Suparit Parinya, Wiratsudakul Anuwat, Modchang Charin
Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand.
Department of Clinical Sciences and Public Health, Faculty of Veterinary Science, Mahidol University, Phutthamonthon, Nakhon Pathom, 73170, Thailand.
Theor Biol Med Model. 2018 Aug 1;15(1):11. doi: 10.1186/s12976-018-0083-z.
Mathematical modeling has become a tool used to address many emerging diseases. One of the most basic and popular modeling frameworks is the compartmental model. Unfortunately, most of the available compartmental models developed for Zika virus (ZIKV) transmission were designed to describe and reconstruct only past, short-time ZIKV outbreaks in which the effects of seasonal change to entomological parameters can be ignored. To make an accurate long-term prediction of ZIKV transmission, the inclusion of seasonal effects into an epidemic model is unavoidable.
We developed a vector-borne compartmental model to analyze the spread of the ZIKV during the 2015-2016 outbreaks in Bahia, Brazil and to investigate the impact of two vector control strategies, namely, reducing mosquito biting rates and reducing mosquito population size. The model considered the influences of seasonal change on the ZIKV transmission dynamics via the time-varying mosquito biting rate. The model was also validated by comparing the model prediction with reported data that were not used to calibrate the model.
We found that the model can give a very good fit between the simulation results and the reported Zika cases in Bahia (R-square = 0.9989). At the end of 2016, the total number of ZIKV infected people was predicted to be 1.2087 million. The model also predicted that there would not be a large outbreak from May 2016 to December 2016 due to the decrease of the susceptible pool. Implementing disease mitigation by reducing the mosquito biting rates was found to be more effective than reducing the mosquito population size. Finally, the correlation between the time series of estimated mosquito biting rates and the average temperature was also suggested.
The proposed ZIKV transmission model together with the estimated weekly biting rates can reconstruct the past long-time multi-peak ZIKV outbreaks in Bahia.
数学建模已成为应对许多新出现疾病的一种工具。最基本且最常用的建模框架之一是 compartmental 模型。不幸的是，大多数为寨卡病毒（ZIKV）传播开发的现有 compartmental 模型仅旨在描述和重建过去的短期 ZIKV 疫情，其中季节变化对昆虫学参数的影响可忽略不计。为了对 ZIKV 传播进行准确的长期预测，将季节效应纳入流行模型是不可避免的。
我们开发了一种媒介传播 compartmental 模型，以分析 2015 - 2016 年巴西巴伊亚州疫情期间 ZIKV 的传播情况，并研究两种媒介控制策略的影响，即降低蚊子叮咬率和减少蚊子种群数量。该模型通过随时间变化的蚊子叮咬率考虑了季节变化对 ZIKV 传播动态的影响。该模型还通过将模型预测与未用于校准模型的报告数据进行比较来进行验证。
我们发现该模型在模拟结果与巴伊亚州报告的寨卡病例之间能给出非常好的拟合（决定系数 R 平方 = 0.9989）。到 2016 年底，预计 ZIKV 感染总人数为 120.87 万。该模型还预测，由于易感人群的减少，2016 年 5 月至 12 月不会出现大规模疫情。结果表明，通过降低蚊子叮咬率来减轻疾病比减少蚊子种群数量更有效。最后，还提出了估计的蚊子叮咬率时间序列与平均温度之间的相关性。
所提出的 ZIKV 传播模型以及估计的每周叮咬率能够重建巴伊亚州过去长期的多峰 ZIKV 疫情。
