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A necessary component of understanding vector‐borne disease risk is accurate characterization of the distributions of their vectors. Species distribution models have been successfully applied to data‐rich species but may produce inaccurate results for sparsely documented vectors. In light of global change, vectors that are currently not well‐documented could become increasingly important, requiring tools to predict their distributions. One way to achieve this could be to leverage data on related species to inform the distribution of a sparsely documented vector based on the assumption that the environmental niches of related species are not independent. Relatedly, there is a natural dependence of the spatial distribution of a disease on the spatial dependence of its vector. Here, we propose to exploit these correlations by fitting a hierarchical model jointly to data on multiple vector species and their associated human diseases to improve distribution models of sparsely documented species. To demonstrate this approach, we evaluated the ability of twelve models – which differed in their pooling of data from multiple vector species and inclusion of disease data – to improve distribution estimates of sparsely documented vectors. We assessed our models on two simulated datasets, which allowed us to generalize our results and examine their mechanisms. We found that when the focal species is sparsely documented, incorporating data on related vector species reduces uncertainty and improves accuracy by reducing overfitting. When data on vector species are already incorporated, disease data only marginally improve model performance. However, when data on other vectors are not available, disease data can improve model accuracy and reduce overfitting and uncertainty. We then assessed the approach on empirical data on ticks and tick‐borne diseases in Florida and found that incorporating data on other vector species improved model performance. This study illustrates the value in exploiting correlated data via joint modeling to improve distribution models of data‐limited species. [ABSTRACT FROM AUTHOR]

Background: Vector control tools, long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS), have significantly contributed to malaria prevention efforts in sub-Saharan Africa. However, insecticide resistance has seriously hampered their efficacy in recent years and new tools are essential to further progress. In2Care® EaveTubes (ETs) are an inexpensive, new resistance-breaking vector control product under World Health Organization (WHO) evaluation informed by mosquito ecology to efficiently target malaria vectors. By installing ETs in the walls of the house at the eave level that funnel the natural airflow, mosquitoes are drawn in by the same heat and odor cues that typically attract them through open eaves. Once inside an ET, mosquitoes are exposed to insecticide-treated netting placed inside the ET. The aim of this study is to test whether ETs as stand-alone tool have an effect on the epidemiology of malaria in villages where houses have been modified with the ET intervention., Methods: A two-armed, cluster randomized controlled trial will be conducted to evaluate the effect of ETs on clinical malaria incidence in children living in Côte d'Ivoire. Thirty-four villages will be selected based on population size and the proportion of houses suitable for modification with ETs (17 treatment arms (ETs + LLINs, 17 control arms (LLINs only)). Based on the population census, 55 households per cluster with eligible children (i.e., between the ages of 6 months to 8 years old at the start of the study) will be randomly selected for recruitment into the active detection cohorts. In the treatment arm, we will enroll eligible children who reside in ET-treated houses. The intervention and control cohorts will be followed for 4 months for baseline covariate measurements and 24 months with intervention. During case detection visits, blood samples will be taken from all febrile children and tested for malaria infection with rapid diagnostic tests (RDTs). All positive clinical malaria infections will be treated. To estimate the impact of the ET on malaria vector densities, entomological measurements (indoor sampling with CDC traps) will be conducted monthly in 20 clusters (10 ET, 10 Control) in 10 randomly selected households per cluster. To estimate the infectiousness of malaria vectors, sporozoite rates will be measured in subsets of the collected mosquito samples., Discussion: Findings will serve as an efficacy trial of ETs and will be submitted to the WHO Vector Control Advisory Group (VCAG) for assessment of public health value. Entomological outcomes will also be measured as proxies of malaria transmission to help develop guidelines for the evaluation of future In2Care® ETs products., Trial Registration: ClinicalTrials.gov NCT05736679. Registered on 10 February 2023., (© 2023. The Author(s).)