Epidemic Mitigation and Marginal Mortality-Gains Using Self-Testing as a Diagnostic Intervention for Epidemic-Prone Diseases in Africa

Background: African Union (AU) guidance identifies decentralized diagnostics as central to epidemic preparedness. However, the epidemiological role of self-testing across epidemic-prone diseases remains underexplored. Drivers for potential impact of self-testing impact were examined conceptually using a transmission model. Methods: A deterministic SEIR model compared standard-of-care testing with additional self-testing. Global sensitivity analysis using Latin Hypercube sampling and partial rank correlation coefficients (PRCCs) examined parameters influencing reductions in peak disease prevalence (mitigation). Dynamics were illustrated using AU pathogen archetypes (Ebola, Influenza A, Cholera, Coronavirus, and Mpox), estimating the number needed to self-test (NNST) to avert one death as a measure of marginal efficiency. Results: Epidemic mitigation was minimal (median 1.9%; IQR: 0.4%–5.8%); correlated with isolation adherence (PRCC = 0.784), self-testing intensity (PRCC = 0.617), lower R0 (basic reproductive number; PRCC = -0.607) and greater duration of infectiousness (PRCC = 0.370). Achieving a 10% reduction in peak prevalence at R₀ = 1.1 required 34 self-tests per 10,000 people per day, exceeding AU COVID-19 operational benchmark of 10 per 10,000 per week. High-mortality, moderate-transmission archetypes (e.g., Ebola) were most responsive to mortality reductions (Median 1,512 NNST/death averted) compared to Mpox (Median 355,708 NNST/death averted). Adherence to post-test isolation exerted greater epidemiological impact than diagnostic accuracy. Conclusions: The epidemiological value of untargeted self-testing depends on pathogen characteristics and post-test behavioral adherence. Epidemic mitigation effects were generally limited under constrained health-system capacity. However, future demonstration studies evaluating rapid, early decentralized self-testing deployment during Ebola-archetype outbreaks may help identify operationally feasible targeted deployment strategies to support mitigation and mortality reduction.