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Effects of the Developing and Using a Model to Predict Dengue Risk Villages Based on Subdistrict Administrative Organization in Southern Thailand

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Listed:
  • Orratai Nontapet

    (Excellent Center for Dengue and Community Public Health (EC for DACH), School of Nursing, Walailak University, Thasala District, Nakhon Si Thammarat 80160, Thailand)

  • Jiraporn Jaroenpool

    (Excellent Center for Dengue and Community Public Health (EC for DACH), School of Allied Health Sciences, Walailak University, Thasala District, Nakhon Si Thammarat 80160, Thailand)

  • Sarunya Maneerattanasa

    (School of Public Health, Walailak University, Thasala District, Nakhon Si Thammarat 80160, Thailand)

  • Supaporn Thongchan

    (Excellent Center for Dengue and Community Public Health (EC for DACH), The Center for Digital Technology, Walailak University, Thasala District, Nakhon Si Thammarat 80160, Thailand)

  • Chumpron Ponprasert

    (Public Health Official of Lansaka District, Nakhon Si Thammarat 80160, Thailand)

  • Patthanasak Khammaneechan

    (Excellent Center for Dengue and Community Public Health (EC for DACH), School of Public Health, Walailak University, Thasala District, Nakhon Si Thammarat 80160, Thailand)

  • Cua Ngoc Le

    (Excellent Center for Dengue and Community Public Health (EC for DACH), School of Public Health, Walailak University, Thasala District, Nakhon Si Thammarat 80160, Thailand)

  • Nirachon Chutipattana

    (Excellent Center for Dengue and Community Public Health (EC for DACH), School of Public Health, Walailak University, Thasala District, Nakhon Si Thammarat 80160, Thailand)

  • Charuai Suwanbamrung

    (Excellent Center for Dengue and Community Public Health (EC for DACH), School of Public Health, Walailak University, Thasala District, Nakhon Si Thammarat 80160, Thailand)

Abstract

The purpose of this study was to evaluate the effects of developing and using a model to predict dengue risk in villages and of a larval indices surveillance system for 2372 households in 10 Thai villages. A community participatory action research method was used in five steps: (1) community preparation covering all stakeholders, (2) assessment of the understanding of a dengue solution and a larval indices surveillance system, (3) development of a prediction and intervention model for dengue risk villages, (4) implementation of the model that responds to all stakeholders, and (5) evaluation of the effects of using the model. The questionnaires to assess and evaluate were validated and reliability tested. The chi-square test and Fisher’s exact test were used to analyze the quantitative data collected by means of questionnaires. Thematic analysis was applied to the qualitative data collected through interviews. The results found that the model consisted of six main activities, including (1) setting team leader responsibility, (2) situation assessment, (3) prediction of the dengue risk in villages, (4) the six steps of the larval indices surveillance system, (5) the understanding of the dengue solution and the understanding of the larval indices surveillance system training program, and (6) local wisdom innovation. The effects of using the model showed a statistically significant increase in correct understanding among 932 family leaders, 109 village health volunteers, and 59 student leaders regarding dengue prevention and control ( p < 0.05). The larval indices and dengue morbidity were diminished and related to the nine themes present in the community leaders’ reflections and to the satisfaction of the community members. Hence, local administrative organizations should use community-based approaches as the subdistrict dengue solution innovation to reduce the dengue problem.

Suggested Citation

  • Orratai Nontapet & Jiraporn Jaroenpool & Sarunya Maneerattanasa & Supaporn Thongchan & Chumpron Ponprasert & Patthanasak Khammaneechan & Cua Ngoc Le & Nirachon Chutipattana & Charuai Suwanbamrung, 2022. "Effects of the Developing and Using a Model to Predict Dengue Risk Villages Based on Subdistrict Administrative Organization in Southern Thailand," IJERPH, MDPI, vol. 19(19), pages 1-23, September.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:11989-:d:921992
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    References listed on IDEAS

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    1. Mojtaba Vaismoradi & Hannele Turunen & Terese Bondas, 2013. "Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study," Nursing & Health Sciences, John Wiley & Sons, vol. 15(3), pages 398-405, September.
    2. PDNN Sirisena & Faseeha Noordeen & Harithra Kurukulasuriya & Thanuja ALAR Romesh & LakKumar Fernando, 2017. "Effect of Climatic Factors and Population Density on the Distribution of Dengue in Sri Lanka: A GIS Based Evaluation for Prediction of Outbreaks," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-14, January.
    3. Xue, Qi & Xie, Xinyan & Liu, Qi & Zhou, Yu & Zhu, Kaiheng & Wu, Hao & Wan, Zihao & Feng, Yanan & Meng, Heng & Zhang, Jiajia & Zuo, Pengxiang & Song, Ranran, 2021. "Knowledge, attitudes, and practices towards COVID-19 among primary school students in Hubei Province, China," Children and Youth Services Review, Elsevier, vol. 120(C).
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