Regional Warming and Emerging Vector-Borne Zoonotic Dirofilariosis in the Russian Federation, Ukraine, and Other Post-Soviet States from 1981 to 2011 and Projection by 2030

V. Kartashev, A. Afonin, J. González-Miguel, R. Sep lveda, L. Simón, R. Morchón, F. Simón

Research outputpeer-review

16 Citations (Scopus)

Abstract

We analyze through a climatic model the influence of regional warming on the geographical spreading and potential risk of infection of human dirofilariosis in Russia, Ukraine, and other post-Soviet states from 1981 to 2011 and estimate the situation by 2030. The model correctly predicts the spatiotemporal location of 97.10% of 2154 clinical cases reported in the area during the studied period, identified by a retrospective review of the literature. There exists also a significant correlation between annual predicted Dirofilaria generations and calculated morbidity. The model states the progressive increase of 14.8% in the potential transmission area, up to latitude 64°N, and 14.7% in population exposure. By 2030 an increase of 18.5% in transmission area and 10.8% in population exposure is expected. These findings strongly suggest the influence of global warming in both geographical spreading and increase in the number of Dirofilaria generations. The results should alert about the epidemiological behavior of d
Original languageEnglish
Pages (from-to)1-11
JournalBioMed Research International
Volume2014
DOIs
Publication statusPublished - 2014

Cite this

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title = "Regional Warming and Emerging Vector-Borne Zoonotic Dirofilariosis in the Russian Federation, Ukraine, and Other Post-Soviet States from 1981 to 2011 and Projection by 2030",
abstract = "We analyze through a climatic model the influence of regional warming on the geographical spreading and potential risk of infection of human dirofilariosis in Russia, Ukraine, and other post-Soviet states from 1981 to 2011 and estimate the situation by 2030. The model correctly predicts the spatiotemporal location of 97.10{\%} of 2154 clinical cases reported in the area during the studied period, identified by a retrospective review of the literature. There exists also a significant correlation between annual predicted Dirofilaria generations and calculated morbidity. The model states the progressive increase of 14.8{\%} in the potential transmission area, up to latitude 64°N, and 14.7{\%} in population exposure. By 2030 an increase of 18.5{\%} in transmission area and 10.8{\%} in population exposure is expected. These findings strongly suggest the influence of global warming in both geographical spreading and increase in the number of Dirofilaria generations. The results should alert about the epidemiological behavior of d",
keywords = "дирофиляриоз, климат, геоанализ, геомоделирование",
author = "V. Kartashev and A. Afonin and J. Gonz{\'a}lez-Miguel and {Sep lveda}, R. and L. Sim{\'o}n and R. Morch{\'o}n and F. Sim{\'o}n",
year = "2014",
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language = "English",
volume = "2014",
pages = "1--11",
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Regional Warming and Emerging Vector-Borne Zoonotic Dirofilariosis in the Russian Federation, Ukraine, and Other Post-Soviet States from 1981 to 2011 and Projection by 2030. / Kartashev, V.; Afonin, A.; González-Miguel, J.; Sep lveda, R.; Simón, L.; Morchón, R.; Simón, F.

In: BioMed Research International, Vol. 2014, 2014, p. 1-11.

Research outputpeer-review

TY - JOUR

T1 - Regional Warming and Emerging Vector-Borne Zoonotic Dirofilariosis in the Russian Federation, Ukraine, and Other Post-Soviet States from 1981 to 2011 and Projection by 2030

AU - Kartashev, V.

AU - Afonin, A.

AU - González-Miguel, J.

AU - Sep lveda, R.

AU - Simón, L.

AU - Morchón, R.

AU - Simón, F.

PY - 2014

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N2 - We analyze through a climatic model the influence of regional warming on the geographical spreading and potential risk of infection of human dirofilariosis in Russia, Ukraine, and other post-Soviet states from 1981 to 2011 and estimate the situation by 2030. The model correctly predicts the spatiotemporal location of 97.10% of 2154 clinical cases reported in the area during the studied period, identified by a retrospective review of the literature. There exists also a significant correlation between annual predicted Dirofilaria generations and calculated morbidity. The model states the progressive increase of 14.8% in the potential transmission area, up to latitude 64°N, and 14.7% in population exposure. By 2030 an increase of 18.5% in transmission area and 10.8% in population exposure is expected. These findings strongly suggest the influence of global warming in both geographical spreading and increase in the number of Dirofilaria generations. The results should alert about the epidemiological behavior of d

AB - We analyze through a climatic model the influence of regional warming on the geographical spreading and potential risk of infection of human dirofilariosis in Russia, Ukraine, and other post-Soviet states from 1981 to 2011 and estimate the situation by 2030. The model correctly predicts the spatiotemporal location of 97.10% of 2154 clinical cases reported in the area during the studied period, identified by a retrospective review of the literature. There exists also a significant correlation between annual predicted Dirofilaria generations and calculated morbidity. The model states the progressive increase of 14.8% in the potential transmission area, up to latitude 64°N, and 14.7% in population exposure. By 2030 an increase of 18.5% in transmission area and 10.8% in population exposure is expected. These findings strongly suggest the influence of global warming in both geographical spreading and increase in the number of Dirofilaria generations. The results should alert about the epidemiological behavior of d

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KW - геомоделирование

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DO - 10.1155/2014/858936

M3 - Literature review

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SN - 2314-6133

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