{"title":"测量曼谷污水处理厂中的 SARS-CoV-2 RNA，并估算 2023 年泰国全面开放后的感染人群。","authors":"Thanchira Saita, Bussarakam Thitanuwat, Nattamon Niyomdecha, Jarunee Prasertsopon, Hatairat Lerdsamran, Pilaipan Puthavathana, Pirom Noisumdaeng","doi":"10.1038/s41598-025-94938-7","DOIUrl":null,"url":null,"abstract":"<p><p>Wastewater-based epidemiology (WBE) has been employed for monitoring the presence of SARS-CoV-2 infected population. Herein, the study aims to apply the WBE for surveillance and monitoring SARS-CoV-2 in Bangkok, where the highest official covid-19 cases reported in Thailand, during the fully opening for international tourists in early 2023. A total of 200 wastewater samples (100 influent and 100 effluent samples) were collected from 10 wastewater treatment plants (WWTPs) during January-May 2023. SARS-CoV-2 RNA was detected by real time qRT-PCR with accounting for 51% (102/200). Of these, 88% (88/100) and 14% (14/100) were detected in influent and effluent samples, respectively. The SARS-CoV-2 RNA concentration was detected in ranged of 4.76 × 10<sup>2</sup>-1.48 × 10<sup>5</sup> copies/L. The amount of SARS-CoV-2 RNA has increased approximately 4 times from the lag phase (January-March) to the log phase (April-May). Spearman's correlation coefficient revealed that correlation between estimated infected population and weekly reported cases was statistically significant (p-value = 0.017). SARS-CoV-2 RNA in influent had a statistically significant relationship with weekly reported cases (r = 0.481, p-value < 0.001). Lag time analysis revealed early warning 1-3 weeks before rising covid-19 cases observed. GIS was applied for spatial-temporal analysis at the province level, suggesting real time dashboard should be further developed.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"9663"},"PeriodicalIF":3.9000,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926235/pdf/","citationCount":"0","resultStr":"{\"title\":\"Measuring SARS-CoV-2 RNA in Bangkok wastewater treatment plants and estimating infected population after fully opening the country in 2023, Thailand.\",\"authors\":\"Thanchira Saita, Bussarakam Thitanuwat, Nattamon Niyomdecha, Jarunee Prasertsopon, Hatairat Lerdsamran, Pilaipan Puthavathana, Pirom Noisumdaeng\",\"doi\":\"10.1038/s41598-025-94938-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Wastewater-based epidemiology (WBE) has been employed for monitoring the presence of SARS-CoV-2 infected population. Herein, the study aims to apply the WBE for surveillance and monitoring SARS-CoV-2 in Bangkok, where the highest official covid-19 cases reported in Thailand, during the fully opening for international tourists in early 2023. A total of 200 wastewater samples (100 influent and 100 effluent samples) were collected from 10 wastewater treatment plants (WWTPs) during January-May 2023. SARS-CoV-2 RNA was detected by real time qRT-PCR with accounting for 51% (102/200). Of these, 88% (88/100) and 14% (14/100) were detected in influent and effluent samples, respectively. The SARS-CoV-2 RNA concentration was detected in ranged of 4.76 × 10<sup>2</sup>-1.48 × 10<sup>5</sup> copies/L. The amount of SARS-CoV-2 RNA has increased approximately 4 times from the lag phase (January-March) to the log phase (April-May). Spearman's correlation coefficient revealed that correlation between estimated infected population and weekly reported cases was statistically significant (p-value = 0.017). SARS-CoV-2 RNA in influent had a statistically significant relationship with weekly reported cases (r = 0.481, p-value < 0.001). Lag time analysis revealed early warning 1-3 weeks before rising covid-19 cases observed. GIS was applied for spatial-temporal analysis at the province level, suggesting real time dashboard should be further developed.</p>\",\"PeriodicalId\":21811,\"journal\":{\"name\":\"Scientific Reports\",\"volume\":\"15 1\",\"pages\":\"9663\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926235/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Reports\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41598-025-94938-7\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-025-94938-7","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Measuring SARS-CoV-2 RNA in Bangkok wastewater treatment plants and estimating infected population after fully opening the country in 2023, Thailand.
Wastewater-based epidemiology (WBE) has been employed for monitoring the presence of SARS-CoV-2 infected population. Herein, the study aims to apply the WBE for surveillance and monitoring SARS-CoV-2 in Bangkok, where the highest official covid-19 cases reported in Thailand, during the fully opening for international tourists in early 2023. A total of 200 wastewater samples (100 influent and 100 effluent samples) were collected from 10 wastewater treatment plants (WWTPs) during January-May 2023. SARS-CoV-2 RNA was detected by real time qRT-PCR with accounting for 51% (102/200). Of these, 88% (88/100) and 14% (14/100) were detected in influent and effluent samples, respectively. The SARS-CoV-2 RNA concentration was detected in ranged of 4.76 × 102-1.48 × 105 copies/L. The amount of SARS-CoV-2 RNA has increased approximately 4 times from the lag phase (January-March) to the log phase (April-May). Spearman's correlation coefficient revealed that correlation between estimated infected population and weekly reported cases was statistically significant (p-value = 0.017). SARS-CoV-2 RNA in influent had a statistically significant relationship with weekly reported cases (r = 0.481, p-value < 0.001). Lag time analysis revealed early warning 1-3 weeks before rising covid-19 cases observed. GIS was applied for spatial-temporal analysis at the province level, suggesting real time dashboard should be further developed.
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