Timeliness of the outbreak surveillance and response process: a retrospective cross-sectional multicountry assessment in the WHO African Region
Year: 2026
Type: article
Study design: Observational Study
Abstract: Introduction: Early detection and response to outbreaks are among the highest expectations of public health responsibility. However, in most WHO African countries, this commitment often encounters persistent challenges that reflect the weakness of health systems and necessitate specific analyses to learn lessons and make timely decisions. Analysing timeliness from detection to response offers a particular advantage by highlighting the different delays recorded at each stage, which guide on the identification of challenges that may arise within the system. Methods: A retrospective cross-sectional study of outbreaks reported in the WHO African Region in 2024 was conducted. This study focused on a descriptive analysis of the reported outbreaks and the computation of median time for seven key indicators associated with four core milestones: detection, notification, investigation and initiation of response. Results: Most reported outbreaks were caused by viral agent, with vaccine-preventable diseases being the most frequently reported category. Overall medians (IQR) were 4 (1-7) days for detection, 0 (0-2) days for notification, 0 (0-0) days for sample collection, 1 (0-2) days for sample reception, 2 (1-4) days for laboratory turnaround, 3 (1-8) days for laboratory confirmation and 1 (0-8) days for response initiation. Significant delays were noted for specific diseases, and at particular stages of the surveillance-to-response cascade, highlighting persistent gaps and weaknesses in outbreak detection and response systems across the Region. Conclusion: Significant delays for specific diseases were noted, emphasising bottlenecks that require strong and sustained commitment from governments and an investment in resources.
Source: BMJ Public Health
Institution: World Health Organization Regional Office for Africa
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7225147392
