Wastewater Surveillance Can Function as an Early Warning System for COVID-19 in Low-Incidence Settings.

INTRODUCTION: During the first two years of the COVID-19 pandemic, Australia implemented a series of international and interstate border restrictions. The state of Queensland experienced limited COVID-19 transmission and relied on lockdowns to stem any emerging COVID-19 outbreaks. However, early detection of new outbreaks was difficult. In this paper, we describe the wastewater surveillance program for SARS-CoV-2 in Queensland, Australia, and report two case studies in which we aimed to assess the potential for this program to provide early warning of new community transmission of COVID-19. Both case studies involved clusters of localised transmission, one originating in a Brisbane suburb (Brisbane Inner West) in July-August 2021, and the other originating in Cairns, North Queensland in February-March 2021. MATERIALS AND METHODS: Publicly available COVID-19 case data derived from the notifiable conditions (NoCs) registry from the Queensland Health data portal were cleaned and merged spatially with the wastewater surveillance data using statistical area 2 (SA2) codes. The positive predictive value and negative predictive value of wastewater detection for predicting the presence of COVID-19 reported cases were calculated for the two case study sites. RESULTS: Early warnings for local transmission of SARS-CoV-2 through wastewater surveillance were noted in both the Brisbane Inner West cluster and the Cairns cluster. The positive predictive value of wastewater detection for the presence of notified cases of COVID-19 in Brisbane Inner West and Cairns were 71.4% and 50%, respectively. The negative predictive value for Brisbane Inner West and Cairns were 94.7% and 100%, respectively. CONCLUSIONS: Our findings highlight the utility of wastewater surveillance as an early warning tool in low COVID-19 transmission settings.

Increased Nicotine Consumption in Australia During the First Months of the COVID-19 Pandemic.

INTRODUCTION: Mixed findings have been reported about the impact of the COVID-19 pandemic on smoking behavior in different populations. AIMS AND METHODS: In this study, we aimed to quantify changes in smoking prevalence through the proxy of nicotine consumption in the Australian population from 2017 to 2020 inclusive. Estimates of nicotine consumption between 2017 and 2020 were retrieved from a national wastewater monitoring program that covers up to 50% of the Australian population. National sales data for nicotine replacement therapy (NRT) products from 2017 to 2020 were also acquired. Linear regression and pairwise comparison were conducted to identify data trends and to test differences between time periods. RESULTS: The average consumption of nicotine in Australia decreased between 2017 and 2019 but increased in 2020. Estimated consumption in the first half of 2020 was significantly higher (~30%) than the previous period. Sales of NRT products increased gradually from 2017 to 2020 although sales in the first half of the year were consistently lower than in the second half. CONCLUSION: Total nicotine consumption increased in Australia during the early stage of the pandemic in 2020. Increased nicotine consumption may be due to people managing higher stress levels, such as from loneliness due to control measures, and also greater opportunities to smoke/vape while working from home and during lockdowns in the early stage of the pandemic. IMPLICATIONS: Tobacco and nicotine consumption have been decreasing in Australia but the COVID-19 pandemic may have temporarily disrupted this trend. In 2020, the higher impacts of lockdowns and working from home arrangements may have led to a temporary reversal of the previous downward trend in smoking during the early stage of the pandemic.

Spatiotemporal trends and impact of Covid-19 lockdown on eight sewage contaminants in Brisbane, Australia, from 2012 to 2020.

This study aims to investigate the spatiotemporal trends and impact of COVID-19 lockdowns to the profile of physiochemical parameters in the influent of wastewater treatment plants (WWTPs) around Brisbane, Australia. One 24-hr composite influent sample was collected from 10 WWTPs and analyzed for a range of physiochemical parameters per week (i.e., chemical oxygen demand (COD), total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), ammonia, volatile suspended solid (VSS)) and per month (i.e., Ni and Cr) from 2012 to 2020, including the period of COVID-19 lockdowns in the region. The catchments studied were urban, with a mix of domestic and industrial activities contributing towards the contaminant profile. Statistical analysis identified that industrial and commercial land use, as well as population size had a large impact to the parameter loads and profile. Per capita mass loads of Cr in one catchment were 100 times higher than in others from one industrial point source. TP demonstrated a potential monotonic decrease over time due to practical reduction policies that have been implemented for phosphorous content in household detergents, except for one catchment where trade waste from food manufacturing industries contributed to an overall increase of 6.9%/year TP. The COVID-19 lockdown (March-April 2020) posed different impact on different catchments, either decrease (7-61%) or increase (2-40%) of most parameter loads (e.g., COD, TOC, TN, TP, VSS, Ammonia), which was likely driven by catchment characteristics (i.e., the proportion of residential, commercial, and industrial land uses). This study enhances our understanding of spatiotemporal trend of contaminants in the catchments for further effective source control.

Assessing the Impact of Traffic Emissions on Fine Particulate Matter and Carbon Monoxide Levels in Hanoi through COVID-19 Social Distancing Periods

Hanoi, Vietnam, is usually ranked as one of the most polluted capital cities in terms of air quality, particularly PM2.5. However, there has not been enough data to determine the main source of this pollution. In this study, we utilized the rare opportunity of the COVID-19 social distancing to assess the contribution of traffic emission to PM2.5 and CO levels when traffic volume was reduced significantly in Hanoi. Hourly PM2.5 and CO concentrations were measured from nine urban and traffic monitoring stations during pre-, soft, hard, and post-social distancing periods. As a result, we observed large reductions in both PM2.5 and CO levels during social distancing periods. PM2.5 concentrations were 14–18% lower during the social distancing than before this period, while CO concentrations had a more considerable drop by 28–41%. It is known that meteorological conditions can have significant effects on the ambient levels of air pollutants. To overcome this challenge, weather normalized concentrations of those pollutants were estimated using the random forest model, a machine learning technique. The normalized weather concentrations showed smaller reductions by 7–10% for PM2.5 and 5–11% for CO, indicating the presence of favorable weather conditions for better air quality during the social distancing period. In further analysis, the apparent improvement of air quality in Hanoi during the social distancing period was in line with reducing traffic emissions while emissions from coal-fired power plants remained relatively stable.