Evidence mapPaperPMID 41361838Full record

ArticleTropical medicine and health2025

Mortality burden of bacterial antimicrobial resistance in East Africa: pooled analysis of modelled estimates.

Yusuff Adebayo Adebisi, Najim Z Alshahrani, Theogene Uwizeyimana

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Article in Tropical medicine and health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yusuff Adebayo AdebisiGlobal Health Focus, Kigali, Rwanda. adebisiyusuff23@yahoo.com.
Najim Z AlshahraniDepartment of Family and Community Medicine, Faculty of Medicine, University of Jeddah, Jeddah, Saudi Arabia.
Theogene UwizeyimanaBill and Joyce Cummings Institute of Global Health, University of Global Health Equity, Kigali, Rwanda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBacterial antimicrobial resistance (AMR) is a major and growing public health threat in East African Community (EAC) countries, where fragile health systems, inadequate diagnostics, and inappropriate antibiotic use drive high levels of resistant infections. Despite this, robust subregional mortality estimates remain limited.

methodsWe conducted a secondary pooled analysis of modelled, publicly available, country-level mortality estimates from the Global Research on Antimicrobial Resistance (GRAM) 2019 project. Data were extracted for six EAC countries: Burundi, Kenya, Rwanda, South Sudan, Tanzania, and Uganda. Because GRAM reports age-standardised mortality rates (ASMRs) with 95% uncertainty intervals, we derived standard errors from these intervals, assuming approximate normality, and used them in the pooled analysis. Using random-effects models with restricted maximum likelihood (REML), we pooled ASMRs per 100,000 population for deaths associated with and attributable to AMR. We calculated 95% confidence intervals and prediction intervals, assessed heterogeneity using I

resultsAcross the six EAC countries, there were an estimated 154,760 deaths associated with AMR and 36,480 deaths attributable to AMR in 2019. The pooled ASMR for AMR-associated deaths was 144.69 per 100,000 (95% CI 129.07-160.30) population, with a 95% prediction interval of 122.57-166.81. Country-specific ASMRs for AMR-associated deaths ranged from 129.5 per 100,000 population in Uganda to 167.0 per 100,000 population in Burundi. For AMR-attributable deaths, the pooled ASMR was 34.62 per 100,000 (95% CI 30.02-39.23) population, with a prediction interval of 28.10-41.14. Country-specific ASMRs for attributable deaths ranged from 30.80 per 100,000 population in Uganda to 41.90 per 100,000 population in Burundi. For both associated and attributable mortality, heterogeneity was negligible (I

conclusionThis pooled secondary analysis indicates a substantial and regionally consistent mortality burden from bacterial AMR in East Africa. The findings reify the need for coordinated investment in AMR surveillance, stewardship, and overall response across the EAC.

Indexed as

Age-standardised mortality rate (ASMR)Antimicrobial resistance (AMR)Bacterial infectionsEast AfricaSurveillance

Identifiers

PMID41361838
PMCPMC12683851

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.