In Aedes aegypti mosquitoes, introduction of certain strains of inherited Wolbachia symbionts results in transmission blocking of various viruses of public health importance, including dengue. This has resulted in a ‘replacement’ strategy for dengue control involving release of male and female mosquitoes, whereupon Wolbachia is able to spread through Ae. aegypti populations to high frequency and reduces the incidence of dengue. Wolbachia strain w AlbB is an effective transmission blocker and stable at high temperatures, making it very suitable for use in hot tropical climates. Following the first trial field releases of the w AlbB strain in Ae. aegypti in Malaysia, releases of w AlbB Ae. aegypti have for the first time become operationalized by the Malaysian health authorities. We report here on changes in dengue incidence based on a set of 20 releases sites and 76 control sites in high rise residential areas, which allows us to directly assess the impact of Wolbachia frequency on dengue incidence. The results indicate an average reduction in dengue of 62.4% (confidence intervals 50-71%); importantly the level of suppression increased with Wolbachia frequency, with suppression of 75.8% (confidence intervals 61-87%) estimated at 100% Wolbachia frequency. These findings emphasize the large impacts of w AlbB Wolbachia invasions on dengue incidence in an operational setting, with the expectation that the level of dengue will further decrease as wider areas are invaded.

Endemic channels are widely used in dengue surveillance to detect unusual increases in case counts. However, conventional approaches that rely on historical averages with fixed standard deviation (SD)-based multipliers may produce unstable thresholds and false alerts. This study compared a conventional SD-based endemic channel with a log-scale SD-based endemic channel incorporating an enhanced alert rule to identify the optimal approach for routine dengue surveillance in Malaysia. Weekly national dengue case data from 2014 to 2024 were analyzed. A rolling validation approach was used to evaluate outbreak detection performance from 2017 to 2023 using three-year historical baselines. Sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and the Youden Index were calculated and pooled across the validation years. The optimal multiplier was selected based on the highest pooled Youden Index using the rolling validation period (2017–2023). The selected approach was then applied independently to the 2024 surveillance data as an operational demonstration of its potential use in routine dengue surveillance. A total of 260 epidemiological weeks were analyzed, of which 42 (16.2%) were classified as outbreak weeks. The log-scale SD-based endemic channel incorporating an enhanced alert rule achieved the highest pooled Youden Index of 0.43 at the optimal multiplier of 0.50. At this multiplier, sensitivity was 0.60, specificity 0.82, positive predictive value 0.35, negative predictive value 0.93, and overall accuracy 0.79. Compared with the conventional SD-based endemic channel at its optimal multiplier (1.00), the proposed approach demonstrated improved sensitivity (0.60 vs. 0.56), specificity (0.82 vs. 0.70), positive predictive value (0.35 vs. 0.23), negative predictive value (0.93 vs. 0.91), accuracy (0.79 vs. 0.68), and Youden Index (0.43 vs. 0.26). The log-scale SD-based endemic channel incorporating an enhanced alert rule demonstrated superior overall outbreak detection performance and was selected as the optimal approach for routine dengue surveillance.