Cholera surveillance time series in Africa between 2010 and 2023.

Abstract

Background: Cholera remains a significant public health challenge in Africa, where outbreaks routinely strain public health and healthcare systems. Cholera surveillance time series data could be used to inform the efficient distribution of resources like oral cholera vaccine (OCV) and emergency response personnel, spur research on the impacts of different cholera control activities, and investigate longer-term epidemiologic patterns in cholera dynamics in this region. However, public reporting of cholera surveillance data historically has been sporadic and often limited to outbreak periods, thus limiting the availability of these useful time series datasets. We sought to fill this gap by preparing, cleaning, and processing weekly consecutive time series and outbreak-specific time series from 2010 to 2023 for African countries from heterogeneous data contributed to a global cholera surveillance database.

Methods: Cholera incidence data in Africa from 2010 to 2023 on suspected cases, confirmed cases, and deaths were compiled from public and non-public cholera surveillance from multiple sources, including ministries of health, World Health Organization, Médecins Sans Frontières, UNICEF, and other sources. Data were processed by aggregating daily records to weekly levels, averaging duplicate entries, filling gaps and surrounding weeks with zero cases, aligning epidemic weeks, adjusting population data, and removing identifying geographic information to preserve confidentiality as appropriate. Outbreaks were subsequently extracted using a systematic definition and summary statistics were produced by spatial scale and population density. Summary outbreak metrics were compared to previously published cholera outbreak datasets for data validation.

Conclusions: The unified surveillance and outbreak datasets provide an extensive compilation of reported cholera activity in Africa from 2010 to 2023, serving as a valuable resource for long-term control planning and early warning systems. Public health researchers can also leverage these datasets to analyze outbreak dynamics, anticipate resource needs, and assess the theoretical impact of control strategies.