tetano
Editor, Senior Moderator
Front Public Health
. 2023 Jul 27;11:1141136.
doi: 10.3389/fpubh.2023.1141136. eCollection 2023. An alternative method for monitoring and interpreting influenza A in communities using wastewater surveillance
Tomas de Melo[SUP] 1 [/SUP], Golam Islam[SUP] 1 [/SUP], Denina B D Simmons[SUP] 1 [/SUP], Jean-Paul Desaulniers[SUP] 1 [/SUP], Andrea E Kirkwood[SUP] 1 [/SUP]
Affiliations
Seasonal influenza is an annual public health challenge that strains healthcare systems, yet population-level prevalence remains under-reported using standard clinical surveillance methods. Wastewater surveillance (WWS) of influenza A can allow for reliable flu surveillance within a community by leveraging existing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) WWS networks regardless of the sample type (primary sludge vs. primary influent) using an RT-qPCR-based viral RNA detection method for both targets. Additionally, current influenza A outbreaks disproportionately affect the pediatric population. In this study, we show the utility of interpreting influenza A WWS data with elementary student absenteeism due to illness to selectively interpret disease spread in the pediatric population. Our results show that the highest statistically significant correlation (R[SUB]s[/SUB] = 0.96, p = 0.011) occurred between influenza A WWS data and elementary school absences due to illness. This correlation coefficient is notably higher than the correlations observed between influenza A WWS data and influenza A clinical case data (R[SUB]s[/SUB] = 0.79, p = 0.036). This method can be combined with a suite of pathogen data from wastewater to provide a robust system for determining the causative agents of diseases that are strongly symptomatic in children to infer pediatric outbreaks within communities.
Keywords: RT-qPCR; SARS-CoV-2; influenza A; student absenteeism; wastewater.
. 2023 Jul 27;11:1141136.
doi: 10.3389/fpubh.2023.1141136. eCollection 2023. An alternative method for monitoring and interpreting influenza A in communities using wastewater surveillance
Tomas de Melo[SUP] 1 [/SUP], Golam Islam[SUP] 1 [/SUP], Denina B D Simmons[SUP] 1 [/SUP], Jean-Paul Desaulniers[SUP] 1 [/SUP], Andrea E Kirkwood[SUP] 1 [/SUP]
Affiliations
- PMID: 37575124
- PMCID: PMC10413874
- DOI: 10.3389/fpubh.2023.1141136
Seasonal influenza is an annual public health challenge that strains healthcare systems, yet population-level prevalence remains under-reported using standard clinical surveillance methods. Wastewater surveillance (WWS) of influenza A can allow for reliable flu surveillance within a community by leveraging existing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) WWS networks regardless of the sample type (primary sludge vs. primary influent) using an RT-qPCR-based viral RNA detection method for both targets. Additionally, current influenza A outbreaks disproportionately affect the pediatric population. In this study, we show the utility of interpreting influenza A WWS data with elementary student absenteeism due to illness to selectively interpret disease spread in the pediatric population. Our results show that the highest statistically significant correlation (R[SUB]s[/SUB] = 0.96, p = 0.011) occurred between influenza A WWS data and elementary school absences due to illness. This correlation coefficient is notably higher than the correlations observed between influenza A WWS data and influenza A clinical case data (R[SUB]s[/SUB] = 0.79, p = 0.036). This method can be combined with a suite of pathogen data from wastewater to provide a robust system for determining the causative agents of diseases that are strongly symptomatic in children to infer pediatric outbreaks within communities.
Keywords: RT-qPCR; SARS-CoV-2; influenza A; student absenteeism; wastewater.