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Review 2: "United States Influenza 2022-2023 Season Characteristics as Inferred from Wastewater Solids, Influenza Hospitalization and Syndromic Data"

Reviewers agreed that this is a strong preprint with important public health implications and well-detailed, appropriate methods.

Published onOct 23, 2023
Review 2: "United States Influenza 2022-2023 Season Characteristics as Inferred from Wastewater Solids, Influenza Hospitalization and Syndromic Data"
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key-enterThis Pub is a Review of
United States influenza 2022-2023 season characteristics as inferred from wastewater solids, influenza hospitalization and syndromic data
United States influenza 2022-2023 season characteristics as inferred from wastewater solids, influenza hospitalization and syndromic data
Description

Abstract Influenza A virus (IAV) causes significant morbidity and mortality in the United States and has pandemic potential. Identifying IAV epidemic patterns is essential to inform the timing of vaccines and non-pharmaceutical interventions. In a prospective, longitudinal study design, we measured IAV RNA in wastewater settled solids at 163 wastewater treatment plants across 33 states to characterize the 2022-2023 influenza season at the state, health and human services (HHS) regional, and national scales. Influenza season onset, offset, duration, peak, and intensity using IAV RNA in wastewater were compared with those determined using laboratory-confirmed influenza hospitalization rates and outpatient visits for influenza-like illness (ILI). The onset for HHS regions as determined by IAV RNA in wastewater roughly corresponded with those determined using ILI when the annual geometric mean of IAV RNA concentration was used as baseline (i.e., the threshold that triggers onset), although offsets between the two differed. IAV RNA in wastewater provided early warning of onset, compared to the ILI estimate, when the baseline was set at twice the limit of IAV RNA detection in wastewater. Peak when determined by IAV RNA in wastewater generally preceded peak determined by IAV hospitalization rate by two weeks or less. Wastewater settled solids data is an IAV-specific indicator that can be used to augment clinical surveillance for seasonal influenza epidemic timing and intensity.

RR:C19 Evidence Scale rating by reviewer:

  • Strong. The main study claims are very well-justified by the data and analytic methods used. There is little room for doubt that the study produced has very similar results and conclusions as compared with the hypothetical ideal study. The study’s main claims should be considered conclusive and actionable without reservation.

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Review:

Wastewater surveillance is a valuable epidemiological tool to enhance influenza surveillance, particularly in situations where multiple respiratory diseases, such as COVID-19, Influenza, and RSV, are concurrently circulating in communities. The authors of this study concluded that the concentration of Influenza A virus RNA in wastewater-settled solids can complement clinical surveillance, providing insights into the timing and intensity of the seasonal influenza epidemic in the US. 

The reviewer strongly supports the conclusion made by the authors in the present study. The authors analyzed Influenza A virus (IAV) RNA concentration in 18,590 wastewater-settled solids, and their methodology and interpretation are robust. There are several strengths to this study. Firstly, the data on IAV RNA concentration is highly reliable. The sample size is likely the largest among previous studies on wastewater surveillance, and the samples were collected across the US. Their wastewater sample processing protocol is well-documented in multiple peer-reviewed journal articles, and thorough quality assurance and quality control (QA/QC) measures were conducted. Secondly, the approach to defining duration and intensity using wastewater surveillance is reasonable. The authors used public health authorities as a benchmark to establish a baseline and create aggregated data for wastewater surveillance, facilitating comparisons between IAV RNA concentrations and clinical indicators such as hospitalization rates or cases of influenza-like illness (ILI). Thirdly, the authors explicitly acknowledge the limitations of their findings. They point out that wastewater samples were not collected from some states including Florida (FL) and Texas (TX), which might exhibit early-season onsets. Additionally, their data covers only one year of the influenza epidemic season. However, these limitations are expected to be addressed as more samples are collected from additional wastewater treatment plants over a longer period. Given that determining the correct baseline is critical for using wastewater-based epidemiology in influenza surveillance, this manuscript would have a more practical implication if the authors explored more multiplication factors of minimum value (3x or 4x the lowest detectable concentration) to determine the baseline since the current baseline with 2x seems to provide too conservative onset time.

Comments
6
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Gwen Simmons:

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Julia Kassen:

One of the key strengths highlighted is the comprehensive approach to correlating wastewater data with clinical indicators such as hospitalization rates and influenza-like illness (ILI), which strengthens the validity of the study's conclusions. The reviewer also appreciates the authors' transparency regarding the study’s limitations, such as the lack of coverage from certain states like Florida and Texas, and the one-year time frame of the data.

A constructive suggestion is made regarding the baseline for determining the onset of influenza activity in the wastewater, proposing that using a higher multiplication factor (3x or 4x) could yield more accurate timing of the epidemic onset, as the current 2x baseline may be too conservative.

Overall, the reviewer’s assessment strongly supports the study’s claims, indicating that the findings are robust, actionable, and valuable for improving influenza surveillance in the future.

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Coral Sutton:

The study is praised for its large sample size and the reliability of the IAV RNA low’s adventures concentration data. The extensive geographical coverage and robust methodology are highlighted as significant strengths.

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Allan Kutcher:

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ulna operating:

Because employing wastewater-based gorilla tag epidemiology relies on establishing the suitable baseline

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Jack Smith:

Tracking influenza through wastewater surveillance is crucial, especially during concurrent outbreaks. The study's robust analysis of Influenza A virus RNA in wastewater supports its conclusion on epidemic timing. The large, nationwide sample size adds strength. Despite acknowledged limitations, ongoing research may address gaps. Exploring alternative baseline factors could refine predictions. By the way, have you tried The Impossible Quiz. It's a fun challenge!