Evidence map›Paper›PMID 35643978›Full record

ArticleThe Journal of animal ecology2022

The predicted impact of resource provisioning on the epidemiological responses of different parasites.

Diana Erazo, Amy B Pedersen, Andy Fenton

Open access · hybridAbstract read
In one paragraph

Article in The Journal of animal ecology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

Diana ErazoSpatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium.ORCID 0000-0002-9726-9502
Amy B PedersenInstitute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-1385-1360
Andy FentonInstitute of Infection, Veterinary & Ecological Sciences, University of Liverpool, Liverpool, UK.ORCID 0000-0002-7676-917X
Université Libre de Bruxelles · BEUniversity of Edinburgh · GBUniversity of Liverpool · GB

Funding

H2020 Marie Skłodowska-Curie Actions 801505Natural Environment Research Council NE/G006830/1Natural Environment Research Council NE/G007349/1Natural Environment Research Council NE/I024038/1Natural Environment Research Council NE/I026367/1Natural Environment Research Council NE/R011397/1University Of EdinburghWellcome TrustWellcome Trust 095831
6 · The paper itself

Abstract

Anthropogenic activities and natural events such as periodic tree masting can alter resource provisioning in the environment, directly affecting animals, and potentially impacting the spread of infectious diseases in wildlife. The impact of these additional resources on infectious diseases can manifest through different pathways, affecting host susceptibility, contact rate and host demography. To date however, empirical research has tended to examine these different pathways in isolation, for example by quantifying the effects of provisioning on host behaviour in the wild or changes in immune responses in controlled laboratory studies. Furthermore, while theory has investigated the interactions between these pathways, this work has focussed on a narrow subset of pathogen types, typically directly transmitted microparasites. Given the diverse ways that provisioning can affect host susceptibility, contact patterns or host demography, we may expect the epidemiological consequences of provisioning to vary among different parasite types, dependent on key aspects of parasite life history, such as the duration of infection and transmission mode. Focusing on an exemplar empirical system, the wood mouse Apodemus sylvaticus, and its diverse parasite community, we developed a suite of epidemiological models to compare how resource provisioning alters responses for a range of these parasites that vary in their biology (microparasite and macroparasite), transmission mode (direct, environmental and vector transmitted) and duration of infection (acute, latent and chronic) within the same host population. We show there are common epidemiological responses to host resource provisioning across all parasite types examined. In particular, the epidemiological impact of provisioning could be driven in opposite directions, depending on which host pathways (contact rate, susceptibility or host demography) are most altered by the addition of resources to the environment. Broadly, these responses were qualitatively consistent across all parasite types, emphasising the importance of identifying general trade-offs between provisioning-altered parameters. Despite the qualitative consistency in responses to provisioning across parasite types, we predicted notable quantitative differences between parasites, with directly transmitted parasites (those conforming to SIR and SIS frameworks) predicted to show the strongest responses to provisioning among those examined, whereas the vector-borne parasites showed negligible responses to provisioning. As such, these analyses suggest that different parasites may show different scales of response to the same provisioning scenario, even within the same host population. This highlights the importance of knowing key aspects of host-parasite biology, to understand and predict epidemiological responses to provisioning for any specific host-parasite system.

Indexed as

Communicable DiseasesParasitesAnimalsAnimals, WildHost-Parasite InteractionsMiceMurinaeApodemus sylvaticuscompartmental modelsdisease ecologyepidemiologyhost-parasite interactionsprovisioningresource levelssupplemental feeding

Identifiers

PMID35643978
PMCPMC9546467
OpenAlexW4281741037

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.