Abstract
his work aimed to evaluate the effects of seasonal climatic variations in the incidence of respiratory diseases by influenza (PI) in the elderly population in the region of metropolitan João Pessoa in the state of Paraíba. Generalized linear models from the linear Poisson regression to relate the dependent variable set to the records of hospitalizations for causes associated with influenza and the independent variables (rainfall, average air temperature and relative humidity) to analyze the relations established by modeling has been used. Aditionally,was applied ANOVA variance test with a significance level of 0.05 of probability to determine which independent variables is more significant. Also the residual generated by adjusting the models in order to identify the distribution that best fitted the data were analyzed. All static analysis was performed using R software. In general is possible to identify that the highest peaks of hospitalizations for PI occur in autumn and winter. Therefore, these results suggest an association between cold and hospitalizations for IP. Statistical modeling performed satisfactory for analysis of the cases of hospitalizations for IP. However, the deepening of these temporal analysis is necessary because health depends not only on environmental factors.Authors hold the Copyright for articles published in this journal, and the journal holds the right for first publication. Because they appear in a public access journal, articles are licensed under Creative Commons Attribution (BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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