A note on metapopulation models
원문 초록
Metapopulation models are commonly used in ecology, evolution, and epidemiology. These models usually entail homogeneity assumptions within patches and study networks of migration between patches to generate insights into conservation of species, differentiation of populations, and persistence of infectious diseases. Here, focusing on infectious disease epidemiology, we take a complementary approach and study the effects of individual variation within patches while neglecting any form of disease transmission between patches. Consistently with previous work on single populations, we show how metapopulation models that neglect in-patch heterogeneity also underestimate basic reproduction numbers ($\mathcal{R}_{0}$) and the effort required to control or eliminate infectious diseases by uniform interventions. We then go beyond this confirmatory result and introduce a scheme to infer distributions of individual susceptibility or exposure to infection based on suitable stratifications of a population into patches. We apply the resulting metapopulation models to a simple case study of the COVID-19 pandemic.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Simple Approximate Bayesian Inference Neural Surrogate for Stochastic Petri Net Models
Clustering and Pruning in Causal Data Fusion
Structural-Temporal Coupling Anomaly Detection with Dynamic Graph Transformer
A Behaviour and Disease Model of Testing and Isolation
Optimal virulence strategies in epidemiological models with asymptomatic transmission
Filtered Markovian Projection: Dimensionality Reduction in Filtering for Stochastic Reaction Networks
토론
이 논문과 연결된 포럼 글이 아직 없습니다.