Evaluating quasi-experimental approaches for estimating epidemiological efficacy of non-randomised field trials: applications in Wolbachia interventions for dengue

Background: Wolbachia symbiosis in Aedes aegypti is an emerging biocontrol measure against dengue. However, assessing its real-world efficacy is challenging due to the non-randomised, field-based nature of most intervention studies. This research re-evaluates the spatial-temporal impact of Wolbachia interventions on dengue incidence using a large battery of quasi-experimental methods and assesses each method's validity.

Methods: A systematic search for Wolbachia intervention data was conducted via PUBMED. Efficacy was reassessed using commonly-used quasi-experimental approaches with extensive robustness checks, including geospatial placebo tests and a simulation study. Intervention efficacies across multiple study sites were computed using high-resolution aggregations to examine heterogeneities across sites and study periods. We further designed a stochastic simulation framework to assess the methods' ability to estimate intervention efficacies (IE).

Results: Wolbachia interventions in Singapore, Malaysia, and Brazil significantly decreased dengue incidence, with reductions ranging from 48.17% to 69.19%. IEs varied with location and duration. Malaysia showed increasing efficacy over time, while Brazil exhibited initial success with subsequent decline, hinting at operational challenges. Singapore's strategy was highly effective despite partial saturation. Simulations identified Synthetic Control Methods (SCM) and its variant, count Synthetic Control Method (cSCM), as superior in precision, with the smallest percentage errors in efficacy estimation. These methods also demonstrated robustness in placebo tests.

Conclusions: Wolbachia interventions exhibit consistent protective effects against dengue. SCM and cSCM provided the most precise and robust estimates of IEs, validated across simulated and real-world settings.