Rawson Thomas, Wilkins Kym E, Bonsall Michael B
Mathematical Ecology Research Group, Department of Zoology, University of Oxford, Oxford OX1 3PS, UK.
School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia.
R Soc Open Sci. 2020 Apr 22;7(4):181843. doi: 10.1098/rsos.181843. eCollection 2020 Apr.
Dengue is a debilitating and devastating viral infection spread by mosquito vectors, and over half the world's population currently live at risk of dengue (and other flavivirus) infections. Here, we use an integrated epidemiological and vector ecology framework to predict optimal approaches for tackling dengue. Our aim is to investigate how vector control and/or vaccination strategies can be best combined and implemented for dengue disease control on small networks, and whether these optimal strategies differ under different circumstances. We show that a combination of vaccination programmes and the release of genetically modified self-limiting mosquitoes (comparable to sterile insect approaches) is always considered the most beneficial strategy for reducing the number of infected individuals, owing to both methods having differing impacts on the underlying disease dynamics. Additionally, depending on the impact of human movement on the disease dynamics, the optimal way to combat the spread of dengue is to focus prevention efforts on large population centres. Using mathematical frameworks, such as optimal control, are essential in developing predictive management and mitigation strategies for dengue disease control.
登革热是一种由蚊媒传播的使人衰弱且具有破坏性的病毒感染,目前全球超过一半的人口面临登革热(以及其他黄病毒)感染的风险。在此,我们使用一个综合的流行病学和病媒生态学框架来预测应对登革热的最佳方法。我们的目的是研究如何将病媒控制和/或疫苗接种策略进行最佳组合并在小型网络中实施以控制登革热疾病,以及这些最佳策略在不同情况下是否有所不同。我们表明,疫苗接种计划和释放转基因自限性蚊子(类似于不育昆虫方法)的组合始终被认为是减少感染个体数量的最有益策略,这是因为这两种方法对潜在疾病动态具有不同的影响。此外,根据人类流动对疾病动态的影响,抗击登革热传播的最佳方法是将预防工作集中在大型人口中心。使用诸如最优控制等数学框架对于制定登革热疾病控制的预测性管理和缓解策略至关重要。