Effects of Gut Microbiome Modulation on Reducing Adverse Health Outcomes among Elderly and Diabetes Patients during the COVID-19 Pandemic: A Randomised, Double-Blind, Placebo-Controlled Trial (IMPACT Study).

Gut microbiota is believed to be a major determinant of health outcomes. We hypothesised that a novel oral microbiome formula (SIM01) can reduce the risk of adverse health outcomes in at-risk subjects during the coronavirus disease 2019 (COVID-19) pandemic. In this single-centre, double-blind, randomised, placebo-controlled trial, we recruited subjects aged ≥65 years or with type two diabetes mellitus. Eligible subjects were randomised in a 1:1 ratio to receive three months of SIM01 or placebo (vitamin C) within one week of the first COVID-19 vaccine dose. Both the researchers and participants were blinded to the groups allocated. The rate of adverse health outcomes was significantly lower in the SIM01 group than the placebo at one month (6 [2.9%] vs. 25 [12.6], p < 0.001) and three months (0 vs. 5 [3.1%], p = 0.025). At three months, more subjects who received SIM01 than the placebo reported better sleep quality (53 [41.4%] vs. 22 [19.3%], p < 0.001), improved skin condition (18 [14.1%] vs. 8 [7.0%], p = 0.043), and better mood (27 [21.2%] vs. 13 [11.4%], p = 0.043). Subjects who received SIM01 showed a significant increase in beneficial Bifidobacteria and butyrate-producing bacteria in faecal samples and strengthened the microbial ecology network. SIM01 reduced adverse health outcomes and restored gut dysbiosis in elderly and diabetes patients during the COVID-19 pandemic.

Evaluation of RT-qPCR Primer-Probe Sets to Inform Public Health Interventions Based on COVID-19 Sewage Tests.

Sewage surveillance is increasingly employed as a supplementary tool for COVID-19 control. Experiences learnt from large-scale trials could guide better interpretation of the sewage data for public health interventions. Here, we compared the performance of seven commonly used primer-probe sets in RT-qPCR and evaluated the usefulness in the sewage surveillance program in Hong Kong. All selected primer-probe sets reliably detected SARS-CoV-2 in pure water at 7 copies per µL. Sewage matrix did not influence RT-qPCR determination of SARS-CoV-2 concentrated from a small-volume sewage (30 mL) but introduced inhibitory impacts on a large-volume sewage (920 mL) with a ΔCt of 0.2-10.8. Diagnostic performance evaluation in finding COVID-19 cases showed that N1 was the best single primer-probe set, while the ORF1ab set is not recommended. Sewage surveillance using the N1 set for over 3200 samples effectively caught the outbreak trend and, importantly, had a 56% sensitivity and a 96% specificity in uncovering the signal sources from new cases and/or convalescent patients in the community. Our study paves the way for selecting detection primer-probe sets in wider applications in responding to the COVID-19 pandemic.

Use of Sewage Surveillance for COVID-19: A Large-Scale Evidence-Based Program in Hong Kong.

BACKGROUND: Sewage surveillance, by detecting SARS-CoV-2 virus circulation at the community level, has the potential to supplement individual surveillance for COVID-19. However, to date, there have been no reports about the large-scale implementation and validation of sewage surveillance for public health action. OBJECTIVE: Here, we developed a standardized approach for SARS-CoV-2 detection in sewage and applied it prospectively to supplement public health interventions. METHODS: We analyzed 1,169 sewage samples collected at 492 sites from December 2020 to March 2021. Forty-seven of 492 sites tested positive, 44 (94%) of them had traceable sources of viral signals in the corresponding sewershed, either from previously unsuspected but subsequently confirmed patients or recently convalescent patients or from both patient groups. RESULTS: Sewage surveillance had a sensitivity of 54%, a specificity of 95%, a positive predictive value of 53%, and a negative predictive value of 95% for identifying a previously unsuspected patient within a sewershed. Sewage surveillance in Hong Kong provided a basis for the statutory public health action to detect silent COVID-19 transmission. DISCUSSION: Considering the epidemiological data together with the sewage testing results, compulsory testing was conducted for individual residents at 27 positive sewage sites and uncovered total of 62 previously unsuspected patients, demonstrating the value of sewage surveillance in uncovering previously unsuspected patients in the community. Our study suggests that sewage surveillance could be a powerful management tool for the control of COVID-19. https://doi.org/10.1289/EHP9966.

Upholding veterinary services as a pillar of one health in Myanmar.

Veterinary service is one of the pillars to restore One Health in Myanmar. In the immediate future, international support provided to Myanmar can relieve food shortage and some humanitarian crises. In the long run, societal trauma from the military coup and violence, infrastructure breakdown, and economic downturn complicated by the COVID-19 pandemic will make recovery of the nation harder. While the building blocks to achieve peace and humanitarianism are long and complicated, part of the interim solution is to restore Myanmar veterinary services. The restoration will ease food scarcity in the short-run, reduce sylvatic and zoonotic infection risks and re-capitalise societal infrastructure building in the long-run. Myanmar society cannot rebuild on its own-it needs international and national support to facilitate peace and humanitarianism.

The first case study of wastewater-based epidemiology of COVID-19 in Hong Kong.

Early detection and surveillance of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) virus are key pre-requisites for the effective control of coronavirus disease (COVID-19). So far, sewage testing has been increasingly employed as an alternative surveillance tool for this disease. However, sampling site characteristics impact the testing results and should be addressed in the early use stage of this emerging tool. In this study, we implemented the sewage testing for SARS-CoV-2 virus across sampling sites with different sewage system characteristics. We first validated a testing method using "positive" samples from a hospital treating COVID-19 patients. This method was used to test 107 sewage samples collected during the third wave of the COVID-19 outbreak in Hong Kong (from June 8 to September 29, 2020), covering sampling sites associated with a COVID-19 hospital, public housing estates, and conventional sewage treatment facilities. The highest viral titer of 1975 copy/mL in sewage was observed in a sample collected from the isolation ward of the COVID-19 hospital. Sewage sampling at individual buildings detected the virus 2 days before the first cases were identified. Sequencing of the detected viral fragment confirmed an identical nucleotide sequence to that of the SARS-CoV-2 isolated from human samples. The virus was also detected in sewage treatment facilities, which serve populations of approximately 40,000 to more than one million people.

Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery.

Disease progression prediction and therapeutic drug target discovery for Coronavirus disease 2019 (COVID-19) are particularly important, as there is still no effective strategy for severe COVID-19 patient treatment. Herein, we performed multi-platform omics analysis of serial plasma and urine samples collected from patients during the course of COVID-19. Integrative analyses of these omics data revealed several potential therapeutic targets, such as ANXA1 and CLEC3B. Molecular changes in plasma indicated dysregulation of macrophage and suppression of T cell functions in severe patients compared to those in non-severe patients. Further, we chose 25 important molecular signatures as potential biomarkers for the prediction of disease severity. The prediction power was validated using corresponding urine samples and plasma samples from new COVID-19 patient cohort, with AUC reached to 0.904 and 0.988, respectively. In conclusion, our omics data proposed not only potential therapeutic targets, but also biomarkers for understanding the pathogenesis of severe COVID-19.

Characterization of respiratory microbial dysbiosis in hospitalized COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of Coronavirus disease 2019 (COVID-19). However, the microbial composition of the respiratory tract and other infected tissues as well as their possible pathogenic contributions to varying degrees of disease severity in COVID-19 patients remain unclear. Between 27 January and 26 February 2020, serial clinical specimens (sputum, nasal and throat swab, anal swab and feces) were collected from a cohort of hospitalized COVID-19 patients, including 8 mildly and 15 severely ill patients in Guangdong province, China. Total RNA was extracted and ultra-deep metatranscriptomic sequencing was performed in combination with laboratory diagnostic assays. We identified distinct signatures of microbial dysbiosis among severely ill COVID-19 patients on broad spectrum antimicrobial therapy. Co-detection of other human respiratory viruses (including human alphaherpesvirus 1, rhinovirus B, and human orthopneumovirus) was demonstrated in 30.8% (4/13) of the severely ill patients, but not in any of the mildly affected patients. Notably, the predominant respiratory microbial taxa of severely ill patients were Burkholderia cepacia complex (BCC), Staphylococcus epidermidis, or Mycoplasma spp. (including M. hominis and M. orale). The presence of the former two bacterial taxa was also confirmed by clinical cultures of respiratory specimens (expectorated sputum or nasal secretions) in 23.1% (3/13) of the severe cases. Finally, a time-dependent, secondary infection of B. cenocepacia with expressions of multiple virulence genes was demonstrated in one severely ill patient, which might accelerate his disease deterioration and death occurring one month after ICU admission. Our findings point to SARS-CoV-2-related microbial dysbiosis and various antibiotic-resistant respiratory microbes/pathogens in hospitalized COVID-19 patients in relation to disease severity. Detection and tracking strategies are needed to prevent the spread of antimicrobial resistance, improve the treatment regimen and clinical outcomes of hospitalized, severely ill COVID-19 patients.