Association Between BCG Policy is Significantly Confounded by Age and is Unlikely to Alter Infection or Mortality Rates

STEFAN Kirov

Data on average population age per country and number of infections was collected from Wikipedia. BCG policy and income level data was obtained from one of the original studies. BCG and rubella immunization rates were obtained from WHO website (13) . Country names were cleaned and data was merged in R (Rstudio 1.1.456 on Ubuntu 16 Linux, R version 3.2.3). All scripts and data files are available from https://github.com/kirovsa/covid19-bcg. As with one of the original studies the countries with population of less than 1M were excluded(4). For analysis of mortality rates countries with no deaths on record were excluded as these are likely to be in the very initial phase of the epidemic and will introduce significant noise. To determine the effect of different factors I used lm function from stats package. Evaluating factors effects on infections in the presence of random effect was done with lme from nlme package. Log likelihood was tested with lrtest from lmtest package. BCG policy and income level were coded according to one of the studies that found the association with COVID19 infection(4): BCG Policy 1 = current universal policy 2= used to recommend, not anymore 3 = never had universal policy 2018 FY income level: Low income (L) -1 Lower middle income (LM)-2 Upper middle income (UM)-3 High income (H)-4