Cited by 102Vector-borne infectious diseasesClimate Change and Health ImpactsVector-Borne Animal Diseases

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index; none of the 29 sources its claims cite is checked for support yet.

Impact of climate change in the epidemiology of vector-borne diseases in domestic carnivores

Open access
Beugnet, F., Chalvet-Monfray, K.·2013·Comparative Immunology, Microbiology and Infectious Diseases

Abstract

Vector-borne diseases are medically important in humans and animals but were long considered tropical and known to first affect production animals. This is no longer true and we can see today that they are common in domestic animals and that they are also present in temperate countries, especially in Europe. In recent years, an increase in the diagnosis of vector borne diseases among humans and animals has been observed, which may partly due to the development of diagnostic tools. Their study requires exchanges and collaborations between the many actors involved, especially since the epidemiology seems to be constantly evolving. The veterinary practitioner is the first one to notice the emergence of cases and to implement prevention measures. He also acts as a sentinel to alert epidemiologists. Many factors can explain the epidemiological changes, i.e. all human factors, such as the increase in commercial transportation, but also owners traveling with their pet during the holidays, the development of "outdoor" activities, the increase of individual housings with gardens; to these human factors must be added the ignorance of the risks, linked to animals in general and to wildlife in particular; then the environmental changes: forest fragmentation, establishment of parks; the increase of wild mammal populations (deer, carnivores, rodents, etc.); finally, climate changes. Climate change is a reality which may explain the increase of density of arthropod vectors, but also of their hosts, changes in periods of activity and variations in geographical distribution. The authors show the proof of the climate modifications and then explain how it has an impact in Europe on ticks, mosquitoes, sandflies and even fleas. They conclude on the practical consequences for veterinary practitioners, especially with the diagnosis of parasitic diseases or diseases in areas where they usually do not occur. However, not any epidemiological modification should be linked to climate change, since many other factors are involved and often even overriding.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This review argues that climate change is a real driver of changing vector-borne disease epidemiology in Europe, affecting ticks, mosquitoes, sandflies, and fleas of domestic carnivores. It concludes that climate change should not be invoked for every epidemiological change because other human and environmental factors are often overriding.

Key findings

  • Global warming accelerated over the last hundred years, with an average gain of 0.74°C in 100 years; effects are not uniform and include shorter, less severe winters in Western and Northern Europe.
  • For ticks, the climatic zone favorable for *Rhipicephalus sanguineus* reproduction expanded by 669% since the 1960s in Europe, and the species can now survive/develop in Southwest France up to Nantes and Southeast France up to Lyon; *Dermacentor reticulatus* is present in 2/3 of French territory and in Slovakia gained 200 km north since the 1970s and 300 m in altitude.
  • For *Ixodes ricinus*, Swiss studies showed altitudinal limits increasing from 620 to 1070 m in some mountain ranges, and Lindgren found in Sweden some areas had 40 fewer days below −12°C and 20 more days above −7°C in winter.
  • For mosquitoes and sandflies, *Dirofilaria immitis* development requires temperatures above 14°C and 130 heartworm development units; using 5475 weather stations and 19 million temperature values over 15 years, heartworm disease can now be maintained beyond the Mediterranean, while *Aedes albopictus* is present in about 1/3 of southern French territory up to Lyon. Flea impacts are difficult to assess, though year-round conditions of >25°C and >85% RH in Florida and Queensland may explain continued heavy cat flea infestations.

Methods

  • Review/synthesis of published literature, meteorological models, field studies, and ECDC distribution maps; no primary sample or new data collection is described.
  • Main analysis is a qualitative synthesis of climate-change impacts on ticks, mosquitoes, sandflies, and fleas, with cited quantitative examples from models and field studies.
  • The paper draws on studies including a meteorological model applied to Europe since 1960, field studies on tick activity and distribution, and a heartworm transmission analysis using 5475 weather stations and 19 million temperature values.

Limitations

  • Stated: the authors caution that not every epidemiological modification should be linked to climate change, since many other factors are involved and often overriding, and climate changes are currently still limited with co-existing human-induced factors.
  • Stated: for sandflies, it is difficult to distinguish an effect of climate over human actions; for fleas, the impact of climate change is very difficult to assess because the life cycle can occur throughout the year, including indoors.
  • Evident: as a review, no systematic search strategy, inclusion criteria, or quantitative meta-analysis is reported; conclusions rely on cited models and field studies.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.cimid.2013.07.003

Cites

28 of 28 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

23 Not checked yet · 9 Own interpretation · 2 No basis given

Verify all 29 references — free account

Show all 14 claims

  • It may state two separate claims as one. 16
  • Probably not a substantial claim. 8
20 of 20
  • The authors state this as an assumption.

    The heartworm transmission model assumes a requirement of 130 heartworm development units (HDUs) for larvae to reach infectivity and a maximum life expectancy of 30 days for a vector mosquito.

    “The seasonal HW transmission model originally formulated by Slocombe et al. (1989) in Canada and reevaluated by Lok and Knight (1998) in the United States assumes a requirement of 130 HDUs for larvae to reach infectivity and a maximum life expectancy of 30 days for a vector mosquito (in [24]).”
  • The paper relies on this without support.

    The risk of transmission of pathogenic agents by mosquitoes is linked to vector competence, meteorological conditions enabling the pathogen's extrinsic cycle during vector activity and vectors being active and abundant, and the presence of the pathogen and at least one reservoir.

    “The risk of transmission of pathogenic agents by mosquitoes is not linked to their mere presence but to: 1. Vector competence (ability to complete the cycle of the pathogenic agent within the vector, followed by transmission); 2. Meteorological conditions enabling: a.The pathogen to complete its extrinsic cycle during the vector's period of activity; b.The vectors to be active and abundant enough”
2 of 2

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

3 of 3

Citations

Cites

Show all 28 references

Research works printed but not linked: 1

  1. Greer, 2008, Climate change and infectious diseases in North America: the road ahead, Canadian Medical Association Journal, 178, 715

Cited by

Sorted by citations

Items 101–102 of 102

Metadata

Authors
Beugnet, F., & Chalvet-Monfray, K.
Corresponding author
Beugnet, F.
Venue
Comparative Immunology, Microbiology and Infectious Diseases
Publisher
Elsevier BV
Published
2013-12
Volume
36
Issue
6
Pages
559-566
ISSN
0147-9571 (ISSN-L)
OpenAlex
W2038395162
Cited by
102
References
28
Citations by year
2026: 6 · 2025: 8 · 2024: 4 · 2023: 5 · 2022: 3 · 2021: 13 · 2020: 19 · 2019: 6 · 2018: 8 · 2017: 7 · 2016: 5 · 2015: 12 · 2014: 5
FWCI
0.91
Type
journal article
Language
en
Open access
Locations
  • Comparative Immunology Microbiology and Infectious Diseases (publishedVersion, cc-by-nc-sa)
  • PubMed (publishedVersion)
  • HAL (submittedVersion)
Topics
  • Life Sciences › Immunology and Microbiology › Parasitology › Vector-borne infectious diseases
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Climate Change and Health Impacts
  • Life Sciences › Immunology and Microbiology › Virology › Vector-Borne Animal Diseases
Keywords
climate change, vector-borne diseases, domestic carnivores, ticks, mosquitoes, sand flies, fleas, arthropod vectors, wildlife reservoirs, domestic animals, veterinary practice, disease surveillance, environmental change, Europe
MeSH terms
Animals, Animal Diseases, Animals, Domestic, Carnivora, Communicable Diseases, Disease Vectors, Europe, Siphonaptera, Humans, Culicidae, Psychodidae, Ticks, Climate Change

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-10-10, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-10-10 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review