Introduction:

A new public health intervention, such as the introduction of a vaccine, implies monitoring the indicators that guarantee its effectiveness, and the possibility of quantifying its benefits. Obtaining accurate estimates of the impact of a health intervention is considered a major challenge.

Objective:

To estimate the causal impact of one of the leading products of the Finlay Institute in Havana: the registered and marketed Cuban vaccine VA-MENGOC-BC®.

Methods:

Data from the health statistics yearbooks from 2009 to 2017 were selected. The incidence rate of the meningococcal disease in Cuba per 100 000 population and a set of co-variables that were not affected by the intervention, such as incidence rate of typhoid fever, tuberculosis, and fatality cases due to infectious diseases (parasitic or intestinal) per 100 000 population were used as variables of interest. The intervention year was 1989. The Bayesian structural time series model was applied to evaluate the causal impact of the continued vaccination with VA-MENGOC-BC® from 1989 to date.

Results:

A significant cumulative causal impact in reducing the incidence of meningococcal disease was estimated. A decrease of 97.2% in the disease was verified.

Conclusions:

The application of the Bayesian structural time series model to estimate the impact of the vaccine VA-MENGOC-BC® was a novel tool to estimate the counterfactual. It was provided an estimate of the impact of the vaccination with VA-MENGOC-BC®, an implemented and globally well-known vaccine.

        · resumen en Español     · texto en Español     · Español ( pdf )