Predicting individual affect of health interventions to reduce HPV prevalence

Courtney D. Corley, Rada Mihalcea, Armin R. Mikler, Antonio Sanfilippo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Recently, human papilloma virus (HPV) has been implicated to cause several throat and oral cancers and HPV is established to cause most cervical cancers. A human papilloma virus vaccine has been proven successful to reduce infection incidence in FDA clinical trials, and it is currently available in the USA. Current intervention policy targets adolescent females for vaccination; however, the expansion of suggested guidelines may extend to other age groups and males as well. This research takes a first step toward automatically predicting personal beliefs, regarding health intervention, on the spread of disease. Using linguistic or statistical approaches, sentiment analysis determines a text's affective content. Self-reported HPV vaccination beliefs published in web and social media are analyzed for affect polarity and leveraged as knowledge inputs to epidemic models. With this in mind, we have developed a discrete-time model to facilitate predicting impact on the reduction of HPV prevalence due to arbitrary age-and gender-targeted vaccination schemes.

Original languageEnglish
Title of host publicationAdvances in Experimental Medicine and Biology
Pages181-190
Number of pages10
Volume696
DOIs
Publication statusPublished - 2011
Externally publishedYes

Publication series

NameAdvances in Experimental Medicine and Biology
Volume696
ISSN (Print)00652598

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Keywords

  • Computational epidemiology
  • Data mining
  • Epidemic models
  • Health informatics
  • Public health
  • Sentiment analysis

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Corley, C. D., Mihalcea, R., Mikler, A. R., & Sanfilippo, A. (2011). Predicting individual affect of health interventions to reduce HPV prevalence. In Advances in Experimental Medicine and Biology (Vol. 696, pp. 181-190). (Advances in Experimental Medicine and Biology; Vol. 696). https://doi.org/10.1007/978-1-4419-7046-6_18