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

Background/

Objectives

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 the potential impact of self-testing 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.

Results

Epidemic mitigation was minimal (median 1.9%; IQR: 0.4-5.8%); this 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). Conditional scenario exploration indicated 34 self-tests per 10,000 people per day to achieve a 10% reduction in peak prevalence at R0 = 1.1, assuming self-test sensitivity 78.7%, specificity 99.3%. This exceeded the WHO Afro 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 1512 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 limited under constrained health-system capacity. Future studies evaluating early decentralized self-testing deployment during Ebola-archetype outbreaks may identify operationally feasible deployment strategies to support mitigation and mortality reduction.