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Wastewater surveillance for COVID-19 response at multiple geographic scales: Aligning wastewater and clinical results at the census-block level and addressing pervasiveness of qPCR non-detects
Hannah Safford; Rogelio E. Zuniga-Montanez; Minji Kim; Xiaoliu Wu; Lifeng Wei; James Sharpnack; Karen Shapiro; Heather Bischel.
Affiliation
  • Hannah Safford; University of California, Davis
  • Rogelio E. Zuniga-Montanez; University of California, Davis
  • Minji Kim; University of California, Davis
  • Xiaoliu Wu; University of California, Davis
  • Lifeng Wei; University of California, Davis
  • James Sharpnack; University of California, Davis
  • Karen Shapiro; University of California, Davis
  • Heather Bischel; University of California, Davis
Preprint in English | medRxiv | ID: ppmedrxiv-22269911
ABSTRACT
Wastewater surveillance is a useful complement to clinical testing for managing COVID-19. While good agreement has been found between community-scale wastewater and clinical data, little is known about sub-community relationships between the two data types. Moreover, effects of non-detects in qPCR wastewater data have been largely overlooked. We used data collected from September 2020-June 2021 in Davis, California (USA) to address these gaps. By applying a predictive probability model to spatially disaggregate clinical results, we compared wastewater and clinical data at the community scale, in 16 sampling zones isolating city sub-regions, and in seven zones isolating high-priority building complexes or neighborhoods. We found reasonable agreement between wastewater and clinical data at all scales. Greater activity (i.e., more frequent detections) in clinical data tended to be mirrored in wastewater data. Small, isolated clinical-data spikes were often matched as well. We also developed a method for handling such non-detects using multiple imputation and compared results to (i) single imputation using half the qPCR limit of detection, (ii) single imputation using maximum qPCR cycle number, and (iii) non-detect censoring. Apparent wastewater trends were significantly influenced by non-detect handling. Multiple imputation improved correlation relative to single imputation, though not necessarily relative to censoring. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/22269911v1_ufig1.gif" ALT="Figure 1"> View larger version (31K) org.highwire.dtl.DTLVardef@5a57f5org.highwire.dtl.DTLVardef@144cf73org.highwire.dtl.DTLVardef@8fa56borg.highwire.dtl.DTLVardef@b52587_HPS_FORMAT_FIGEXP M_FIG C_FIG
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study Language: English Year: 2022 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study Language: English Year: 2022 Document type: Preprint
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