Wiratsudakul Anuwat, Suparit Parinya, Modchang Charin
Department of Clinical Sciences and Public Health, Faculty of Veterinary Science, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand.
The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals, Faculty of Veterinary Science, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand.
PeerJ. 2018 Mar 22;6:e4526. doi: 10.7717/peerj.4526. eCollection 2018.
The Zika virus was first discovered in 1947. It was neglected until a major outbreak occurred on Yap Island, Micronesia, in 2007. Teratogenic effects resulting in microcephaly in newborn infants is the greatest public health threat. In 2016, the Zika virus epidemic was declared as a Public Health Emergency of International Concern (PHEIC). Consequently, mathematical models were constructed to explicitly elucidate related transmission dynamics.
In this review article, two steps of journal article searching were performed. First, we attempted to identify mathematical models previously applied to the study of vector-borne diseases using the search terms "dynamics," "mathematical model," "modeling," and "vector-borne" together with the names of vector-borne diseases including chikungunya, dengue, malaria, West Nile, and Zika. Then the identified types of model were further investigated. Second, we narrowed down our survey to focus on only Zika virus research. The terms we searched for were "compartmental," "spatial," "metapopulation," "network," "individual-based," "agent-based" AND "Zika." All relevant studies were included regardless of the year of publication. We have collected research articles that were published before August 2017 based on our search criteria. In this publication survey, we explored the Google Scholar and PubMed databases.
We found five basic model architectures previously applied to vector-borne virus studies, particularly in Zika virus simulations. These include compartmental, spatial, metapopulation, network, and individual-based models. We found that Zika models carried out for early epidemics were mostly fit into compartmental structures and were less complicated compared to the more recent ones. Simple models are still commonly used for the timely assessment of epidemics. Nevertheless, due to the availability of large-scale real-world data and computational power, recently there has been growing interest in more complex modeling frameworks.
Mathematical models are employed to explore and predict how an infectious disease spreads in the real world, evaluate the disease importation risk, and assess the effectiveness of intervention strategies. As the trends in modeling of infectious diseases have been shifting towards data-driven approaches, simple and complex models should be exploited differently. Simple models can be produced in a timely fashion to provide an estimation of the possible impacts. In contrast, complex models integrating real-world data require more time to develop but are far more realistic. The preparation of complicated modeling frameworks prior to the outbreaks is recommended, including the case of future Zika epidemic preparation.
寨卡病毒于1947年首次被发现。直到2007年在密克罗尼西亚的雅浦岛发生大规模疫情之前，它一直未受到关注。导致新生儿小头畸形的致畸效应是最大的公共卫生威胁。2016年，寨卡病毒疫情被宣布为国际关注的突发公共卫生事件（PHEIC）。因此，构建了数学模型以明确阐释相关的传播动态。
在这篇综述文章中，进行了两个步骤的期刊文章检索。首先，我们试图通过使用搜索词“动态”“数学模型”“建模”和“媒介传播”以及包括基孔肯雅热、登革热、疟疾、西尼罗河病毒和寨卡病毒在内的媒介传播疾病名称，来识别先前应用于媒介传播疾病研究的数学模型。然后对已识别的模型类型进行进一步研究。其次，我们缩小调查范围，仅关注寨卡病毒研究。我们搜索的术语是“分区”“空间”“集合种群”“网络”“基于个体”“基于主体”以及“寨卡”。无论发表年份如何，所有相关研究都被纳入。根据我们的搜索标准，我们收集了2017年8月之前发表的研究文章。在这次出版物调查中，我们检索了谷歌学术和PubMed数据库。
我们发现了五种先前应用于媒介传播病毒研究，特别是寨卡病毒模拟的基本模型架构。这些包括分区模型、空间模型、集合种群模型、网络模型和基于个体的模型。我们发现，针对早期疫情构建的寨卡模型大多符合分区结构，并且与近期模型相比不太复杂。简单模型仍常用于及时评估疫情。然而，由于大规模现实世界数据的可用性和计算能力，最近人们对更复杂的建模框架越来越感兴趣。
数学模型用于探索和预测传染病在现实世界中的传播方式、评估疾病输入风险以及评估干预策略的有效性。随着传染病建模趋势已转向数据驱动方法，简单模型和复杂模型应区别使用。简单模型可以及时生成，以提供对可能影响的估计。相比之下，整合现实世界数据的复杂模型需要更多时间来开发，但更现实。建议在疫情爆发前准备复杂的建模框架，包括未来寨卡疫情的准备情况。
