Analysis of spatial and temporal patterns of COVID-19 incidence and its determinants in Thailand
Full Metadata
| Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Apiradee Sae Lim | - |
| dc.contributor.author | Nualnapa Poukparn | - |
| dc.contributor.department | ?????????????????????????? | - |
| dc.contributor.department | Faculty of Science and Technology | - |
| dc.date.accessioned | 2024-06-22 06:13 | - |
| dc.date.accessioned | 2026-02-11T02:42:25Z | - |
| dc.date.available | 2024-06-22 06:13 | - |
| dc.date.issued | 2024 | - |
| dc.description | ????????,?????????????????,2567 | - |
| dc.description.abstract | The variation in the COVID-19 incidence rate at different locations and timeframes is indicative of the situation and the severity of the problem. This study aimed to investigate spatial and temporal patterns of COVID-19 incidence rates and identify the factors associated with the COVID-19 incidence rates in Thailand. The data on daily COVID-19 infected cases were downloaded from the Department of Disease Control website at the Ministry of Public Health (MoPH) of Thailand from January 2020 to April 2022. COVID-19-infected cases were pooled daily to form monthly cases. The log-linear models were used to estimate the spatial and temporal COVID-19 infection rates. The results showed that a total of 3,344,191 subjects were infected by COVID-19 in the given period. The median COVID-19 incidence rate was 1.05 cases per 1,000 population per month (min = 0; max = 105.33), while the average was 3.32 cases per 1,000 population per month. Both genders aged 20�39 years exhibited significantly higher incidence rates than the average. The COVID-19 pandemic experienced three peaks. The first peak occurred between June and November 2020. The second peak was in August 2021 followed by a third peak between March and April 2022. Central and southern regions of Thailand had considerably higher COVID-19 incidence rates than the overall average. The incidence of COVID-19 is mostly determined by personal characteristics, as well as time and geographical characteristics. However, in the next studies, the emerging diseases with similar outbreak characteristics and long-term health effects can be emphasized. | - |
| dc.description.abstract | ????????????????????????-19 ??????????????????????????????????????????????????????????????????????? ??????????????????????????????????????????????????????????????????????????????????????-19 ?????????????????????????????????????????????????????-19 ??????????? ?????????????????????????-19 ?????? ???????????????????????????????? ???????????????? (MOPH) ?????????????????? 2563 ????????? 2565 ???????????????????????????????????????????????????? (Log-linear regression) ?????????????????????????????????????-19 ??????????? ??????????????? ???????????????????????????????-19 ????? 3,344,191 ??? ????????????????????-19 ??????????????????? 1.05 ????????????? 1,000 ?????????? (?????? = 0; ?????? = 105.33) ???????????????????????? 3.32 ????????????? 1,000 ?????????? ?????????????????????????????????????? 20-39 ?? ???????????????????????????????????????????????????????? ???????????????????????-19 ??????????? 3 ????????? ?????????????????????????????????????????????? ?.?. 2563 ??????????????????????????????? 2564 ?????????????????????????????????????? 2566 ???????????????????????????????????????? ????????????????????????????????????????????????????????????-19 ??????????????????? ???????????????????-19 ???????????????????????????????? ???? ?????????????????????? ??????? ???????????????????????????????????????????????????????????????????? ??????????????????????????????????? | - |
| dc.identifier.uri | https://kb.psu.ac.th/handle/2025/19842 | - |
| dc.language.iso | en | - |
| dc.publisher | Prince of Songkla University | - |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Thailand | - |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/th/ | - |
| dc.subject | COVID-19 incidence rate | - |
| dc.subject | Spatial-temporal | - |
| dc.subject | Log-linear model | - |
| dc.title | Analysis of spatial and temporal patterns of COVID-19 incidence and its determinants in Thailand | - |
| dc.title.alternative | Analysis of spatial and temporal patterns of COVID-19 incidence and its determinants in Thailand | - |
| dc.type | Thesis | - |
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