Assessing the Impact of Wastewater Flow Rates on SARS‐CoV‐2 RNA Detection: Insights for Environmental Surveillance and Policymaking

ABSTRACT Wastewater‐based epidemiology (WBE) has been widely applied for SARS‐CoV‐2 surveillance. Yet, operational parameters such as influent flow rate and sewer system characteristics may reflect underlying hydraulic variability relevant to detection performance, raising questions about the representativeness of results from small and medium‐sized plants. We conducted a systematic meta‐analysis of 10 published studies assessing SARS‐CoV‐2 RNA detection across wastewater treatment plants of different sizes and flow ranges. Data were extracted into 2 × 2 tables and analyzed in R using the meta and metafor packages. Odds ratios (ORs) were pooled with Mantel–Haenszel random‐effects models and DerSimonian–Laird τ 2 estimation. Subgroup analyses compared studies from developed versus emerging economies, meta‐regression tested population size as a moderator, and publication bias was evaluated with funnel plots and Egger's test. The overall pooled OR was 2.08 (95% CI: 0.99–4.37, p = 0.053; I 2 = 82.3%), indicating a non‐significant trend toward higher detection at higher flow rates. Subgroup analyses showed similar pooled effects across developed and emerging economies, though heterogeneity was lower in emerging settings. Meta‐regression revealed no significant association between population size and detection (slope = 0.29, p = 0.52). Funnel plots were relatively symmetric, and Egger's test did not indicate significant publication bias ( p = 0.169). Overall, these findings suggest that influent flow rate is not significantly associated with the probability of SARS‐CoV‐2 detection in WBE studies, supporting the inclusion of small and medium‐sized treatment plants in surveillance networks. At the same time, the concentration of studies in high‐income countries highlights inequities in the global WBE literature and in site deployment, with vulnerable populations often underrepresented. Expanding WBE infrastructure in underserved regions is necessary to ensure equitable and representative surveillance capacity.

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Publication Details

Journal
Environmental Quality Management
Published
2026-03-27
DOI
https://doi.org/10.1002/tqem.70341
Primary Topic
SARS-CoV-2 detection and testing
Type
article
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article

Assessing the Impact of Wastewater Flow Rates on SARS‐CoV‐2 RNA Detection: Insights for Environmental Surveillance and Policymaking

Nédia de Castilhos Ghisi, Naiana Cristine Gabiatti, Deborah Catharine de Assis Leite, Betty Cristiane Kuhn et al.
Environmental Quality Management
SARS-CoV-2 detection and testing
article

Assessing the Impact of Wastewater Flow Rates on SARS‐CoV‐2 RNA Detection: Insights for Environmental Surveillance and Policymaking

Nédia de Castilhos Ghisi, Naiana Cristine Gabiatti, Deborah Catharine de Assis Leite, Betty Cristiane Kuhn, Felipe Beijamini, A. C. Trentin, Flávia Regina Oliveira de Barros, Juliana Morini Küpper Cardoso, Andre Felipe Bendix, Simone N. Wendt
article en

Abstract

ABSTRACT Wastewater‐based epidemiology (WBE) has been widely applied for SARS‐CoV‐2 surveillance. Yet, operational parameters such as influent flow rate and sewer system characteristics may reflect underlying hydraulic variability relevant to detection performance, raising questions about the representativeness of results from small and medium‐sized plants. We conducted a systematic meta‐analysis of 10 published studies assessing SARS‐CoV‐2 RNA detection across wastewater treatment plants of different sizes and flow ranges. Data were extracted into 2 × 2 tables and analyzed in R using the meta and metafor packages. Odds ratios (ORs) were pooled with Mantel–Haenszel random‐effects models and DerSimonian–Laird τ 2 estimation. Subgroup analyses compared studies from developed versus emerging economies, meta‐regression tested population size as a moderator, and publication bias was evaluated with funnel plots and Egger's test. The overall pooled OR was 2.08 (95% CI: 0.99–4.37, p = 0.053; I 2 = 82.3%), indicating a non‐significant trend toward higher detection at higher flow rates. Subgroup analyses showed similar pooled effects across developed and emerging economies, though heterogeneity was lower in emerging settings. Meta‐regression revealed no significant association between population size and detection (slope = 0.29, p = 0.52). Funnel plots were relatively symmetric, and Egger's test did not indicate significant publication bias ( p = 0.169). Overall, these findings suggest that influent flow rate is not significantly associated with the probability of SARS‐CoV‐2 detection in WBE studies, supporting the inclusion of small and medium‐sized treatment plants in surveillance networks. At the same time, the concentration of studies in high‐income countries highlights inequities in the global WBE literature and in site deployment, with vulnerable populations often underrepresented. Expanding WBE infrastructure in underserved regions is necessary to ensure equitable and representative surveillance capacity.

Environmental Quality ManagementVol. 35(4)
Universidade Tecnológica Federal do Paraná (BR), Purdue University West Lafayette (US), Universidade Federal da Fronteira Sul (BR)
Clean water and sanitation
Openalex Percentile: Top 6%
SARS-CoV-2 detection and testing
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