Investigate the weaponization of water during the Syrian conflict and the correlation of attacks on water, sanitation, and hygiene (WASH) infrastructure in Idlib and Aleppo governorates with trends in waterborne diseases reported by Early Warning and Response surveillance systems. Methods: We reviewed literature and databases to obtain information on attacks on WASH in Aleppo and Idlib governorates between 2011 and 2019. We plotted weekly trends in waterborne diseases from two surveillance systems operational in Aleppo and Idlib governorates between 2015 and early 2020. Results: The literature review noted several attacks on water and related infrastructure in both governorates, suggesting that WASH infrastructure was weaponized by state and non-state actors. Most interference with WASH in the Aleppo governorate occurred before 2019 and in the Idlib governorate in the summer of 2020. Other acute diarrhea represented >90% of cases of diarrhea; children under 5 years contributed 50% of cases. There was substantial evidence (p < 0.001) of an overall upward trend in cases of diarrheal disease. Conclusions: Though no direct correlation can be drawn between the weaponization of WASH and the burden of waterborne infections due to multiple confounders, this research introduces important concepts on attacks on WASH and their potential impacts on waterborne diseases.

The Global Task Force on Cholera Control (GTFCC) created a strategy for early outbreak detection, hotspot identification, and resource mobilization coordination in response to the Yemeni cholera epidemic. This strategy requires a systematic approach for defining and classifying outbreak signatures, or the profile of an epidemic curve and its features. We used publicly available data to quantify outbreak features of the ongoing cholera epidemic in Yemen and clustered governorates using an adaptive time series methodology. We characterized outbreak signatures and identified clusters using a weekly time series of cholera rates in 20 Yemeni governorates and nationally from 4 September 2016 through 29 December 2019 as reported by the World Health Organization (WHO). We quantified critical points and periods using Kolmogorov–Zurbenko adaptive filter methodology. We assigned governorates into six clusters sharing similar outbreak signatures, according to similarities in critical points, critical periods, and the magnitude of peak rates. We identified four national outbreak waves beginning on 12 September 2016, 6 March 2017, 28 May 2018, and 28 January 2019. Among six identified clusters, we classified a core regional hotspot in Sana’a, Sana’a City, and Al-Hudaydah—the expected origin of the national outbreak. The five additional clusters differed in Wave 2 and Wave 3 peak frequency, timing, magnitude, and geographic location. As of 29 December 2019, no governorates had returned to pre-Wave 1 levels. The detected similarity in outbreak signatures suggests potentially shared environmental and human-made drivers of infection; the heterogeneity in outbreak signatures implies the potential traveling waves outwards from the core regional hotspot that could be governed by factors that deserve further investigation.

Widespread destruction from the Yemeni Civil War (2014–present) triggered the world’s largest cholera outbreak. We compiled a comprehensive health dataset and created dynamic maps to demonstrate spatiotemporal changes in cholera infections and war conflicts. We aligned and merged daily, weekly, and monthly epidemiological bulletins of confirmed cholera infections and daily conflict events and fatality records to create a dataset of weekly time series for Yemen at the governorate level (subnational regions administered by governors) from 4 January 2016 through 29 December 2019. We demonstrated the use of dynamic mapping for tracing the onset and spread of infection and manmade factors that amplify the outbreak. We report curated data and visualization techniques to further uncover associations between infectious disease outbreaks and risk factors and to better coordinate humanitarian aid and relief efforts during complex emergencies.

The protracted and violent conflict in Syria has resulted in large-scale displacement of people and destruction of health and sanitation infrastructure. The aim of this study was to examine epidemiological trends in vector-borne disease (VBD) outbreaks before and following the onset of the Syrian conflict (2011). Methods: ProMED, a digital disease surveillance tool, was queried for VBD outbreak reports affecting humans and animals in Syria and select bordering countries between 2003 and 2018. Data were normalized by dividing the number of unique VBD events by the total number of unique outbreak events reported by ProMED for each year. Suspected and confirmed case counts and deaths were manually extracted. Results: Reports on VBDs increased from a mean of 2.9/year pre-2011 to 12.8/year post-2011, a 343.5% (p < 0.05) increase. After normalization, reports increased by 485.5% (p < 0.05) over the time periods. Post-2011, the most commonly reported VBDs were leishmaniasis, Crimean-Congo hemorrhagic fever, and lumpy skin disease. Reported numbers of suspected and confirmed cases and deaths increased during the conflict period. Conclusions: VBD outbreak events in ProMED increased in Syria and select bordering countries after the onset of the Syrian conflict in 2011. Enhanced disease surveillance is critical to detect and manage outbreaks in conflict settings.