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Research Article

Respiratory virus transmission dynamics determine timing of asthma exacerbation peaks: Evidence from a population-level model

View ORCID ProfileRosalind M. Eggo, James G. Scott, Alison P. Galvani, and Lauren Ancel Meyers
  1. aDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX 78712;
  2. bDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom;
  3. cDepartment of Statistics and Data Sciences, The University of Texas at Austin, Austin, TX 78712;
  4. dMcCombs School of Business, The University of Texas at Austin, Austin, TX 78712;
  5. eCenter for Infectious Disease Modeling, Yale School of Public Health, New Haven, CT 06520;
  6. fSanta Fe Institute, Santa Fe, NM 87501

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PNAS February 23, 2016 113 (8) 2194-2199; first published February 8, 2016; https://doi.org/10.1073/pnas.1518677113
Rosalind M. Eggo
aDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX 78712;
bDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom;
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  • ORCID record for Rosalind M. Eggo
  • For correspondence: r.eggo@lshtm.ac.uk
James G. Scott
cDepartment of Statistics and Data Sciences, The University of Texas at Austin, Austin, TX 78712;
dMcCombs School of Business, The University of Texas at Austin, Austin, TX 78712;
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Alison P. Galvani
eCenter for Infectious Disease Modeling, Yale School of Public Health, New Haven, CT 06520;
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Lauren Ancel Meyers
aDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX 78712;
fSanta Fe Institute, Santa Fe, NM 87501
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  1. Edited by Kenneth W. Wachter, University of California, Berkeley, CA, and approved January 7, 2016 (received for review September 23, 2015)

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Significance

Asthma exacerbations are frequently triggered by common cold infections. Whereas prior studies have swabbed individual patients to detect viruses, we take a population level approach to investigate common cold circulation and its consequences for asthmatics. We introduce a dynamic model of common cold transmission with different contact patterns for adults and children, which are modified by school vacations. By jointly fitting this and an asthma risk model to daily hospitalization rates in eight large cities in Texas, we found that the common cold is a primary driver of asthma exacerbations, and both are predictably influenced by the school calendar. This provides actionable insight for assessing asthma hospitalization risk and targeting preventive measures.

Abstract

Asthma exacerbations exhibit a consistent annual pattern, closely mirroring the school calendar. Although respiratory viruses—the “common cold” viruses—are implicated as a principal cause, there is little evidence to link viral prevalence to seasonal differences in risk. We jointly fit a common cold transmission model and a model of biological and environmental exacerbation triggers to estimate effects on hospitalization risk. Asthma hospitalization rate, influenza prevalence, and air quality measures are available, but common cold circulation is not; therefore, we generate estimates of viral prevalence using a transmission model. Our deterministic multivirus transmission model includes transmission rates that vary when school is closed. We jointly fit the two models to 7 y of daily asthma hospitalizations in adults and children (66,000 events) in eight metropolitan areas. For children, we find that daily viral prevalence is the strongest predictor of asthma hospitalizations, with transmission reduced by 45% (95% credible interval =41–49%) during school closures. We detect a transient period of nonspecific immunity between infections lasting 19 (17–21) d. For adults, hospitalizations are more variable, with influenza driving wintertime peaks. Neither particulate matter nor ozone was an important predictor, perhaps because of the large geographic area of the populations. The school calendar clearly and predictably drives seasonal variation in common cold prevalence, which results in the “back-to-school” asthma exacerbation pattern seen in children and indirectly contributes to exacerbation risk in adults. This study provides a framework for anticipating the seasonal dynamics of common colds and the associated risks for asthmatics.

  • asthma
  • common cold
  • mathematical model
  • transmission
  • Bayesian inference

Footnotes

  • ↵1To whom correspondence should be addressed. Email: r.eggo{at}lshtm.ac.uk.
  • Author contributions: R.M.E., J.G.S., and L.A.M. designed research; R.M.E. performed research; R.M.E., J.G.S., and L.A.M. contributed new reagents/analytic tools; R.M.E. and L.A.M. analyzed data; and R.M.E., J.G.S., A.P.G., and L.A.M. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1518677113/-/DCSupplemental.

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Asthma exacerbations and common cold dynamics
Rosalind M. Eggo, James G. Scott, Alison P. Galvani, Lauren Ancel Meyers
Proceedings of the National Academy of Sciences Feb 2016, 113 (8) 2194-2199; DOI: 10.1073/pnas.1518677113

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Asthma exacerbations and common cold dynamics
Rosalind M. Eggo, James G. Scott, Alison P. Galvani, Lauren Ancel Meyers
Proceedings of the National Academy of Sciences Feb 2016, 113 (8) 2194-2199; DOI: 10.1073/pnas.1518677113
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Proceedings of the National Academy of Sciences: 113 (8)
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