Objective

Public health indicators, such as the mortality rate from cardiovascular disease, indicate the magnitude of the population's health problems, which is why it is necessary to generate strategies that allow predicting their behavior to evaluate the fulfillment of the objectives and programs in public health. Thus, it was proposed to apply a methodology based on the probabilistic random walk and a second-degree equation to predict the cardiovascular mortality rate in the department of Magdalena.

Method

Values of the mortality rates due to cardiovascular disease in the department of Magdalena were obtained from the historical records reported by the National Institute of Health between 1998 and 2011. Subsequently, it was observed that the behavior of this variable was compatible with walking randomly to later establish probability spaces and a second-degree equation with which the value of this index was predicted for 2011 in order to verify the effectiveness of the method.

Results

The predicted result of the variable was 93.2, when compared with the real value reported of 91.1, it indicates that the method has a 98 % predictive precision.

Conclusions

It is possible to predict with high precision the behavior of indicators in public health using physical-mathematical methods, which is useful for epidemiological surveillance entities to verify the efficacy of population-based interventions in public health.