Nighttime lights as a proxy for conflict intensity and infrastructure recovery in Yemen and Ukraine

Bibliographic Data

ID19536820
AuthorsMaia C Tarnas (0000-0003-1470-313X, Institute of Population and Public Health, corresponding author), Tetyana I Vasylyeva (0000-0002-9736-7022, University of California, Irvine), Volodymyr M Minin (University of California, Irvine), Daniel M Parker (0000-0002-5352-7338, University of California, Irvine)
Year2026
Volume20
Issue1
Publication date2026-05-11
Open AccessYes
TypeARTICLE
VenueConflict and Health (JOURNAL)
Journal identifiersISSN: 1752-1505 • E-ISSN: 1752-1505
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1186/s13031-026-00801-5
PMID42116107
OpenAlexW7160856398
LanguageEN
References cited27

INTRODUCTION: Quantifying the impacts of armed conflict on civilians and infrastructure remains a major challenge, particularly where reporting is limited. Most conflict measurement tools require affected populations to report events and are limited by short time series, under-reporting, and varying methods. These tools do not capture infrastructural rebuilding, which has important health implications. Given this, we demonstrate the utility of nighttime lights (NTL) as a complementary tool for measuring conflict dynamics and infrastructure recovery with an epidemiological application. METHODS: We used monthly NASA Black Marble data to analyze NTL patterns in Yemen (2012-2022) and Ukraine (2019-2024) before and after the onset of large-scale military operations. We calculated month-specific NTL ratios relative to pre-event baselines and assessed the alignment of structural breakpoints, identified using BFAST methods, with aerial attack onset. Generalized additive models were used to measure the relationship between NTL and aerial attacks while accounting for the built environment, population, diesel price (Yemen), and spatiotemporal factors. Finally, we applied NTL to an existing model on the association between conflict, measured via air raids, and cholera in Yemen by replacing the original conflict categories with ones defined by NTL and included a variable for NTL recovery. RESULTS: Mean NTL declined by 53.3% in Yemen and 21.0% in Ukraine following conflict escalation, with detected breakpoints aligning with aerial attack onset in 85.7% of Yemeni governorates and 51.9% of Ukrainian oblasts. Generalized additive models showed that attacks were significantly associated with NTL reductions, independent of built environment factors. Incorporating NTL-based conflict measures into a cholera transmission model for Yemen produced results consistent with attack-based models and found that light recovery was associated with reduced disease risk. DISCUSSION: NTL is a viable tool for measuring conflict and can offer insights on dynamics that are not present in standard tools while avoiding many of these tools' limitations. These data have epidemiological applications and can be a proxy for important events affecting transmission dynamics. While event-based tools have vast utility, NTL can complement them with specific strengths and means of application

Armed conflict · Barometer · Climate change · Distributed lag · Proxy (statistics) · Public health · Refugee · Circadian rhythm and melatonin · Impact of Light on Environment and Health · Traffic and Road Safety

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