Geographical shifting of cholera burden in Africa and its implications for disease control
Abstract
Cholera outbreaks cause substantial morbidity and mortality in Africa, yet changes in the geographic distribution of cholera burden over time remain uncharacterized. We used surveillance data and spatial statistical models to estimate the mean annual incidence of reported suspected cholera for 2011-2015 and 2016-2020 on a 20-km grid across Africa. Across 43 countries, mean annual incidence rates remained at 11 cases per 100,000 population, with 125,701 cases estimated annually (95% credible interval (CrI): 124,737-126,717) from 2016 to 2020. Cholera incidence shifted from western to eastern Africa. There were 296 million people (95% CrI: 282-312 million) in high-incidence second-level administrative (ADM2) units (≥10 cases per 100,000 per year) in 2020, 135 million of whom experienced low incidence (<1 per 100,000) in 2011-2015. ADM2 units with high incidence in central and eastern Africa from 2011 to 2020 were more likely to report cholera in 2022-2023. In hypothetical scenarios of preventive disease control planning, targeting the 100 million highest-burden populations had potential to reach up to 63% of 2016-2020 mean annual cases but only 37% when targeting by past incidence. This retrospective analysis highlights spatiotemporal instability in cholera burden and can be used as a benchmark for tracking future progress in disease control.
Javier Perez-Saez
Research Scientist
I am interested in infectious disease dynamics and epidemiology with a focus on methods development and application.
Christina Alam
Research Analyst
My research interests include investigating spatial processes driving disease transmission, focusing on using spatial statistics and data analysis to improve the effectiveness of cholera interventions
Sonia T. Hegde
Research Scientist
My research interests include infectious disease dynamics, vaccines, and surveillance.
Elizabeth C. Lee
Research Scientist
I am interested in understanding the mechanisms behind the surveillance data we observe and improving their applications to public health policy.