Epidemics · 2026
Optimizing malaria diagnostic sensitivity as a prerequisite for targeted vector control and rational antimalarial deployment: A compartmental modeling analysis.
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Cole O Andrew, Odhiambo John, Kokwaro Gilbert
Аннотация
BACKGROUND: Gains in malaria transmission reduction achieved through insecticide-treated nets (ITNs) are reversing amid emerging artemisinin partial resistance. While sensitive diagnostics are key to monitoring resistant parasite-driven outbreaks, most malaria outbreak models treat diagnostic sensitivity as a fixed background parameter, obscuring its role both in clinical progression and disease burden.
METHODS: We developed an eight-compartment deterministic model in which diagnostic sensitivity acts as a bifurcation parameter partitioning individuals infected with uncomplicated malaria into treated and false-negative pathways, incorporating severity-stratified gametocyte production and asymmetric disease-progression rates. The model was validated through local stability and sensitivity analysis. Seven intervention strategies spanning vector control, diagnostics, and treatment allocation were compared via simulations using two complementary outcomes: time for the parasite reservoir to reach ≤ 10% of baseline, and cumulative severe case-days.
RESULTS: Raising sensitivity from 0.95 to 0.98 reduced false-negative cases by 60% and mortality by 14%. The top-ranked strategy (90% diagnostic allocation) reached the modeled reservoir threshold 29% faster and 46% cheaper than current ITN-focused practice. Programmatic experiences from Rwanda and Cabo Verde, which have approached or achieved elimination under diagnostic-prioritized frameworks were qualitatively, though not formally, consistent with model predictions.
CONCLUSION: Diagnostic sensitivity is a high-leverage, currently underused control point that should precede and inform targeted vector-control deployment and rational antimalarial treatment allocation, offering a lower-cost path toward WHO 2030 elimination targets. Formal model validation against country-level surveillance data and explicit simulation of WHO-recommended antimalarial drug-diversification approaches such as adaptive rotation are identified as priorities for future work.
METHODS: We developed an eight-compartment deterministic model in which diagnostic sensitivity acts as a bifurcation parameter partitioning individuals infected with uncomplicated malaria into treated and false-negative pathways, incorporating severity-stratified gametocyte production and asymmetric disease-progression rates. The model was validated through local stability and sensitivity analysis. Seven intervention strategies spanning vector control, diagnostics, and treatment allocation were compared via simulations using two complementary outcomes: time for the parasite reservoir to reach ≤ 10% of baseline, and cumulative severe case-days.
RESULTS: Raising sensitivity from 0.95 to 0.98 reduced false-negative cases by 60% and mortality by 14%. The top-ranked strategy (90% diagnostic allocation) reached the modeled reservoir threshold 29% faster and 46% cheaper than current ITN-focused practice. Programmatic experiences from Rwanda and Cabo Verde, which have approached or achieved elimination under diagnostic-prioritized frameworks were qualitatively, though not formally, consistent with model predictions.
CONCLUSION: Diagnostic sensitivity is a high-leverage, currently underused control point that should precede and inform targeted vector-control deployment and rational antimalarial treatment allocation, offering a lower-cost path toward WHO 2030 elimination targets. Formal model validation against country-level surveillance data and explicit simulation of WHO-recommended antimalarial drug-diversification approaches such as adaptive rotation are identified as priorities for future work.