are particularly vulnerable to the direct and indirect effects of the COVID-19 pandemic. Deaths associated with ADRD increased substantially in pandemic year 1. It is unclear whether mortality associated with ADRD declined when better prevention strategies, testing, and vaccines became widely available in year 2. Objective To compare pandemic-era excess deaths associated with ADRD between year 1 and year 2 overall and by age, sex, race and ethnicity, and place of death. Design, Setting, and Participants This time series analysis used all death certificates of US decedents 65 years and older with ADRD as an underlying or contributing cause of death from January 2014 through February 2022. Exposure COVID-19 pandemic era. Main Outcomes and Measures Pandemic-era excess deaths associated with ADRD were defined as the difference between deaths with ADRD as an underlying or contributing cause observed from March 2020 to February 2021 (year 1) and March 2021 to February 2022 (year 2) compared with expected deaths during this period. Expected deaths were estimated using data from January 2014 to February 2020 fitted with autoregressive integrated moving average models. Results Overall, 2 334 101 death certificates were analyzed. A total of 94 688 (95% prediction interval [PI], 84 192-104 890) pandemic-era excess deaths with ADRD were estimated in year 1 and 21 586 (95% PI, 10 631-32 450) in year 2. Declines in ADRD-related deaths in year 2 were substantial for every age, sex, and racial and ethnic group evaluated. Pandemic-era ADRD-related excess deaths declined among nursing home/long-term care residents (from 34 259 [95% PI, 25 819-42 677] in year 1 to -22 050 [95% PI, -30 765 to -13 273] in year 2), but excess deaths at home remained high (from 34 487 [95% PI, 32 815-36 142] in year 1 to 28 804 [95% PI, 27 067-30 571] in year 2). Conclusions and Relevance This study found that large increases in mortality with ADRD as an underlying or contributing cause of death occurred in COVID-19 pandemic year 1 but were largely mitigated in pandemic year 2. The most pronounced declines were observed for deaths in nursing home/long-term care settings. Conversely, excess deaths at home and in medical facilities remained high in year 2.
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Affiliation(s)
- Ruijia Chen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
| | - Marie-Laure Charpignon
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge
| | - Rafeya V. Raquib
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts
| | - Jingxuan Wang
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
| | - Erika Meza
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
| | - Hélène E. Aschmann
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
| | - Michelle A. DeVost
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
| | - Alyssa Mooney
- Institute for Health Policy Studies, University of California, San Francisco, San Francisco
| | - Kirsten Bibbins-Domingo
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
- Department of Medicine, University of California, San Francisco, San Francisco
- Editor in Chief, JAMA
| | - Alicia R. Riley
- Department of Sociology, University of California, Santa Cruz, Santa Cruz
| | - Mathew V. Kiang
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
| | - Yea-Hung Chen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
| | - Andrew C. Stokes
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts
| | - M. Maria Glymour
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
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Bumburidi Y, Dzhalimbekova A, Malisheva M, Moolenaar RL, Horth R, Singer D, Otorbaeva D. Excess deaths directly and indirectly attributable to COVID-19 using routinely reported mortality data, Bishkek, Kyrgyzstan, 2020: a cross-sectional study. BMJ Open 2023; 13:e069521. [PMID: 37433726 DOI: 10.1136/bmjopen-2022-069521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/13/2023] Open
Abstract
OBJECTIVES Studies on excess deaths (ED) show that reported deaths from COVID-19 underestimate death. To understand mortality for improved pandemic preparedness, we estimated ED directly and indirectly attributable to COVID-19 and ED by age groups. DESIGN Cross-sectional study using routinely reported individual deaths data. SETTINGS The 21 health facilities in Bishkek that register all city deaths. PARTICIPANTS Residents of Bishkek who died in the city from 2015 to 2020. OUTCOME MEASURE We report weekly and cumulative ED by age, sex and causes of death for 2020. EDs are the difference between observed and expected deaths. Expected deaths were calculated using the historical average and the upper bound of the 95% CI from 2015 to 2019. We calculated the percentage of deaths above expected using the upper bound of the 95% CI of expected deaths. COVID-19 deaths were laboratory confirmed (U07.1) or probable (U07.2 or unspecified pneumonia). RESULTS Of 4660 deaths in 2020, we estimated 840-1042 ED (79-98 ED per 100 000 people). Deaths were 22% greater than expected. EDs were greater for men (28%) than for women (20%). EDs were observed in all age groups, with the highest ED (43%) among people 65-74 years of age. Hospital deaths were 45% higher than expected. During peak mortality (1 July -21 July), weekly ED was 267% above expected, and ED by disease-specific cause of death were above expected: 193% for ischaemic heart diseases, 52% for cerebrovascular diseases and 421% for lower respiratory diseases. COVID-19 was directly attributable to 69% of ED. CONCLUSION Deaths directly and indirectly associated with the COVID-19 pandemic were markedly higher than reported, especially for older populations, in hospital settings, and during peak weeks of SARS-CoV-2 transmission. These ED estimates can support efforts to prioritise support for persons at greatest risk of dying during surges.
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Affiliation(s)
- Yekaterina Bumburidi
- Division of Global Health Protection, Central Asia Office, US Centers for Disease Control and Prevention, Almaty, Kazakhstan
| | - Altynai Dzhalimbekova
- Office of Prevention of Infectious, Parasitic Diseases and Epidemiological Surveillance, State Sanitary Surveillance and Disease Prevention Department, Bishkek, Kyrgyzstan
| | - Marina Malisheva
- Office of Prevention of Infectious, Parasitic Diseases and Epidemiological Surveillance, State Sanitary Surveillance and Disease Prevention Department, Bishkek, Kyrgyzstan
- Central Asia Field Epidemiology Training Program, Bishkek, Kyrgyzstan
| | - Ronald L Moolenaar
- Division of Global Health Protection, US Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Roberta Horth
- Division of Global Health Protection, Central Asia Office, US Centers for Disease Control and Prevention, Almaty, Kazakhstan
- Central Asia Field Epidemiology Training Program, Bishkek, Kyrgyzstan
| | - Daniel Singer
- Division of Global Health Protection, Central Asia Office, US Centers for Disease Control and Prevention, Almaty, Kazakhstan
| | - Dinagul Otorbaeva
- Office of Prevention of Infectious, Parasitic Diseases and Epidemiological Surveillance, State Sanitary Surveillance and Disease Prevention Department, Bishkek, Kyrgyzstan
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8
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Paglino E, Lundberg DJ, Zhou Z, Wasserman JA, Raquib R, Luck AN, Hempstead K, Bor J, Preston SH, Elo IT, Stokes AC. Monthly excess mortality across counties in the United States during the COVID-19 pandemic, March 2020 to February 2022. SCIENCE ADVANCES 2023; 9:eadf9742. [PMID: 37352359 PMCID: PMC10289647 DOI: 10.1126/sciadv.adf9742] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 05/18/2023] [Indexed: 06/25/2023]
Abstract
Excess mortality is the difference between expected and observed mortality in a given period and has emerged as a leading measure of the COVID-19 pandemic's mortality impact. Spatially and temporally granular estimates of excess mortality are needed to understand which areas have been most impacted by the pandemic, evaluate exacerbating factors, and inform response efforts. We estimated all-cause excess mortality for the United States from March 2020 through February 2022 by county and month using a Bayesian hierarchical model trained on data from 2015 to 2019. An estimated 1,179,024 excess deaths occurred during the first 2 years of the pandemic (first: 634,830; second: 544,194). Overall, excess mortality decreased in large metropolitan counties but increased in nonmetropolitan counties. Despite the initial concentration of mortality in large metropolitan Northeastern counties, nonmetropolitan Southern counties had the highest cumulative relative excess mortality by July 2021. These results highlight the need for investments in rural health as the pandemic's rural impact grows.
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Affiliation(s)
- Eugenio Paglino
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Dielle J. Lundberg
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
- Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA, USA
| | - Zhenwei Zhou
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
| | | | - Rafeya Raquib
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
| | - Anneliese N. Luck
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jacob Bor
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
| | - Samuel H. Preston
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Irma T. Elo
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew C. Stokes
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
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Ledesma JR, Isaac CR, Dowell SF, Blazes DL, Essix GV, Budeski K, Bell J, Nuzzo JB. Evaluation of the Global Health Security Index as a predictor of COVID-19 excess mortality standardised for under-reporting and age structure. BMJ Glob Health 2023; 8:e012203. [PMID: 37414431 PMCID: PMC10335545 DOI: 10.1136/bmjgh-2023-012203] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/29/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND Previous studies have observed that countries with the strongest levels of pandemic preparedness capacities experience the greatest levels of COVID-19 burden. However, these analyses have been limited by cross-country differentials in surveillance system quality and demographics. Here, we address limitations of previous comparisons by exploring country-level relationships between pandemic preparedness measures and comparative mortality ratios (CMRs), a form of indirect age standardisation, of excess COVID-19 mortality. METHODS We indirectly age standardised excess COVID-19 mortality, from the Institute for Health Metrics and Evaluation modelling database, by comparing observed total excess mortality to an expected age-specific COVID-19 mortality rate from a reference country to derive CMRs. We then linked CMRs with data on country-level measures of pandemic preparedness from the Global Health Security (GHS) Index. These data were used as input into multivariable linear regression analyses that included income as a covariate and adjusted for multiple comparisons. We conducted a sensitivity analysis using excess mortality estimates from WHO and The Economist. RESULTS The GHS Index was negatively associated with excess COVID-19 CMRs (table 2; β= -0.21, 95% CI= -0.35 to -0.08). Greater capacities related to prevention (β= -0.11, 95% CI= -0.22 to -0.00), detection (β= -0.09, 95% CI= -0.19 to -0.00), response (β = -0.19, 95% CI= -0.36 to -0.01), international commitments (β= -0.17, 95% CI= -0.33 to -0.01) and risk environments (β= -0.30, 95% CI= -0.46 to -0.15) were each associated with lower CMRs. Results were not replicated using excess mortality models that rely more heavily on reported COVID-19 deaths (eg, WHO and The Economist). CONCLUSION The first direct comparison of COVID-19 excess mortality rates across countries accounting for under-reporting and age structure confirms that greater levels of preparedness were associated with lower excess COVID-19 mortality. Additional research is needed to confirm these relationships as more robust national-level data on COVID-19 impact become available.
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Affiliation(s)
- Jorge Ricardo Ledesma
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA
| | | | - Scott F Dowell
- Bill & Melinda Gates Foundation, Seattle, Washington, USA
| | - David L Blazes
- Bill & Melinda Gates Foundation, Seattle, Washington, USA
| | | | | | | | - Jennifer B Nuzzo
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA
- Pandemic Center, Brown University School of Public Health, Providence, Rhode Island, USA
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Paglino E, Lundberg DJ, Zhou Z, Wasserman JA, Raquib R, Hempstead K, Preston SH, Elo IT, Stokes AC. Differences Between Reported COVID-19 Deaths and Estimated Excess Deaths in Counties Across the United States, March 2020 to February 2022. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.16.23284633. [PMID: 36712059 PMCID: PMC9882565 DOI: 10.1101/2023.01.16.23284633] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Accurate and timely tracking of COVID-19 deaths is essential to a well-functioning public health surveillance system. The extent to which official COVID-19 death tallies have captured the true toll of the pandemic in the United States is unknown. In the current study, we develop a Bayesian hierarchical model to estimate monthly excess mortality in each county over the first two years of the pandemic and compare these estimates to the number of deaths officially attributed to Covid-19 on death certificates. Overall, we estimated that 268,176 excess deaths were not reported as Covid-19 deaths during the first two years of the Covid-19 pandemic, which represented 23.7% of all excess deaths that occurred. Differences between excess deaths and reported COVID-19 deaths were substantial in both the first and second year of the pandemic. Excess deaths were less likely to be reported as COVID-19 deaths in the Mountain division, in the South, and in nonmetro counties. The number of excess deaths exceeded COVID-19 deaths in all Census divisions except for the New England and Middle Atlantic divisions where there were more COVID-19 deaths than excess deaths in large metro areas and medium or small metro areas. Increases in excess deaths not assigned to COVID-19 followed similar patterns over time to increases in reported COVID-19 deaths and typically preceded or occurred concurrently with increases in reported COVID-19 deaths. Estimates from this study can be used to inform targeting of resources to areas in which the true toll of the COVID-19 pandemic has been underestimated.
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Affiliation(s)
- Eugenio Paglino
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA
| | - Dielle J. Lundberg
- Department of Global Health, Boston University School of Public Health, Boston, MA
- Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA
| | - Zhenwei Zhou
- Department of Global Health, Boston University School of Public Health, Boston, MA
| | | | - Rafeya Raquib
- Department of Global Health, Boston University School of Public Health, Boston, MA
| | | | - Samuel H. Preston
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA
| | - Irma T. Elo
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA
| | - Andrew C. Stokes
- Department of Global Health, Boston University School of Public Health, Boston, MA
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11
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Paglino E, Lundberg DJ, Zhou Z, Wasserman JA, Raquib R, Luck AN, Hempstead K, Bor J, Preston SH, Elo IT, Stokes AC. Monthly excess mortality across counties in the United States during the Covid-19 pandemic, March 2020 to February 2022. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.04.23.22274192. [PMID: 35547848 PMCID: PMC9094106 DOI: 10.1101/2022.04.23.22274192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Excess mortality is the difference between expected and observed mortality in a given period and has emerged as a leading measure of the overall impact of the Covid-19 pandemic that is not biased by differences in testing or cause-of-death assignment. Spatially and temporally granular estimates of excess mortality are needed to understand which areas have been most impacted by the pandemic, evaluate exacerbating and mitigating factors, and inform response efforts, including allocating resources to affected communities. We estimated all-cause excess mortality for the United States from March 2020 through February 2022 by county and month using a Bayesian hierarchical model trained on data from 2015 to 2019. An estimated 1,159,580 excess deaths occurred during the first two years of the pandemic (first: 620,872; second: 538,708). Overall, excess mortality decreased in large metropolitan counties, but increased in nonmetro counties, between the first and second years of the pandemic. Despite the initial concentration of mortality in large metropolitan Northeast counties, beginning in February 2021, nonmetro South counties had the highest cumulative relative excess mortality. These results highlight the need for investments in rural health as the pandemic's disproportionate impact on rural areas continues to grow.
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Affiliation(s)
- Eugenio Paglino
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA
| | - Dielle J. Lundberg
- Department of Global Health, Boston University School of Public Health, Boston, MA
- Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA
| | - Zhenwei Zhou
- Department of Global Health, Boston University School of Public Health, Boston, MA
| | | | - Rafeya Raquib
- Department of Global Health, Boston University School of Public Health, Boston, MA
| | - Anneliese N. Luck
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA
| | | | - Jacob Bor
- Department of Global Health, Boston University School of Public Health, Boston, MA
| | - Samuel H. Preston
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA
| | - Irma T. Elo
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA
| | - Andrew C. Stokes
- Department of Global Health, Boston University School of Public Health, Boston, MA
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12
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Nguyen VH, Mould-Quevedo JF. Estimating the Impact of Influenza Vaccination on Acute and ICU Hospital Bed Usage in an Influenza Season under Endemic COVID-19 in the US. Vaccines (Basel) 2022; 10:vaccines10111908. [PMID: 36423004 PMCID: PMC9693626 DOI: 10.3390/vaccines10111908] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/04/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022] Open
Abstract
In 2021–2022, influenza vaccine coverage in the US dropped below pre-COVID-19 pandemic levels. Cocirculation of COVID-19 and influenza could place a substantial burden on hospital utilization in future seasons, particularly given the reduced exposure to influenza during the pandemic. We used a dynamic susceptible-exposed-infected-recovered model to simulate influenza transmission with varying influenza vaccine coverage against a background of COVID-19 circulation, in order to estimate acute and ICU hospital bed occupancy for both diseases. We evaluated two vaccine scenarios: egg-based quadrivalent influenza vaccine (QIVe) for all age groups or cell-based QIV (QIVc) for 0.5–64 year-olds with adjuvanted QIV (aQIV) for ≥65 year-olds. ICU bed availability was more limiting than general hospital bed availability, with a vaccine coverage of ≥70% required to avoid negatively impacting ICU bed availability in a high-incidence influenza season. The timing of disease peaks was a key factor together with vaccine coverage, with a difference of ≥50 days needed between peak influenza and COVID-19 bed usage together with 65% influenza vaccine coverage to avoid negative impacts. QIVc + aQIV resulted in lower bed occupancy which, while not substantial, may be critical in very high hospital resource usage situations. In a situation with co-circulating influenza and COVID-19, proactive vaccination planning could help to avert overwhelming healthcare systems in upcoming influenza seasons.
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Markovic S, Salom I, Rodic A, Djordjevic M. Analyzing the GHSI puzzle of whether highly developed countries fared worse in COVID-19. Sci Rep 2022; 12:17711. [PMID: 36271249 PMCID: PMC9587258 DOI: 10.1038/s41598-022-22578-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 10/17/2022] [Indexed: 01/18/2023] Open
Abstract
Global Health Security Index (GHSI) categories are formulated to assess the capacity of world countries to deal with infectious disease risks. Thus, higher values of these indices were expected to translate to lower COVID-19 severity. However, it turned out to be the opposite, surprisingly suggesting that higher estimated country preparedness to epidemics may lead to higher disease mortality. To address this puzzle, we: (i) use a model-derived measure of COVID-19 severity; (ii) employ a range of statistical learning approaches, including non-parametric machine learning methods; (iii) consider the overall excess mortality, in addition to official COVID-19 fatality counts. Our results suggest that the puzzle is, to a large extent, an artifact of oversimplified data analysis and a consequence of misclassified COVID-19 deaths, combined with the higher median age of the population and earlier epidemics onset in countries with high GHSI scores.
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Affiliation(s)
- Sofija Markovic
- grid.7149.b0000 0001 2166 9385Quantitative Biology Group, Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | - Igor Salom
- grid.7149.b0000 0001 2166 9385Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade, Belgrade, Serbia
| | - Andjela Rodic
- grid.7149.b0000 0001 2166 9385Quantitative Biology Group, Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | - Marko Djordjevic
- grid.7149.b0000 0001 2166 9385Quantitative Biology Group, Faculty of Biology, University of Belgrade, Belgrade, Serbia
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14
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Antonio-Villa NE, Bello-Chavolla OY, Fermín-Martínez CA, Aburto JM, Fernández-Chirino L, Ramírez-García D, Pisanty-Alatorre J, González-Díaz A, Vargas-Vázquez A, Barquera S, Gutiérrez-Robledo LM, Seiglie JA. Socio-demographic inequalities and excess non-COVID-19 mortality during the COVID-19 pandemic: a data-driven analysis of 1 069 174 death certificates in Mexico. Int J Epidemiol 2022; 51:1711-1721. [PMID: 36174226 PMCID: PMC9619535 DOI: 10.1093/ije/dyac184] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 09/08/2022] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND In 2020, Mexico experienced one of the highest rates of excess mortality globally. However, the extent of non-COVID deaths on excess mortality, its regional distribution and the association between socio-demographic inequalities have not been characterized. METHODS We conducted a retrospective municipal and individual-level study using 1 069 174 death certificates to analyse COVID-19 and non-COVID-19 deaths classified by ICD-10 codes. Excess mortality was estimated as the increase in cause-specific mortality in 2020 compared with the average of 2015-2019, disaggregated by primary cause of death, death setting (in-hospital and out-of-hospital) and geographical location. Correlates of individual and municipal non-COVID-19 mortality were assessed using mixed effects logistic regression and negative binomial regression models, respectively. RESULTS We identified a 51% higher mortality rate (276.11 deaths per 100 000 inhabitants) compared with the 2015-2019 average period, largely attributable to COVID-19. Non-COVID-19 causes comprised one-fifth of excess deaths, with acute myocardial infarction and type 2 diabetes as the two leading non-COVID-19 causes of excess mortality. COVID-19 deaths occurred primarily in-hospital, whereas excess non-COVID-19 deaths occurred in out-of-hospital settings. Municipal-level predictors of non-COVID-19 excess mortality included levels of social security coverage, higher rates of COVID-19 hospitalization and social marginalization. At the individual level, lower educational attainment, blue-collar employment and lack of medical care assistance prior to death were associated with non-COVID-19 deaths. CONCLUSION Non-COVID-19 causes of death, largely chronic cardiometabolic conditions, comprised up to one-fifth of excess deaths in Mexico during 2020. Non-COVID-19 excess deaths occurred disproportionately out-of-hospital and were associated with both individual- and municipal-level socio-demographic inequalities.
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Affiliation(s)
- Neftali Eduardo Antonio-Villa
- Corresponding author. Division de Investigación, Instituto Nacional de Geriatría, Anillo Perif. 2767, San Jerónimo Lídice, La Magdalena Contreras, 10200 Mexico City, Mexico. E-mail:
| | | | - Carlos A Fermín-Martínez
- Division de Investigación, Instituto Nacional de Geriatría, Mexico City, Mexico,MD/PhD (PECEM) Program, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - José Manuel Aburto
- Leverhulme Centre for Demographic Science, Department of Sociology, University of Oxford, Oxford, United Kindom,Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, Odense, Denmark
| | - Luisa Fernández-Chirino
- Division de Investigación, Instituto Nacional de Geriatría, Mexico City, Mexico,Faculty of Chemistry, National Autonomous University of Mexico, Mexico City, Mexico
| | | | - Julio Pisanty-Alatorre
- Instituto Mexicano del Seguro Social, Mexico City, Mexico,Departamento de Salud Pública, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Armando González-Díaz
- Facultad de Ciencias Politicas Sociales y Sociales, National Autonomous University of Mexico, Mexico City, Mexico
| | - Arsenio Vargas-Vázquez
- Division de Investigación, Instituto Nacional de Geriatría, Mexico City, Mexico,MD/PhD (PECEM) Program, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Simón Barquera
- Health and Nutrition Research Center, National Institute of Public Health, Cuernavaca, Mexico
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15
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Brosi DN, Mays GP. Local Public Health System Capabilities and COVID-19 Death Rates. Public Health Rep 2022; 137:980-987. [PMID: 35634877 PMCID: PMC9357746 DOI: 10.1177/00333549221097660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVES Efforts to contain the health effects of the COVID-19 pandemic have achieved less success in the United States than in many comparable countries. Previous research documented wide variability in the capabilities of local public health systems to carry out core disease prevention and control activities, but it is unclear how this variability relates to COVID-19 control. Our study explored this relationship by using a nationally representative sample of 725 US communities. METHODS We used data collected from the National Longitudinal Survey of Public Health Systems to classify each community into 1 of 3 ordinal categories indicating limited, intermediate, or comprehensive public health system capabilities. We used 2-part generalized linear models to estimate the relationship between public health system capabilities and COVID-19 death rates while controlling population and community characteristics associated with COVID-19 risk. RESULTS Across 3 waves of the pandemic in 2020, we found a significant negative association between COVID-19 mortality and public health system capabilities. Compared with comprehensive public health systems, intermediate public health systems had an average of 4.97 to 19.02 more COVID-19 deaths per 100 000 residents, while limited public health systems had an average of 5.95 to 18.10 more COVID-19 deaths per 100 000 residents. CONCLUSION Overall, communities with stronger public health capabilities had significantly fewer deaths. Future initiatives to strengthen pandemic preparedness and reduce health disparities in the United States should focus on local public health system capabilities.
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Affiliation(s)
- Deena N. Brosi
- Department of Health Systems,
Management and Policy, Colorado School of Public Health, University of
Colorado–Anschutz Medical Campus, Aurora, CO, USA
| | - Glen P. Mays
- Department of Health Systems,
Management and Policy, Colorado School of Public Health, University of
Colorado–Anschutz Medical Campus, Aurora, CO, USA
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16
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Chen YH, Stokes AC, Aschmann HE, Chen R, DeVost S, Kiang MV, Koliwad S, Riley AR, Glymour MM, Bibbins-Domingo K. Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021. PNAS NEXUS 2022; 1:pgac079. [PMID: 35832865 PMCID: PMC9272175 DOI: 10.1093/pnasnexus/pgac079] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 05/27/2022] [Indexed: 02/06/2023]
Abstract
Excess mortality has exceeded reported deaths from Covid-19 during the pandemic. This gap may be attributable to deaths that occurred among individuals with undiagnosed Covid-19 infections or indirect consequences of the pandemic response such as interruptions in medical care; distinguishing these possibilities has implications for public health responses. In the present study, we examined patterns of excess mortality over time and by setting (in-hospital or out-of-hospital) and cause of death using death certificate data from California. The estimated number of excess natural-cause deaths from 2020 March 1 to 2021 February 28 (69,182) exceeded the number of Covid-19 diagnosed deaths (53,667) by 29%. Nearly half, 47.4% (32,775), of excess natural-cause deaths occurred out of the hospital, where only 28.6% (9,366) of excess mortality was attributed to Covid-19. Over time, increases or decreases in excess natural non-Covid-19 mortality closely mirrored increases or decreases in Covid-19 mortality. The time series were positively correlated in out-of-hospital settings, particularly at time lags when excess natural-cause deaths preceded reported Covid-19 deaths; for example, when comparing Covid-19 deaths to excess natural-cause deaths in the week prior, the correlation was 0.73. The strong temporal association of reported Covid-19 deaths with excess out-of-hospital deaths from other reported natural-cause causes suggests Covid-19 deaths were undercounted during the first year of the pandemic.
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Affiliation(s)
- Yea-Hung Chen
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Andrew C Stokes
- Department of Global Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Hélène E Aschmann
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Ruijia Chen
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Shelley DeVost
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Mathew V Kiang
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Suneil Koliwad
- Department of Medicine, and Diabetes Center, University of California, San Francisco, CA 94117, USA
| | - Alicia R Riley
- Department of Sociology, University of California, Santa Cruz, CA 95064, USA
| | - M Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Kirsten Bibbins-Domingo
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
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17
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Paglino E, Lundberg DJ, Cho A, Wasserman JA, Raquib R, Luck AN, Hempstead K, Bor J, Elo IT, Preston SH, Stokes AC. Excess all-cause mortality across counties in the United States, March 2020 to December 2021. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022. [PMID: 35547848 DOI: 10.1101/2022.06.29.222770652022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Official Covid-19 death counts have underestimated the mortality impact of the Covid-19 pandemic in the United States. Excess mortality, which compares observed deaths to deaths expected in the absence of the pandemic, is a useful measure for assessing the total effect of the pandemic on mortality levels. In the present study, we produce county-level estimates of excess mortality for 3,127 counties between March 2020 and December 2021. We fit two hierarchical linear models to county-level death rates from January 2015 to December 2019 and predict expected deaths for each month during the pandemic. We compare observed deaths to these estimates to obtain excess deaths for each county-month. An estimated 936,911 excess deaths occurred during 2020 and 2021, of which 171,168 (18.3%) were not assigned to Covid-19 on death certificates as an underlying cause of death. Urban counties in the Far West, Great Lakes, Mideast, and New England experienced a substantial mortality disadvantage in 2020, whereas rural counties in these regions had higher mortality in 2021. In the Southeast, Southwest, Rocky Mountain, and Plains regions, there was a rural mortality disadvantage in 2020, which was exacerbated in 2021. The proportion of excess deaths assigned to Covid-19 was lower in 2020 (76.3%) than in 2021 (87.0%), suggesting that a larger fraction of excess deaths was assigned to Covid-19 later in the pandemic. However, in rural areas and in the Southeast and Southwest a large share of excess deaths was still not assigned to Covid-19 during 2021. SIGNIFICANCE Deaths during the Covid-19 pandemic have been primarily monitored through death certificates containing reference to Covid-19. This approach has missed more than 170,000 deaths related to the pandemic between 2020 and 2021. While the ascertainment of Covid-19 deaths improved during 2021, the full effects of the pandemic still remained obscured in some regions. County-level estimates of excess mortality are useful for studying geographic inequities in the mortality burden associated with the pandemic and identifying specific regions where the full mortality burden was significantly underreported (i.e. Southeast). They can also be used to inform resource allocation decisions at the federal and state levels and encourage uptake of preventive measures in communities with low vaccine uptake.
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18
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Schwab N, Nienhold R, Henkel M, Baschong A, Graber A, Frank A, Mensah N, Koike J, Hernach C, Sachs M, Daun T, Zsikla V, Willi N, Junt T, Mertz KD. COVID-19 Autopsies Reveal Underreporting of SARS-CoV-2 Infection and Scarcity of Co-infections. Front Med (Lausanne) 2022; 9:868954. [PMID: 35492342 PMCID: PMC9046787 DOI: 10.3389/fmed.2022.868954] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 03/22/2022] [Indexed: 12/12/2022] Open
Abstract
Coronavirus disease 2019 (COVID-19) mortality can be estimated based on reliable mortality data. Variable testing procedures and heterogeneous disease course suggest that a substantial number of COVID-19 deaths is undetected. To address this question, we screened an unselected autopsy cohort for the presence of SARS-CoV-2 and a panel of common respiratory pathogens. Lung tissues from 62 consecutive autopsies, conducted during the first and second COVID-19 pandemic waves in Switzerland, were analyzed for bacterial, viral and fungal respiratory pathogens including SARS-CoV-2. SARS-CoV-2 was detected in 28 lungs of 62 deceased patients (45%), although only 18 patients (29%) were reported to have COVID-19 at the time of death. In 23 patients (37% of all), the clinical cause of death and/or autopsy findings together with the presence of SARS-CoV-2 suggested death due to COVID-19. Our autopsy results reveal a 16% higher SARS-CoV-2 infection rate and an 8% higher SARS-CoV-2 related mortality rate than reported by clinicians before death. The majority of SARS-CoV-2 infected patients (75%) did not suffer from respiratory co-infections, as long as they were treated with antibiotics. In the lungs of 5 patients (8% of all), SARS-CoV-2 was found, yet without typical clinical and/or autopsy findings. Our findings suggest that underreporting of COVID-19 contributes substantially to excess mortality. The small percentage of co-infections in SARS-CoV-2 positive patients who died with typical COVID-19 symptoms strongly suggests that the majority of SARS-CoV-2 infected patients died from and not with the virus.
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Affiliation(s)
- Nathalie Schwab
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Ronny Nienhold
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Maurice Henkel
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Albert Baschong
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Anne Graber
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Angela Frank
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Nadine Mensah
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Jacqueline Koike
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Claudia Hernach
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Melanie Sachs
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Till Daun
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Veronika Zsikla
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Niels Willi
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
| | - Tobias Junt
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Kirsten D. Mertz
- Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland
- University of Basel, Basel, Switzerland
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Caruntu A, Moraru L, Comaneanu R, Costache R, Farcasiu T, Scheau C, Costache D, Caruntu C. A combination of two regional flaps for the complex reconstruction after head and neck cancer surgery as an alternative approach during the COVID‑19 pandemic: A case report. Exp Ther Med 2022; 23:364. [PMID: 35493435 PMCID: PMC9019615 DOI: 10.3892/etm.2022.11291] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 03/18/2022] [Indexed: 11/06/2022] Open
Affiliation(s)
- Ana Caruntu
- Department of Oral and Maxillofacial Surgery, ‘Carol Davila’ Central Military Emergency University Hospital, Bucharest 010825, Romania
| | - Liliana Moraru
- Department of Oral and Maxillofacial Surgery, ‘Carol Davila’ Central Military Emergency University Hospital, Bucharest 010825, Romania
| | - Raluca Comaneanu
- Faculty of Dental Medicine, ‘Titu Maiorescu’ University, Bucharest 031593, Romania
| | - Raluca Costache
- Department of Gastroenterology, ‘Carol Davila’ Central Military Emergency University Hospital, Bucharest 010825, Romania
| | - Titus Farcasiu
- Department of Removable Prosthodontics, ‘Carol Davila’ University of Medicine and Pharmacy, Bucharest 010209, Romania
| | - Cristian Scheau
- Department of Physiology, ‘Carol Davila’ University of Medicine and Pharmacy, Bucharest 050474, Romania
| | - Daniel Costache
- Department of Dermatology, ‘Carol Davila’ Central Military Emergency Hospital, Bucharest 010825, Romania
| | - Constantin Caruntu
- Department of Physiology, ‘Carol Davila’ University of Medicine and Pharmacy, Bucharest 050474, Romania
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20
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Impact of the COVID-19 Pandemic on Pediatric Surgical Volume in Four Low- and Middle-Income Country Hospitals: Insights from an Interrupted Time Series Analysis. World J Surg 2022; 46:984-993. [PMID: 35267077 PMCID: PMC8908743 DOI: 10.1007/s00268-022-06503-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/13/2022] [Indexed: 12/24/2022]
Abstract
Background The impact of the COVID-19 pandemic on surgical care delivery in low- and middle-income countries (LMIC) has been challenging to assess due to a lack of data. This study examines the impact of COVID-19 on pediatric surgical volumes at four LMIC hospitals. Methods Retrospective and prospective pediatric surgical data collected at hospitals in Burkina Faso, Ecuador, Nigeria, and Zambia were reviewed from January 2019 to April 2021. Changes in surgical volume were assessed using interrupted time series analysis. Results 6078 total operations were assessed. Before the pandemic, overall surgical volume increased by 21 cases/month (95% CI 14 to 28, p < 0.001). From March to April 2020, the total surgical volume dropped by 32%, or 110 cases (95% CI − 196 to − 24, p = 0.014). Patients during the pandemic were younger (2.7 vs. 3.3 years, p < 0.001) and healthier (ASA I 69% vs. 66%, p = 0.003). Additionally, they experienced lower rates of post-operative sepsis (0.3% vs 1.5%, p < 0.001), surgical site infections (1.3% vs 5.8%, p < 0.001), and mortality (1.6% vs 3.1%, p < 0.001). Conclusions During the COVID-19 pandemic, children’s surgery in LMIC saw a sharp decline in total surgical volume by a third in the month following March 2020, followed by a slow recovery afterward. Patients were healthier with better post-operative outcomes during the pandemic, implying a widening disparity gap in surgical access and exacerbating challenges in addressing the large unmet burden of pediatric surgical disease in LMICs with a need for immediate mitigation strategies. Supplementary Information The online version contains supplementary material available at 10.1007/s00268-022-06503-2.
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Ackley CA, Lundberg DJ, Ma L, Elo IT, Preston SH, Stokes AC. County-level estimates of excess mortality associated with COVID-19 in the United States. SSM Popul Health 2022. [PMID: 35018297 DOI: 10.1101/2021.04.23.21255564] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2023] Open
Abstract
The COVID-19 pandemic in the U.S. has been largely monitored using death certificates containing reference to COVID-19. However, prior analyses reveal that a significant percentage of excess deaths associated with the pandemic were not directly assigned to COVID-19. In this study, we estimated a generalized linear model of expected mortality based on historical trends in deaths by county of residence between 2011 and 2019. We used the results of the model to generate estimates of excess mortality and excess deaths not assigned to COVID-19 in 2020 for 1470 county sets in the U.S. representing 3138 counties. Across the country, we estimated that 438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19. Some regions (Mideast, Great Lakes, New England, and Far West) reported the most excess deaths in large central metros, whereas other regions (Southwest, Southeast, Plains, and Rocky Mountains) reported the highest excess mortality in nonmetro areas. The proportion assigned to COVID-19 was lowest in large central metro areas (79.3%). Regionally, the proportion of excess deaths assigned to COVID-19 was lowest in the Southeast (81.6%), Southwest (82.6%), Far West (83.7%), and Rocky Mountains (86.7%). Across the regions, the number of excess deaths exceeded the number of directly assigned COVID-19 deaths in most counties. The exception to this pattern occurred in New England, which reported more directly assigned COVID-19 deaths than excess deaths in metro and nonmetro areas. Many county sets had substantial numbers of excess deaths that were not accounted for in direct COVID-19 death counts. Estimates of excess mortality at the local level can inform the allocation of resources to areas most impacted by the pandemic and contribute to positive behavior feedback loops, such as increases in mask-wearing and vaccine uptake.
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Affiliation(s)
| | - Dielle J Lundberg
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
| | - Lei Ma
- Department of Economics, Boston University, Boston, MA, USA
| | - Irma T Elo
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Samuel H Preston
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew C Stokes
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
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22
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Ackley CA, Lundberg DJ, Ma L, Elo IT, Preston SH, Stokes AC. County-level estimates of excess mortality associated with COVID-19 in the United States. SSM Popul Health 2022; 17:101021. [PMID: 35018297 PMCID: PMC8730693 DOI: 10.1016/j.ssmph.2021.101021] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 12/16/2021] [Accepted: 12/31/2021] [Indexed: 02/07/2023] Open
Abstract
The COVID-19 pandemic in the U.S. has been largely monitored using death certificates containing reference to COVID-19. However, prior analyses reveal that a significant percentage of excess deaths associated with the pandemic were not directly assigned to COVID-19. In this study, we estimated a generalized linear model of expected mortality based on historical trends in deaths by county of residence between 2011 and 2019. We used the results of the model to generate estimates of excess mortality and excess deaths not assigned to COVID-19 in 2020 for 1470 county sets in the U.S. representing 3138 counties. Across the country, we estimated that 438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19. Some regions (Mideast, Great Lakes, New England, and Far West) reported the most excess deaths in large central metros, whereas other regions (Southwest, Southeast, Plains, and Rocky Mountains) reported the highest excess mortality in nonmetro areas. The proportion assigned to COVID-19 was lowest in large central metro areas (79.3%). Regionally, the proportion of excess deaths assigned to COVID-19 was lowest in the Southeast (81.6%), Southwest (82.6%), Far West (83.7%), and Rocky Mountains (86.7%). Across the regions, the number of excess deaths exceeded the number of directly assigned COVID-19 deaths in most counties. The exception to this pattern occurred in New England, which reported more directly assigned COVID-19 deaths than excess deaths in metro and nonmetro areas. Many county sets had substantial numbers of excess deaths that were not accounted for in direct COVID-19 death counts. Estimates of excess mortality at the local level can inform the allocation of resources to areas most impacted by the pandemic and contribute to positive behavior feedback loops, such as increases in mask-wearing and vaccine uptake. 438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19. There was substantial heterogeneity in excess death rates across counties. The mortality impact of the Covid-19 pandemic was effectively hidden in many counties. The percent of excess deaths assigned to COVID-19 was lowest in the South and West. New England uniquely reported more direct COVID-19 deaths than excess deaths.
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Affiliation(s)
| | - Dielle J Lundberg
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
| | - Lei Ma
- Department of Economics, Boston University, Boston, MA, USA
| | - Irma T Elo
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Samuel H Preston
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew C Stokes
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
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Guimarães RM, Oliveira MPRPBD, Dutra VGP. Excess mortality according to group of causes in the first year of the COVID-19 pandemic in Brazil. REVISTA BRASILEIRA DE EPIDEMIOLOGIA 2022; 25:e220029. [DOI: 10.1590/1980-549720220029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 08/05/2022] [Indexed: 12/23/2022] Open
Abstract
ABSTRACT Objective: To estimate excess mortality by cause of death in Brazil and states in 2020. Methods: We estimated the expected number of deaths considering a linear trend analysis with the number of deaths between 2015 and 2019 for each group of causes and each federative unit. We calculated standardized mortality ratios (SMR) and 95% confidence intervals for each SMR assuming a Poisson distribution. We performed the analyses in the R program, version 4.1.3. Results: We observed a 19% excess in deaths in 2020 (SMR=1.19; 95%CI=1.18–1.20). The Infectious and Parasitic Diseases group stood out among the defined causes (SMR=4.80; 95%CI 4.78–4.82). The ill-defined causes showed great magnitude in this period (SMR=6.08; 95%CI 6.06–6.10). Some groups had lower-than-expected deaths: respiratory diseases (10% lower than expected) and external causes (4% lower than expected). In addition to the global analysis of the country, we identified significant heterogeneity among the federative units. States with the highest SMR are concentrated in the northern region, and those with the lowest SMR are concentrated in the southern and southeastern regions. Conclusion: Excess mortality occurs during the COVID-19 pandemic. This excess results not only from COVID-19 itself, but also from the social response and the management of the health system in responding to a myriad of causes that already had a trend pattern before it.
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Guimarães RM, Oliveira MPRPBD, Dutra VGP. Excesso de mortalidade segundo grupo de causas no primeiro ano de pandemia de COVID-19 no Brasil. REVISTA BRASILEIRA DE EPIDEMIOLOGIA 2022. [DOI: 10.1590/1980-549720220029.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
RESUMO Objetivo: Estimar o excesso de mortalidade segundo causa de óbito no Brasil e estados em 2020. Métodos: O número de óbitos esperado foi estimado considerando análise de tendência linear com o número de mortes entre os anos de 2015 e 2019, para cada grupo de causas e cada unidade da federação. Calculamos as razões de mortalidade padronizadas, e os intervalos com 95% de confiança para cada SMR foram calculados assumindo uma distribuição Poisson. As análises foram realizadas no programa R, versão 4.1.3. Resultados: Observamos um excesso de 19% nos óbitos em 2020 (SMR=1,19; IC=1,18–1,20). O grupo de Doenças Infecciosas e Parasitárias obteve maior destaque entre as causas definidas (SMR=4,80; IC95% 4,78–4,82). As causas mal definidas apresentaram grande magnitude neste período (SMR=6,08; IC95% 6,06–6,10). Há, ainda, grupos que apresentaram número de óbitos abaixo do esperado: doenças do aparelho respiratório (10% abaixo do esperado) e causas externas (4% abaixo do esperado). Além da análise global para o país, identificamos grande heterogeneidade entre as unidades da federação. Os estados com maiores SMR estão concentrados na região norte, e os que possuem menores SMR estão concentrados nas regiões sul e sudeste. Conclusões: Há um excesso de mortalidade ocorrendo durante a pandemia de COVID-19. Este excesso é resultado não apenas da COVID-19 em si, mas da resposta social e da gestão do sistema de saúde em responder a uma miríade de causas que já possuíam um ritmo de tendência anterior a ela.
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Luck AN, Preston SH, Elo IT, Stokes AC. The unequal burden of the Covid-19 pandemic: Capturing racial/ethnic disparities in US cause-specific mortality. SSM Popul Health 2021; 17:101012. [PMID: 34961843 PMCID: PMC8697426 DOI: 10.1016/j.ssmph.2021.101012] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 11/22/2021] [Accepted: 12/18/2021] [Indexed: 11/24/2022] Open
Abstract
Despite a growing body of literature focused on racial/ethnic disparities in Covid-19 mortality, few previous studies have examined the pandemic's impact on 2020 cause-specific mortality by race and ethnicity. This paper documents changes in mortality by underlying cause of death and race/ethnicity between 2019 and 2020. Using age-standardized death rates, we attribute changes for Black, Hispanic, and White populations to various underlying causes of death and show how these racial and ethnic patterns vary by age and sex. We find that although Covid-19 death rates in 2020 were highest in the Hispanic community, Black individuals faced the largest increase in all-cause mortality between 2019 and 2020. Exceptionally large increases in mortality from heart disease, diabetes, and external causes of death accounted for the adverse trend in all-cause mortality within the Black population. Within Black and White populations, percentage increases in all-cause mortality were similar for men and women, as well as for ages 25–64 and 65+. Among the Hispanic population, however, percentage increases in mortality were greatest for working-aged men. These findings reveal that the overall impact of the pandemic on racial/ethnic disparities in mortality was much larger than that captured by official Covid-19 death counts alone.
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Affiliation(s)
- Anneliese N Luck
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Samuel H Preston
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Irma T Elo
- Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew C Stokes
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
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