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Through the eye of a mosquito: theoretical modelling of vector-borne zoonotic pathogens

Through the eye of a mosquito: theoretical modelling of vector-borne zoonotic pathogens

Objective

The spillover of wildlife diseases into humans is increasing, and represents one of the biggest global health challenges we are facing today. Many zoonoses are transmitted by vectors (i.e. mosquitos) and had a large number of vertebrates as reservoirs. Thus, to reduce its impact on humans, it is essential to understand the factors that promote or inhibite spillover into human populations. Thus, it is necessary to consider the epidemiology of the pathogens both in vertebrate and vector communities. Technically, this requires an integration of community and disease ecology into a single mathematical framework, which explicitly considers vectors and hosts as distinct species, with different potential for pathogen amplification and contact rates. While mechanistic models exploring vector population dynamics have a long history, multihost-multivector model have not adequately integrated heterogeneity in host-vector interactions, despite their obvious importance. Here, I will study the role of vector species with distinct behaviour and ecological requirements in shaping the complex pathogen transmission dynamics, and ultimately determining the spillover, persistance or extinction of pathogens. My objectives are at the interface of theoretical and empirical research: 1) I use a rich data set to characterize the web of interactions between vectors and hosts, 2) I extend existing theory to explicitly consider vectors as distinct species and 3) I then study the role that behavioural heterogeneity has in shaping the larder web, and ultimately determining the risk of spilling over vs. disease extinction. Because of there is an urgent need to combine theory with data, I will also create an open source webpage where all the details of my work will be regularly updated in order to set practical guidelines supporting integration of mathematical modelling, fieldwork and laboratory work into OneHealth studies.
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Coordinator

UNIVERSITEIT VAN AMSTERDAM

Address

Spui 21
1012wx Amsterdam

Netherlands

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 187 572,48

Project information

Grant agreement ID: 844285

Status

Grant agreement signed

  • Start date

    1 September 2020

  • End date

    31 August 2022

Funded under:

H2020-EU.1.3.2.

  • Overall budget:

    € 187 572,48

  • EU contribution

    € 187 572,48

Coordinated by:

UNIVERSITEIT VAN AMSTERDAM

Netherlands