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

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.