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Background <p>Many studies assessing urban air-pollution health impacts assign outdoor PM₂.₅ at a single residential address, ignoring children’s daily movements between home and school. This simplification may misclassify exposure and bias short-term risk estimates, potentially misguiding school-area prevention priorities.</p> Methods <p>Using 2,543 laboratory-confirmed influenza cases among school-aged children in Guangzhou (2014–2019) and hourly monitoring–derived PM₂.₅ concentration fields, we tested whether mobility-aware exposure assignment changes short-term PM₂.₅–influenza risk estimates. We constructed a residence-based model (RBM) and a multi-context activity-weighted model (MCAWM) that reallocates hourly PM₂.₅ across home, school, and street-network commute corridors using stylized school-day schedules and open-source street networks.</p> Results <p>Although RBM and MCAWM lag-0 daily PM₂.₅ estimates were highly correlated (<i>r</i> = 0.93), 15.8% of child-days differed by ≥ 10&#xa0;µg/m³. Per 10&#xa0;µg/m³, cumulative relative risks were 1.04 (95% CI: 1.02–1.06) for RBM and 1.10 (1.06–1.14) for MCAWM, with improved fit and slightly more persistent lag effects under MCAWM. The concentration-dependent difference in cumulative relative risk between MCAWM and RBM increased above ~ 20&#xa0;µg/m³, with a breakpoint near 45&#xa0;µg/m³ indicating more rapid RBM underestimation at higher concentrations. Stratification by school environment revealed the largest mobility gains in high-density, low-greenspace schools. Scenario-based population attributable fractions indicated that, at 50&#xa0;µg/m³, residence-only exposure would miss roughly 0.20 additional attributable cases per 1,000 children per season.</p> Conclusions <p>A synthetic “ground-truth” experiment and sensitivity analyses suggest these gains reflect structural reductions in exposure misclassification rather than model tuning. Aligning hourly PM₂.₅ with children’s home–school–commute activity spaces indicates that residence-only assignment tends to attenuate the estimated PM₂.₅–influenza relationship and can understate preventable burden, supporting scalable targeting of school-area interventions such as school greening, near-school traffic management, and lower-exposure commuting corridors.</p>

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Estimating PM₂.₅–influenza risk using home–school–commute exposure modeling from hourly monitoring data: schoolchildren in Guangzhou, China, 2014–2019

  • 期刊论文

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  • 发表日期：

    2026年4月9日

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  • Fengrui Jing,
  • Jinjing Hu,
  • Suhong Zhou,
  • Zihan Kan,
  • Guanhao He,
  • Jianxiong Hu,
  • Tao Liu,
  • Meiqi Zhang,
  • Lei Luo,
  • Mengmeng Ma,
  • Ziqiang Lin,
  • Sui Zhu,
  • Yanhui Liu,
  • Wenjun Ma

摘要

Background

Many studies assessing urban air-pollution health impacts assign outdoor PM₂.₅ at a single residential address, ignoring children’s daily movements between home and school. This simplification may misclassify exposure and bias short-term risk estimates, potentially misguiding school-area prevention priorities.

Methods

Using 2,543 laboratory-confirmed influenza cases among school-aged children in Guangzhou (2014–2019) and hourly monitoring–derived PM₂.₅ concentration fields, we tested whether mobility-aware exposure assignment changes short-term PM₂.₅–influenza risk estimates. We constructed a residence-based model (RBM) and a multi-context activity-weighted model (MCAWM) that reallocates hourly PM₂.₅ across home, school, and street-network commute corridors using stylized school-day schedules and open-source street networks.

Results

Although RBM and MCAWM lag-0 daily PM₂.₅ estimates were highly correlated (r = 0.93), 15.8% of child-days differed by ≥ 10 µg/m³. Per 10 µg/m³, cumulative relative risks were 1.04 (95% CI: 1.02–1.06) for RBM and 1.10 (1.06–1.14) for MCAWM, with improved fit and slightly more persistent lag effects under MCAWM. The concentration-dependent difference in cumulative relative risk between MCAWM and RBM increased above ~ 20 µg/m³, with a breakpoint near 45 µg/m³ indicating more rapid RBM underestimation at higher concentrations. Stratification by school environment revealed the largest mobility gains in high-density, low-greenspace schools. Scenario-based population attributable fractions indicated that, at 50 µg/m³, residence-only exposure would miss roughly 0.20 additional attributable cases per 1,000 children per season.

Conclusions

A synthetic “ground-truth” experiment and sensitivity analyses suggest these gains reflect structural reductions in exposure misclassification rather than model tuning. Aligning hourly PM₂.₅ with children’s home–school–commute activity spaces indicates that residence-only assignment tends to attenuate the estimated PM₂.₅–influenza relationship and can understate preventable burden, supporting scalable targeting of school-area interventions such as school greening, near-school traffic management, and lower-exposure commuting corridors.