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Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand
BACKGROUND: Risk assessment criteria for predicting dengue outbreak must be appropriated at village levels. We aimed to develop risk dengue village prediction criteria, predict village dengue risk, and strengthen dengue prevention based on community participation. METHODS: This participatory researc...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114320/ https://www.ncbi.nlm.nih.gov/pubmed/33966515 http://dx.doi.org/10.1177/21501327211013298 |
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author | Suwanbamrung, Charuai Le, Cua Ngoc Kaewsawat, Supreecha Chutipattana, Nirachon Khammaneechan, Patthanasak Thongchan, Supaporn Nontapet, Orratai Thongsuk, Cherd Laopram, Suphap Niyomchit, Chamaiporn Sinthu, Ruchira |
author_facet | Suwanbamrung, Charuai Le, Cua Ngoc Kaewsawat, Supreecha Chutipattana, Nirachon Khammaneechan, Patthanasak Thongchan, Supaporn Nontapet, Orratai Thongsuk, Cherd Laopram, Suphap Niyomchit, Chamaiporn Sinthu, Ruchira |
author_sort | Suwanbamrung, Charuai |
collection | PubMed |
description | BACKGROUND: Risk assessment criteria for predicting dengue outbreak must be appropriated at village levels. We aimed to develop risk dengue village prediction criteria, predict village dengue risk, and strengthen dengue prevention based on community participation. METHODS: This participatory research conducted in Southern Thailand included the following 5 phases: (i) preparing communities in 3 districts; (ii) developing risk dengue village prediction criteria; (iii) applying computer program; (iv) predicting village dengue risk with 75 public health providers in 39 PCUs; and (v) utilizing findings to strengthen dengue prevention activities in 220 villages. Data collecting for prediction used secondary data from primary care units in the past 5 year and current year. Descriptive statistics used calculating criteria and comparing with standard level to adjust score of risk. RESULTS: Risk dengue village assessment criteria had 2 aspects: dengue severity (3 factors) and dengue outbreak opportunity (3 factors). Total scores were 33 points and cut-off of 17 points for high and low dengue risks villages. All criteria were applied using computer program (http://surat.denguelim.com). Risk prediction involved stakeholder participation in 220 villages, and used for strengthening dengue prevention activities. The concept of integrated vector management included larval indices surveillance system, garbage management, larval indices level lower than the standard, community capacity activities for dengue prevention, and school-based dengue prevention. The risk prediction criteria and process mobilized villages for dengue prevention activities to decrease morbidity rate. CONCLUSION: Dengue risk assessment criteria were appropriated within the village, with its smallest unit, the household, included. The data can be utilized at village levels for evaluating dengue outbreak risks. |
format | Online Article Text |
id | pubmed-8114320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-81143202021-05-19 Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand Suwanbamrung, Charuai Le, Cua Ngoc Kaewsawat, Supreecha Chutipattana, Nirachon Khammaneechan, Patthanasak Thongchan, Supaporn Nontapet, Orratai Thongsuk, Cherd Laopram, Suphap Niyomchit, Chamaiporn Sinthu, Ruchira J Prim Care Community Health Original Research BACKGROUND: Risk assessment criteria for predicting dengue outbreak must be appropriated at village levels. We aimed to develop risk dengue village prediction criteria, predict village dengue risk, and strengthen dengue prevention based on community participation. METHODS: This participatory research conducted in Southern Thailand included the following 5 phases: (i) preparing communities in 3 districts; (ii) developing risk dengue village prediction criteria; (iii) applying computer program; (iv) predicting village dengue risk with 75 public health providers in 39 PCUs; and (v) utilizing findings to strengthen dengue prevention activities in 220 villages. Data collecting for prediction used secondary data from primary care units in the past 5 year and current year. Descriptive statistics used calculating criteria and comparing with standard level to adjust score of risk. RESULTS: Risk dengue village assessment criteria had 2 aspects: dengue severity (3 factors) and dengue outbreak opportunity (3 factors). Total scores were 33 points and cut-off of 17 points for high and low dengue risks villages. All criteria were applied using computer program (http://surat.denguelim.com). Risk prediction involved stakeholder participation in 220 villages, and used for strengthening dengue prevention activities. The concept of integrated vector management included larval indices surveillance system, garbage management, larval indices level lower than the standard, community capacity activities for dengue prevention, and school-based dengue prevention. The risk prediction criteria and process mobilized villages for dengue prevention activities to decrease morbidity rate. CONCLUSION: Dengue risk assessment criteria were appropriated within the village, with its smallest unit, the household, included. The data can be utilized at village levels for evaluating dengue outbreak risks. SAGE Publications 2021-05-08 /pmc/articles/PMC8114320/ /pubmed/33966515 http://dx.doi.org/10.1177/21501327211013298 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Suwanbamrung, Charuai Le, Cua Ngoc Kaewsawat, Supreecha Chutipattana, Nirachon Khammaneechan, Patthanasak Thongchan, Supaporn Nontapet, Orratai Thongsuk, Cherd Laopram, Suphap Niyomchit, Chamaiporn Sinthu, Ruchira Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand |
title | Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand |
title_full | Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand |
title_fullStr | Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand |
title_full_unstemmed | Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand |
title_short | Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand |
title_sort | developing risk assessment criteria and predicting high- and low-dengue risk villages for strengthening dengue prevention activities: community participatory action research, thailand |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114320/ https://www.ncbi.nlm.nih.gov/pubmed/33966515 http://dx.doi.org/10.1177/21501327211013298 |
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