Effective strategies to prevent coronavirus disease-2019 (COVID-19) outbreak in hospital

Background: The first death by COVID-19 in Spain was on February 13th However, on that precise date the tracking of positive cases of infection was mainly limited to subjects at high risk of contagion The aim of this study was to determine whether unexpected changes in trend of the all-cause mortality curve, could serve as an indicator to provide early preventive interventions Method: To analyze all-cause mortality data a Poisson distribution was selected with a Log function The goodness of fit statistics was studied, and both the predicted value of mean of response and residual were obtained For daily mortality, a seasonal decomposition was performed by weighted moving averages method Finding: The results showed a constantly increasing risk from the ninth week (Sunday 23 rd February) Three weeks before lockdown Adjusted RR: 0·403 (Week 8), 0·406 (W9), 0·408 (W10), 0·446 (W11), 0·583 (W12), P 0·001 in all cases In males the risk increased from the same week Adjusted RR: 0·372 (W8), 0·386 (W9), 0·388 (W10), 0·429 (W11), 0·578 (W12), P0·001 In contrast, for females the risk started to increase from week 11 By groups of age there were again two weeks of difference between the population under 65 years (W 11) vs over 74 years of age (W 9) Six days were earned using baseline years with similar seasonal trend pattern Interpretation: Facing an unknown viral process, epidemiological surveillance must pay attention to subtle modifications of seasonal trend patterns to take appropriate preventive measures as early as possible