Bayesian spatio-temporal modeling to assess the effect of land-use changes on the incidence of Cutaneous Leishmaniasis in the Brazilian Amazon.
Details
Serval ID
serval:BIB_71D1DE69A801
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Bayesian spatio-temporal modeling to assess the effect of land-use changes on the incidence of Cutaneous Leishmaniasis in the Brazilian Amazon.
Journal
The Science of the total environment
ISSN
1879-1026 (Electronic)
ISSN-L
0048-9697
Publication state
Published
Issued date
25/11/2024
Peer-reviewed
Oui
Volume
953
Pages
176064
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Publication Status: ppublish
Abstract
Cutaneous Leishmaniasis (CL) is a vector-borne disease caused by a protozoan of the genus Leishmania and is considered one of the most important neglected tropical diseases. The Brazilian Amazon Forest harbors one of the highest diversity of Leishmania parasites and vectors and is one of the main focuses of the disease in the Americas. Previous studies showed that some types of anthropogenic disturbances have affected the abundance and distribution of CL vectors and hosts; however, few studies have thoroughly investigated the influence of different classes of land cover and land-use changes on the disease transmission risk. Here, we quantify the effect of land use and land-cover changes on the incidence of CL in all municipalities within the Brazilian Amazon Forest, from 2001 to 2017. We used a structured spatiotemporal Bayesian model to assess the effect of forest cover, agriculture, livestock, extractivism, and- deforestation on CL incidence, accounting for confounding variables such as population, climate, socioeconomic, and spatiotemporal random effects. We found that the increased risk of CL was associated with deforestation, especially modulated by a positive interaction between forest cover and livestock. Landscapes with ongoing deforestation for extensive cattle ranching are typically found in municipalities within the Amazon Frontier, where a high relative risk for CL was also identified. These findings provide valuable insights into developing effective public health policies and land-use planning to ensure healthier landscapes for people.
Keywords
Brazil/epidemiology, Leishmaniasis, Cutaneous/epidemiology, Incidence, Bayes Theorem, Conservation of Natural Resources, Forests, Animals, Agriculture, Humans, Spatio-Temporal Analysis, Bayesian modeling, Disease risk, Land use change, Spatio-temporal
Pubmed
Create date
13/09/2024 15:34
Last modification date
28/09/2024 7:09