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A predictive model for Dengue Hemorrhagic Fever epidemics

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dc.contributor Australian Institute Of Marine Science
dc.contributor Sch Math & Phys Sci
dc.contributor Hasanuddin Univ
dc.contributor James Cook Univ
dc.contributor James Cook University
dc.contributor Universitas Hasanuddin
dc.contributor Australian Inst Marine Sci
dc.contributor Dept Phys
dc.contributor Australian Institute Of Marine Science (aims) en
dc.contributor.author RIDD, PETER
dc.contributor.author HALIDE, HALMAR
dc.date.accessioned 2017-03-21T01:21:41Z
dc.date.accessioned 2013-02-28T06:50:17Z
dc.date.accessioned 2013-02-28T06:50:17Z
dc.date.accessioned 2018-11-01T03:04:22Z
dc.date.available 2013-02-28T06:50:17Z
dc.date.available 2017-03-21T01:21:41Z
dc.date.available 2013-02-28T06:50:17Z
dc.date.available 2018-11-01T03:04:22Z
dc.date.issued 2008-01-01
dc.identifier 7849 en
dc.identifier.citation Halide H and Ridd PV (2008) A predictive model for Dengue Hemorrhagic Fever epidemics. International Journal of Environmental Health Research . 18: 253-265. en
dc.identifier.issn 0960-3123
dc.identifier.uri http://epubs.aims.gov.au/11068/7849
dc.description Link to abstract/full text - http://dx.doi.org/10.1080/09603120801966043 en
dc.description.abstract A statistical model for predicting monthly Dengue Hemorrhagic Fever (DHF) cases from the city of Makassar is developed and tested. The model uses past and present DHF cases, climate and meteorological observations as inputs. These inputs are selected using a stepwise regression method to predict future DHF cases. The model is tested independently and its skill assessed using two skill measures. Using the selected variables as inputs, the model is capable of predicting a moderately-severe epidemic at lead times of up to six months. The most important input variable in the prediction is the present number of DHF cases followed by the relative humidity three to four months previously. A prediction 1-6 months in advance is sufficient to initiate various activities to combat DHF epidemic. The model is suitable for warning and easily becomes an operational tool due to its simplicity in data requirement and computational effort.
dc.description.uri http://dx.doi.org/10.1080/09603120801966043 en
dc.language en en
dc.language English
dc.relation.ispartof International Journal of Environmental Health Research - pages: 18: 253-265 en
dc.relation.ispartof Null
dc.subject Environmental Sciences
dc.subject El-nino
dc.subject Aedes-aegypti Diptera
dc.subject Life Table Model
dc.subject Dhf Epidemics
dc.subject Vector Control
dc.subject Borne Diseases
dc.subject Culicidae
dc.subject Climate Variability
dc.subject Temperature
dc.subject Rainfall Anomalies
dc.subject Yes-no Forecasts
dc.subject Public, Environmental & Occupational Health, Sci
dc.subject Public, Environmental & Occupational Health
dc.subject Prediction Skill
dc.subject Statistical Model
dc.subject Environmental Sciences & Ecology
dc.title A predictive model for Dengue Hemorrhagic Fever epidemics
dc.type journal article en
dc.identifier.doi 10.1080/09603120801966043
dc.identifier.wos WOS:000258081400002


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