ArticleSpatial and spatio-temporal epidemiology2018
Risk maps for cities: Incorporating streets into geostatistical models.
Article in Spatial and spatio-temporal epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Domestic (re)infestation risk with the main vector Triatoma infestans increases with surrounding green vegetation and social vulnerability in the Argentine Chaco.Parasites & vectors · 2024Article
- Incentivizing optimal risk map use for Triatoma infestans surveillance in urban environments.PLOS global public health · 2022Article
- Dispersal patterns of Trypanosoma cruzi in Arequipa, Peru.PLoS neglected tropical diseases · 2020Article
- Integrating evidence, models and maps to enhance Chagas disease vector surveillance.PLoS neglected tropical diseases · 2018Article
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Authors and funding
7 authors.
Funding
Abstract
Vector-borne diseases commonly emerge in urban landscapes, and Gaussian field models can be used to create risk maps of vector presence across a large environment. However, these models do not account for the possibility that streets function as permeable barriers for insect vectors. We describe a methodology to transform spatial point data to incorporate permeable barriers, by distorting the map to widen streets, with one additional parameter. We use Gaussian field models to estimate this additional parameter, and develop risk maps incorporating streets as permeable barriers. We demonstrate our method on simulated datasets and apply it to data on Triatoma infestans, a vector of Chagas disease in Arequipa, Peru. We found that the transformed landscape that best fit the observed pattern of Triatoma infestans infestation, approximately doubled the true Euclidean distance between neighboring houses on different city blocks. Our findings may better guide control of re-emergent insect populations.
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