# Excess mortality and underlying causes of death during the COVID-19 pandemic in rural Bangladesh: insights from the Matlab health and demographic surveillance system

**Authors:** Sayed Saidul Alam, Nur E Jannat Amee, Srizan Chowdhury, Md Mehedi Hasan, Chodziwadziwa Whiteson Kabudula, Jean Juste Harrisson Bashingwa, Md. Sharoardy Sagar, Munirul Alam Bhuiyan, M. Zahirul Haq, Beth A. Tippett Barr, Stephen Tollman, Syed Manzoor Ahmed Hanifi

PMC · DOI: 10.1186/s12963-025-00447-0 · 2026-03-19

## TL;DR

This study examines increased mortality and causes of death during the COVID-19 pandemic in rural Bangladesh, focusing on older adults with noncommunicable and respiratory diseases.

## Contribution

The study provides insights into excess mortality and underlying causes of death in rural Bangladesh during the pandemic using longitudinal health surveillance data.

## Key findings

- Crude mortality rates increased from 7.4 to 8.5 deaths per 1000 person-years during the pandemic.
- Mortality from respiratory diseases rose by 82% during the pandemic period.
- Older adults experienced a significant increase in mortality linked to noncommunicable and respiratory diseases.

## Abstract

Bangladesh, home to 165 million people, reported its first COVID-19 case in March 2020. This prompted a range of public health measures to control the epidemic. However, limited access to COVID-19 testing and incomplete or inaccurate death registration likely obscured the pandemic’s true impact. We use longitudinal data from the Matlab Health and Demographic Surveillance System (HDSS) in Bangladesh to assess excess mortality and underlying causes of death during the COVID-19 pandemic.

We analysed mortality among 299,775 individuals residing within the Matlab HDSS catchment area between January 1, 2018 and December 31, 2021. Crude mortality rates were compared between the Pre-COVID-19 (2018–2019) and COVID-19 (2020–2021) periods. Adjusted sub-distribution hazard ratios (SHR) were estimated using the Fine and Gray competing risk model. Causes of death were determined using the WHO 2016 Verbal Autopsy questionnaire with supplementary COVID-19 module. We assessed changes in the distribution of causes of death and calculated cause-specific mortality rates by period and sex.

Crude mortality rate increased to from 7.4 deaths per 1000 person-years in 2018–2019 (pre–COVID-19 period) to 8.5 deaths per 1000 person-years during the COVID-19 period (2020–2021). Among individuals aged 60 years and above, the COVID-19-related mortality rate was 3.5 deaths per 1000 person-years during the COVID-19 period. Overall mortality rate increased from 44.1 (95% CI: 42.4–45.9) deaths to 50.9 (95% CI: 49.1–52.7) deaths per 1000 person-years, corresponding to an adjusted SHR of 1.19 (95% CI: 1.12–1.25). Compared with the Pre-COVID-19 period, mortality attributable to non-communicable diseases (NCDs) increased by 11% (mortality rate ratio (MRR): 1.11; 95% CI: 1.04–1.18), while mortality from respiratory diseases increased by 82% (MRR: 1.82; 95% CI: 1.24–2.73) during the COVID-19 period.

During the COVID-19 period, mortality increased in rural Bangladesh, with the sharpest increase observed among older adults with noncommunicable and respiratory diseases. Future pandemic preparedness efforts should prioritise these high-risk subgroups to reduce adverse health outcomes and mortality.

The online version contains supplementary material available at 10.1186/s12963-025-00447-0.

## Linked entities

- **Diseases:** COVID-19 (MONDO:0100096)

## Full-text entities

- **Genes:** CMPK1 (cytidine/uridine monophosphate kinase 1) [NCBI Gene 51727] {aka CK, CMK, CMPK, UMK, UMP-CMPK, UMPK}
- **Diseases:** HDSS (OMIM:603663), IPS (MESH:C536271), NCDs (MESH:D000073296), MSS (MESH:D013132), infectious diseases (MESH:D003141), respiratory diseases (MESH:D012140), COVID-19 (MESH:D000086382), respiratory disorders (MESH:D012131), pulmonary TB (MESH:D014390), DVD (MESH:D001072), infected (MESH:D007239), FRS (MESH:D014947), Diarrhoeal Disease (MESH:D004194), tuberculosis (MESH:D014376), CMR (MESH:D003643)
- **Species:** Capra hircus (domestic goat, species) [taxon 9925], Anas platyrhynchos (duck, species) [taxon 8839], Bos taurus (bovine, species) [taxon 9913], Gallus gallus (bantam, species) [taxon 9031], Homo sapiens (human, species) [taxon 9606], Ovis aries (domestic sheep, species) [taxon 9940]

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13003680/full.md

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Source: https://tomesphere.com/paper/PMC13003680