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Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high.

ABSTRACT: Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this limitation. Here we investigated how the dynamics of new COVID-19 infections estimated based on wastewater monitoring or confirmed cases compare to true COVID-19 incidence dynamics. We focused on the first pandemic wave in Switzerland (February to April, 2020), when test positivity ranged up to 26%. SARS-CoV-2 RNA loads were determined 2-4 times per week in three Swiss wastewater treatment plants (Lugano, Lausanne and Zurich). Wastewater and case data were combined with a shedding load distribution and an infection-to-case confirmation delay distribution, respectively, to estimate infection incidence dynamics. Finally, the estimates were compared to reference incidence dynamics determined by a validated compartmental model. Incidence dynamics estimated based on wastewater data were found to better track the timing and shape of the reference infection peak compared to estimates based on confirmed cases. In contrast, case confirmations provided a better estimate of the subsequent decline in infections. Under a regime of high-test positivity rates, WBE thus provides critical information that is complementary to clinical data to monitor the pandemic trajectory.

SUBMITTER: Fernandez-Cassi X

PROVIDER: S-EPMC8126994 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high.

Fernandez-Cassi Xavier X Scheidegger Andreas A Bänziger Carola C Cariti Federica F Tuñas Corzon Alex A Ganesanandamoorthy Pravin P Lemaitre Joseph C JC Ort Christoph C Julian Timothy R TR Kohn Tamar T

Water research 20210517

Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this limitation. Here we investigated how the dynamics of new COVID-19 infections estimated based on wastewater monitoring or confirmed cases compare to true COVID-19 incidence dynamics. We focused on the first pandemic wave in Switzerland (February t ...[more]

PMID: 34048984

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Project description:BackgroundHigh altitude settings in Eastern Africa have been reported to experience increased malaria burden due to vector habitat expansion. This study explored possible associations between malaria test positivity rates and its predictors including malaria control measures and meteorological factors at a high-altitude, low malaria transmission setting, south of Mount Kilimanjaro.MethodsMalaria cases reported at the Tanganyika Plantation Company (TPC) hospital's malaria registers, meteorological data recorded at TPC sugar factory and data on bed nets distributed in Lower Moshi from 2009 to 2018 were studied. Correlation between bed nets distributed and malaria test positivity rates were explored by using Pearson correlation analysis and the associations between malaria test positivity rates and demographic and meteorological variables were determined by logistic regression and negative binomial regression analyses, respectively.ResultsMalaria cases reported at TPC hospital ranged between 0.48 and 2.26% per year and increased slightly at the introduction of malaria rapid diagnostic tests. The risk of testing positive for malaria were significantly highest among individuals aged between 6 and 15 years (OR = 1.65; 1.65 CI = 1.28-2.13; p = 0.001) and 16-30 years (OR = 1.49; CI = 1.17-1.89; p = 0.001) and when adjusted for age, the risk were significantly higher among male individuals when compared to female individuals (OR = 1.54; 1.00-1.31; p = 0.044). Malaria test positivity rates were positively associated with average monthly minimum temperatures and negatively associated with average monthly maximum temperatures (incidence rate ratio (IRR) = 1.37, 95% confidence interval (CI) = 1.05-1.78, p = 0.019 and IRR = 0.72, 95% CI = 0.58-0.91, p = 0.005, respectively). When analysed with one month lag for predictor variables, malaria test positivity rates were still significantly associated with average monthly minimum and maximum temperatures (IRR = 1.67, 95% CI = 1.28-2.19, p = 0.001 and IRR = 0.68, 95% CI = 0.54-0.85, p = 0.001, respectively). Average monthly rainfall and relative humidity with or without a one month lag was not associated with malaria test positivity rates in the adjusted models. Explopring possible associations between distribution of long-lasting insecticidal nets, (LLINs) and malaria test positivity rates showed no apparent correlation between numbers of LLINs distributed in a particular year and malaria test positivity rates.ConclusionIn Lower Moshi, the risk of being tested positive for malaria was highest for older children and male individuals. Higher minimum and lower maximum temperatures were the strongest climatic predictors for malaria test positivity rates. In areas with extensive irrigation activity as in Lower Moshi, vector abundance and thus malaria transmission may be less dependent on rainfall patterns and humidity. Mass distribution of LLINs did not have an effect in this area with already very low malaria transmission.

Project description:Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) wastewater-based epidemiology (WBE) has been applied as a complementary approach for spatial tracking of coronavirus disease 2019 cases (COVID-19) as well as early warning of the occurrence of infected populations. The present study presents the result of the monitoring of sanitary sewerage in the municipality of Niterói, a metropolitan region of Rio de Janeiro (Brazil) and its use as a complementary indicator in the surveillance of COVID-19 cases, thus assisting actions of public health from local authorities. Twelve composite raw sewage samples were weekly collected from two wastewater treatment plants (WWTPs) and alternately from 17 sewer pipes (SP) from surrounding neighbourhoods and slums throughout 20 weeks (April 15th to August 25th, 2020). Two hundred twenty-three samples were concentrated using the ultracentrifugation-based method and SARS-CoV-2 RNA detected and quantified by RT-qPCR using primers and probe targeting the N2 genome. SARS-CoV-2 RNA was detected in 84.3% (188/223) of samples with a positive rate ranging from 42% (5/12) in the first week of monitoring to 100% during the peak of epidemic with viral concentration ranging from 3.1 to 7.1 log10 genome copies /100 mL throughout the studied period. Positive rates were higher in WWTPs when compared to SP, being useful tool for monitoring trends in the evolution of the COVID-19 curve, while SP data were more effective when health public interventions were needed. Whole-genome sequencing using Illumina MiSeq System confirmed the lineage of three genomes as B.1.1.33 (clade G) containing the nucleotide substitutions observed in strains that circulate in the Rio de Janeiro during the period of this study. In addition, geoprocessing tool was used to build heat maps based on SARS-CoV-2 data from sewage samples, which were weekly updated and available online to the general population as an indicator of the ongoing epidemic situation in Niterói city, raising public awareness.

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Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high.

Publications

Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high.

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