Understanding zoonotic disease risk using dynamic ecological models

The natural world is expected to undergo a significant transformation over the next century, driven by climate change, habitat destruction, human population increase and greater globalisation. Many diseases, such as Ebola, Plague and Anthrax, are caught when people come into contact with wild animals and these diseases are called 'zoonoses'. Processes within the natural and human world dictate where the species that carry zoonoses are currently found, and any changes to these underlying processes will lead to differences in where disease-carrying species can live, and therefore, the locations where people can catch diseases from them. I will create the first, comprehensive but general model of the ecology and epidemiology of a set of high priority African zoonoses, focusing on those diseases that have a major impact on the livelihoods of poor and vulnerable human communities. My modelling approach will capture the seasonal and annual differences to the environmental conditions that host species experience and then determine the different physical routes by which species can then move around the globe to respond to environmental change. After testing against real disease case data, my modelling framework will, for the first time, allow researchers and policy makers to simultaneously aim to minimise the number of people who can contract a wide set of very different zoonoses, and then predict how climate and land-use change will impact these policy decisions in the future. My work has the potential to reduce disease burden and consequently levels of human suffering across Africa in the future.

The natural world is expected to undergo a significant transformation over the next century, driven by climate change, habitat destruction, human population increases and greater globalisation. Many animal-borne or zoonotic human diseases (e.g. Ebola, Plague, Anthrax) are caught from non-domesticated, wild species and these host species will likely alter their spatial distribution and behaviour in response to environmental change. To examine how this process will impact human zoonotic diseases, I will first create a dynamic, species distribution model that incorporates the latest, fine-scale remote-sensed data, to predict the real-time environmental suitability for disease-carrying host species. On these suitability surfaces, I will run mechanistic models of host species population dynamics, which I can use to assess the role of seasonal and annual changes to the environment and to better predict host abundance and, subsequently, host-human contact rates. I will then create two environmentally-responsive movement networks, the first consisting of major animal migrations and the second of human transportation methods, which I can then apply to historical and future environments to model zoonotic disease spread and animal invasions. I will then integrate these major work threads into a global, dynamic, 'whole systems' modelling framework of zoonotic diseases, containing both a dynamic ecological model component and a previously developed, empirically-based model of human population density, poverty and behaviour. This framework, when validated against empirical animal occurrence and disease case data, will be allowed to run on a set of high priority zoonoses in Africa to test policy interventions in present day conditions and then test how different drivers of expected future global change will impact the efficacy of these interventions.