Using Mathematical Models to Explore the Co-infection Dynamics Between Dengue, Chikungunya, Zika and Malaria

虫媒病毒感染在南美洲、非洲和亚洲具有严重影响。寨卡病毒、登革热和基孔肯雅热都给全球带来了沉重的负担。严重的登革热具有潜在的致命性，寨卡病毒会导致神经系统并发症和先天性畸形，而基孔肯雅热则会导致数周甚至数年的严重关节疼痛。更令人担忧的是合并感染的可能性，这可能会对患者的预后产生什么影响？基孔肯雅热、登革热和寨卡病毒是由同一种蚊子-埃及伊蚊和白纹伊蚊-携带的，已经有证据表明蚊子和人类同时感染。随着这些疾病变得越来越普遍，合并感染很可能会变得更加常见。虽然预计来自这些虫媒病毒的混合感染的影响将是严重的，但奇怪的是，研究表明，疟疾这种疟原虫的混合感染再次保护了基孔肯雅病的病理。有没有可能它对其他虫媒病毒也有保护作用？疟疾也是由同样的蚊子传播的，也是造成高全球负担的罪魁祸首，可能导致死亡，而且令人担忧的是，疟疾对治疗的抵抗率很高。观察疟疾和三种虫媒病毒之间的相互作用将是非常有趣的；与疟疾合并感染是否可能保护人口或使病理恶化。该项目旨在利用南美洲的数学模型和数据来探索人群和个人层面的联合感染之间的相互作用。通过研究几个邻国的联合感染动态，希望能够与危险因素一起阐明联合感染的趋势。该模型将使用区域数据来探索每个国家内的空间动态，这将考虑到环境差异。在项目后期，将探索预防战略，试图降低这些感染和混合感染的风险。

Arbovirus infections have a serious impact in the South Americas, Africa and Asia. Zika, dengue and chikungunya all have a high global burden. Severe dengue is potentially deadly, zika can result in neurological complications and congenital malformations whilst chikungunya can cause severe joint pain for weeks occasionally years. Even more concerning is the possibility for co-infection, what impact might this have on patient prognosis? Chikungunya, dengue and zika are carried by the same species of mosquito, Aedes aegypti and Aedes albopictus, and there has already been evidence of co-infection in mosquitos as well as in humans. As these diseases become more widespread it is quite possible that co-infection will become much more common. Whilst, it is expected that the impact of co-infection from these arboviruses would be severe, it is curious that research has indicated that co-infection of malaria, a plasmodium, protects again the pathologies of chikungunya. Is it possible that it is protective of the other arboviruses too? Malaria is also carried by the same mosquitos and is also responsible for a high global burden possibly causing death and rather worryingly has high rates of resistance to treatment. It would be very interesting to see the interaction between malaria and the three arboviruses; whether co-infection with malaria might protect the population or exasperate pathologies. This project aims to explore the interplay between co-infection at a population and individualistic level using mathematical models and data from the South Americas. By studying co-infection dynamics across several neighbouring countries, it is hoped that trends in co-infection might be able to be elucidated alongside risk factors. The model will use regional data to explore spatial dynamics within each country which will allow for environmental differences. Later in the project prevention strategies will be explored to try to reduce the risk of these infections and co-infection.