Impact of Cohort Effects on Hepatitis A Vaccination Models
Author Information
Author(s): Srinivasa Rao Arni, Maggie H Chen, Ba' Z Pham, Andrea C Tricco, Vladimir Gilca, Bernard Duval, Murray D Krahn, Chris T Bauch
Primary Institution: Department of Mathematics and Statistics, University of Guelph
Hypothesis
How do cohort effects influence the predictions of vaccination impact for Hepatitis A?
Conclusion
Including cohort effects in dynamic models significantly alters the predicted impact of vaccination on incidence and mortality.
Supporting Evidence
- Hepatitis A transmissibility has declined by a factor of 2.8 since the early twentieth century.
- Failure to include cohort effects leads to significant over-predictions of incidence and mortality.
- The percentage reduction in incidence and mortality due to vaccination is over-predicted when cohort effects are not included.
Takeaway
When we look at how many people get sick from Hepatitis A, we need to remember that older people got sick more in the past than younger people do now, which changes how we think about vaccines.
Methodology
An age-structured compartmental model was developed to analyze Hepatitis A transmission and vaccination effects in Canada.
Potential Biases
Potential bias from using seroprevalence data in multiple ways during parameterization.
Limitations
The model may not account for all heterogeneities in transmission and relies on historical data that may not reflect current conditions.
Participant Demographics
Canadian-born individuals of various age classes.
Digital Object Identifier (DOI)
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