Context-dependent host dispersal and habitat fragmentation determine heterogeneity in infected tick burdens: an agent-based modelling study.

Borrelia burgdorferi Ixodes scapularis agent-based model host dispersal tick burden tick-borne disease

Journal

Royal Society open science
ISSN: 2054-5703
Titre abrégé: R Soc Open Sci
Pays: England
ID NLM: 101647528

Informations de publication

Date de publication:
Mar 2022
Historique:
received: 26 02 2022
accepted: 28 02 2022
entrez: 1 4 2022
pubmed: 2 4 2022
medline: 2 4 2022
Statut: epublish

Résumé

As the incidence of tick-borne diseases has sharply increased over the past decade, with serious consequences for human and animal health, there is a need to identify ecological drivers contributing to heterogeneity in tick-borne disease risk. In particular, the relative importance of animal host dispersal behaviour in its three context-dependent phases of emigration, transfer and settlement is relatively unexplored. We built a spatially explicit agent-based model to investigate how the host dispersal process, in concert with the tick and host demographic processes, habitat fragmentation and the pathogen transmission process, affects infected tick distributions among hosts. A sensitivity analysis explored the impacts of different input parameters on infected tick burdens on hosts and infected tick distributions among hosts. Our simulations indicate that ecological predictors of infected tick burdens differed among the post-egg life stages of ticks, with tick attachment and detachment, tick questing activity and pathogen transmission dynamics identified as key processes, in a coherent way. We also found that the type of host settlement strategy and the proportion of habitat suitable for hosts determined super-spreading of infected ticks. We developed a theoretical mechanistic framework that can serve as a first step towards applied studies of on-the-ground public health intervention strategies.

Identifiants

pubmed: 35360357
doi: 10.1098/rsos.220245
pii: rsos220245
pmc: PMC8965412
doi:

Banques de données

figshare
['10.6084/m9.figshare.c.5899186']
Dryad
['10.5061/dryad.nzs7h44rx']

Types de publication

Journal Article

Langues

eng

Pagination

220245

Informations de copyright

© 2022 The Authors.

Déclaration de conflit d'intérêts

We declare we have no competing interests.

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Auteurs

Olivia Tardy (O)

Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2.

Christian E Vincenot (CE)

Department of Social Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501, Japan.

Catherine Bouchard (C)

Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2.
Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2.

Nicholas H Ogden (NH)

Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2.
Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2.

Patrick A Leighton (PA)

Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2.

Classifications MeSH