My research focuses on the intersection of disease and macroecology. My main goal is to fill research gaps that will lead to a better understanding of the patterns and mechanisms contributing to parasite spread and the possible ways to mitigate pathogen impacts. While I have explored a broad range of avian parasites, from ticks to protozoans, such as Babesia, most of my research is focused on malaria and malaria-like (haemosporidian) parasites. I have studied malaria parasites using a range of advanced modelling techniques, including network analysis and hierarchical Bayesian models. My work investigates macroecological and evolutionary patterns of parasite-host dynamics and the consequences of land use change for disease in humans and wildlife. To do so, I apply remote sensing and causal inference analysis to quantify the impact of global change on disease transmission. My research contributes to mitigating disease outbreaks and wildlife burdens, ultimately improving conservation programs and human health policies in times of global change. 

Land use and climate change affect how parasites interact with their hosts and the environment, impacting parasite emergence, spillover risk, and infection patterns worldwide. My research aims to elucidate and predict the impact of land use and climate change on parasite transmission and emergence in wildlife and humans. Specifically, I aim to (1) quantify and forecast the burden of vector-borne diseases in response to land use and climate change and (2) elucidate the drivers of parasite community assembly, distribution, and diversity. My work leverages large databases for computational modelling. Insights from my research can help examine the community-level impacts of global change on environmental resilience, public health, and parasite-host interactions. 

1. Vector-borne disease burden in response to land use and climate change

Global change is rapidly altering ecosystems and life on Earth. Changes in land use, temperature, and precipitation patterns affect the distribution and dynamics of pathogens and their vectors. For instance, warming temperatures are predicted to alter malaria and dengue fever transmission. At the same time, forest loss can increase the incidence of diseases like malaria and leishmaniasis at the forest edge, while urbanisation is associated with a higher risk of urban diseases (e.g., dengue fever) and reduced risk of sylvatic and rural diseases. Understanding how global change affects parasite infection risk is crucial for preventing disease outbreaks and improving human health. 

I study how changes in land use and climate affect the dynamics of human vector-borne pathogens. My work integrates ecological modelling and spatial analysis techniques using global and publicly available data on wildlife parasites. This will enable the creation of sophisticated and quantitative models that predict the potential distribution, spillover, and emergence of multiple parasites under various global change scenarios. Key unanswered questions—such as the impact of climate change on disease distribution, the evolutionary mechanisms behind wildlife-to-human spillover, and the influence of land use on disease dynamics—are central to my research.

2. Drivers of parasite community assembly, distribution, and diversity

Parasites play a pivotal role in ecosystem functioning by altering host fitness, survival, and mediating species interactions. Hence, my research will explore wildlife vector-borne pathogens (e.g., malaria, Trypanosoma, microfilaria) and use hierarchical Bayesian modelling, machine learning, and simulations to address several critical ecological questions, including: How do host behaviour, vector traits, and climate change affect parasite diversity and distribution? How do co-infections and parasite-host community structure alter ecological dynamics, such as prevalence and diversity? What are the mechanisms contributing to parasite dispersal, including vector movement and human-mediated dispersal? My research aims to enhance our understanding of parasite dynamics and their broader ecological implications using quantitative mathematical modelling. Filling this knowledge gap is essential for developing strategies to mitigate the impacts of infectious diseases and global change on wildlife and human health.