Modelling vector-borne disease epidemic risks using forward climate projections

A large amount of work has been done in the field of vector-borne diseases. Work from here can be used to build models for vector-borne diseases of interest (such as Zika virus or Dengue fever). This is a very frequently researched area and so models of these diseases are robust and have been shown to make sensible real-world predictions. Studies have also been done on climate dependent mosquito population models [3,4]. These models vary in their complexity and include parameters such as temperature, humidity and rainfall to provide forward projections for the population of mosquitoes. Such models can be used in this project and embedded within the aforementioned epidemiological models to create systems where climate varying epidemic risks can be studied. These models have been used to estimate the reproduction number of a disease and to simulate outbreak dynamics but not to estimate the risk that early cases generate an epidemic. The IER is frequently examined because it is a very standard result in epidemiology and is widely used in many studies [5], particularly those in which climate effects on epidemic risks are not accounted for. The IER is often computed using a population model embedded inside an epidemiological model as detailed above. However, there is very little work done on the CER. The CER has been examined in a basic host-vector model but this only allows for varying death rates (and not varying population of mosquitoes) [6]. Studies on the CER do not use climate change forward projections, and instead focus on local change in climatic conditions over the course of a year. This research fits well into the broader context of the field because very little work has been done on the CER with none having been done using real-world climate projections. This project aims to answer several questions in the field of epidemic risk and vector-borne diseases. Are vector-borne diseases more likely under a changing climate? Is it the case that climate change uniformly increases the risk of large outbreaks of vector-borne diseases occurring or are there geographical areas where the risk is likely to decrease? What is the distribution of regions that are high and low risk? Other questions to be answered include, is the IER a suitable approximation for the epidemic risk or does the CER need to be computed? Can these two theoretical quantities be related to practically useful outbreak risk metrics, such as the probability of an outbreak exceeding a certain number of cases? How much variation is there in epidemic risk in a given region when the initial conditions for the climate simulations are varied? Do there exist places where the epidemic risk is consistently high or consistently low? This research closely relates to the EPSRC in both content and wider goals. The content is in the field of mathematical epidemiology where novel methodologies will be used to construct a mathematical framework for predicting the outbreak risk of vector-borne diseases. This project also extends to the physical sciences (due to climate change data), living with environmental change and global uncertainties. Particular emphasis will be placed on communicating research outcomes with both the external partner and the scientific community as a whole. There is also potential for public outreach and generating awareness of the topic. Research areas; Global uncertainties, LWEC [Living With Environmental Change], Mathematical Sciences, Physical Sciences External Partner; Colorado State University, and National Center for Atmospheric Research, USA