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remove ability to apply IFR to arbitrary population pyramids

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Marc Bevand
2020-09-27 11:34:31 -07:00
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README.md
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# Calculating the age-stratified infection fatality ratio (IFR) of COVID-19
*Updated: 02 Sep 2020*
*Updated: 27 Sep 2020*
Author: Marc Bevand
# Calculating the age-stratified infection fatality ratio (IFR) of COVID-19
The largest serological prevalence survey of COVID-19 was conducted by Spain
during the second round of a study that analyzed 63 564 samples between 18 May
2020 and 01 June 2020. We used its [provisional results][sero] published on 03
@@ -71,26 +71,6 @@ So a false negative rate anywhere from 3% to 21% could be possible, and we
think it is premature to adjust IFR calculations given the exact sensitivity is
not known.
# Applying the age-stratified IFR to other countries
The script `calc_ifr.py` is also able to apply the age-stratified IFR to
another population pyramid, thus calculating the expected average IFR for other
countries.
In the second half of the script, edit `pyramid_target` with the demographics data.
As an example, we supply pyramid data for the United States and calculate an IFR of **0.658%**:
```
$ ./calc_ifr.py
[...]
IFR on target country assuming disease prevalence equal among ages: 0.658%
```
However the average IFR is highly dependent on factors other than age: varying
prevalence among age brackets, underlying health conditions, access to
healthcare, socioeconomic status, ethnicity, etc, so this estimate should be
interpreted with caution.
[sero]: https://www.mscbs.gob.es/ciudadanos/ene-covid/docs/ESTUDIO_ENE-COVID19_SEGUNDA_RONDA_INFORME_PRELIMINAR.pdf
[daily]: https://www.mscbs.gob.es/profesionales/saludPublica/ccayes/alertasActual/nCov-China/documentos/Actualizacion_120_COVID-19.pdf
[dailyalt]: https://www.mscbs.gob.es/profesionales/saludPublica/ccayes/alertasActual/nCov-China/documentos/Actualizacion_109_COVID-19.pdf