ARBOVERSE, a data-driven platform and disease modeling to anticipate and mitigate arbovirus emergence


  • Dr Nuno Faria

    Imperial College London, United Kingdom

  • Dr William de Souza

    University of Texas Medical Branch, United States

  • Dr Seth Flaxman

    University of Oxford, United Kingdom

  • Dr Swapnil Mishra

    University of Copenhagen, Denmark

  • Dr Samir Bhatt

    Imperial College London, United Kingdom

Project summary

Arboviral diseases are critical climate-sensitive infectious diseases and increasing global public health threats.

Arboviral epidemics will continue to occur as urban growth and globalization expand; however, predicting where and when the next arbovirus epidemic will occur remains challenging. Therefore, investigating and understanding the environmental determinants associated with arbovirus (re-)emergence is essential to developing the most cost-effective and sustainable strategies to prevent outbreaks and reduce arboviral disease burden.

Currently, there are three major research gaps to anticipating, preparing, and mitigating outbreaks and epidemics caused by arboviruses, including:

(i) data about the global diversity of arboviruses remains unsynthetized

(ii) lack of knowledge about the global distribution of arboviruses, and

(iii) some potential generalized patterns and drivers associated with (re-)emergence of arboviruses remain poorly investigated.

In this study, we will create a user-friendly data-driven platform that provides open access to knowledge about arboviruses in a broad context. Then, we will evaluate the impact of macro-ecological traits (e.g., climate change, deforestation, urbanization, and human mobility) on the (re-)emergence of arboviruses and determine the potential hotspots for arbovirus discovery.

Overall, our results will improve understanding of arboviral emergence and provide tools to mitigate them, with direct implications for global public health.