Garcia, G. A. | bioRxiv Science

bioRxiv2025

Wolbachia introgression in Rio de Janeiro remains at sub-optimal levels 30 months after its crash: challenges in the sustainability of wMel interventions for dengue control

The deployment of the Wolbachia wMel strain is currently underway in multiple dengue-endemic municipalities across Brazil. The efficacy of this strategy in Rio de Janeiro remains uncertain, primarily due to the difficulty in sustaining high wMel prevalence in regions previously subjected to large-scale releases. A key contributing factor was the routine rotation of insecticides within the framework of Integrated Vector Management (IVM), which led to the use of the larvicide Spinosad for Aedes control in urban areas. This compound was associated with a precipitous decline in Aedes aegypti mosquitoes, regardless the wMel infection status. While wMel-uninfected population recovered within weeks, wMel-infected population remained at low levels likely due to the fitness costs imposed by wMel on egg viability. To assess the long-term persistence of wMel following this demographic collapse, we conducted mosquito sampling across 12 neighborhoods in Rio de Janeiro, 30 months after mosquito populations crashed. Our findings reveal that wMel introgression remains suboptimal, with a mean frequency of 9.87% across the sampled areas. Only two neighborhoods exhibited wMel frequencies exceeding 15%, likely reflecting ongoing localized releases. The reduced prevalence underscores the challenges of achieving self-sustaining wMel establishment in complex urban environments and highlight critical considerations for the implementation of Wolbachia-based dengue control programs in endemic regions. SponsorshipThis study was supported by grants from the CNPq - Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (312282/2022-2, 307209/2023-7) and by FAPERJ - Fundacao Carlos Chagas Filho de Amparo a Pesquisa no Estado do Rio de Janeiro (E-26/211.159/2019, E-26/204.108/2024, E26/2001.844/2017, E-26/210.335/2022, E-26/210.537/2024).

ecology↗

bioRxiv2020

Measuring the accuracy of gridded human population density surfaces: a case study in Bioko Island, Equatorial Guinea

Geospatial datasets of population are becoming more common in models used for health policy. Publicly-available maps of human population in sub-Saharan Africa make a consistent picture from inconsistent census data, and the techniques they use to impute data makes each population map unique. Each mapping model explains its methods, but it can be difficult to know which map is appropriate for which policy work. Gold-standard census datasets, where available, are a unique opportunity to characterize maps by comparing them with truth. We use census data from Bioko Island, in Equatorial Guinea, to evaluate LandScan (LS), WorldPop (WP), and the High-Resolution Settlement Layer (HRSL). Each layer is compared to the gold-standard using statistical measures to evaluate distribution, error, and bias. We investigated how map choice affects burden estimates from a malaria prevalence model. Specific population layers were able to match the gold-standard distribution at different population densities. LandScan was able to most accurately capture highly urban distribution, HRSL matched best at all other lower population densities and WorldPop performed poorly everywhere. Correctly capturing empty pixels is key, and smaller pixel sizes (100 m vs 1 km) improve this. Normalizing areas based on known district populations increased performance. The use of differing population layers in a malaria model showed a disparity in results around transition points between endemicity levels. The metrics in this paper, some of them novel in this context, characterize how these population maps differ from the gold standard census and from each other. We show that the metrics help understand the performance of a population map within a malaria model. The closest match to the census data would combine LandScan within urban areas and the HRSL for rural areas. Researchers should prefer particular maps if health calculations have a strong dependency on knowing where people are not, or if it is important to categorize variation in density within a city.

ecology↗