Short-term predictability of influenza AH1N1 cases based on deterministic models

Influenza AH1N1 severely affected the population of Chile. It has high transmissibility, which may stress the health system capacity. An adequate prediction of number of cases and frequency of complications is needed. Chilean and OMS dialy reports of cases from April to Jun 2009 were analyzed in this study. We developed a simple methodology for short-term forecast of case number, based on deterministic models. Predicted and observed values were compared with regression analyses and Bland-Altman diagrams. We found that the intrinsic rate of increase of the number of cases in the world and in Chile, after an initial high instability, decreases to stable values, allowing a relatively accurate forecasting the next day and for a serial period. The estimators obtained are over-estimators, which allow an adequate safety factor for the estimations. The method is easy to implement in software for routine use and can be useful in monitoring this epidemic and others in the future.