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Describe the bug
The src/posts/paper/7-basic-method.ts paper says that the formula for adjusting the prevalence ratio is prevalance_ratio = 1250 / (day_i + 25) * positive_test_rate ** 0.5 + 2 and points to https://covid19-projections.com/estimating-true-infections-revisited/ for justification.
The calculations in src/data/calculate.ts and /update_prevalence.py instead use (1000 / (day_i + 10)) * (positivityRate / 100) ** 0.5 + 2.
It's also unclear to me that the same prevalence ratio formula should be used for US and for countries with widespread asymptomatic lateral flow testing, but that's a separate question (and I don't have a recommendation for a replacement).
The text was updated successfully, but these errors were encountered:
I've also noticed for several states I've checked, that it's calculating vaccination percentages for a given area as the percentage of eligible population vaccinated as opposed to the percentage of the entire population vaccinated. Since kids under 12 can't be vaccinated yet, that makes the percentage of vaccinated people significantly lower in the general population than just calculating the percentage of people old enough to qualify that are vaccinated.
I've also noticed for several states I've checked, that it's calculating vaccination percentages for a given area as the percentage of eligible population vaccinated as opposed to the percentage of the entire population vaccinated. Since kids under 12 can't be vaccinated yet, that makes the percentage of vaccinated people significantly lower in the general population than just calculating the percentage of people old enough to qualify that are vaccinated.
Can you please open this as a separate issue? Thanks!
Hi @rmbellovin, thanks for catching the discrepancy. Note the update text on covid19-projections:
December 10, 2020 Update: We adjusted the constant in the prevalence ratio formula from a = 1500 / (day_i + 50) to a = 1000 / (day_i + 10). This results in a slightly higher prevalence ratio in the beginning of the pandemic and a lower prevalence ratio currently.
So the code currently matches their most up to date formula. I'll update the text in the white paper to match.
Describe the bug
The
src/posts/paper/7-basic-method.ts
paper says that the formula for adjusting the prevalence ratio isprevalance_ratio = 1250 / (day_i + 25) * positive_test_rate ** 0.5 + 2
and points to https://covid19-projections.com/estimating-true-infections-revisited/ for justification.The calculations in
src/data/calculate.ts
and/update_prevalence.py
instead use(1000 / (day_i + 10)) * (positivityRate / 100) ** 0.5 + 2
.Neither of these matches the current formula at https://covid19-projections.com/estimating-true-infections-revisited/, which is
prevalance_ratio = 1500 / (day_i + 50) * positive_test_rate ** 0.5 + 2
It's also unclear to me that the same prevalence ratio formula should be used for US and for countries with widespread asymptomatic lateral flow testing, but that's a separate question (and I don't have a recommendation for a replacement).
The text was updated successfully, but these errors were encountered: