Inference for Vector-borne Diseases

Vector-borne diseases are a class of diseases in which infection is transmitted between hosts by a vector organism. Examples rank highly among the world's most devastating diseases, for example malaria transmitted between humans by mosquitos, and African sleeping sickness transmitted between many species of mammalian hosts (including humans) by the tsetse fly vector.

This project is developing methodology for forecasting vector-borne diseases using stochastic dynamical models:

  • Statistical fitting algorithms for inference on dynamical disease models.
  • Data assimilation for including many sources of epidemiological and ecological data.
  • Spatial latent risk surfaces for vector-associated disease risk.