ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2019
A probabilistic census-travel model to predict introduction sites of exotic plant, animal and human pathogens.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Modelling the spread and mitigation of an emerging vector-borne pathogen: Citrus greening in the U.S.PLoS computational biology · 2023Article
- Article
- Optimising risk-based surveillance for early detection of invasive plant pathogens.PLoS biology · 2020Article
- Canine olfactory detection of a vectored phytobacterial pathogen, Liberibacter asiaticus, and integration with disease control.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Emergence of a Plant Pathogen in Europe Associated with Multiple Intercontinental Introductions.Applied and environmental microbiology · 2020Article
- Preface to theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
- Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
International travel offers an extensive network for new and recurring human-mediated introductions of exotic infectious pathogens and biota, freeing geographical constraints. We present a predictive census-travel model that integrates international travel with endpoint census data and epidemiological characteristics to predict points of introduction. Population demographics, inbound and outbound travel patterns, and quantification of source strength by country are combined to estimate and rank risk of introduction at user-scalable land parcel areas (e.g. state, county, zip code, census tract, gridded landscapes (1 mi
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