Mathematical Biosciences Institute, The Ohio State University, Columbus, 43210 Ohio, United States of America.
Department of National Statistics, Korea University, Sejong, 30019, Republic of Korea.
PLoS One. 2018 Nov 7;13(11):e0206418. doi: 10.1371/journal.pone.0206418. eCollection 2018.
We describe a method for analyzing the within-household network dynamics of a disease transmission. We apply it to analyze the occurrences of endemic diarrheal disease in Cameroon, Central Africa based on observational, cross-sectional data available from household health surveys.
To analyze the data, we apply formalism of the dynamic SID (susceptible-infected-diseased) process that describes the disease steady-state while adjusting for the household age-structure and environment contamination, such as water contamination. The SID transmission rates are estimated via MCMC method with the help of the so-called synthetic likelihood approach.
The SID model is fitted to a dataset on diarrhea occurrence from 63 households in Cameroon. We show that the model allows for quantification of the effects of drinking water contamination on both transmission and recovery rates for household diarrheal disease occurrence as well as for estimation of the rate of silent (unobserved) infections.
The new estimation method appears capable of genuinely capturing the complex dynamics of disease transmission across various human, animal and environmental compartments at the household level. Our approach is quite general and can be used in other epidemiological settings where it is desirable to fit transmission rates using cross-sectional data.
The R-scripts for carrying out the computational analysis described in the paper are available at https://github.com/cbskust/SID.
我们描述了一种分析疾病传播的家庭网络动态的方法。我们应用它来分析中非喀麦隆基于家庭健康调查的观测性横断面数据中地方性腹泻病的发生情况。
为了分析数据，我们应用描述疾病稳态的动态 SID（易感-感染-患病）过程的形式主义，同时调整家庭年龄结构和环境污染（如水污染）。SID 传播率通过 MCMC 方法借助所谓的综合似然方法进行估计。
SID 模型拟合了来自喀麦隆 63 个家庭的腹泻发生数据集。我们表明，该模型允许量化饮用水污染对家庭腹泻病发生的传播和恢复率的影响，以及对沉默（未观察到）感染率的估计。
新的估计方法似乎能够真正捕捉家庭层面上各种人类、动物和环境隔室中疾病传播的复杂动态。我们的方法非常通用，可以在其他希望使用横断面数据拟合传播率的流行病学环境中使用。
可在 https://github.com/cbskust/SID 上获取执行本文所述计算分析的 R 脚本。
