| Popis: |
Background and QuestionIt is unclear which variables contribute to the variance in corona-virus disease (Covid-19) related deaths and Corono-virus2 (Cov2) cases. We wanted to see which contribution public health variables make in addition to health systems, health, and population variables to explain Covid-19 cases and deathsMethodWe modelled the relationship of various predictors (health systems variables, population and population health indicators) together with variables indicating public health measures (school closures, border closures, country lockdown) in 40 European and other countries, using Generalized Linear Models and minimized information criteria to select the best fitting and most parsimonious models.ResultsWe fitted two models with log-linearly linked variables on gamma-distributed outome variables (CoV2 cases and Covid-19 related deaths, standardized on population). CoV2-cases were best predicted by number of tests (b = 2*10−7, p =.00005), life-expectancy in a country (b = 0.19, p < .000001), and border closure (b = −0.93, p = .001). Population standardized deaths were best predicted by time, the virus had been in the country (b = 0.02, p = .02), life expectancy (b = 0.2, p = .000005), smoking (b = −0.08, p = .00001), and school closures (b = 2.54, p = .0001). Model fit statistics and model adequacy were good (model 1: Chi2/DF = 0.43; model 2: Chi2/DF = 0.88).Discussion and InterpretationOnly few variables were good predictors. Of the public health variables only border closure had the potential of preventing cases and none were predictors for preventing deaths. School closures, likely as a proxy for social distancing in severely ill patients, was associated with increased deaths.ConclusionThe pandemic seems to run its autonomous course and only border closure has the potential to prevent cases. None of them contributes to preventing deaths. |
