COVID-19 monitoring with sparse sampling of sewered and non-sewered wastewater in urban and rural communities

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.

Real world effectiveness of early ensitrelvir treatment in patients with SARS-CoV-2, a retrospective case series

Background

Ensitrelvir, a 3C-like protease inhibitor, received emergency approval in Japan in November 2022 for treating non-hospitalized patients with mild-to-moderate COVID-19. However, confirmation of its real-world clinical effectiveness is limited.

Methods

This retrospective study evaluated 18 vaccinated outpatients (15 men; median age, 39.5 years; range, 26-56), treated with a 5-day oral ensitrelvir regimen (375 mg loading dose, followed by 125 mg daily) between December 1, 2022, and January 31, 2023. Nasal swabs were collected on days 0, 3, 6, and 9 for RT-qPCR to assess viral load. Variants were identified by Sanger sequencing, and outcomes were compared to historical controls. Patients were followed for 60 days to monitor for post-acute sequelae of COVID-19 (PASC).

Results

Symptoms such as mild fever and sore throat improved rapidly after one day of ensitrelvir treatment, with 66 % of patients recovering within six days. All individuals were infected with the BA.5 Omicron variant. Viral loads, as measured by Ct values, increased significantly from 21.82 at symptom onset to 37.65 b y day 6, with SARS-CoV-2 RNA undetectable in most patients by day 9. Those treated within 48 h of symptom onset showed the viral load reduction. Compared to historical controls, where symptom resolution took 8.5 days, ensitrelvir shortened recovery time to as little as 1.4 days for over 66 % of patients.

Conclusion

Ensitrelvir treatment resulted in rapid symptom relief and significant viral load reduction, with no adverse events, viral rebound, or PASC symptoms, demonstrating its potential efficacy and safety. Larger studies are needed for further confirmation.

Impact of COVID-19 Vaccination in Thailand: Averted Deaths and Severe Infections Across Age Groups

The COVID-19 pandemic has underscored the pivotal role of vaccines in mitigating the devastating impact of the virus. In Thailand, the vaccination campaign against SARS-CoV-2 began on 28 February 2021, initially prioritizing healthcare professionals before expanding into a nationwide effort on 7 June 2021. This study employs a mathematical model of COVID-19 transmission with vaccination to analyze the impact of Thailand's COVID-19 vaccination program from 1 March 2021 to 31 December 2022. We specifically assess the potential loss of lives and occurrence of severe infections across various age groups in a hypothetical scenario where vaccines were not administered. By fitting our model with officially reported COVID-19 death data, our analysis reveals that vaccination efforts prevented a total of 300,234 deaths (95% confidence interval: 295,938-304,349) and averted 1.60 million severe COVID-19 infections (95% confidence interval: 1.54-1.65 million). Notably, the elderly population over 80 years old benefited the most from vaccination, with an estimated 84,518 lives saved, constituting 4.28% of this age group. Furthermore, individuals aged between 70 and 74 years experienced the highest reduction in severe infections, with vaccination potentially preventing 8.35% of this age bracket from developing severe COVID-19.

Identification of protein biomarkers in wastewater linked to the incidence of COVID-19

Wastewater-based epidemiological (WBE) surveillance is a viable disease surveillance technique capable of monitoring the spread of infectious disease agents in sewershed communities. In addition to detecting viral genomes in wastewater, WBE surveillance can identify other endogenous biomarkers that are significantly elevated and excreted in the saliva, urine, and/or stool of infected individuals. Human protein biomarkers allow the realization of real-time WBE surveillance using highly sensitive biosensors. In this study, we analyzed endogenous protein biomarkers present in wastewater influent through liquid chromatography-tandem mass spectrophotometry and scaffold data-independent acquisition to identify candidate target protein biomarkers for WBE surveillance of SARS-CoV-2. We found that out of the 1382 proteins observed in the wastewater samples, 44 were human proteins associated with infectious diseases. These included immune response substances such as immunoglobulins, cytokine-chemokines, and complements, as well as proteins belonging to antimicrobial and antiviral groups. A significant correlation was observed between the intensity of human infectious disease-related protein biomarkers in wastewater and COVID-19 case numbers. Real-time WBE surveillance using biosensors targeting immune response proteins, such as antibodies or immunoglobulins, in wastewater holds promise for expediting the implementation of relevant policies for the effective prevention of infectious diseases in the near future.

Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand

BACKGROUND

Timely and informed public health responses to infectious diseases such as COVID-19 necessitate reliable information about infection dynamics. The case ascertainment rate (CAR), the proportion of infections that are reported as cases, is typically much less than one and varies with testing practices and behaviours, making reported cases unreliable as the sole source of data. The concentration of viral RNA in wastewater samples provides an alternate measure of infection prevalence that is not affected by clinical testing, healthcare-seeking behaviour or access to care.

METHODS

We construct a state-space model with observed data of levels of SARS-CoV-2 in wastewater and reported case incidence and estimate the hidden states of the effective reproduction number, R, and CAR using sequential Monte Carlo methods.

RESULTS

We analyse data from 1 January 2022 to 31 March 2023 from Aotearoa New Zealand. Our model estimates that R peaks at 2.76 (95% CrI 2.20, 3.83) around 18 February 2022 and the CAR peaks around 12 March 2022. We calculate that New Zealand's second Omicron wave in July 2022 is similar in size to the first, despite fewer reported cases. We estimate that the CAR in the BA.5 Omicron wave in July 2022 is approximately 50% lower than in the BA.1/BA.2 Omicron wave in March 2022.

CONCLUSIONS

Estimating R, CAR, and cumulative number of infections provides useful information for planning public health responses and understanding the state of immunity in the population. This model is a useful disease surveillance tool, improving situational awareness of infectious disease dynamics in real-time.

A systematic review and meta-analysis, investigating dose and time of fluvoxamine treatment efficacy for COVID-19 clinical deterioration, death, and Long-COVID complications

There have been 774,075,242 cases of COVID-19 and 7,012,986 deaths worldwide as of January 2024. In the early stages of the pandemic, there was an urgent need to reduce the severity of the disease and prevent the need for hospitalization to avoid stress on healthcare systems worldwide. The repurposing of drugs to prevent clinical deterioration of COVID-19 patients was trialed in many studies using many different drugs. Fluvoxamine (an SSRI and sigma-1 receptor agonist) was initially identified to potentially provide beneficial effects in COVID-19-infected patients, preventing clinical deterioration and the need for hospitalization. Fourteen clinical studies have been carried out to date, with seven of those being randomized placebo-controlled studies. This systematic review and meta-analysis covers the literature from the outbreak of SARS-CoV-2 in late 2019 until January 2024. Search terms related to fluvoxamine, such as its trade names and chemical names, along with words related to COVID-19, such as SARS-CoV-2 and coronavirus, were used in literature databases including PubMed, Google Scholar, Scopus, and the ClinicalTrials.gov database from NIH, to identify the trials used in the subsequent analysis. Clinical deterioration and death data were extracted from these studies where available and used in the meta-analysis. A total of 7153 patients were studied across 14 studies (both open-label and double-blind placebo-controlled). 681 out of 3553 (19.17%) in the standard care group and 255 out of 3600 (7.08%) in the fluvoxamine-treated group experienced clinical deterioration. The estimated average log odds ratio was 1.087 (95% CI 0.200 to 1.973), which differed significantly from zero (z = 2.402, p = 0.016). The seven placebo-controlled studies resulted in a log odds ratio of 0.359 (95% CI 0.1111 to 0.5294), which differed significantly from zero (z = 3.103, p = 0.002). The results of this study identified fluvoxamine as effective in preventing clinical deterioration, and subgrouping analysis suggests that earlier treatment with a dose of 200 mg or above provides the best outcomes. We hope the outcomes of this study can help design future studies into respiratory viral infections and potentially improve clinical outcomes.

Wastewater-based epidemiological surveillance of SARS-CoV-2 new variants BA.2.86 and offspring JN.1 in South and Southeast Asia

Discover the shifting landscape of SARS-CoV-2 variants from October to December 2023, with JN.1 dominating South and Southeast Asia wastewater samples, increasing from &lt;10% to &gt;90%. Experience the dynamic evolution of viral strains in this period.

Small-scale wastewater-based epidemiology (WBE) for infectious diseases and antibiotic resistance: A scoping review

Wastewater analysis can serve as a source of public health information. In recent years, wastewater-based epidemiology (WBE) has emerged and proven useful for the detection of infectious diseases. However, insights from the wastewater treatment plant do not allow for the small-scale differentiation within the sewer system that is needed to analyze the target population under study in more detail. Small-scale WBE offers several advantages, but there has been no systematic overview of its application. The aim of this scoping review is to provide a comprehensive overview of the current state of knowledge on small-scale WBE for infectious diseases, including methodological considerations for its application. A systematic database search was conducted, considering only peer-reviewed articles. Data analyses included quantitative summary and qualitative narrative synthesis. Of 2130 articles, we included 278, most of which were published since 2020. The studies analyzed wastewater at the building level (n = 203), especially healthcare (n = 110) and educational facilities (n = 80), and at the neighborhood scale (n = 86). The main analytical parameters were viruses (n = 178), notably SARS-CoV-2 (n = 161), and antibiotic resistance (ABR) biomarkers (n = 99), often analyzed by polymerase chain reaction (PCR), with DNA sequencing techniques being less common. In terms of sampling techniques, active sampling dominated. The frequent lack of detailed information on the specification of selection criteria and the characterization of the small-scale sampling sites was identified as a concern. In conclusion, based on the large number of studies, we identified several methodological considerations and overarching strategic aspects for small-scale WBE. An enabling environment for small-scale WBE requires inter- and transdisciplinary knowledge sharing across countries. Promoting the adoption of small-scale WBE will benefit from a common international conceptualization of the approach, including standardized and internationally accepted terminology. In particular, the development of good WBE practices for different aspects of small-scale WBE is warranted. This includes the establishment of guidelines for a comprehensive characterization of the local sewer system and its sub-sewersheds, and transparent reporting to ensure comparability of small-scale WBE results.

LSTM-Powered COVID-19 prediction in central Thailand incorporating meteorological and particulate matter data with a multi-feature selection approach

The COVID-19 pandemic has significantly impacted public health and necessitated urgent actions to mitigate its spread. Monitoring and predicting the outbreak's progression have become vital to devise effective strategies and allocate resources efficiently. This study presents a novel approach utilizing Multivariate Long Short-Term Memory (LSTM) to analyze and predict COVID-19 trends in Central Thailand, particularly emphasizing the multi-feature selection process. To consider a comprehensive view of the pandemic's dynamics, our research dataset encompasses epidemiological, meteorological, and particulate matter features, which were gathered from reliable sources. We propose a multi-feature selection technique to identify the most relevant and influential features that significantly impact the spread of COVID-19 in the region to enhance the model's performance. Our results highlight that relative humidity is the key factor driving COVID-19 transmission in Central Thailand. The proposed multi-feature selection technique significantly improves the model's accuracy, ensuring that only the most informative variables contribute to the predictions, avoiding the potential noise or redundancy from less relevant features. The proposed LSTM model demonstrates its capability to forecast COVID-19 cases, facilitating informed decision-making for public health authorities and policymakers.

AH, Storer RJ, Ounjai P, Kanthawee P, Ngamwongsatit N, Kupwiwat R, Kupwiwat C, Brimson JM, Devanga Ragupathi NK, Charuluxananan S, Leelahavanichkul A, Kanjanabuch T, Higgins PG, Badavath VN, Amarasiri M, Verhasselt V, Kicic A, Chatsuwan T, Pirzada K, Jalali F, Reiersen AM, Abe S, Ishikawa H. Early treatment with fluvoxamine, bromhexine, cyproheptadine, and niclosamide to prevent clinical deterioration in patients with symptomatic COVID-19: a randomized clinical trial

Background

Repurposed drugs with host-directed antiviral and immunomodulatory properties have shown promise in the treatment of COVID-19, but few trials have studied combinations of these agents. The aim of this trial was to assess the effectiveness of affordable, widely available, repurposed drugs used in combination for treatment of COVID-19, which may be particularly relevant to low-resource countries.

Methods

We conducted an open-label, randomized, outpatient, controlled trial in Thailand from October 1, 2021, to June 21, 2022, to assess whether early treatment within 48-h of symptoms onset with combinations of fluvoxamine, bromhexine, cyproheptadine, and niclosamide, given to adults with confirmed mild SARS-CoV-2 infection, can prevent 28-day clinical deterioration compared to standard care. Participants were randomly assigned to receive treatment with fluvoxamine alone, fluvoxamine + bromhexine, fluvoxamine + cyproheptadine, niclosamide + bromhexine, or standard care. The primary outcome measured was clinical deterioration within 9, 14, or 28 days using a 6-point ordinal scale. This trial is registered with ClinicalTrials.gov (NCT05087381).

Findings

Among 1900 recruited, a total of 995 participants completed the trial. No participants had clinical deterioration by day 9, 14, or 28 days among those treated with fluvoxamine plus bromhexine (0%), fluvoxamine plus cyproheptadine (0%), or niclosamide plus bromhexine (0%). Nine participants (5.6%) in the fluvoxamine arm had clinical deterioration by day 28, requiring low-flow oxygen. In contrast, most standard care arm participants had clinical deterioration by 9, 14, and 28 days. By day 9, 32.7% (110) of patients in the standard care arm had been hospitalized without requiring supplemental oxygen but needing ongoing medical care. By day 28, this percentage increased to 37.5% (21). Additionally, 20.8% (70) of patients in the standard care arm required low-flow oxygen by day 9, and 12.5% (16) needed non-invasive or mechanical ventilation by day 28. All treated groups significantly differed from the standard care group by days 9, 14, and 28 (p < 0.0001). Also, by day 28, the three 2-drug treatments were significantly better than the fluvoxamine arm (p < 0.0001). No deaths occurred in any study group. Compared to standard care, participants treated with the combination agents had significantly decreased viral loads as early as day 3 of treatment (p < 0.0001), decreased levels of serum cytokines interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and interleukin-1 beta (IL-1β) as early as day 5 of treatment, and interleukin-8 (IL-8) by day 7 of treatment (p < 0.0001) and lower incidence of post-acute sequelae of COVID-19 (PASC) symptoms (p < 0.0001). 23 serious adverse events occurred in the standard care arm, while only 1 serious adverse event was reported in the fluvoxamine arm, and zero serious adverse events occurred in the other arms.

Interpretation

Early treatment with these combinations among outpatients diagnosed with COVID-19 was associated with lower likelihood of clinical deterioration, and with significant and rapid reduction in the viral load and serum cytokines, and with lower burden of PASC symptoms. When started very soon after symptom onset, these repurposed drugs have high potential to prevent clinical deterioration and death in vaccinated and unvaccinated COVID-19 patients.

Funding

Ped Thai Su Phai (Thai Ducks Fighting Danger) social giver group.

Vaccination strategies impact the probability of outbreak extinction: A case study of COVID-19 transmission

Mass vaccination has proven to be an effective control measure for mitigating the transmission of infectious diseases. Throughout history, various vaccination strategies have been employed to control infections and terminate outbreaks. In this study, we utilized the transmission of COVID-19 as a case study and constructed a stochastic age-structured compartmental model to investigate the effectiveness of different vaccination strategies. Our analysis focused on estimating the outbreak extinction probability under different vaccination scenarios in both homogeneous and heterogeneous populations. Notably, we found that population heterogeneity can enhance the likelihood of outbreak extinction at varying levels of vaccine coverage. Prioritizing vaccinations for individuals with higher infection risk was found to maximize outbreak extinction probability and reduce overall infections, while allocating vaccines to those with higher mortality risk has been proven more effective in reducing deaths. Moreover, our study highlighted the significance of booster doses as the vaccine effectiveness wanes over time, showing that they can significantly enhance the extinction probability and mitigate disease transmission.

AH, Fernandez S, Huang AT, Vatanaprasan P, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Ngamwongsatit N, Badavath VN, Thuptimdang W, Leelahavanichkul A, Kanjanabuch T, Miyanaga K, Cui L, Nanbo A, Shibuya K, Kupwiwat R, Sano D, Furukawa T, Sei K, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, Ishikawa H, Amarasiri M, Modchang C, Wannigama DL. Exploring indoor and outdoor dust as a potential tool for detection and monitoring of COVID-19 transmission

This study investigated the potential of using SARS-CoV-2 viral concentrations in dust as an additional surveillance tool for early detection and monitoring of COVID-19 transmission. Dust samples were collected from 8 public locations in 16 districts of Bangkok, Thailand, from June to August 2021. SARS-CoV-2 RNA concentrations in dust were quantified, and their correlation with community case incidence was assessed. Our findings revealed a positive correlation between viral concentrations detected in dust and the relative risk of COVID-19. The highest risk was observed with no delay (0-day lag), and this risk gradually decreased as the lag time increased. We observed an overall decline in viral concentrations in public places during lockdown, closely associated with reduced human mobility. The effective reproduction number for COVID-19 transmission remained above one throughout the study period, suggesting that transmission may persist in locations beyond public areas even after the lockdown measures were in place.

Fate-and-transport modeling of SARS-CoV-2 for rural wastewater-based epidemiology application benefit

Wastewater-based epidemiology (WBE) for the detection of agents of concern such as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been prevalent in literature since 2020. The majority of reported research focuses on large urban centers with few references to rural communities. In this research the EPA-Storm Water Management Model (EPA-SWMM) software was used to describe a small sewershed and identify the effects of temperature, temperature-affected decay rate, flow rate, flush time, fecal shedding rate, and historical infection rates during the spread of the Omicron variant of the SARS-CoV-2 virus within the sewershed. Due to the sewershed's relative isolation from the rest of the city, its wastewater quality behavior is similar to a rural sewershed. The model was used to assess city wastewater sampling campaigns to best appropriate field and or lab equipment when sampling wastewater. An important aspect of the assessment was the comparison of SARS-CoV-2 quantification methods with specifically between a traditional microbiological lab (practical quantitation limit, PQL, 1 GC/mL) versus what can be known from a field method (PQL 10 GC/mL). Understanding these monitoring choices will help rural communities make decisions on how to best implement the collection and testing for WBE agents of concern. An important outcome of this work is the knowledge that it is possible to simulate a WBE agent of concern with reasonable precision, if uncertainties are incorporated into model sensitivity. These ideas could form the basis for future mixed monitoring-modeling studies that will enhance its application and therefore adoption of WBE techniques in communities of many sizes and financial means.

Modeling vaccination strategies with limited early COVID-19 vaccine access in low- and middle-income countries: A case study of Thailand

Low- and middle-income countries faced significant challenges in accessing COVID-19 vaccines during the early stages of the pandemic. In this study, we utilized an age-structured modeling approach to examine the implications of various vaccination strategies, vaccine prioritization, and vaccine rollout speeds in Thailand, an upper-middle-income country experiencing vaccine shortages during the early stages of the pandemic. The model directly compares the effectiveness of several vaccination strategies, including the heterologous vaccination where CoronaVac (CV) vaccine was administered as the first dose, followed by ChAdOx1 nCoV-19 (AZ) vaccine as the second dose, under varying disease transmission dynamics. We found that the traditional AZ homologous vaccination was more effective than the CV homologous vaccination, regardless of disease transmission dynamics. However, combining CV and AZ vaccines via either parallel homologous or heterologous vaccinations was more effective than relying solely on AZ homologous vaccination. Additionally, prioritizing vaccination for the elderly aged 60 years and above was the most effective way to reduce mortality when community transmission is well-controlled. On the other hand, prioritizing workers aged 20-59 was most effective in lowering COVID-19 cases, irrespective of the transmission dynamics. Lastly, despite the vaccine prioritization strategy, rapid vaccine rollout speeds were crucial in reducing COVID-19 infections and deaths. These findings suggested that in low- and middle-income countries where early access to high-efficacy vaccines might be limited, obtaining any accessible vaccines as early as possible and using them in parallel with other higher-efficacy vaccines might be a better strategy than waiting for and relying solely on higher-efficacy vaccines.

Tracing the transmission of mpox through wastewater surveillance in Southeast Asia

High population density and tourism in Southeast Asia increase the risk of mpox due to frequent interpersonal contacts. Our wastewater surveillance in six Southeast Asian countries revealed positive signals for Monkeypox virus (MPXV) DNA, indicating local transmission. This alerts clinicians and helps allocate resources like testing, vaccines and therapeutics in resource-limited countries.