Dataset Information

SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

ABSTRACT: Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we use longitudinal wastewater analysis to track SARS-CoV-2 dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. Viral titers in wastewater increased exponentially from mid-March to mid-April, after which they began to decline. Viral titers in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral titers as a convolution of back-dated new clinical cases with the viral shedding function of an individual. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. Finally, we found that wastewater viral titers at the neighborhood level correlate better with demographic variables than with population size. This work suggests that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and may shed light on infection characteristics that are difficult to capture in clinical investigations, such as early viral shedding dynamics.

SUBMITTER: Wu F

PROVIDER: S-EPMC7325186 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

Wu Fuqing F Xiao Amy A Zhang Jianbo J Moniz Katya K Endo Noriko N Armas Federica F Bonneau Richard R Brown Megan A MA Bushman Mary M Chai Peter R PR Duvallet Claire C Erickson Timothy B TB Foppe Katelyn K Ghaeli Newsha N Gu Xiaoqiong X Hanage William P WP Huang Katherine H KH Lee Wei Lin WL Matus Mariana M McElroy Kyle A KA Nagler Jonathan J Rhode Steven F SF Santillana Mauricio M Tucker Joshua A JA Wuertz Stefan S Zhao Shijie S Thompson Janelle J Alm Eric J EJ

medRxiv : the preprint server for health sciences 20200706

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we use longitudinal wastewater analysis to track SARS-CoV-2 dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. Viral titers in wastewater increa ...[more]

PMID: 32607521

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Project description:Taking advantage of Estonia's small size and population, we have employed wastewater-based epidemiology approach to monitor the spread of SARS-CoV-2, releasing weekly nation-wide updates. In this study we report results obtained between August 2020 and December 2021. Weekly 24 h composite samples were collected from wastewater treatment plants of larger towns already covered 65% of the total population that was complemented up to 40 additional grab samples from smaller towns/villages and the specific sites of concern. The N3 gene abundance was quantified by RT-qPCR. The N3 gene copy number (concentration) in wastewater fluctuated in accordance with the SARS-CoV-2 spread within the total population, with N3 abundance starting to increase 1.25 weeks (9 days) (95% CI: [1.10, 1.41]) before a rise in COVID-19 positive cases. Statistical model between the load of virus in wastewater and number of infected people validated with the Alpha variant wave (B.1.1.17) could be used to predict the order of magnitude in incidence numbers in Delta wave (B.1.617.2) in fall 2021. Targeted testing of student dormitories, retirement and nursing homes and prisons resulted in successful early discovery of outbreaks. We put forward a SARS-CoV-2 Wastewater Index (SARS2-WI) indicator of normalized virus load as COVID-19 infection metric to complement the other metrics currently used in disease control and prevention: dynamics of effective reproduction number (Re), 7-day mean of new cases, and a sum of new cases within last 14 days. In conclusion, an efficient surveillance system that combines analysis of composite and grab samples was established in Estonia. There is considerable discussion how the viral load in wastewater correlates with the number of infected people. Here we show that this correlation can be found. Moreover, we confirm that an increased signal in wastewater is observed before the increase in the number of infections. The surveillance system helped to inform public health policy and place direct interventions during the COVID-19 pandemic in Estonia via early warning of epidemic spread in various regions of the country.

Project description:Over two years into the COVID-19 pandemic, it is apparent that some populations across the world are more susceptible than others to SARS-CoV-2 infection and spread. Understanding how populations with varying demographic patterns are impacted by COVID-19 may highlight which factors are most important in targeting to combat global suffering. The first objective of this study was to investigate the association of various socioeconomic status (SES) parameters and confirmed COVID-19 cases in the state of Ohio, USA. This study examines the largest and capital city of Ohio (Columbus) and various small-medium-sized communities. The second objective was to determine the relationship between SES parameters and community-level SARS-CoV-2 concentrations using municipal wastewater samples from each city's respective wastewater treatment plants from August 2020 to January 2021. SES parameters include population size, median income, poverty, race/ethnicity, education, health care access, types of COVID-19 testing sites, and social vulnerability index. Statistical analysis results show that confirmed (normalized and/or non-normalized) COVID-19 cases were negatively associated with White percentage and registered hospitals, and positively associated with registered physicians and various COVID-19 testing sites. Wastewater viral concentrations were negatively associated with poverty, and positively associated with median income, community health centers, and onsite rapid testing locations. Additional analyses conclude that population is a significant factor in determining COVID-19 cases and SARS-CoV-2 wastewater concentrations. Results indicate that community healthcare parameters relate to a negative health outcome (COVID-19) and that demographic parameters can be associated with community-level SARS-CoV-2 wastewater concentrations. As the first study that examines the association between socioeconomic parameters and SARS-CoV-2 wastewater concentrations as well as confirmed COVID-19 cases, it is apparent that social determinants have an impact in determining the health burden of small-medium sized Ohioan cities. This study design and innovative approach are scalable and applicable for endemic and pandemic surveillance across the world.

Dataset Information

SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

Publications

SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

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