Understanding the impact of global change on animal-borne diseases

Grant number: 220179

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Key facts

  • Disease

    Lassa Haemorrhagic Fever
  • Start & end year

    2020
    2025
  • Known Financial Commitments (USD)

    $897,506.28
  • Funder

    Wellcome Trust
  • Principal Investigator

    Dr. David Redding
  • Research Location

    United Kingdom
  • Lead Research Institution

    University College London
  • Research Priority Alignment

    N/A
  • Research Category

    Animal and environmental research and research on diseases vectors

  • Research Subcategory

    Animal source and routes of transmission

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

We know little about how future climate change, habitat destruction, human population increases and greater globalisation processes will impact human zoonotic diseases. Here, I investigate the use of dynamic, seasonal host population models to better predict the impact of real-time environmental change on disease-carrying host species, within a general systems-dynamics, disease framework. Specifically, I will combine a mathematical compartmental disease model with a host population ecology model, within a spatial and temporal Bayesian framework. Using this approach, I will first model Lassa Fever using climate and land-use observations, collaborating with the Nigerian government. I will then augment my model to account for animal movement patterns and vector species abundances, to examine arboviral disease spread in North America. Then, I will integrate these threads into a general, dynamic modelling framework for zoonotic diseases, which will contain both the newly developed components and my previously developed model of human movement and behaviour. Working with the World Health Organisation, I will create short- and long-term disease forecasts for a set of high priority zoonoses. Once validated against human case data, these mechanistic models can be used to test interventions and create future disease management plans that are robust to upcoming global change.

Publicationslinked via Europe PMC

Protocol to produce a systematic Arenavirus and Hantavirus host-pathogen database: Project ArHa.

Towards a 'people and nature' paradigm for biodiversity and infectious disease.