Dengue hemorrhagic fever prevention and control: DHF-solve model using linebot-application and GIS

Dengue hemorrhagic fever (DHF) poses a significant health challenge in Thailand, highlighting the need for a better understanding of its transmission and characteristics. Innovation and technology are essential for effective prevention and control measures. This research article centres on developin...

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Main Authors: Mala, M., Meenongwar, C., Jundaeng, J., Osman, M., Viegus, Z., Nithikathkul, C.
Format: Article
Language:English
Published: Association for Geoinformation Technology 2024
Online Access:http://psasir.upm.edu.my/id/eprint/114820/
http://psasir.upm.edu.my/id/eprint/114820/1/114820.pdf
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author Mala, M.
Meenongwar, C.
Jundaeng, J.
Osman, M.
Viegus, Z.
Nithikathkul, C.
author_facet Mala, M.
Meenongwar, C.
Jundaeng, J.
Osman, M.
Viegus, Z.
Nithikathkul, C.
author_sort Mala, M.
building UPM Institutional Repository
collection Online Access
description Dengue hemorrhagic fever (DHF) poses a significant health challenge in Thailand, highlighting the need for a better understanding of its transmission and characteristics. Innovation and technology are essential for effective prevention and control measures. This research article centres on developing a model to prevent and control DHF, utilising the DHF-Solve model, a Linebot, and Geographic Information Systems (GIS). The research was conducted in four phases. Phase 1 focused on identifying risk factors and high-risk areas for DHF. Phase 2 examined the factors influencing people's behaviours regarding DHF prevention and control. Phase 3 was dedicated to developing the model, while Phase 4 assessed its effectiveness. The research employed various tools, including GIS, questionnaires, Linebot, assessment forms, and primary and secondary data collection. Risk areas were identified through frequency and weighting techniques as well as descriptive statistical analysis. The factor that most significantly influenced behaviour was people's perception of DHF, which received an average score of 4.19. The findings from the model development indicated that the DHF-Solve Linebot is an effective management and control system for DHF. It features six menus accessible through the Line Official Account (LOA) and can function as a real-time platform. This Linebot incorporates AI chatbot commands and GIS technology, which proved to be the most effective in terms of promptness and responsiveness. It has demonstrated the potential to reduce morbidity rates during two outbreak generations. Therefore, this model effectively addresses the issue of DHF and should be implemented as a response mechanism in emergencies where DHF outbreaks may arise.
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institution Universiti Putra Malaysia
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spelling upm-1148202025-02-03T06:32:22Z http://psasir.upm.edu.my/id/eprint/114820/ Dengue hemorrhagic fever prevention and control: DHF-solve model using linebot-application and GIS Mala, M. Meenongwar, C. Jundaeng, J. Osman, M. Viegus, Z. Nithikathkul, C. Dengue hemorrhagic fever (DHF) poses a significant health challenge in Thailand, highlighting the need for a better understanding of its transmission and characteristics. Innovation and technology are essential for effective prevention and control measures. This research article centres on developing a model to prevent and control DHF, utilising the DHF-Solve model, a Linebot, and Geographic Information Systems (GIS). The research was conducted in four phases. Phase 1 focused on identifying risk factors and high-risk areas for DHF. Phase 2 examined the factors influencing people's behaviours regarding DHF prevention and control. Phase 3 was dedicated to developing the model, while Phase 4 assessed its effectiveness. The research employed various tools, including GIS, questionnaires, Linebot, assessment forms, and primary and secondary data collection. Risk areas were identified through frequency and weighting techniques as well as descriptive statistical analysis. The factor that most significantly influenced behaviour was people's perception of DHF, which received an average score of 4.19. The findings from the model development indicated that the DHF-Solve Linebot is an effective management and control system for DHF. It features six menus accessible through the Line Official Account (LOA) and can function as a real-time platform. This Linebot incorporates AI chatbot commands and GIS technology, which proved to be the most effective in terms of promptness and responsiveness. It has demonstrated the potential to reduce morbidity rates during two outbreak generations. Therefore, this model effectively addresses the issue of DHF and should be implemented as a response mechanism in emergencies where DHF outbreaks may arise. Association for Geoinformation Technology 2024-11-28 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/114820/1/114820.pdf Mala, M. and Meenongwar, C. and Jundaeng, J. and Osman, M. and Viegus, Z. and Nithikathkul, C. (2024) Dengue hemorrhagic fever prevention and control: DHF-solve model using linebot-application and GIS. International Journal of Geoinformatics, 20 (11). pp. 162-176. ISSN 1686-6576; eISSN: 2673-0014 https://journals.sfu.ca/ijg/index.php/journal/article/view/3717 10.52939/ijg.v20i11.3717
spellingShingle Mala, M.
Meenongwar, C.
Jundaeng, J.
Osman, M.
Viegus, Z.
Nithikathkul, C.
Dengue hemorrhagic fever prevention and control: DHF-solve model using linebot-application and GIS
title Dengue hemorrhagic fever prevention and control: DHF-solve model using linebot-application and GIS
title_full Dengue hemorrhagic fever prevention and control: DHF-solve model using linebot-application and GIS
title_fullStr Dengue hemorrhagic fever prevention and control: DHF-solve model using linebot-application and GIS
title_full_unstemmed Dengue hemorrhagic fever prevention and control: DHF-solve model using linebot-application and GIS
title_short Dengue hemorrhagic fever prevention and control: DHF-solve model using linebot-application and GIS
title_sort dengue hemorrhagic fever prevention and control: dhf-solve model using linebot-application and gis
url http://psasir.upm.edu.my/id/eprint/114820/
http://psasir.upm.edu.my/id/eprint/114820/
http://psasir.upm.edu.my/id/eprint/114820/
http://psasir.upm.edu.my/id/eprint/114820/1/114820.pdf