Socio-ecological dynamics of zoonotic and vector-borne diseases in changing landscapes: implications for surveillance and control

Grant number: 221963

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Key facts

  • Disease

    Zika virus disease, Dengue
  • Start & end year

    2021
    2026
  • Known Financial Commitments (USD)

    $1,636,323.96
  • Funder

    Wellcome Trust
  • Principal Investigator

    Professor Daniel Haydon
  • Research Location

    United Kingdom
  • Lead Research Institution

    University of Glasgow
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Disease transmission dynamics

  • 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

Landscape changes disrupt infectious disease dynamics, requiring new approaches to characterise risks and prevent outbreaks. Focusing on emerging (Chikungunya, Zika) and epidemic (malaria, dengue) zoonotic and vector-borne diseases in Malaysia and the Philippines, I aim to design and evaluate enhanced surveillance systems linking health and environmental data to detect and prevent pathogen spillover and transmission. By developing novel models relating social and ecological processes across spatial and temporal scales, I will bridge critical gaps linking environmental change with human behaviour and health systems. Fine-scale studies of human mobility, behaviour and infection risks will be integrated within a large-scale experiment on tropical forest modification to understand how landscape change both interacts with and alters environmental factors (e.g. seasonality, biodiversity) and socioeconomic and biological factors (e.g. demography, mobility, immunity) to determine disease dynamics. Statistical and mathematical models will be used to explore factors across ecological settings, integrating routine surveillance data, population-based serological surveys and multitemporal Earth Observation data to reconstruct historical disease transmission over major environmental shifts. Predictive models will be designed to identify how future land use can reduce disease risks and how control programmes can use environmental data from new sources of real-time Earth Observation data to improve disease surveillance.

Publicationslinked via Europe PMC

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Exploring barriers to and facilitators of malaria prevention practices: a photovoice study with rural communities at risk to Plasmodium knowlesi malaria in Sabah, Malaysia.

Mapping Malaria Vector Habitats in West Africa: Drone Imagery and Deep Learning Analysis for Targeted Vector Surveillance.

A protocol for a longitudinal, observational cohort study of infection and exposure to zoonotic and vector-borne diseases across a land-use gradient in Sabah, Malaysian Borneo: a socio-ecological systems approach.

A protocol for a longitudinal, observational cohort study of infection and exposure to zoonotic and vector-borne diseases across a land-use gradient in Sabah, Malaysian Borneo: a socio-ecological systems approach

High diversity and suggested endemicity of culturable Actinobacteria in an extremely oligotrophic desert oasis.