Assessment of the Surveillance System for Coronavirus Disease 2019 (COVID-19) of Bamrasnaradura Infectious Diseases Institute Between 3rd July 2022 and 30th November 2022
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Abstract
This study aimed to study the reporting process of COVID-19, quantitative characteristics of the COVID-19 surveillance system, including sensitivity, positive predictive value, timeliness, data quality and representativeness, and usefulness. The qualitative characteristics of the COVID-19 surveillance system at Bamrasnaradura Infectious Diseases Institute, including stakeholder acceptability, simplicity, flexibility and system stability, and provide recommendations for improving the COVID-19 surveillance system at Bamrasnaradura Infectious Diseases Institute, Nonthaburi Province. This study using a cross-sectional study and a qualitative study, medical records were reviewed according to the reporting form of patients who met the definition of reporting, which were suspected patients with positive results from the Antigen Test Kit (ATK). We reviewed guidelines for disease surveillance and in-depth interviews a total of 19 administrators and relevant practitioners. We analyzed qualitative data using thematic analysis and quantitative data using descriptive statistics.
The results showed that from the reviewed medical records of 1,025 cases, 582 patients met the definition and reported in the surveillance system, 168 patients were not meet the definition and reported. The sensitivity was 87.16%. From July 3rd, 2022 to September 30th, 2022, Total cases (100%) was reported timely within 3 hours. Positive Predictive Value was 70.93%. Data Representativeness classified by gender, age, onset date of illness, was 99.56, 99.56 and 13.00, respectively. Between October 1st, 2022 and November 30th, 2022, 97.07% of cases were reported timely within 7 days. The Positive Predictive Value was at a high level of 92.31%. The sensitivity of report was high because there are workers 24 hours a day, especially during the epidemic. However, the suggestion is that service units should jointly monitor coronavirus disease 2019 by supporting modern technology that is easy to use, timely for analyzing, planning, and managing the disease to prevent the spread.
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References
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