ArticleJournal of the Royal Society, Interface2020
A multivariate geostatistical framework for combining multiple indices of abundance for disease vectors and reservoirs: a case study of
Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
- Incorporating Machine Learning Techniques to Enhance Rodent Surveillance in Marginalized Urban Communities.Ecology and evolution · 2025Article
- Disentangling the influence of reservoir abundance and pathogen shedding on zoonotic spillover of theFrontiers in public health · 2024Article
- Burden of leptospirosis in Brazil in the last decade.Revista de saude publica · 2024Article
- Article
- Population dynamics of synanthropic rodents after a chemical and infrastructural intervention in an urban low-income community.Scientific reports · 2022Article
- Effect of Sewerage on the Contamination of Soil with PathogenicEnvironmental science & technology · 2021Article
Corrections and comments
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Authors and funding
13 authors at 6 institutions in 4 countries.
Funding
Abstract
A key requirement in studies of endemic vector-borne or zoonotic disease is an estimate of the spatial variation in vector or reservoir host abundance. For many vector species, multiple indices of abundance are available, but current approaches to choosing between or combining these indices do not fully exploit the potential inferential benefits that might accrue from modelling their joint spatial distribution. Here, we develop a class of multivariate generalized linear geostatistical models for multiple indices of abundance. We illustrate this novel methodology with a case study on Norway rats in a low-income urban Brazilian community, where rat abundance is a likely risk factor for human leptospirosis. We combine three indices of rat abundance to draw predictive inferences on a spatially continuous latent process,
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.