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Titlebook: Epidemics; Models and Data Usin Ottar N. Bjørnstad Book 2023Latest edition The Editor(s) (if applicable) and The Author(s), under exclusive

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Pamela Milner,Geoffrey Burnstockminal paper that introduced the equations for the general Susceptible–Infected–Removed model and showed how a set of restrictive assumptions lead to the standard SIR model of ordinary differential equations.
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https://doi.org/10.1007/978-3-540-77596-6ity may build up with age, how age-specific heterogeneities may affect this, and how we can use immune data to back-calculate key dynamic quantities. There are two main branches of the adaptive immune system—the part of the immune system that helps to build a repertoire for protection against reinfection.
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https://doi.org/10.1007/978-3-540-69334-5ve stages outside the host and via host demographies from changing birth rates, carrying capacitities, social organization, etc. Sometimes such influences have relatively subtle consequences (e.g., slight changes in ..) as is likely the effect of absolute humidity oninfluenza transmission (Lowen et al., .; Bjørnstad & Viboud, .).
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https://doi.org/10.1007/978-3-322-91414-9raphic and environmental stochasticity (sometimes referred to jointly as “process error”), observation error, and partial (missing) observation. The strategies also often vary by whether the underlying dynamics is thought to be best approximated in continuous time (differential models) or discrete time (difference models).
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https://doi.org/10.1007/978-3-663-02297-8s classified as rabies, there are a wide range of related lyssaviruses of bats that can also spill over to humans. These viruses are transmitted from saliva during aggressive encounters involving biting.
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Malahat Wittmann,Kerstin Dübner-Gee stability, and resonant periodicity. As remarked by Nisbet and Gurney (.) more generally, linear approximation can often provide remarkably useful insights for nonlinear ecological systems as long as they are not too nonlinear.
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