Predicting Individual Affect of Health Interventions to Reduce HPV Prevalence
Recently, human papilloma virus 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 United States. 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 towards automatically predicting personal beliefs, regarding health intervention, on the spread of disease. Using linguistic or statistical approaches, sentiment analysis determines a texts 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.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1023726
- Report Number(s):
- PNNL-SA-69222; TRN: US201120%%1062
- Resource Relation:
- Related Information: Software Tools and Algorithms for Biological Systems: Advances in Experimental Medicine and Biology, 696 (Part 2):181-190
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
60 APPLIED LIFE SCIENCES
ADOLESCENTS
AGE GROUPS
CLINICAL TRIALS
FEMALES
FORECASTING
HUMAN POPULATIONS
MALES
NEOPLASMS
ONCOGENIC VIRUSES
ORAL CAVITY
UROGENITAL SYSTEM DISEASES
PHARYNX
PUBLIC HEALTH
RECOMMENDATIONS
REDUCTION
SIMULATION
VACCINES
Epidemic Models
Health Informatics
Computational Epidemiology
Public Health