Dynamic mapping of cholera outbreak during the Yemeni Civil War, 2016–2019

Abstract

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.

Global Patterns of Trends in Cholera Mortality

“…Widespread destruction during the Yemeni Civil War (2014–2019) triggered the world’s largest documented cholera epidemic of modern times [ 34 ]. In 2017 and 2019, war-torn Yemen accounted for 84% and 93% of all cholera cases in the world, with children constituting the majority of reported cases [ 1 , 34 ].…”

“…Widespread destruction during the Yemeni Civil War (2014–2019) triggered the world’s largest documented cholera epidemic of modern times [ 34 ]. In 2017 and 2019, war-torn Yemen accounted for 84% and 93% of all cholera cases in the world, with children constituting the majority of reported cases [ 1 , 34 ]. The case fatality risk was 0.22%, particularly in people younger than 5 years, as well as in people with poor nutrition status, with less access to food and purchasing power [ 34 , 35 , 36 , 37 ].…”

“…In 2017 and 2019, war-torn Yemen accounted for 84% and 93% of all cholera cases in the world, with children constituting the majority of reported cases [ 1 , 34 ]. The case fatality risk was 0.22%, particularly in people younger than 5 years, as well as in people with poor nutrition status, with less access to food and purchasing power [ 34 , 35 , 36 , 37 ]. Namely, in approximately half of all children under five, a high prevalence of chronic malnutrition was reported, which lowered their resilience toward cholera [ 35 , 36 , 37 ].…”

Global seasonal and pandemic patterns in influenza: An application of longitudinal study designs

“…Dynamic maps and heatmaps are complex graphical presentations and could compress large amounts of spatially and temporally refined data into an animated or a single image and serve as an effective communication tool. In our early work, we created several graphical templates that utilised shared axes and various graph types to reveal hidden trends and patterns, better recognise underlying heterogeneities and uncertainties (Castronovo et al ., 2009 ; Moorthy et al ., 2012 ; Chui et al ., 2011b ; Simpson et al ., 2022b ). In this paper, we expanded the use of complex heatmaps and dynamic maps by collating our findings into an analecta of visualisations to demonstrate the detected global patterns and seasonality of influenza over two decades (Naumova et al ., 2022 ).…”

Visualization of Spatial–Temporal Epidemiological Data: A Scoping Review

“…Choropleth maps are widely used to visualize the state of a variable across a geographic area. In the papers, this technique was mostly used to represent the number of cases or cumulative cases in an area [17,22,24,27,46,48,52,56,58,[60][61][62][63]65,67,71,76,79,84,87,99,103,105,[113][114][115][116]119,121,127], along with the incidence of a disease [30,32,56,62,63,105,119,120,127]. It was also used to a lesser extent to visualize other measures, such as prevalence [35,64,76] and morbidity [111].…”