Cayden
Cayden
Programming language:Whatever
2021-07-16 19:24:09
0
Q:

Bayes Covid

English Learner exact
English Learner exact
Code: Whatever
2021-08-21 07:09:18 
TO UNDERSTAND THE ISSUE AT A HIGH LEVEL, TWO SIMPLISTIC EXAMPLES...
EX1: Of 1000 ASYMPTOMATIC...
if rapidTest *sensitivity* is 80%... 20% will have false negatives
assume 1% of pop are positive ( @ 2% - false positives)
if rapidTest *specificity* is 100% all infection-free would test negative)
from the pre-test probability (1%) 
 10 in 1000 will have it, 990 will not
 considering the 80% sensitivity  
  8 will test positive,  
  2 will test negative (false negatives)
Of the 990,  100% test negative ( *specificity* is 100%) 
    Positive predictive value =  100%  
    Negative predictive value =  99.8%     (990/992 = not having Covid-19 if the test is negative)

EX2: Of the 1000 SYMPTOMATIC with PRE-TEST probablity at 30%  (Sensitivity and Specificity remaining the same)
300 will have the disease 
  240 (80%) testing positive, 
  60  (20%) testing negative (falsely)

https://www.statnews.com/2020/08/20/covid-19-test-accuracy-supplement-the-math-of-bayes-theorem/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269418/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315940/
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