ABSTRACT
Wastewater-based epidemiology (WBE) has emerged as a key method for continuous monitoring of COVID-19 prevalence including circulating SARS-CoV-2 lineages. WBE addresses limitations of traditional clinical COVID-19 surveillance such as clinical test availability, fluctuating testing rates and increased reliance on rapid antigen tests. Our study in Perth, Western Australia, found a significant positive correlation between SARS-CoV-2 concentrations in wastewater and clinical PCR positivity rates (rs = 0.772; p < 0.001) over an 18-month period that included four successive COVID-19 waves. A strong positive correlation was apparent between the proportions of SARS-CoV-2 lineages in wastewater and clinical cases within the same region (rs = 0.728; p < 0.001), including earlier detection of Omicron and recombinant lineages in wastewater before clinical case confirmation. The successful integration of WBE with healthcare data underscores its critical role in enhancing public health decision-making and pandemic management. This approach not only demonstrates the value of WBE in current global health surveillance efforts but also highlights the potential of WBE to address future public health challenges, as a comprehensive disease monitoring and response approach.
Subject(s)
COVID-19ABSTRACT
Objective: To characterise Long COVID in a highly vaccinated population infected by Omicron. Design: Follow-up survey of persons testing positive for SARS-CoV-2 in Western Australia, 16 July-3 August 2022. Setting: Community Participants: 22,744 persons with COVID-19 who had agreed to participate in research at the time of diagnosis were texted a survey link 90 days later; non-responders were telephoned. Post stratification weights were applied to responses from 11,697 (51.4%) participants, 94.0% of whom had received >= 3 vaccine doses. Main outcome measures: Prevalence of Long COVID - defined as reporting new or ongoing COVID-19 illness-related symptoms or health issues 90 days post diagnosis; associated health care utilisation, reductions in work/study and risk factors were assessed using log-binomial regression. Results: 18.2% (n=2,130) of respondents met case definition for Long COVID. Female sex, being 50-69 years of age, pre-existing health issues, residing in a rural or remote area, and receiving fewer vaccine doses were significant independent predictors of Long COVID (p < 0.05). Persons with Long COVID reported a median of 6 symptoms, most commonly fatigue (70.6%) and difficulty concentrating (59.6%); 38.2% consulted a GP and 1.6% reported hospitalisation in the month prior to the survey due to ongoing symptoms. Of 1,778 respondents with Long COVID who were working/studying before their COVID-19 diagnosis, 17.9% reported reducing/discontinuing work/study. Conclusion: 90 days post Omicron infection, almost 1 in 5 respondents reported Long COVID symptoms; 1 in 15 of all persons with COVID-19 sought healthcare for associated health concerns >=2 months after the acute illness.