Modeling Childhood Infectious Diseases Before and After Vaccination
Author Information
Author(s): Helen Trottier, Philippe Pierre, Roch Roy
Primary Institution: University of Montréal
Hypothesis
The study aims to analyze the stochastic dynamics of childhood infectious disease time series and their statistical structure before and after mass vaccination.
Conclusion
The study found that mass vaccination does not change the stochastic dependency of childhood infectious diseases, which are represented by similar statistical models.
Supporting Evidence
- Mass vaccination was introduced for pertussis in 1943, measles in 1963, and mumps and rubella in 1969.
- The study analyzed time series data from Health Canada covering several decades.
- Statistical models showed that the number of new cases is influenced by previous cases and random factors.
- Despite biological differences, the diseases exhibited similar statistical structures.
- Models explained between 68% and 90% of the variance in the differenced series.
Takeaway
The study looked at how diseases like measles and mumps spread over time and found that even after vaccines were introduced, the way these diseases behave didn't really change.
Methodology
The study used Box-Jenkins or ARIMA modeling to analyze time series data of childhood infectious diseases in Canada.
Potential Biases
The study notes that the notification system may not capture all cases, leading to potential overestimation or underestimation of disease incidence.
Limitations
The study acknowledges underreporting of cases and changes in the surveillance system over time, which may affect the results.
Participant Demographics
The data analyzed included childhood infectious diseases in Canada, covering various time periods before and after vaccination.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website