Toward an early warning system for dengue prevention: modeling climate impact on dengue transmission
Dengue fever is the most prevalent mosquito-borne viral disease of humans in tropical lands. As an efficient vaccine is not yet available, the only means to prevent epidemics is to control mosquito populations. These are influenced by human behavior and climatic conditions and thus, need constant ef...
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description | Dengue fever is the most prevalent mosquito-borne viral disease of humans in tropical lands. As an efficient vaccine is not yet available, the only means to prevent epidemics is to control mosquito populations. These are influenced by human behavior and climatic conditions and thus, need constant effort and are very expansive. Examples of succeeded prevention are rare because of the continuous reintroduction of virus or vector from outside, or growing resistance of mosquito populations to insecticides. Climate variability and global warming are other factors which may favour epidemics of dengue. During a pilot study in Claris EC project, a model for the transmission of dengue was built, to serve as a tool for estimating the risk of epidemic transmission and eventually forecasting the risk under climatic change scenarios. An ultimate objective would be to use the model as an early warning system with meteorological forecasts as input, thus allowing better decision making and prevention. |
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As an efficient vaccine is not yet available, the only means to prevent epidemics is to control mosquito populations. These are influenced by human behavior and climatic conditions and thus, need constant effort and are very expansive. Examples of succeeded prevention are rare because of the continuous reintroduction of virus or vector from outside, or growing resistance of mosquito populations to insecticides. Climate variability and global warming are other factors which may favour epidemics of dengue. During a pilot study in Claris EC project, a model for the transmission of dengue was built, to serve as a tool for estimating the risk of epidemic transmission and eventually forecasting the risk under climatic change scenarios. An ultimate objective would be to use the model as an early warning system with meteorological forecasts as input, thus allowing better decision making and prevention.</description><identifier>ISSN: 0165-0009</identifier><identifier>EISSN: 1573-1480</identifier><identifier>DOI: 10.1007/s10584-009-9747-3</identifier><identifier>CODEN: CLCHDX</identifier><language>eng</language><publisher>Dordrecht: Dordrecht : Springer Netherlands</publisher><subject>Aquatic insects ; Atmospheric Sciences ; Climate ; Climate change ; Climate Change/Climate Change Impacts ; Climate variability ; Climatic conditions ; Climatology ; Dengue fever ; Disease prevention ; Disease transmission ; Early warning systems ; Earth and Environmental Science ; Earth Sciences ; Epidemics ; Estimating ; Freshwater ; Global warming ; Humidity ; Insecticides ; Malaria ; Mathematical models ; Mosquitoes ; Ocean, Atmosphere ; Oceanography ; Pest control ; Populations ; Prevention ; Reintroduction ; Risk ; Sciences of the Universe ; Tropical diseases ; Vector-borne diseases ; Viral diseases</subject><ispartof>Climatic change, 2010-02, Vol.98 (3-4), p.581-592</ispartof><rights>Springer Science+Business Media B.V. 2009</rights><rights>Springer Science+Business Media B.V. 2010</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c470t-9a74a023fe9b0612b1163de8bd3f96a552b5ff7a3812b56994159bcdd014c7173</citedby><cites>FETCH-LOGICAL-c470t-9a74a023fe9b0612b1163de8bd3f96a552b5ff7a3812b56994159bcdd014c7173</cites><orcidid>0000-0002-0044-036X ; 0000-0002-1126-6950 ; 0000-0002-1457-9696</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10584-009-9747-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10584-009-9747-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://hal.science/hal-02433364$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Degallier, Nicolas</creatorcontrib><creatorcontrib>Favier, Charly</creatorcontrib><creatorcontrib>Menkes, Christophe</creatorcontrib><creatorcontrib>Lengaigne, Matthieu</creatorcontrib><creatorcontrib>Ramalho, Walter M</creatorcontrib><creatorcontrib>Souza, Régilo</creatorcontrib><creatorcontrib>Servain, Jacques</creatorcontrib><creatorcontrib>Boulanger, Jean-Philippe</creatorcontrib><title>Toward an early warning system for dengue prevention: modeling climate impact on dengue transmission</title><title>Climatic change</title><addtitle>Climatic Change</addtitle><description>Dengue fever is the most prevalent mosquito-borne viral disease of humans in tropical lands. As an efficient vaccine is not yet available, the only means to prevent epidemics is to control mosquito populations. These are influenced by human behavior and climatic conditions and thus, need constant effort and are very expansive. Examples of succeeded prevention are rare because of the continuous reintroduction of virus or vector from outside, or growing resistance of mosquito populations to insecticides. Climate variability and global warming are other factors which may favour epidemics of dengue. During a pilot study in Claris EC project, a model for the transmission of dengue was built, to serve as a tool for estimating the risk of epidemic transmission and eventually forecasting the risk under climatic change scenarios. An ultimate objective would be to use the model as an early warning system with meteorological forecasts as input, thus allowing better decision making and prevention.</description><subject>Aquatic insects</subject><subject>Atmospheric Sciences</subject><subject>Climate</subject><subject>Climate change</subject><subject>Climate Change/Climate Change Impacts</subject><subject>Climate variability</subject><subject>Climatic conditions</subject><subject>Climatology</subject><subject>Dengue fever</subject><subject>Disease prevention</subject><subject>Disease transmission</subject><subject>Early warning systems</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Epidemics</subject><subject>Estimating</subject><subject>Freshwater</subject><subject>Global warming</subject><subject>Humidity</subject><subject>Insecticides</subject><subject>Malaria</subject><subject>Mathematical models</subject><subject>Mosquitoes</subject><subject>Ocean, Atmosphere</subject><subject>Oceanography</subject><subject>Pest control</subject><subject>Populations</subject><subject>Prevention</subject><subject>Reintroduction</subject><subject>Risk</subject><subject>Sciences of the Universe</subject><subject>Tropical diseases</subject><subject>Vector-borne diseases</subject><subject>Viral 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subjects | Aquatic insects Atmospheric Sciences Climate Climate change Climate Change/Climate Change Impacts Climate variability Climatic conditions Climatology Dengue fever Disease prevention Disease transmission Early warning systems Earth and Environmental Science Earth Sciences Epidemics Estimating Freshwater Global warming Humidity Insecticides Malaria Mathematical models Mosquitoes Ocean, Atmosphere Oceanography Pest control Populations Prevention Reintroduction Risk Sciences of the Universe Tropical diseases Vector-borne diseases Viral diseases |
title | Toward an early warning system for dengue prevention: modeling climate impact on dengue transmission |
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