Climate and landscape features associated with successful Wolbachia replacement in the municipality of Rio de Janeiro, Brazil.
7 affiliations
- 1Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK. [email protected].
- 2Department of Infectious Disease Epidemiology and Dynamics, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK. [email protected].
- 3Division of Biosciences, University College London, London, UK. [email protected].
- 4Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
- 5Department of Infectious Disease Epidemiology and Dynamics, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
- 6Interdisciplinary Centre for Scientific Computing, Heidelberg University, Heidelberg, Germany.
- 7Heidelberg Institute for Geoinformation Technology, Heidelberg, Germany.
Abstract
Background
Wolbachia replacement is a promising strategy for reducing arboviral transmission by Aedes aegypti. Wolbachia infection is refractory to arboviruses, including dengue and chikungunya, and Wolbachia spreads in mosquito populations by maternal transmission and cytoplasmic incompatibility, whereby mating between infected males and uninfected females produce nonviable offspring. Deployment programmes seek to establish stable, high Wolbachia prevalence through the release of Wolbachia-infected mosquitoes; however, prevalence varies spatially, particularly in complex urban environments where fine-scale heterogeneity in temperature and built environment may influence mosquito population dynamics. Here, we investigate how climate and landscape features are associated with heterogeneous Wolbachia replacement outcomes using wMel prevalence data from releases in the municipality of Rio de Janeiro, Brazil (2017-2019).Methods
Across a 26-month period, 500 × 500 m spatial units were clustered into four distinct replacement trajectories: unsuccessful, low, moderate, and high success, defined using predicted Wolbachia prevalence time series generated from cell-level binomial regression models and grouped using k-means clustering. Associations were explored between each trajectory and features related to Ae. aegypti habitat suitability, climate sensitivity, flight barriers, and Wolbachia deployment barriers using a multinomial generalised additive model (GAM). We used forward selection based on Akaike Information Criterion, explicit consideration of spatial autocorrelation and screening for collinearity among covariates. Of the 23 covariates examined, four covariates were retained: proportion of tall buildings (% > 6 m in height), average air temperature (°C), average elevation (m above sea level), and average daily rainfall (mm).Results
Results show high replacement success was mostly associated with areas with fewer tall buildings [β = -0.93 (95% CI -1.43, -0.44), P < 0.001] and higher temperatures [β = 1.11 (95% CI 0.59, 1.62), P < 0.001], while higher elevation and lower rainfall were associated with poorer outcomes. These associations may also reflect unmeasured socioeconomic or infrastructure variation, and context-dependent temperature effects on mosquito and Wolbachia fitness. Model-based predictions indicate non-linear dynamics, with areas of more tall buildings and higher temperatures showing divergent predicted outcomes towards either high success or failure rather than intermediate replacement. Residual spatial clustering suggests additional neighbourhood-scale processes not captured by the available covariates.Conclusions
Outcomes in high-rise and topographically complex areas appear less likely to stabilise at intermediate replacement. Such areas may require higher release densities, targeted supplemental interventions, and more intensive monitoring, although these remain as hypotheses requiring empirical evaluation. Through iterative modelling, it is possible to support rapid hypothesis identification to inform field tests and operational refinement as more evidence becomes available. These findings reinforce the role of urban permeability, vertical structure, and local environmental conditions in shaping the outcomes of Wolbachia replacement programmes.
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BibTeX
@article{tiley2026climate,
title = {{Climate and landscape features associated with successful Wolbachia replacement in the municipality of Rio de Janeiro, Brazil.}},
author = {Katie Tiley and Katie Milligan Susong and Steffen Knoblauch and Kathleen M O'Reilly and Oliver J Brady},
journal = {Parasites \& vectors},
year = {2026},
month = aug,
doi = {10.1186/s13071-026-07602-y},
url = {https://europepmc.org/article/MED/42968087},
note = {CC BY},
}
RIS
TY - JOUR
TI - Climate and landscape features associated with successful Wolbachia replacement in the municipality of Rio de Janeiro, Brazil.
AU - Katie Tiley
AU - Katie Milligan Susong
AU - Steffen Knoblauch
AU - Kathleen M O'Reilly
AU - Oliver J Brady
PY - 2026
DA - 2026/08/04
JO - Parasites & vectors
DO - 10.1186/s13071-026-07602-y
UR - https://europepmc.org/article/MED/42968087
AB - Background Wolbachia replacement is a promising strategy for reducing arboviral transmission by Aedes aegypti. Wolbachia infection is refractory to arboviruses, including dengue and chikungunya, and Wolbachia spreads in mosquito populations by maternal transmission and cytoplasmic incompatibility, whereby mating between infected males and uninfected females produce nonviable offspring. Deployment programmes seek to establish stable, high Wolbachia prevalence through the release of Wolbachia-infected mosquitoes; however, prevalence varies spatially, particularly in complex urban environments where fine-scale heterogeneity in temperature and built environment may influence mosquito population dynamics. Here, we investigate how climate and landscape features are associated with heterogeneous Wolbachia replacement outcomes using wMel prevalence data from releases in the municipality of Rio de Janeiro, Brazil (2017-2019).Methods Across a 26-month period, 500 × 500 m spatial units were clustered into four distinct replacement trajectories: unsuccessful, low, moderate, and high success, defined using predicted Wolbachia prevalence time series generated from cell-level binomial regression models and grouped using k-means clustering. Associations were explored between each trajectory and features related to Ae. aegypti habitat suitability, climate sensitivity, flight barriers, and Wolbachia deployment barriers using a multinomial generalised additive model (GAM). We used forward selection based on Akaike Information Criterion, explicit consideration of spatial autocorrelation and screening for collinearity among covariates. Of the 23 covariates examined, four covariates were retained: proportion of tall buildings (% > 6 m in height), average air temperature (°C), average elevation (m above sea level), and average daily rainfall (mm).Results Results show high replacement success was mostly associated with areas with fewer tall buildings [β = -0.93 (95% CI -1.43, -0.44), P < 0.001] and higher temperatures [β = 1.11 (95% CI 0.59, 1.62), P < 0.001], while higher elevation and lower rainfall were associated with poorer outcomes. These associations may also reflect unmeasured socioeconomic or infrastructure variation, and context-dependent temperature effects on mosquito and Wolbachia fitness. Model-based predictions indicate non-linear dynamics, with areas of more tall buildings and higher temperatures showing divergent predicted outcomes towards either high success or failure rather than intermediate replacement. Residual spatial clustering suggests additional neighbourhood-scale processes not captured by the available covariates.Conclusions Outcomes in high-rise and topographically complex areas appear less likely to stabilise at intermediate replacement. Such areas may require higher release densities, targeted supplemental interventions, and more intensive monitoring, although these remain as hypotheses requiring empirical evaluation. Through iterative modelling, it is possible to support rapid hypothesis identification to inform field tests and operational refinement as more evidence becomes available. These findings reinforce the role of urban permeability, vertical structure, and local environmental conditions in shaping the outcomes of Wolbachia replacement programmes.
SN - 1756-3305
ER -