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Background <p>Current respiratory virus surveillance relies primarily on medically attended, symptomatic cases, which may distort the true patterns of respiratory virus infection. Estimating the underlying respiratory viral infection patterns, regardless of the symptomatic status, may help us to better intervene and address issues of racial and ethnic health equity. We tested decedents from the Wayne County Medical Examiner’s Office (Wayne &amp; Monroe Counties, Michigan including Detroit) regardless of the cause of death.</p> Methods <p>Nasopharyngeal samples were collected from decedents at the Wayne County Medical Examiner’s Office between October 2020 and September 2022 and tested for a panel of respiratory viruses. We identified 3430 decedents with catchment addresses, which we linked to the social vulnerability index (SVI) and area deprivation index (ADI) through US Census tract/block. We evaluated non-linear associations between each of adenovirus (AdV), SARS-CoV-2, parainfluenza virus 2 (PIV2), rhinovirus (RV), and respiratory syncytial virus (RSV) prevalence and ADI, SVI, and SVI subthemes using splines in log-binomial regression models.</p> Results <p>There were few statistically significant associations observed between overall SVI or ADI and respiratory virus infection prevalence. However, RV was significantly associated with ADI, SVI, and most SVI subthemes. The SVI Minority Status and Language (MSL) subtheme was statistically significantly associated with the prevalence of AdV and RV (<i>p</i> &lt; 0.05) and associations with SARS-CoV-2 and RSV approached significance (<i>p</i> &lt; 0.10).</p> Conclusions <p>Our results suggest that the MSL subtheme of SVI may be the most informative community-level predictor of respiratory virus infections and could be used to prioritize health-equity-focused distribution of public health resources.</p>

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Associations Between Community Social Vulnerability or Socioeconomic Deprivation and Respiratory Virus Infection in Decedents in a Large, Urban Medical Examiner’s Office

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月20日

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  • Xinnuo Zhao,
  • Carl J. Schmidt,
  • Jon Zelner,
  • Emily T. Martin,
  • Marisa C. Eisenberg,
  • Paul R. Lephart,
  • Andrea Jaworski,
  • Allecia M. Wilson,
  • Andrew F. Brouwer

摘要

Background

Current respiratory virus surveillance relies primarily on medically attended, symptomatic cases, which may distort the true patterns of respiratory virus infection. Estimating the underlying respiratory viral infection patterns, regardless of the symptomatic status, may help us to better intervene and address issues of racial and ethnic health equity. We tested decedents from the Wayne County Medical Examiner’s Office (Wayne & Monroe Counties, Michigan including Detroit) regardless of the cause of death.

Methods

Nasopharyngeal samples were collected from decedents at the Wayne County Medical Examiner’s Office between October 2020 and September 2022 and tested for a panel of respiratory viruses. We identified 3430 decedents with catchment addresses, which we linked to the social vulnerability index (SVI) and area deprivation index (ADI) through US Census tract/block. We evaluated non-linear associations between each of adenovirus (AdV), SARS-CoV-2, parainfluenza virus 2 (PIV2), rhinovirus (RV), and respiratory syncytial virus (RSV) prevalence and ADI, SVI, and SVI subthemes using splines in log-binomial regression models.

Results

There were few statistically significant associations observed between overall SVI or ADI and respiratory virus infection prevalence. However, RV was significantly associated with ADI, SVI, and most SVI subthemes. The SVI Minority Status and Language (MSL) subtheme was statistically significantly associated with the prevalence of AdV and RV (p < 0.05) and associations with SARS-CoV-2 and RSV approached significance (p < 0.10).

Conclusions

Our results suggest that the MSL subtheme of SVI may be the most informative community-level predictor of respiratory virus infections and could be used to prioritize health-equity-focused distribution of public health resources.