Challenges detecting SARS-CoV-2 in Costa Rican domestic wastewater and river water

This study presents the development of a SARS-CoV-2 detection method for domestic wastewater and river water in Costa Rica, a middle-income country in Central America. Over a three-year period (November to December 2020, July to November 2021, and June to October 2022), 80 composite wastewater samples (43 influent and 37 effluent) were collected from a Wastewater Treatment Plant (SJ-WWTP) located in San Jose, Costa Rica. Additionally, 36 river water samples were collected from the Torres River near the SJ-WWTP discharge site. A total of three protocols for SARS-CoV-2 viral concentration and RNA detection and quantification were analyzed. Two protocols using adsorption-elution with PEG precipitation (Protocol A and B, differing in the RNA extraction kit; n = 82) were used on wastewater samples frozen prior to concentration, while wastewater (n = 34) collected in 2022 were immediately concentrated using PEG precipitation. The percent recovery of Bovine coronavirus (BCoV) was highest using the Zymo Environ Water RNA (ZEW) kit with PEG precipitation executed on the same day as collection (mean 6.06 % & PLUSMN; 1.37 %). It was lowest when samples were frozen and thawed, and viruses were concentrated using adsorption-elution and PEG concentration methods using the PureLinkTM Viral RNA/DNA Mini (PLV) kit (protocol A; mean 0.48 % & PLUSMN; 0.23 %). Pepper mild mottle virus and Bovine coronavirus were used as process controls to understand the suitability and potentialimpact of viral recovery on the detection/quantification of SARS-CoV-2 RNA. Overall, SARS-CoV-2 RNA was detected in influent and effluent wastewater samples collected in 2022 but not in earlier years when the method was not optimized. The burden of SARS-CoV-2 at the SJ-WWTP decreased from week 36 to week 43 of 2022, coinciding with a decline in the national COVID-19 prevalence rate. Developing comprehensive nationwide surveillance programs for wastewater based epidemiology in low-middle-income countries involves significant technical and logistical challenges.