Malaria vectors have acquired an enzyme that metabolizes pyrethroids. To tackle this problem, we evaluated long-lasting insecticidal nets incorporating piperonyl butoxide (PBO-LLINs) with a community-based cluster randomized control trial in western Kenya. The primary endpoints were anopheline density and Plasmodium falciparum polymerase chain reaction (PCR)-positive prevalence (PCRpfPR) of children aged 7 months to 10 years. Four clusters were randomly selected for each of the treatment and control arms (eight clusters in total) from 12 clusters, and PBO-LLINs and standard LLINs were distributed in February 2011 to 982 and 1,028 houses for treatment and control arms, respectively. Entomological surveys targeted 20 houses in each cluster, and epidemiological surveys targeted 150 children. Cluster-level permutation tests evaluated the effectiveness using the fitted values from individual level regression models adjusted for baseline. Bootstrapping estimated 95% confidence intervals (CIs). The medians of anophelines per house were 1.4 (interquartile range [IQR]: 2.3) and 3.4 (IQR: 3.7) in the intervention and control arms after 3 months, and 0.4 (IQR: 0.2) and 1.6 (IQR: 0.5) after 10 months, respectively. The differences were –2.5 (95% CI: –6.4 to –0.6) and –1.3 (95% CI: –2.0 to –0.7), respectively. The datasets of 861 and 775 children were analyzed in two epidemiological surveys. The median PCRpfPRs were 25% (IQR: 11%) in the intervention arm and 52% (IQR: 11%) in the control arm after 5 months and 33% (IQR: 11%) and 45% (IQR: 5%) after 12 months. The PCRpfPR ratios were 0.67 (95% CI: 0.38, 0.91) and 0.74 (95% CI: 0.53, 0.90), respectively. We confirmed the superiority of PBO-LLINs.

The impact of insecticide resistance in malaria vectors is poorly understood and quantified. Here a series of geospatial datasets for insecticide resistance in malaria vectors are provided so that trends in resistance in time and space can be quantified and the impact of resistance found in wild populations on malaria transmission in Africa can be assessed. Data are also provided for common genetic markers of resistance to support analyses of whether these genetic data can improve the ability to monitor resistance in low resource settings. Specifically, data have been collated and geopositioned for the prevalence of insecticide resistance, as measured by standard bioassays, in representative samples of individual species or species complexes. Data are provided for the Anopheles gambiae species complex, the Anopheles funestus subgroup, and for nine individual vector species. In addition, allele frequencies for known resistance associated markers in the Voltage-gated sodium channel ( Vgsc ) are provided. In total, eight analysis-ready, standardised, geopositioned datasets encompassing over 20,000 African mosquito collections between 1957 and 2017 are provided.

If water surfaces are left untreated, mosquito larvae can develop into adult vectors within a few weeks, posing a significant risk of infectious disease. Consequently, technology for weekly on-site detection of mosquito larvae is required to control such situations effectively. Using autonomous UAV-captured images based on water surface mapping, this study establishes a technological foundation to detect mosquito larvae using deep learning, targeting automated larval source management for vector control. To enable local entomologists to build and adapt models using free, no-code cloud services, determining the minimum viable training dataset is essential. Therefore, we built an object detection model using Google Cloud Platform's Vertex AI with an extremely limited annotated dataset comprising 10 images and 371 annotations in total, of which 8 images (300 annotations) were allocated for training, to evaluate feasibility under resource-constrained conditions. The model was tested on two external datasets: controlled indoor images (JIHS, Japan) and field photographs from natural breeding sites (Malawi). Results demonstrated that while the model achieved high Recall (75.0–100.0%) and Precision (56.3–57.1%) in controlled environments (F1 0.643–0.727), Precision dropped substantially to 9.1–13.3% in turbid field conditions due to false positives from environmental noise, such as floating particles. These findings indicate that dataset diversification incorporating diverse backgrounds is essential for real-world deployment.

The use of a metofluthrin-impregnated spatial repellent device (MSRD) is a new, practically effective method for preventing mosquito blood feeding. Indoor environmental factors such as room temperature and ventilation rate are thought to be important for MSRD activity. Measurements of room temperature and vaporization of metofluthrin from MSRD in typical rural metal-roof houses and thatched-roof houses in southeastern Malawi were conducted. The relationship between house structure and number of collected Anopheline mosquitoes with and without MSRD treatment was also investigated. The difference between daytime room temperature and nighttime room temperature was significantly higher in metal-roof houses than thatched-roof houses. The vaporization of metofluthrin from the MSRD was not accelerated by the high room temperature, but by the high indoor air flow by ventilation. The number of mosquito collections was significantly higher in thatched-roof houses than in metal-roof houses. MSRD-treated thatched-roof houses have a higher probability of mosquito infestation, but the vaporization of metofluthrin is also higher due to indoor air flow, resulting in a reduction in mosquito numbers. Metal-roof houses with closed eaves reduce the probability of mosquito invasion, and a longer predicted effectiveness occurs with MSRD because of the controlled release of metofluthrin through lower indoor air flow.