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Network analyses to quantify effects of host movement in multilevel disease transmission models using foot and mouth disease in Cameroon as a case study.
Pomeroy, Laura W; Kim, Hyeyoung; Xiao, Ningchuan; Moritz, Mark; Garabed, Rebecca.
Afiliación
  • Pomeroy LW; Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, United States of America.
  • Kim H; Department of Geography, The Ohio State University, Columbus, OH, United States of America.
  • Xiao N; Department of Disease Control and Epidemiology, National Verterinary Institute, Uppsala, Sweden.
  • Moritz M; Department of Geography, The Ohio State University, Columbus, OH, United States of America.
  • Garabed R; Department of Anthropology, The Ohio State University, Columbus, OH, United States of America.
PLoS Comput Biol ; 15(8): e1007184, 2019 08.
Article en En | MEDLINE | ID: mdl-31465448
ABSTRACT
The dynamics of infectious diseases are greatly influenced by the movement of both susceptible and infected hosts. To accurately represent disease dynamics among a mobile host population, detailed movement models have been coupled with disease transmission models. However, a number of different host movement models have been proposed, each with their own set of assumptions and results that differ from the other models. Here, we compare two movement models coupled to the same disease transmission model using network analyses. This application of network analysis allows us to evaluate the fit and accuracy of the movement model in a multilevel modeling framework with more detail than established statistical modeling fitting methods. We used data that detailed mobile pastoralists' movements as input for 100 stochastic simulations of a Spatio-Temporal Movement (STM) model and 100 stochastic simulations of an Individual Movement Model (IMM). Both models represent dynamic movement and subsequent contacts. We generated networks in which nodes represent camps and edges represent the distance between camps. We simulated pathogen transmission over these networks and tested five network metrics-strength, betweenness centrality, three-step reach, density, and transitivity-to determine which could predict disease simulation outcomes and thereby be used to correlate model simulation results with disease transmission simulations. We found that strength, network density, and three-step reach of movement model results correlated with the final epidemic size of outbreak simulations. Betweenness centrality only weakly correlated for the IMM model. Transitivity only weakly correlated for the STM model and time-varying IMM model metrics. We conclude that movement models coupled with disease transmission models can affect disease transmission results and should be carefully considered and vetted when modeling pathogen spread in mobile host populations. Strength, network density, and three-step reach can be used to evaluate movement models before disease simulations to predict final outbreak sizes. These findings can contribute to the analysis of multilevel models across systems.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fiebre Aftosa / Modelos Biológicos Tipo de estudio: Prognostic_studies Límite: Animals / Humans País/Región como asunto: Africa Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fiebre Aftosa / Modelos Biológicos Tipo de estudio: Prognostic_studies Límite: Animals / Humans País/Región como asunto: Africa Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos