Evidence map›Paper›PMID 40312760›Full record

ArticleBMC global and public health2025

A population-level analysis of armed conflict and diphtheria at the subnational level in the WHO African Region 2017-2024.

Tierney O'Sullivan, Lindsay T Keegan

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Article in BMC global and public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing 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

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Tierney O'SullivanDepartment of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT, 84108, USA. T.osullivan@utah.edu.
Lindsay T KeeganDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, 84108, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiphtheria has been re-emerging around the world at alarming rates, raising concerns about emergency preparedness, especially when global supplies of life-saving diphtheria antitoxin are insufficient. Outbreaks have occurred in areas with suboptimal coverage of the three-dose diphtheria tetanus and pertussis (DTP3) vaccine and regions experiencing conflict, but systematic studies assessing the association between these variables and the risk of diphtheria emergence are limited. This population-level study investigated the relationship between fatalities from armed conflict, childhood DTP3 vaccination coverage, and the presence of reported diphtheria cases in countries in the World Health Organization's (WHO) African region from 2017 to 2024.

methodsThe analysis was conducted at a subnational geographic scale (I countries = 35, N subnational regions = 541). Data sources include DTP3 coverage from the Demographic Health Surveys (DHS), conflict-related fatalities from the Armed Conflict Location and Event Database (ACLED), and diphtheria cases from the WHO. We first assessed whether a history of fatalities from armed conflict is a predictor of childhood DTP3 coverage using mixed-effects beta regression. To assess the relationship between conflict and diphtheria emergence, we fit a crude logistic regression model to assess their overall association in the study period, as well as repeated measures mixed-effects models to estimate the relationship between time-varying rates of conflict-related fatalities and diphtheria status, adjusting for diphtheria vaccine coverage estimates.

resultsConflict and subsequent childhood DTP3 vaccine coverage were negatively associated (odds ratio [OR] = 0.93, 95% CI 0.88-0.98). Conflict is also a significant predictor of diphtheria presence, both in the crude (OR = 1.41, 95% CI 1.17-1.68) and best-fitting repeated measures model (OR = 30.30, 95% CI 23.30-39.39), though risk varied by location. The best-fit model also associated lower estimates of diphtheria risk in areas with high (> 80%) and low (< 25%) vaccine coverage, though this is possibly due to underreporting of the true burden of disease in low-resource settings.

conclusionsThis exploratory analysis indicates that conflict-related fatalities are potentially helpful indicators of subnational diphtheria risk in countries in the WHO African region from 2017 to 2024. Further, it may be especially useful in cases where estimates of population-level diphtheria immunity are limited.

Indexed as

Armed conflictDiphtheriaDTP3 vaccineVaccine-preventable disease

Identifiers

PMID40312760
PMCPMC12046743

What Socratic holds

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LicenceCC BY-NC-ND
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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.