Mweya Clement N, Holst Niels, Mboera Leonard E G, Kimera Sharadhuli I
National Institute for Medical Research, Tukuyu, Tanzania; Department of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania.
Department of Agroecology, Aarhus University, Slagelse, Denmark.
PLoS One. 2014 Sep 26;9(9):e108430. doi: 10.1371/journal.pone.0108430. eCollection 2014.
Rift Valley Fever (RVF) is weather dependent arboviral infection of livestock and humans. Population dynamics of mosquito vectors is associated with disease epidemics. In our study, we use daily temperature and rainfall as model inputs to simulate dynamics of mosquito vectors population in relation to disease epidemics.
METHODS/FINDINGS: Time-varying distributed delays (TVDD) and multi-way functional response equations were implemented to simulate mosquito vectors and hosts developmental stages and to establish interactions between stages and phases of mosquito vectors in relation to vertebrate hosts for infection introduction in compartmental phases. An open-source modelling platforms, Universal Simulator and Qt integrated development environment were used to develop models in C++ programming language. Developed models include source codes for mosquito fecundity, host fecundity, water level, mosquito infection, host infection, interactions, and egg time. Extensible Markup Language (XML) files were used as recipes to integrate source codes in Qt creator with Universal Simulator plug-in. We observed that Floodwater Aedines and Culicine population continued to fluctuate with temperature and water level over simulation period while controlled by availability of host for blood feeding. Infection in the system was introduced by floodwater Aedines. Culicines pick infection from infected host once to amplify disease epidemic. Simulated mosquito population show sudden unusual increase between December 1997 and January 1998 a similar period when RVF outbreak occurred in Ngorongoro district.
CONCLUSION/SIGNIFICANCE: Findings presented here provide new opportunities for weather-driven RVF epidemic simulation modelling. This is an ideal approach for understanding disease transmission dynamics towards epidemics prediction, prevention and control. This approach can be used as an alternative source for generation of calibrated RVF epidemics data in different settings.
裂谷热（RVF）是一种受天气影响的、感染牲畜和人类的虫媒病毒感染。蚊媒的种群动态与疾病流行有关。在我们的研究中，我们将每日温度和降雨量作为模型输入，以模拟与疾病流行相关的蚊媒种群动态。
方法/发现：采用时变分布延迟（TVDD）和多向功能反应方程来模拟蚊媒和宿主的发育阶段，并建立蚊媒各阶段与相之间与脊椎动物宿主的相互作用，以便在分区阶段引入感染。使用开源建模平台通用模拟器和Qt集成开发环境，用C++编程语言开发模型。开发的模型包括蚊繁殖力、宿主繁殖力、水位、蚊感染、宿主感染、相互作用和卵期的源代码。可扩展标记语言（XML）文件用作将Qt Creator中的源代码与通用模拟器插件集成的方法。我们观察到，在整个模拟期内，洪水伊蚊和库蚊种群随温度和水位持续波动，同时受宿主血液供应的控制。系统中的感染由洪水伊蚊引入。库蚊一旦从受感染宿主身上感染，就会扩大疾病流行。模拟的蚊种群在1997年12月至1998年1月间出现突然异常增加，这一时期恩戈罗恩戈罗区发生了裂谷热疫情。
结论/意义：本文的研究结果为天气驱动的裂谷热疫情模拟建模提供了新机会。这是理解疾病传播动态以进行疫情预测、预防和控制的理想方法。这种方法可作为在不同环境中生成校准后的裂谷热疫情数据的替代来源。
