Longitudinal and Long-Term Wastewater Surveillance for COVID-19: Infection Dynamics and Zoning of Urban Community.

Wastewater-based epidemiology (WBE) is emerging as a potential approach to study the infection dynamics of SARS-CoV-2 at a community level. Periodic sewage surveillance can act as an indicative tool to predict the early surge of pandemic within the community and understand the dynamics of infection and, thereby, facilitates for proper healthcare management. In this study, we performed a long-term epidemiological surveillance to assess the SARS-CoV-2 spread in domestic sewage over one year (July 2020 to August 2021) by adopting longitudinal sampling to represent a selected community (~2.5 lakhs population). Results indicated temporal dynamics in the viral load. A consistent amount of viral load was observed during the months from July 2020 to November 2020, suggesting a higher spread of the viral infection among the community, followed by a decrease in the subsequent two months (December 2020 and January 2021). A marginal increase was observed during February 2021, hinting at the onset of the second wave (from March 2021) that reached it speak in April 2021. Dynamics of the community infection rates were calculated based on the viral gene copies to assess the severity of COVID-19 spread. With the ability to predict the infection spread, longitudinal WBE studies also offer the prospect of zoning specific areas based on the infection rates. Zoning of the selected community based on the infection rates assists health management to plan and manage the infection in an effective way. WBE promotes clinical inspection with simultaneous disease detection and management, in addition to an advance warning signal to anticipate outbreaks, with respect to the slated community/zones, to tackle, prepare for and manage the pandemic.

Quantitative SARS-CoV-2 Viral-Load Curves in Paired Saliva Samples and Nasal Swabs Inform Appropriate Respiratory Sampling Site and Analytical Test Sensitivity Required for Earliest Viral Detection.

Early detection of SARS-CoV-2 infection is critical to reduce asymptomatic and presymptomatic transmission, curb the spread of variants, and maximize treatment efficacy. Low-analytical-sensitivity nasal-swab testing is commonly used for surveillance and symptomatic testing, but the ability of these tests to detect the earliest stages of infection has not been established. In this study, conducted between September 2020 and June 2021 in the greater Los Angeles County, California, area, initially SARS-CoV-2-negative household contacts of individuals diagnosed with COVID-19 prospectively self-collected paired anterior-nares nasal-swab and saliva samples twice daily for viral-load quantification by high-sensitivity reverse-transcription quantitative PCR (RT-qPCR) and digital-RT-PCR assays. We captured viral-load profiles from the incidence of infection for seven individuals and compared diagnostic sensitivities between respiratory sites. Among unvaccinated persons, testing saliva with a high-analytical-sensitivity assay detected infection up to 4.5 days before viral loads in nasal swabs reached concentrations detectable by low-analytical-sensitivity nasal-swab tests. For most participants, nasal swabs reached higher peak viral loads than saliva but were undetectable or at lower loads during the first few days of infection. High-analytical-sensitivity saliva testing was most reliable for earliest detection. Our study illustrates the value of acquiring early (within hours after a negative high-sensitivity test) viral-load profiles to guide the appropriate analytical sensitivity and respiratory site for detecting earliest infections. Such data are challenging to acquire but critical to designing optimal testing strategies with emerging variants in the current pandemic and to respond to future viral pandemics.

Bacterial pulmonary superinfections are associated with longer duration of ventilation in critically ill COVID-19 patients.

The impact of secondary bacterial infections (superinfections) in coronavirus disease 2019 (COVID-19) is not well understood. In this prospective, monocentric cohort study, we aim to investigate the impact of superinfections in COVID-19 patients with acute respiratory distress syndrome. Patients are assessed for concomitant microbial infections by longitudinal analysis of tracheobronchial secretions, bronchoalveolar lavages, and blood cultures. In 45 critically ill patients, we identify 19 patients with superinfections (42.2%). Superinfections are detected on day 10 after intensive care admission. The proportion of participants alive and off invasive mechanical ventilation at study day 28 (ventilator-free days [VFDs] at 28 days) is substantially lower in patients with superinfection (subhazard ratio 0.37; 95% confidence interval [CI] 0.15-0.90; p = 0.028). Patients with pulmonary superinfections have a higher incidence of bacteremia, virus reactivations, yeast colonization, and required intensive care treatment for a longer time. Superinfections are frequent and associated with reduced VFDs at 28 days despite a high rate of empirical antibiotic therapy.