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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lakkana Thaikruea | en_US |
dc.contributor.author | Lertrak Srikitjakarn | en_US |
dc.contributor.author | Nopasit Chakpitak | en_US |
dc.contributor.author | Sakorn Pornprasert | en_US |
dc.contributor.author | Rujira Ouncharoen | en_US |
dc.contributor.author | Woottichai Khamduang | en_US |
dc.contributor.author | Boontuan Kaewpinta | en_US |
dc.contributor.author | Sakulrat Pattamakaew | en_US |
dc.contributor.author | Ekkachai Laiya | en_US |
dc.contributor.author | Somsak Chanaim | en_US |
dc.contributor.author | Jiraporn Wongyai | en_US |
dc.date.accessioned | 2022-05-27T08:41:00Z | - |
dc.date.available | 2022-05-27T08:41:00Z | - |
dc.date.issued | 2022-01-01 | en_US |
dc.identifier.issn | 16851994 | en_US |
dc.identifier.other | 2-s2.0-85124556631 | en_US |
dc.identifier.other | 10.12982/CMUJNS.2022.006 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85124556631&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/73422 | - |
dc.description.abstract | This study aimed to design and test a COVID-19 surveillance system model for community-industry population. A prospective cohort study was conducted from May to December, 2020. Researchers designed a COVID-19 surveillance system and presented it to stakeholders from the community-industry setting in Lamphun and Chiang Mai provinces, Thailand. The model was adjusted following feedback and tested. The model was an Active surveillance for early Alert and rapid Action using Big data and mobile phone application technology for a Community-industry setting (3ABC model). The major components were active surveillance, community-based surveillance, event-based surveillance, and early warning and rapid response. A drive-thru testing unit was operated to enable early detection. Alerts and recommended action on individual and administrative levels were sent via an application and networks. In the testing of the model, risk assessment was initially conducted with regard to COVID-19 transmission in the factories. Researchers provided recommendations based on findings. The improvements included human resource management, systems, and structure. The 3ABC model work well as designed. The participants actively reported events daily including prevention and control activities, animal diseases (foot-and-mouth disease in buffalos and hog cholera), human diseases (dengue and chikungunya), and absent of COVID-19 outbreak. Only five quarantined COVID-19 cases whom were monitored. Daily reports of no abnormal event was also high (70.2% to 71.1%). It is practical and feasible to implement the 3ABC model in a community-industry setting. A further study for a longer period to verify its level of effectiveness should be done. | en_US |
dc.subject | Multidisciplinary | en_US |
dc.title | Model of COVID-19 Surveillance System for a Community-industry Setting | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Chiang Mai University Journal of Natural Sciences | en_US |
article.volume | 21 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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