Between 2020 and 2022, Thailand encountered multiple SARS-CoV-2 variants causing a total of five waves of covid-19, e.g., S-clade for the 1st wave, GH-clade for the 2nd wave, Alpha variant for the 3rd wave, Delta variant for the 4th wave and finally Omicron variant for the 5th wave46. Bangkok, the capital city of Thailand, was greatly affected with the highest number of infected cases reported34. It is an area where tourists come in first, allowing new variants and outbreaks before the viruses spread to other provinces. After declining of covid-19 reported cases in early 2023, this allows to fully-open the country for welcoming foreign tourists, including Chinese tourists, on January 9, 2023. However, there are still concerns about a new wave of outbreaks that may occur after the country opening, Chinese New Year, and Songkran Festival.
Wastewater-based epidemiology (WBE) has been widely used as a tool for evaluating monitoring, surveillance, estimating infected populations, and outbreak warning prediction in several countries covering seven continents13,19,23,24,26,27,28,29,47,48. Therefore, this research has applied WBE for studying in Bangkok after fully opening the country. The premise of WBE is that people infected with SARS-CoV-2 can shed the virus in their respiratory secretions and gastrointestinal tract, such as feces, into wastewater treatment systems. The SARS-CoV-2 RNA could be detected in the wastewater, it would indicate the presence of infected persons in that area29,49. Several gene targets, i.e., N, S, E, and ORF1ab regions have been used for qualitative and quantitative detecting SARS-CoV-2 RNA in wastewater by using real time qRT-PCR, ddPCR, and next generation sequencing, and varying in termed of water concentration method, extraction, and different wastewater characteristics was noted33,34,35,36,37. Nevertheless, the N target region was widely reported for measuring RNA since its conservation across multiple SARS-CoV-2 variants50. Our study demonstrated the superior detection using N1 primer/probe set for detecting three variants, (hCoV-19/Thailand/MUMT-3/2020 [Wuhan-like strain], hCoV-19/Thailand/MUMT-53/2021 [Delta variant, and hCoV-19/Thailand/MUMT-11/2022 [Omicron variant]), used as the test viruses for real time qRT-PCR validation.
The current study was conducted on 10 representative WWTPs (six large-scale and four small-scale), covering 132.03 km2 for a registered population of approximately 2,520,700 people51. SARS-CoV-2 RNA was detected in 51% (102/200) wastewater samples, 88% in influent and 14% effluent samples, demonstrating a high concentration of SARS-CoV-2 RNA present in influent and RNA degradation (decay) over time52,53. The range of SARS-CoV-2 RNA was between 4.76 × 102 and 1.48 × 105 copies/L which corresponded to other previous reported13,35,37,54. Most previous studies collected untreated or raw wastewater and found a high SARS-CoV-2 RNA positive rate with a concentration of 101 to 106 copies/L10,22. There are a few studies that could detect SARS-CoV-2 RNA in effluent wastewater collected from WWTPs in Paris and Spain27,55. Corresponding to our study, we detected SARS-CoV-2 RNA in the effluent in ranges of 4.76 × 102 to 4.34 × 103 copies/L. Nevertheless, the RNA concentration detected in the effluent, treated wastewater, showed a reduction of 1.5–260 times compared to the RNA concentration detected in the influent. Even though our study could detect SARS-CoV-2 RNA in effluent samples, implying that the virus was potentially released to the environment. Several investigators demonstrated that SARS-CoV-2 RNA could be detected in the secondary and tertiary treated wastewater; but the infectious SARS-CoV-2 particle could not be isolated, demonstrating no viable viruses presented in effluent14,56,57.
Estimated infected populations have been calculated using modified estimated models reported from previous studies13,19,43. The estimated infected population corresponded to the weekly reported cases by showing a significant correlation (r = 0.351, p-value < 0.001). However, the estimated infected population from our study was higher than the reported cases, reflecting the real covid-19 infected cases were underestimated19,42. The estimation model depended on two variables: (1) the feces or urine rate per person per day, and (2) the RNA rate per gram of feces of Thais. However, the current sewage disposal system in Thailand could not effectively separate human feces and urine resulting no data available on feces or urine rates per person for Thais. Therefore, our study used a total excretion rate reported from the Department of Health for calculation44. In addition, for the amount of RNA shedding per gram in excretion of Thai people, our study applied the average SARS-CoV-2 RNA of 3.634 × 106 copies/gfeces found in Asian persons as reported by Saththasivam et al.43 and Zheng et al.45, which studied in Qatar and China, respectively. Furthermore, our study used an average daily flowrate annually reported from the Drainage and Sewerage Department in the estimation model. However, the use of the average daily flowrate obtained in a study period (January–May) might be more accurate than the annual average daily flowrate, particularly in regions such as Thailand where there is a wet and dry period of the year. Nevertheless, the flowrate could also vary from one week to another depending on the number of tourists that are present in the city.
Several studies reported the viral RNA concentration in wastewater has been related to reported cases21,24,27,29,31. Similarly, this study found that the amount of viral RNA in the influent significantly correlated with weekly reported cases (r = 0.481, p-value < 0.001). Two large-scale WWTPs, Chatuchak and Bang Sue, showed a strong correlation (r = 0.964, p-value < 0.001) and r = 0.842, p-value = 0.002), respectively; while, a Huai Kwang small-scale WWTP showed a moderate correlation (r = 0.675, p-value = 0.032), implying that size of WWTPs was not a factor effected the correlation analysis. However, Sangsanont J. et al.37, studied the WWTPs in Bangkok and found no correlation with viral RNA concentration and reported cases in the serve area. This was probably different by sampling, concentration, and extraction methods. According to the correlation between viral RNA concentration and reported cases in the service area, WWTPs are related on both small and large scales, which means that the scale of WWTPs is not a factor in the result.
In addition, our detected SARS-CoV-2 RNA in effluent samples did not show the correlation to the reported cases. Unfortunately, we did not have information on the wastewater characteristics such as BOD, COD, pH, Temperature, Total suspended solid (TSS), Total Kjeldahl nitrogen (TKN), etc., in influent and effluent samples. However, we know that most of Bangkok WWTPs (90%) used the activated sludge (AS) system for treating wastewater resulting in sludge formation presented in the treatment process. Previous reports revealed that the majority of SARS-CoV-2 RNA (82.5–92.5%) was found in sludge58, postulated that it is the main factor causing no correlation between SARS-CoV-2 RNA in effluent and covid-19 reported cases. For further investigation, WWTP treatment efficiency should be studied in mass balance of SARS-CoV-2 RNA in all treatment processes to determine the efficiency of wastewater treatment systems.
The WBE can be used as an early warning 2–14 days before an outbreak by using lag time correlation analysis in several countries9,24. Early warning of 4–10 days before an outbreak was reported from Massachusetts, USA31. The signal early warning 2 days before new covid-19 cases and 4 days before hospitalizations were reported in Canada29. Early warning was issued about 12–16 days before new cases were discovered in Spain, allowing governance to prepare resources and plan for mitigation outbreaks27. Likewise, in Thailand, Wannigama et al.35 studied WBE with reporting early warning of 20 days for rural areas and 14 days for urban areas, before new cases were reported. The study of Sangsanont S. et al.37 found correlation time to be as 22–24 days early warning in Bangkok. Both of the studies were conducted during the third wave SARS-CoV-2 outbreak in Thailand. The variable used for estimation is reported cases, some studies use the daily reported cases21,24,29, and some studies use accumulative cases by weekly report26,30,31. The estimated infected population in the post-pandemic period in Bangkok was calculated in our study. The official covid-19 cases were reported by week; therefore, this study used the 1-week average reported cases at different lag times (0–6 weeks). The lag time correlation was considered to be 6 weeks because SARS-CoV-2 can be shed in feces for more than 20 days31, and a previous study in Bangkok considered 40 days at a different lag time37. Consequently, a recent study found that a higher and stronger correlation was seen in the lag time correlation analysis between estimated infected cases and the 1-week average reported cases compared to viral RNA concentration. Although the estimated infected population had a higher correlation than viral RNA concentration, the overall lag time correlation in Bangkok was found to be significant time from a day to a week with a moderate correlation (p-value < 0.001).
Previous studies demonstrated that spatial analysis using GIS could be used to monitor the density and movement of infected populations, identify clusters, and evaluate efficiency after using prevention and control strategies59. Around 72 countries use the data from WBE to create GIS and dashboards for announcements to citizens among those countries60. The GIS has been used to control the covid-19 outbreaks, and the web-GIS system has provided beneficial information to the citizens, including the location of the detected patients, high-risk locations, and information about the available medical facilities61. This study first applied GIS for SARS-CoV-2 surveillance based on WBE in Bangkok. As spatial analysis, early detection was detected on mapping during the study period. Nevertheless, some of the spatial analysis demonstrated varying patterns due to the movement dynamics of a population. Bangkok is the most popular city for tourist destination, and a highest covid-19 cases was reported. In 2023, approximately 27 million cumulative tourists come to Thailand as reported by the Economics Tourism and Sport Division, Thailand. It is noted that the new SARS-CoV-2 variants might be potentially imported to the country. Nowadays, covid-19 cases have been frequently reported in many crowned places especially in the inner district of Bangkok. The real time dashboard of wastewater-based SARS-CoV-2 surveillance should be developed for monitoring new variants and supporting epidemiological data to government agencies and healthcare sectors for outbreak preparedness. Our study first demonstrated that the WBE combining with GIS might be a powerful tool implemented for disease surveillance systems in Bangkok, Thailand.
