Significant factors associated with malaria spread in Thailand: a cross-sectional study

PurposeThis paper aims to uncover new factors that influence the spread of malaria.Design/methodology/approachThe historical data related to malaria were collected from government agencies. Later, the data were cleaned and standardized before passing through the analysis process. To obtain the simpl...

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Bibliographic Details
Published in:Journal of Health Research 2022-04, Vol.36 (3), p.515-523
Main Authors: Krainara, Patcharaporn, Dumrongrojwatthana, Pongchai, Bhattarakosol, Pattarasinee
Format: Article
Language:English
Subjects:
Classification
Cross-sectional studies
Decision trees
Drug resistance
Epidemiology
logistic model tree
Malaria
malaria control
malaria distribution
Mosquitoes
Population
Provinces
Public health
risk factors
risk model
thailand
Variables
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Summary:PurposeThis paper aims to uncover new factors that influence the spread of malaria.Design/methodology/approachThe historical data related to malaria were collected from government agencies. Later, the data were cleaned and standardized before passing through the analysis process. To obtain the simplicity of these numerous factors, the first procedure involved in executing the factor analysis where factors' groups related to malaria distribution were determined. Therefore, machine learning was deployed, and the confusion matrices are computed. The results from machine learning techniques were further analyzed with logistic regression to study the relationship of variables affecting malaria distribution.FindingsThis research can detect 28 new noteworthy factors. With all the defined factors, the logistics model tree was constructed. The precision and recall of this tree are 78% and 82.1%, respectively. However, when considering the significance of all 28 factors under the logistic regression technique using forward stepwise, the indispensable factors have been found as the number of houses without electricity (houses), number of irrigation canals (canals), number of shallow wells (places) and number of migrated persons (persons). However, all 28 factors must be included to obtain high accuracy in the logistics model tree.Originality/valueThis paper may lead to highly-efficient government development plans, including proper financial management for malaria control sections. Consequently, the spread of malaria can be reduced naturally.
ISSN:0857-4421
2586-940X
DOI:10.1108/JHR-11-2020-0575