ArticleJAMA network open2021
Assessment of Excess Mortality and Household Income in Rural Bangladesh During the COVID-19 Pandemic in 2020.
Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Excess mortality during the COVID-19 pandemic in low-and lower-middle-income countries: a systematic review and meta-analysis.BMC public health · 2024Pooled it
- Do Mobile Phone Surveys Supplement Other Mortality Surveillance Methods? Results From a National Study in Bangladesh.Tropical medicine & international health : TM & IH · 2026Article
- Excess mortality during COVID-19 and prediction of mortality in Bangladesh: an analysis based on death records in urban graveyards.Journal of global health · 2025Article
- Excess mortality during COVID-19 pandemic in Bangladesh - evidence from a rural survey.Journal of global health · 2024Article
- Article
- Excess mortality during the COVID-19 pandemic (2020-2021) in an urban community of Bangladesh.PLOS global public health · 2023Article
- Relationship between initial symptoms and the prognosis, sex, and demographic area of patients with COVID-19.Frontiers in medicine · 2022Article
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7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: A slow or incomplete civil registry makes it impossible to determine excess mortality due to COVID-19 and difficult to inform policy. Objective: To quantify the association of the COVID-19 pandemic with excess mortality and household income in rural Bangladesh in 2020. Design, Setting, and Participants: This repeated survey study is based on an in-person census followed by 2 rounds of telephone calls. Data were collected from a sample of 135 villages within a densely populated 350-km2 rural area of Bangladesh. Household data were obtained first in person and subsequently over the telephone. For the analysis, mortality data were stratified by month, age, sex, and household education. Mortality rates were modeled by bayesian multilevel regression, and the strata were aggregated to the population by poststratification. Data analysis was performed from February to April 2021. Exposures: Date and cause of any changes in household composition, as well as changes in income and food availability. Main Outcomes and Measures: Mortality rates were compared for 2019 and 2020, both without adjustment and after adjustment for nonresponse and differences in demographic variables between surveys. Income and food availability reported for January, May, and November 2020 were also compared. Results: Enumerators collected data from an initial 16 054 households in January 2020; 14 551 households (91%) responded when contacted again by telephone in May 2020, and 11 933 households (74%)responded when reached again over the telephone in November 2020, for a total of 58 806 individuals (29 726 female participants [50.5%]; mean [SD] age, 26.4 [19.8] years). A total of 276 deaths were reported between February and the end of October 2020 for the subset of the population that could be contacted twice over the telephone, slightly below the 289 deaths reported for the same population over the same period in 2019. After adjustment for survey nonresponse and poststratification, 2020 mortality changed by -8% (95% CI, -21% to 7%) compared with an annualized mortality of 6.1 deaths per 1000 individuals in 2019. However, in May 2020, salaried primary income earners reported a 40% decrease in monthly income (from 17 485 to 10 835 Bangladeshi Taka), and self-employed earners reported a 60% decrease in monthly income (23 083 to 8521 Bangladeshi Taka), with only a small recovery observed by November 2020. Conclusions and Relevance: In this study of households in rural Bangladesh, all-cause mortality was lower in 2020 compared with 2019. Restrictions imposed by the government may have limited the scale of the COVID-19 pandemic in rural areas, although economic data suggest that these restrictions need to be accompanied by expanded welfare programs.
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