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- W3080597931 abstract "Early theories of pathogen transmission were based on random interactions among host individuals with models essentially borrowed from chemistry (1), providing fundamental analytical results including the structure of the basic reproductive number for pathogen invasion (the number of secondary cases caused by an infectious individual in a susceptible population) and the “herd immunity” fraction of a population that must be immunized to eradicate disease (2). Moreover, these “well-mixed” models have done an impressive job in explaining complex patterns in disease data (3). However, the collation and sharing of high-quality data have pushed the field forward, identifying the importance of movement of individuals between discrete populations in the persistence and spread of infectious diseases (4, 5). In efforts to identify how detailed models must be to explain and predict spatial dynamics, gravity models have proven their worth (6⇓–8). At their simplest, connectivity between populations depends positively on population sizes and inversely on distance. However, these hybrid mechanistic–statistical models can test far more than the importance of population sizes and geographic location. The challenge is to identify the kinds of data that … [↵][1]1Email: awpark{at}uga.edu. [1]: #xref-corresp-1-1" @default.
- W3080597931 created "2020-09-01" @default.
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- W3080597931 date "2020-08-24" @default.
- W3080597931 modified "2023-09-24" @default.
- W3080597931 title "Trip duration modifies spatial spread of infectious diseases" @default.
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- W3080597931 doi "https://doi.org/10.1073/pnas.2015730117" @default.
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