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Published on: January 28, 2019
Modelling the epidemiological impact of rotavirus vaccination in Germany--a Bayesian approach
Felix Weidemann1, Manuel Dehnert2, Judith Koch1
1Department for Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany.
Insights
Routine rotavirus (RV) infant vaccination significantly reduces RV infections in children under 5 years old in Germany. This study models the vaccine
Area of Science:
- Epidemiology
- Infectious Diseases
- Vaccinology
Background:
- Rotavirus (RV) infection is a leading cause of severe gastroenteritis in young children globally and in Germany.
- The German Standing Committee on Vaccination (STIKO) recommended routine RV infant immunization in 2013.
- Statistical modeling was employed to predict the epidemiological impact of RV vaccination in Germany.
Purpose of the Study:
- To predict the epidemiological impact of routine rotavirus (RV) vaccination in Germany.
- To estimate RV vaccine effectiveness (VE) in a real-world setting.
- To assess the population-level incidence of RV infection following high vaccination coverage.
Main Methods:
- A dynamic, population-based transmission model for RV infection was developed.
- Bayesian inference with adaptive Markov Chain Monte Carlo was used to estimate RV vaccine effectiveness (VE).
- Data from communicable disease reporting and vaccination coverage surveys were utilized.
Main Results:
- RV vaccination demonstrated high effectiveness (VE=96%) against symptomatic RV infection, maintaining maximum protection for approximately three years.
- Routine vaccination at 90% coverage is predicted to decrease symptomatic RV incidence in children <5 years by 84%, including 2.5% from herd protection.
- A potential increase in RV incidence was predicted for older age groups (5-59 years and >60 years) ten years post-vaccine introduction.
Conclusions:
- Routine infant rotavirus (RV) vaccination is projected to substantially lower RV incidence in German children under 5 years old.
- The study provides estimates of RV vaccine effectiveness (VE) and predicts population-level impacts.
- Model and prediction uncertainties were addressed in evaluating future statements regarding RV vaccination impact.
Background:
Rotavirus (RV) infection is the primary cause of severe gastroenteritis in children aged <5 years in Germany and worldwide. In 2013 the German Standing Committee on Vaccination (STIKO) developed a national recommendation for routine RV-immunization of infants. To support informed decision-making we predicted the epidemiological impact of routine RV-vaccination in Germany using statistical modelling.
Methods:
We developed a population-based model for the dynamic transmission of RV-infection in a vaccination setting. Using data from the communicable disease reporting system and survey records on the vaccination coverage from the eastern federal states, where the vaccine was widely used before recommended at national level, we first estimated RV vaccine effectiveness (VE) within a Bayesian framework utilizing adaptive Markov Chain Monte Carlo inference. The calibrated model was then used to compute the predictive distribution of RV-incidence after achieving high vaccination coverage with the introduction of routine vaccination.
Results:
Our model estimated that RV-vaccination provides high protection against symptomatic RV-infection (VE=96%; 95% credibility interval (CI): 91-99%) that remains at its maximum level for three years (95% CI: 1.43-5.80 years) and is fully waned after twelve years. At population level, routine vaccination at 90% coverage is predicted to reduce symptomatic RV-incidence among children aged <5 years by 84% (95% prediction interval (PI): 71-90%) including a 2.5% decrease due to herd protection. Ten years after vaccine introduction an increase in RV incidences of 12% (95% PI: -16 to 85%) among persons aged 5-59 years and 14% (95% PI: -6 to 109%) within the age-group >60 years was predicted.
Conclusion:
Routine infant RV-vaccination is predicted to considerably reduce RV-incidence in Germany among children <5 years. Our work generated estimates of RV VE in the field and predicted the population-level impact, while adequately addressing the role of model and prediction uncertainty when making statements about the future.
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