Marc Bevand
75 lines
3.6 KiB
Markdown
75 lines
3.6 KiB
Markdown
# Calculating the age-stratified infection fatality ratio (IFR) of COVID-19
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*Updated: 10 June 2020*
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Author: Marc Bevand
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The largest serological prevalence survey of COVID-19 was conducted by Spain
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during the second round of a study that analyzed 63 564 samples between 18 May
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2020 and 01 June 2020. We used its [provisional results][sero] published on 03
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June to calculate the overall and age-stratified IFR of COVID-19 with the
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Python script `calc_ifr.py`:
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```
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$ ./calc_ifr.py
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Ages 0 to 9: 115013 infected, 4 deaths, 0.003% IFR
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Ages 10 to 19: 177929 infected, 7 deaths, 0.004% IFR
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Ages 20 to 29: 212099 infected, 32 deaths, 0.015% IFR
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Ages 30 to 39: 281290 infected, 86 deaths, 0.030% IFR
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Ages 40 to 49: 447942 infected, 287 deaths, 0.064% IFR
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Ages 50 to 59: 410213 infected, 874 deaths, 0.213% IFR
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Ages 60 to 69: 334709 infected, 2404 deaths, 0.718% IFR
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Ages 70 to 79: 270572 infected, 6451 deaths, 2.384% IFR
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Ages 80 to 89: 131703 infected, 11150 deaths, 8.466% IFR
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Ages 90 to 199: 46631 infected, 5827 deaths, 12.497% IFR
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Ages 0 to 199: 2428102 infected, 27121 deaths, 1.117% IFR
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```
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The average IFR for Spain is **1.117%**. However the true IFR may be higher due
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to right-censoring and under-reporting of deaths.
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The Spanish serological study remains the largest published study available to
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this day. The age-stratified IFR was calculated from three sources:
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1. Detailed *prevalence data for age brackets*, from the [serosurvey][sero] (table 1)
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1. *Total deaths* and *deaths per age bracket* from the [Ministry of Health's daily report for 29 May][daily] (table 2 and table 3)
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1. *Population pyramid* for Spain, from [worldpopulationreview.com][wpop]
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In order to minimize right-censoring, the parameters *total deaths* and *deaths
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per age bracket* should be obtained from a point in time as close as possible
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to when the serosurvey was conducted (18 May to 01 June.) We found only two
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Ministry of Health reports in this time period that document deaths per age
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bracket: [18 May][dailyalt], [29 May][daily]. However the Ministry of Health
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has made significant corrections to deaths statistics on 25 May by subtracting
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approximately 2 000 deaths. Therefore we trusted the statistics from 29 May over
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those of 18 May.
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Important detail to note: there were 27 121 total deaths, however age information
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was only available for 20 585 deaths, and was missing for 6 536 deaths.
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We assume that these 6 536 deaths were distributed proportionally—not equally—among age
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brackets, which seems to be a reasonable assumption.
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# Applying the age-stratified IFR to other countries
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The script `calc_ifr.py` is also able to apply the age-stratified IFR to
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another population pyramid, thus calculating the expected average IFR for other
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countries.
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In the second half of the script, edit `pyramid_target` with the demographics data.
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As an example, we supply pyramid data for the United States and calculate an IFR of **0.658%**:
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```
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$ ./calc_ifr.py
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[...]
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IFR on target country assuming disease prevalence equal among ages: 0.658%
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```
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However IFR is highly dependent on factors other than age: availability
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of healthcare, population health, etc, so this estimate should be interpreted
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with caution.
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[sero]: https://portalcne.isciii.es/enecovid19/ene_covid19_inf_pre2.pdf
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[daily]: https://www.mscbs.gob.es/profesionales/saludPublica/ccayes/alertasActual/nCov-China/documentos/Actualizacion_120_COVID-19.pdf
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[dailyalt]: https://www.mscbs.gob.es/profesionales/saludPublica/ccayes/alertasActual/nCov-China/documentos/Actualizacion_109_COVID-19.pdf
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[wpop]: https://worldpopulationreview.com/countries/spain-population/
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