Developing a community-based COVID-19 surveillance system for Rural Kalasin, Thailand 10.55131/jphd/2026/240210
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Abstract
The transition of COVID-19 from a dangerous communicable disease to a notifiable disease in Thailand highlights the need for robust post-pandemic surveillance systems. Particularly in rural areas, limited resources can affect the performance of disease surveillance. This study aimed to develop a community-based COVID-19 surveillance system. Amixed-methods research approach was employed, consisting of a quantitative phase to evaluate the surveillance system and determine the factors associated with its operation and a qualitative phase to develop and evaluate a surveillance system using Kemmis and McTaggart’s framework. The study was conducted from January 2022 to May 2024 and involved 568 public health officials, 414 case reports, and 52 stakeholders who collaboratively designed a surveillance system with brainstorming and used it to support quantitative findings. To analyze the data, multiple linear regression analyses, independent samples t-tests, chi-square tests, and content analyses were employed. Most of the respondents were female (76.06%), with a mean age and surveillance experience of 35.7 and 8.51 years, respectively. The COVID-19 surveillance system, comprising five proactive activities—surveillance strengthening, guideline development, agility, strategic planning, and after-action reviews—showed improvements in data quality, timeliness, and staff operational performance (P < 0.05) within the experimental area. The COVID-19 surveillance operational performance of the staff was strongly associated with case notification and verification (β = 0.428, 95%CI: 0.879, 1.108, P< 0.001), application of surveillance data for action (β = 0.328, 95%CI: 0.589, 0.762, P< 0.001) and epidemiological data collection and analysis (β = 0.297, 95%CI: 0.439, 0.552 P< 0.001), with an adjusted R² value of 0.854. These findings highlight the need for standardized guidelines, context-specific strategies, interagency collaboration, targeted training, and advanced digital tools —such as real-time mobile reporting and outbreak prediction tools— to enhance system performance, strengthen workforce capacity, and improve preparedness for future epidemics.
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