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Risk maps for cities: Incorporating streets into geostatistical models

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dc.contributor.author Billig, Erica
dc.contributor.author Lee, Kwonsang
dc.contributor.author Roy, Jason A.
dc.contributor.author Small, Dylan
dc.contributor.author Ross, Michelle E.
dc.contributor.author Castillo Neyra, Ricardo
dc.contributor.author Levy, Michael Z.
dc.date.accessioned 2019-03-05T15:24:21Z
dc.date.available 2019-03-05T15:24:21Z
dc.date.issued 2018
dc.identifier.uri https://hdl.handle.net/20.500.12866/5921
dc.description.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. en_US
dc.language.iso eng
dc.publisher Elsevier
dc.relation.ispartofseries Spatial and Spatio-temporal Epidemiology
dc.rights info:eu-repo/semantics/restrictedAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject Chagas disease en_US
dc.subject City streets en_US
dc.subject Gaussian field en_US
dc.subject INLA en_US
dc.subject Triatoma infestans en_US
dc.subject Vector en_US
dc.title Risk maps for cities: Incorporating streets into geostatistical models en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://doi.org/10.1016/j.sste.2018.08.003
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.03.09
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.03.08
dc.relation.issn 1877-5853


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