tetano
Editor, Senior Moderator
J Water Health
. 2026 Jun;24(6):773-783.
doi: 10.2166/wh.2026.223. Epub 2026 May 18.
Community-level wastewater influenza concentrations and school attendance in Jefferson County, Kentucky (2022-2025)
Anna Dusterhoff[SUP] 1 [/SUP], Lauren B Anderson[SUP] 1 [/SUP], Rochelle H Holm[SUP] 2 [/SUP], Emily Reece[SUP] 3 [/SUP], Eva Stone[SUP] 3 [/SUP], Ted Smith[SUP] 1 [/SUP]
Affiliations
Community-transmitted seasonal infectious diseases pose a significant challenge to school systems across the nation. School attendance is central to student learning progress and is a key public health indicator. We aimed to evaluate the incremental explanatory value of community-level seasonal influenza wastewater concentrations for estimating school absenteeism within the corresponding geographic sewershed in Louisville, Kentucky (USA). We used community wastewater seasonal influenza concentrations from a catchment area that geographically encompassed 51 public elementary, middle, and high schools. These data were compared with daily school-level attendance records provided by Jefferson County Public Schools for three academic years (2022-2025). Two random forest models were developed that incorporated community influenza A wastewater concentrations, environmental variables (e.g., rainfall and maximum temperature), school-level attendance, and total enrollment to predict attendance outcomes. Across the sewershed, the all-schools model (N = 51) performed well (training R[SUP]2[/SUP] = 0.94, testing R[SUP]2[/SUP] = 0.60, and MAE = 2.88); however, the high school-only model (N = 7) performed better (training R[SUP]2[/SUP] = 0.98, testing R[SUP]2[/SUP] = 0.86, and MAE = 3.22). Our findings present a preliminary approach for using wastewater-based epidemiology and machine learning to enhance early-warning capacity and inform health-supportive responses across educational settings.
Keywords: influenza; random forest; schools; sewershed; wastewater-based epidemiology.
. 2026 Jun;24(6):773-783.
doi: 10.2166/wh.2026.223. Epub 2026 May 18.
Community-level wastewater influenza concentrations and school attendance in Jefferson County, Kentucky (2022-2025)
Anna Dusterhoff[SUP] 1 [/SUP], Lauren B Anderson[SUP] 1 [/SUP], Rochelle H Holm[SUP] 2 [/SUP], Emily Reece[SUP] 3 [/SUP], Eva Stone[SUP] 3 [/SUP], Ted Smith[SUP] 1 [/SUP]
Affiliations
- PMID: 42378415
- DOI: 10.2166/wh.2026.223
Community-transmitted seasonal infectious diseases pose a significant challenge to school systems across the nation. School attendance is central to student learning progress and is a key public health indicator. We aimed to evaluate the incremental explanatory value of community-level seasonal influenza wastewater concentrations for estimating school absenteeism within the corresponding geographic sewershed in Louisville, Kentucky (USA). We used community wastewater seasonal influenza concentrations from a catchment area that geographically encompassed 51 public elementary, middle, and high schools. These data were compared with daily school-level attendance records provided by Jefferson County Public Schools for three academic years (2022-2025). Two random forest models were developed that incorporated community influenza A wastewater concentrations, environmental variables (e.g., rainfall and maximum temperature), school-level attendance, and total enrollment to predict attendance outcomes. Across the sewershed, the all-schools model (N = 51) performed well (training R[SUP]2[/SUP] = 0.94, testing R[SUP]2[/SUP] = 0.60, and MAE = 2.88); however, the high school-only model (N = 7) performed better (training R[SUP]2[/SUP] = 0.98, testing R[SUP]2[/SUP] = 0.86, and MAE = 3.22). Our findings present a preliminary approach for using wastewater-based epidemiology and machine learning to enhance early-warning capacity and inform health-supportive responses across educational settings.
Keywords: influenza; random forest; schools; sewershed; wastewater-based epidemiology.