, Volume 15, Issue 2, pp 290–301 | Cite as

Linking Time-Use Data to Explore Health Outcomes: Choosing to Vaccinate Against Influenza

  • Kevin BerryEmail author
  • Julia E. Anderson
  • Jude Bayham
  • Eli P. Fenichel
Original Contribution


To inform public health and medical decision makers concerning vaccination interventions, a methodology for merging and analyzing detailed activity data and health outcomes is presented. The objective is to investigate relationships between individual’s activity choices and their decision to receive an influenza vaccination. Data from the Behavioral Risk Factor Surveillance System (BRFSS) are used to predict vaccination rates in the American Time Use Survey (ATUS) data between 2003 and 2013 by using combined socioeconomic and demographic characteristics. The correlations between the extensive (do or not do) and intensive (how much) decisions to perform activities and influenza vaccination are further explored. Significant positive and negative correlations were found between several activities and vaccination. For some activities, the sign of the correlation flips when considering either the intensive or the extensive decision. This flip occurs with highly studied activities, like smoking. Correlations between activities and vaccination can provide an additional metric for targeting those least likely to vaccinate. The methodology outlined in this paper can be replicated to explore correlation among actions and other health outcomes.


Nontraditional vaccination campaigns American Time Use Survey Influenza Behavioral Risk Factor Surveillance System Survey Public health Vaccination 



This publication was made possible by Grant Number 1R01GM100471-01 from the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health and NSF. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NIGMS. This work was also funded by NSF Grant No. 1414374 as part of the joint NSF-NIH-USDA Ecology and Evolution of Infectious Diseases program.

Supplementary material

10393_2017_1296_MOESM1_ESM.docx (103 kb)
Supplementary material 1 (DOCX 102 kb)


  1. Arcavi, L., & Benowitz, N. L. (2004). Cigarette smoking and infection. Archives of Internal Medicine, 164(20), 2206–2216.CrossRefPubMedGoogle Scholar
  2. Avery, E. J., & Lariscy, R. W. (2014). Preventable disease practices among a lower SES, multicultural, nonurban, US Community: the roles of vaccination efficacy and personal constraints. Health Communication, 29(8), 826–836.CrossRefPubMedGoogle Scholar
  3. Bayham, J., Kuminoff, N. V, Gunn, Q., & Fenichel, E. P. (2015). Measured voluntary avoidance behaviour during the 2009 A/H1N1 epidemic. In Proc. R. Soc. B (Vol. 282, p. 20150814). The Royal Society.Google Scholar
  4. Bearden, D. T., & Holt, T. (2005). Statewide impact of pharmacist-delivered adult influenza vaccinations. American Journal of Preventive Medicine, 29(5), 450–452.CrossRefPubMedGoogle Scholar
  5. Berry, K., Bayham, J., Meyer, S. R., & Fenichel, E. P. (2017). The Allocation of Time and Risk of Lyme: A Case of Ecosystem Service Income and Substitution Effects. Environmental and Resource Economics, 1–20.Google Scholar
  6. Bish, A., Yardley, L., Nicoll, A., & Michie, S. (2011). Factors associated with uptake of vaccination against pandemic influenza: a systematic review. Vaccine, 29(38), 6472–6484.CrossRefPubMedGoogle Scholar
  7. BLS. (2012). American Time Use Survey. Washington, DC.Google Scholar
  8. Burns, V. E., Ring, C., & Carroll, D. (2005). Factors influencing influenza vaccination uptake in an elderly, community-based sample. Vaccine, 23(27), 3604–3608.CrossRefPubMedGoogle Scholar
  9. CDC. (2013). Behavioral Risk Factor Surveillance System Survey Data. Atlanta, Georgia. Retrieved from
  10. CDC. (2016a). ACIP Recommendations. Retrieved from
  11. CDC. (2016b). Flu Vaccination Coverage, United States, 2014-15 Influenza Season. Retrieved from
  12. Culotta, A., Kumar, N. R., & Cutler, J. (2015). Predicting the Demographics of Twitter Users from Website Traffic Data. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (pp. 72–78).Google Scholar
  13. DHHS. (2012). Healthy People 2020. Retrieved from
  14. Dredze, M., Broniatowski, D. A., Smith, M. C., & Hilyard, K. M. (2016). Understanding Vaccine Refusal: Why We Need Social Media Now. American Journal of Preventive Medicine (Vol. 50).
  15. Frew, P. M., Saint-Victor, D. S., Owens, L. E., & Omer, S. B. (2014). Socioecological and message framing factors influencing maternal influenza immunization among minority women. Vaccine, 32(15), 1736–1744.CrossRefPubMedGoogle Scholar
  16. Jacob, V., Chattopadhyay, S. K., Hopkins, D. P., Morgan, J. M., Pitan, A. A., Clymer, J. M., & Force, C. P. S. T. (2016). Increasing Coverage of Appropriate Vaccinations: A Community Guide Systematic Economic Review. American Journal of Preventive Medicine, 50(6), 797–808.CrossRefPubMedPubMedCentralGoogle Scholar
  17. Kosinski, M., Stillwell, D., & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110(15), 5802–5805. Scholar
  18. Lee, B. Y., Mehrotra, A., Burns, R. M., & Harris, K. M. (2009). Alternative vaccination locations: who uses them and can they increase flu vaccination rates? Vaccine, 27(32), 4252–4256.CrossRefPubMedPubMedCentralGoogle Scholar
  19. Merrill, R. M., & Beard, J. D. (2009). Influenza vaccination in the United States, 2005–2007. Medical Science Monitor Basic Research, 15(7), PH92-PH100.Google Scholar
  20. Mostow, S. R. (2001). Use of alternative sites to administer influenza vaccine improves acceptance by both physicians and patients. In International Congress Series (Vol. 1219, pp. 703–706). Elsevier.Google Scholar
  21. Mullahy, J. (1998). It’ll only hurt a second? Microeconomic determinants of who gets flu shots. National Bureau of Economic Research.Google Scholar
  22. Nichol, K. L., Mac Donald, R., & Hauge, M. (1996). Factors associated with influenza and pneumococcal vaccination behavior among high-risk adults. Journal of General Internal Medicine, 11(11), 673–677.CrossRefPubMedGoogle Scholar
  23. Plans-Rubió, P., & Plans-Rubio, P. (2012). The vaccination coverage required to establish herd immunity against influenza viruses. Preventive Medicine, 55(1), 72–77.CrossRefPubMedGoogle Scholar
  24. Postema, A. S., & Breiman, R. F. (2000). Adult Immunization Programs in Nontraditional Settings: Quality Standards and Guidance for Program Evaluation: A Report of the National Vaccine Advisory Committee. Morbidity and Mortality Weekly Report: Recommendations and Reports, vii-13.Google Scholar
  25. R Core Team. (2015). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from
  26. Reed, C., Kim, I. K., Singleton, J. A., Chaves, S. S., Flannery, B., Finelli, L., … Jernigan, D. (2014). Estimated influenza illnesses and hospitalizations averted by vaccination–United States, 2013-14 influenza season. MMWR. Morbidity and Mortality Weekly Report, 63(49), 1151–1154.PubMedPubMedCentralGoogle Scholar
  27. Scheminske, M., Henninger, M., Irving, S. A., Thompson, M., Williams, J., Shifflett, P., … Naleway, A. L. (2015). The Association Between Influenza Vaccination and Other Preventative Health Behaviors in a Cohort of Pregnant Women. Health Education & Behavior, 42(3), 402–408.CrossRefGoogle Scholar
  28. Singleton, J. A., Poel, A. J., Lu, P.-J., Nichol, K. L., & Iwane, M. K. (2005). Where adults reported receiving influenza vaccination in the United States. American Journal of Infection Control, 33(10), 563–570.CrossRefPubMedGoogle Scholar
  29. Stehr-Green, P. A., Sprauer, M. A., Williams, W. W., & Sullivan, K. M. (1990). Predictors of vaccination behavior among persons ages 65 years and older. American Journal of Public Health, 80(9), 1127–1129.CrossRefPubMedPubMedCentralGoogle Scholar
  30. Stockwell, M. S., Kharbanda, E. O., Martinez, R. A., Vargas, C. Y., Vawdrey, D. K., & Camargo, S. (2012). Effect of a text messaging intervention on influenza vaccination in an urban, low-income pediatric and adolescent population: a randomized controlled trial. JAMA, 307(16), 1702–1708.CrossRefPubMedGoogle Scholar
  31. Uscher-Pines, L., Harris, K. M., Burns, R. M., & Mehrotra, A. (2012). The growth of retail clinics in vaccination delivery in the US. American Journal of Preventive Medicine, 43(1), 63–66.CrossRefPubMedPubMedCentralGoogle Scholar
  32. Ward, C. J. (2014). Influenza vaccination campaigns: is an ounce of prevention worth a pound of cure? American Economic Journal: Applied Economics, 6(1), 38–72.Google Scholar
  33. Weitzel, K. W., & Goode, J. V. (1999). Implementation of a pharmacy-based immunization program in a supermarket chain. Journal of the American Pharmaceutical Association (1996), 40(2), 252–256.Google Scholar
  34. Zagheni, E., Billari, F. C., Manfredi, P., Melegaro, A., Mossong, J., & Edmunds, W. J. (2008). Using time-use data to parameterize models for the spread of close-contact infectious diseases. American Journal of Epidemiology, 168(9), 1082–1090.CrossRefPubMedGoogle Scholar

Copyright information

© EcoHealth Alliance 2017

Authors and Affiliations

  • Kevin Berry
    • 1
    • 2
    Email author
  • Julia E. Anderson
    • 1
    • 3
  • Jude Bayham
    • 1
    • 4
  • Eli P. Fenichel
    • 1
  1. 1.School of Forestry and Environmental StudiesYale UniversityNew HavenUSA
  2. 2.Institute of Social and Economic ResearchUniversity of Alaska AnchorageAnchorageUSA
  3. 3.School of Public HealthYale UniversityNew HavenUSA
  4. 4.Department of Agricultural and Resource EconomicsColorado State UniversityFort CollinsUSA

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