Seroprevalence and incidence of Puumala orthohantavirus in its bank vole (Myodes glareolus) host population in northeastern France: Between-site and seasonal variability

Given the difficulty of measuring pathogen transmission in wildlife, epidemiological studies frequently rely on cross-sectional seroprevalence. However, seropositivity indicates only exposure to a pathogen at an unknown time. By allowing to obtain repeated test results from individuals sampled multi...

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Main Authors: E. Monchatre-Leroy, F. Sauvage, F. Boué, D. Augot, P. Marianneau, V. Hénaux, L. Crespin
Format: Article
Language:English
Published: Elsevier 2022-09-01
Series:Epidemics
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1755436522000457
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author E. Monchatre-Leroy
F. Sauvage
F. Boué
D. Augot
P. Marianneau
V. Hénaux
L. Crespin
author_facet E. Monchatre-Leroy
F. Sauvage
F. Boué
D. Augot
P. Marianneau
V. Hénaux
L. Crespin
author_sort E. Monchatre-Leroy
collection DOAJ
description Given the difficulty of measuring pathogen transmission in wildlife, epidemiological studies frequently rely on cross-sectional seroprevalence. However, seropositivity indicates only exposure to a pathogen at an unknown time. By allowing to obtain repeated test results from individuals sampled multiple times over an extended period, longitudinal data help reduce this uncertainty. We used capture-mark-recapture data on bank vole (Myodes glareolus) individuals collected at four sites over ten years in northeastern France to investigate the impact of environmental variables on seroprevalence and incidence of Puumala orthohantavirus (PUUV). PUUV causes a chronic infection without apparent symptoms, that may however impair survival of its rodent host in the wild. Viral transmission between rodents may occur through direct contact or via the environment. Principal component analysis was used to deal with multicollinearity among environmental variables. Incidence and seroprevalence were investigated with either generalized estimating equations or Poisson regression models depending on the number of observations for each season. In spring, only the factor site was found to be significant for seroprevalence, while a principal component including meteorological conditions of the previous winter and the normalized difference vegetation index (NDVI) of both the previous winter and spring had a significant effect on incidence. In autumn, only the factor site was significant for incidence, while two principal components, including either the meteorological conditions of the autumn and previous spring or NDVI of the autumn significantly affected seroprevalence. We discuss these results in light of the particular demography of small mammals. We encourage other researchers to investigate the relationships between demographic parameters of wild host populations and the environment, by using both incidence and seroprevalence.
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spelling doaj.art-ce690817ed6548d08c7d6ee90f54178b2022-12-22T01:49:07ZengElsevierEpidemics1755-43652022-09-0140100600Seroprevalence and incidence of Puumala orthohantavirus in its bank vole (Myodes glareolus) host population in northeastern France: Between-site and seasonal variabilityE. Monchatre-Leroy0F. Sauvage1F. Boué2D. Augot3P. Marianneau4V. Hénaux5L. Crespin6Anses, Laboratoire de la rage et de la faune sauvage, Nancy 54220, France; Corresponding author.SEENOVATE, 8 Rue de la Bourse, 69002 Lyon, France; UMR–CNRS 5558 Biométrie et Biologie évolutive, Université C. Bernard Lyon-1, Villeurbanne, FranceAnses, Laboratoire de la rage et de la faune sauvage, Nancy 54220, FranceAnses, Laboratoire de la rage et de la faune sauvage, Nancy 54220, France; Usc VECPAR-ANSES LSA, EA 7510, SFR Cap Santé, Université Champagne-Ardenne, Reims, FranceUniversité de Lyon, Anses, Laboratoire de Lyon, Unité de virologie, Lyon 69364, FranceUniversité de Lyon, Anses, Laboratoire de Lyon, Unité épidémiologie et appui à la surveillance (EAS), Lyon 69364, FranceUMR–CNRS 5558 Biométrie et Biologie évolutive, Université C. Bernard Lyon-1, Villeurbanne, France; Université Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, 63122 Saint-Genès-Champanelle, France; Université Lyon, INRAE, VetAgro Sup, UMR EPIA, 69280 Marcy-L′Etoile, FranceGiven the difficulty of measuring pathogen transmission in wildlife, epidemiological studies frequently rely on cross-sectional seroprevalence. However, seropositivity indicates only exposure to a pathogen at an unknown time. By allowing to obtain repeated test results from individuals sampled multiple times over an extended period, longitudinal data help reduce this uncertainty. We used capture-mark-recapture data on bank vole (Myodes glareolus) individuals collected at four sites over ten years in northeastern France to investigate the impact of environmental variables on seroprevalence and incidence of Puumala orthohantavirus (PUUV). PUUV causes a chronic infection without apparent symptoms, that may however impair survival of its rodent host in the wild. Viral transmission between rodents may occur through direct contact or via the environment. Principal component analysis was used to deal with multicollinearity among environmental variables. Incidence and seroprevalence were investigated with either generalized estimating equations or Poisson regression models depending on the number of observations for each season. In spring, only the factor site was found to be significant for seroprevalence, while a principal component including meteorological conditions of the previous winter and the normalized difference vegetation index (NDVI) of both the previous winter and spring had a significant effect on incidence. In autumn, only the factor site was significant for incidence, while two principal components, including either the meteorological conditions of the autumn and previous spring or NDVI of the autumn significantly affected seroprevalence. We discuss these results in light of the particular demography of small mammals. We encourage other researchers to investigate the relationships between demographic parameters of wild host populations and the environment, by using both incidence and seroprevalence.http://www.sciencedirect.com/science/article/pii/S1755436522000457SeroprevalenceIncidenceBank volesPuumala orthohantavirusSuppress normalized difference vegetation indexGeneralized estimating equations
spellingShingle E. Monchatre-Leroy
F. Sauvage
F. Boué
D. Augot
P. Marianneau
V. Hénaux
L. Crespin
Seroprevalence and incidence of Puumala orthohantavirus in its bank vole (Myodes glareolus) host population in northeastern France: Between-site and seasonal variability
Epidemics
Seroprevalence
Incidence
Bank voles
Puumala orthohantavirus
Suppress normalized difference vegetation index
Generalized estimating equations
title Seroprevalence and incidence of Puumala orthohantavirus in its bank vole (Myodes glareolus) host population in northeastern France: Between-site and seasonal variability
title_full Seroprevalence and incidence of Puumala orthohantavirus in its bank vole (Myodes glareolus) host population in northeastern France: Between-site and seasonal variability
title_fullStr Seroprevalence and incidence of Puumala orthohantavirus in its bank vole (Myodes glareolus) host population in northeastern France: Between-site and seasonal variability
title_full_unstemmed Seroprevalence and incidence of Puumala orthohantavirus in its bank vole (Myodes glareolus) host population in northeastern France: Between-site and seasonal variability
title_short Seroprevalence and incidence of Puumala orthohantavirus in its bank vole (Myodes glareolus) host population in northeastern France: Between-site and seasonal variability
title_sort seroprevalence and incidence of puumala orthohantavirus in its bank vole myodes glareolus host population in northeastern france between site and seasonal variability
topic Seroprevalence
Incidence
Bank voles
Puumala orthohantavirus
Suppress normalized difference vegetation index
Generalized estimating equations
url http://www.sciencedirect.com/science/article/pii/S1755436522000457
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