Early detection of malaria in an endemic area : Model development

A malaria epidemic warning system was established in Thailand in 1984 using graphs displaying the median or mean incidence of malaria over the previous five years compiled from malaria surveillance data throughout the country. This reporting mechanism is not timely enough to detect the occurrence of...

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Veröffentlicht in:Southeast Asian journal of tropical medicine and public health 2006-11, Vol.37 (6), p.1067-1071
Hauptverfasser: KONCHOM, Supawadee, SINGHASIVANON, Pratap, KAEWKUNGWAL, Jaranit, CHUPRAPAWAN, Sirichai, THIMASARN, Krongthong, KIDSON, Chev, YIMSAMRAN, Surapon, ROJANAWATSIRIVET, Chaiporn
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container_issue 6
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container_title Southeast Asian journal of tropical medicine and public health
container_volume 37
creator KONCHOM, Supawadee
SINGHASIVANON, Pratap
KAEWKUNGWAL, Jaranit
CHUPRAPAWAN, Sirichai
THIMASARN, Krongthong
KIDSON, Chev
YIMSAMRAN, Surapon
ROJANAWATSIRIVET, Chaiporn
description A malaria epidemic warning system was established in Thailand in 1984 using graphs displaying the median or mean incidence of malaria over the previous five years compiled from malaria surveillance data throughout the country. This reporting mechanism is not timely enough to detect the occurrence of a malaria epidemic which usually occurs at the district level over a short period of time. An alternative method for early detection of a malaria epidemic employing the Poisson model has been proposed. The development of this early malaria epidemic detection model involved 3 steps: model specification, model validation and model testing. The model was based on data collected at the Vector Borne Disease Control Unit (VBDU) Level. The results of model testing reveal the model can detect increasing numbers of cases earlier, one to two weeks prior to reaching their highest peak of transmission. The system was tested using data from Kanchanaburi Province during 2000 to 2001. Results from model testing show the model may be used for monitoring the weekly malaria situation at the district level. The Poisson model was able to detect malaria early in a highly endemic province with a satisfactory level of prediction. As the application is essential for the malaria officers in monitoring of malaria epidemics, this early detection system was introduced into malaria epidemiological work. The model may be helpful in the decision making process, planning and budget allocation for the Malaria Control Program. The software for early malaria detection is currently implemented in several endemic areas throughout Thailand.
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This reporting mechanism is not timely enough to detect the occurrence of a malaria epidemic which usually occurs at the district level over a short period of time. An alternative method for early detection of a malaria epidemic employing the Poisson model has been proposed. The development of this early malaria epidemic detection model involved 3 steps: model specification, model validation and model testing. The model was based on data collected at the Vector Borne Disease Control Unit (VBDU) Level. The results of model testing reveal the model can detect increasing numbers of cases earlier, one to two weeks prior to reaching their highest peak of transmission. The system was tested using data from Kanchanaburi Province during 2000 to 2001. Results from model testing show the model may be used for monitoring the weekly malaria situation at the district level. The Poisson model was able to detect malaria early in a highly endemic province with a satisfactory level of prediction. 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This reporting mechanism is not timely enough to detect the occurrence of a malaria epidemic which usually occurs at the district level over a short period of time. An alternative method for early detection of a malaria epidemic employing the Poisson model has been proposed. The development of this early malaria epidemic detection model involved 3 steps: model specification, model validation and model testing. The model was based on data collected at the Vector Borne Disease Control Unit (VBDU) Level. The results of model testing reveal the model can detect increasing numbers of cases earlier, one to two weeks prior to reaching their highest peak of transmission. The system was tested using data from Kanchanaburi Province during 2000 to 2001. Results from model testing show the model may be used for monitoring the weekly malaria situation at the district level. The Poisson model was able to detect malaria early in a highly endemic province with a satisfactory level of prediction. 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source MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Animals
Biological and medical sciences
Disease Vectors
Endemic Diseases
General aspects
Human protozoal diseases
Humans
Infectious diseases
Malaria
Malaria - epidemiology
Medical sciences
Models, Statistical
Parasitic diseases
Poisson Distribution
Population Surveillance - methods
Protozoal diseases
Seasons
Software
Thailand - epidemiology
title Early detection of malaria in an endemic area : Model development
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