期刊
MATHEMATICAL BIOSCIENCES
卷 246, 期 2, 页码 252-259出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.mbs.2013.10.007
关键词
Dengue; Mathematical model; Parameter estimation; Markov chain Monte Carlo (MCMC)
资金
- Clemson University
- Oregon State University
Various simple mathematical models have been used to investigate dengue transmission. Some of these models explicitly model the mosquito population, while others model the mosquitoes implicitly in the transmission term. We study the impact of modeling assumptions on the dynamics of dengue in Thailand by fitting dengue hemorrhagic fever (DHF) data to simple vector-host and SIR models using Bayesian Markov chain Monte Carlo estimation. The parameter estimates obtained for both models were consistent with previous studies. Most importantly, model selection found that the SIR model was substantially better than the vector-host model for the DHF data from Thailand. Therefore, explicitly incorporating the mosquito population may not be necessary in modeling dengue transmission for some populations. (C) 2013 Elsevier Inc. All rights reserved.
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