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

Purpose - This paper aims to uncover new factors that influence the spread of malaria. Design/methodology/approach - The 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 th...

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Main Authors: Patcharaporn Krainara (Author), Pongchai Dumrongrojwatthana (Author), Pattarasinee Bhattarakosol (Author)
Format: Book
Published: College of Public Health Sciences, Chulalongkorn University, 2022-04-01T00:00:00Z.
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001 doaj_a438ca0ac4b744c6b1cf6ea7376a21c9
042 |a dc 
100 1 0 |a Patcharaporn Krainara  |e author 
700 1 0 |a Pongchai Dumrongrojwatthana  |e author 
700 1 0 |a Pattarasinee Bhattarakosol  |e author 
245 0 0 |a Significant factors associated with malaria spread in Thailand: a cross-sectional study 
260 |b College of Public Health Sciences, Chulalongkorn University,   |c 2022-04-01T00:00:00Z. 
500 |a 0857-4421 
500 |a 2586-940X 
500 |a 10.1108/JHR-11-2020-0575 
520 |a Purpose - This paper aims to uncover new factors that influence the spread of malaria. Design/methodology/approach - The 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. Findings - This 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/value - This 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. 
546 |a EN 
690 |a malaria distribution 
690 |a malaria control 
690 |a logistic model tree 
690 |a risk factors 
690 |a risk model 
690 |a thailand 
690 |a Other systems of medicine 
690 |a RZ201-999 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n Journal of Health Research, Vol 36, Iss 3, Pp 515-523 (2022) 
787 0 |n https://www.emerald.com/insight/content/doi/10.1108/JHR-11-2020-0575/full/pdf?title=significant-factors-associated-with-malaria-spread-in-thailand-a-cross-sectional-study 
787 0 |n https://doaj.org/toc/0857-4421 
787 0 |n https://doaj.org/toc/2586-940X 
856 4 1 |u https://doaj.org/article/a438ca0ac4b744c6b1cf6ea7376a21c9  |z Connect to this object online.