Background

Few things are more anticipated in 2020 than the arrival of an effective and safe COVID vaccine. On that note, I wanted to compare the deaths from COVID to peak deaths from commonly known vaccine preventable diseases prior to vaccines existing for those diseases.

I found a paper in JAMA that looked at the peak deaths from diseases for which we now have vaccines that are recommended as part of routine immunization programs. These diseases include:

Diseases with Vaccines Licensed Before 1980

  1. Diphtheria*
  2. Measles**
  3. Mumps**
  4. Pertussis*
  5. Polio
  6. Rubella**
  7. Smallpox
  8. Tetanus*

*Part of DTaP vaccine

**Part of MMR vaccine

Diseases with Vaccines Licensed from 1980 to 2005

  1. Hepatitis A
  2. Hepatitis B
  3. Invasive pneumococcal disease
  4. Varicella (chickenpox)

From that JAMA paper I took the peak death counts and converted them to the 2020 US population using data from the US Census Bureau. I did not include Hemophilus influenzae B because no peak death statistics were included.

#COVID deaths from CDC as of July 6, 2020
disease<-c("Diphtheria","Measles","Mumps","Pertussis","Polio, Acute","Polio,Paralytic","Rubella","Cong Rubella","Smallpox","Tetanus","Hep A","Hep B","Pneumo","Varicella","COVID")
deaths<-c(3065,552,50,7518,2720,3145,24,2160,2510,511,298,267,7300,138,129811)
#populations for 2020 from https://www.census.gov/content/dam/Census/library/publications/2020/demo/p25-1144.pdf and for all other years from https://www.census.gov/population/estimates/nation/popclockest.txt and are all in 100,000s
years<-c(1936,1958,1964,1934,1949,1952,1968,1964,1902,1947,1971,1985,1999,1973,2020)
pops<-c(1280.5318,1748.81904,1918.88791,1263.73773,1491.8813,1575.5274,2007.06052,1918.88791,791.63,1441.26071,2076.60677,2379.23795,2726.90813,2119.08788,3326.39)
deaths_per_pop<-deaths/pops
df<-data.frame(disease,deaths,years,pops,deaths_per_pop)
#now I lumped a few diseases together to make fewer categories for better visualization; diphtheria, tetanus and pertussis are given together as the DTaP vaccine, measles, mumps and rubella as MMR, and then the two types of polio into one
diseases<-c("DTaP","MMR","Polio","Smallpox","Hep A","Hep B","Pneumo","Varicella","COVID")
deathrates<-c(df$deaths_per_pop[1]+df$deaths_per_pop[10]+df$deaths_per_pop[4],df$deaths_per_pop[2]+df$deaths_per_pop[3]+df$deaths_per_pop[7]+df$deaths_per_pop[8],df$deaths_per_pop[5]+df$deaths_per_pop[6],df$deaths_per_pop[9],df$deaths_per_pop[11],df$deaths_per_pop[12],df$deaths_per_pop[13],df$deaths_per_pop[14],df$deaths_per_pop[15])
#convert to 2020 pop
deaths<-ceiling(deathrates*3326.390)
df<-data.frame(diseases=diseases,deaths=deaths)
df$group<-c(rep("Vaccine-Preventable Illnesses",8),"COVID")

Graphing Deaths

I will arrange the data frame by number of deaths so that when the bar graph is generated, everything looks in order.

Conclusion

From the graph above you can see that were all of these vaccine-preventable illnesses killing Americans at the same rate as they were in their peak pre-vaccine year, they still would only kill roughly half of what COVID has killed so far only HALFWAY through this year.