RESUMO
We present and demonstrate a quantitative statistical linear trend analysis (QTA) approach to analyze and interpret SARS-CoV-2 RNA wastewater surveillance results concurrently with clinical case data. This demonstration is based on the work completed under the Ontario (Canada) Wastewater Surveillance Initiative (WSI) by two laboratories in four large sewersheds within the Toronto Public Health (TPH) jurisdiction. The sewersheds were sampled over a 9-month period and data were uploaded to the Ontario Wastewater Surveillance Data and Visualization Hub (Ontario Dashboard) along with clinical case counts, both on a sewershed-specific basis. The data from the last 5-months, representing a range of high and low cases, was used for this demonstration. The QTA was conducted on a sewershed specific approach using the recommendations for public health interpretation and use of wastewater surveillance data by the United States Centers for Disease Control and Prevention (US CDC). The interpretation of the QTA results was based on the integration of both clinical and wastewater virus signals using an integration matrix in an interim draft guide by the Public Health Agency of Canada (PHAC). The key steps in the QTA consisted of (i) the calculation of Pepper Mild Mottle Virus (PMMoV), flow and flow-PMMoV-normalized virus loads; (ii) computation of the linear trends including interval estimation to identify the key inflection points using a segmented linear regression method and (iii) integrated interpretations based on consideration of both the cases and wastewater signals, as well as end user actionability. This approach is considered a complementary tool to commonly used qualitative analyses of SARS-CoV-2 RNA in wastewater and is intended to directly support public health decisions using a systematic quantitative approach.
