ArticlePopulation health metrics2025
Accounting for uncertainty in conflict mortality estimation: an application to the Gaza War in 2023-2024.
Article in Population health metrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- What we count, and who gets counted: Population Health Metrics on World Population Day.Population health metrics · 2026Article
- Patient characteristics and interventions at a trauma stabilization point in Gaza- a retrospective analysis.Conflict and health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ongoing Gaza War has resulted in significant loss of life and intensified an existing humanitarian crisis. Despite increasing demand for accurate data, mortality estimates remain challenging due to the inherent 'statistical fog of war'. Accurate quantification is hindered by incomplete reporting and uncertain age-sex distributions of casualties. Official death tolls are likely influenced by damaged infrastructure, security disruptions, and political motivations, complicating detailed demographic verification. Our study introduces a novel methodological approach-a Bayesian model incorporating novel priors-to explicitly account for measurement errors in mortality estimation by addressing reporting completeness and uncertainty in demographic distributions. We use these methods to estimate sex- and age-specific mortality patterns and associated life expectancy (LE) and LE losses due to direct conflict deaths from the Gaza War. We find that LE in Gaza was 42.3 (39.4-45.0) in 2023 and 40.4 (37.5-43.0) in 2024, corresponding to LE losses of 34.4 (31.7-37.3) and 36.4 (33.8-39.3) years, respectively, compared to a counterfactual scenario with no conflict-related deaths. This corresponds to 78,318 (70,614-87,504) conflict deaths by the end of 2024, reflecting a 14-fold increase in all-cause mortality during the conflict's first year. The age-sex pattern of Gaza's conflict deaths aligns with UN-IGME profiles from past genocides. To contextualize these estimates, we compare them with LE losses observed in the Gaza Strip, the West Bank, and all of Palestine between 2012 and 2019. Our estimates align with previously published work, after adjusting the reporting priors to ignore underreporting. Our versatile and robust framework for mortality estimation under conditions of data scarcity can inform future conflict research.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.