Factors Associated with the Incidence of COVID-19 in Muang Pattani District, Thailand

Abstract

COVID-19 caused a severe public health concern worldwide. This study aimed to (1) investigate the characteristics of confirmed COVID-19 cases and (2) examine factors associated with the incidence of COVID-19 in Muang Pattani District, Thailand. A total of 16,065 confirmed cases from April 2021 to September 2022 were analyzed. The dependent variable was the number of COVID-19 cases, while independent variables included gender, age group, sub-district, and month-year. Negative binomial regression was applied to estimate adjusted incidence rates with 95% confidence intervals, based on sum contrast approach after identifying overdispersion in the poisson model. Descriptive results revealed that females accounted for a higher proportion of confirmed cases (58.52%) compared to males (41.48%). Most cases were reported among individuals aged 20�29 (18.49%) and 30�39 (18.24%) years. Spatially, the Sabarang sub-district recorded the highest number of cases (3,289 cases; 20.47%), followed by Bana (19.63%) and Ru Samilae (16.82%). Temporally, the incidence peaked during the second half of 2021 and early 2022, with the highest monthly proportions observed in October 2021 (17.12%) and March 2022 (17.09%). Multivariate results showed that females and individuals aged 30�49 years had significantly higher adjusted incidence rates compared to the overall mean. Sub-districts such as Chabang Tiko exhibited notably elevated rates, while rural sub-districts like Baraho, Kamiyo, Khlong Maning, and Paka Harang showed relatively lower rates. These findings highlighted the influence of demographic, spatial, and temporal factors on COVID-19 incidence and support targeted interventions, including enhanced surveillance in high-risk areas, prioritized vaccination for risk groups, and control measures adapted to local contexts.

?????????????????????? 2019 (?????-19) ?????????????????????????????????? ?????????????????????????????? (1) ????????????????????????????????-19 ??? (2) ??????????????????????????????????????????????????????????????-19 ??????????????????? ?????????????? ?????????????????????????????? 16,065 ??? ?????????????????????????????? ?.?. 2564 ??????????????? ?.?. 2565 ?????????????????????????????-19 ??????????????? ?????? ??? ????????? ???? ????????�???????????????? ??????????????????????????? overdispersion ?????????????????????????????? ??????????????????????????????????? (negative binomial regression) ????????????????????????????????????????-19 ?????????????? (adjusted incidence rate) ?????????????????????? 95% ?????????? sum contrast ??????????????????? ???????????????????????????????????? ????????????? 58.52 ??? 41.48 ???????? ????????????????????????????????????????? 20�29 ?? (?????? 18.49) ??? 30�39 ?? (?????? 18.24) ????????????????????????????? ??? ??????????? (3,289 ??? ????????????? 20.47) ?????????????????? (19.63%) ??? ???????? (16.82%) ??????????????????????????? ??? ??????????? ?.?. 2564 ????????????????????????????? ?.?. 2565 ????????????????????????????????????????????????-19 ??????????????????????????????????????????????? 30�49 ?????????????????????????????????? ??????????????????????????????? ??????????????????????????????? ???????????????? ???? ???????? ?????? ????????? ???????????? ?????????????????? ???????????????????????????????????????????????????????? ??????? ?????????????????????????????????????????-19 ???????????????????????????????????????????????????????? ?????? ?????????????????????????????????????? ?????????????????????????????????????????????????? ????????????????????????????????????????????