With covid-policy-modelling/covid-policy-modelling#56, we released a first draft of an export. There are a number of metrics that we omitted however, that we should now investigate adding:
| Value |
Description |
Possible Calculation |
prevalence |
% of the population who would test positive for COVID-19 (Nowcast) |
Mild + ILI + SARI + Critical + CritRecov / population (which we'd have to lookup)? |
prevalence_mtp |
% of the population who would test positive for COVID-19 (MTP) |
Uncertain of difference to prevalance |
weekly_cases_per_100k |
Number of weekly cases per 100,000 people |
incMild + incILI + incSARI + incCritical + incCritRecov for the last week * 100000 / population? |
community_prev |
Number of current infections in the community |
Is this Mild + ILI + SARI + Critical + CritRecov, although unsure if there is some meaning to "community", e.g. may be just Mild + ILI? |
type28_death_inc_line |
New daily deaths by date of death within 28 days of first positive specimen date (Forecast) |
This is deaths after a positive test, whereas most of the models just do deaths, so not sure we'll be able to support this |
num_positive_tests |
The number of positive tests |
This should take into account the fact that not all cases are tested, so again not sure if models produce this number |
incidence |
Daily incidence estimate |
incMild + incILI + incSARI + incCritical + incCritRecov, although it's not clear from the description if this should then be given as a proportion, e.g. of population |
mean_generation_time |
Mean of the generation interval |
Would need to be added to output schema, e.g. WSS assumes it's 5 |
var_generation_time |
Variance of the generation time |
Might need to be added to output schema, e.g. WSS assumes generation time is constant |
kappa |
Variance of the generation time |
Same as var_generation_time? |
growth_rate |
Daily rate of exponential growth |
Might need to be added to output schema, e.g. WSS assumes it's exp[(R-1)/mean_generation_time], but that might not be universal |
doubling_time |
Number of days between doubling |
Might need to be added to output schema, e.g. WSS assumes it's log2 * genTime / (R-1), but that might not be universal |
I do not think we need to support all the values.
If there is one that we do not have the information in the output schema to produce (and it can't be looked up from some data source like population), we can decide whether we need to update our schema, or just choose to ignore that value.
We can potentially go back to ask questions about the external schema if things aren't clear, although I don't know how quickly we'd get a response.
This may get split into separate issues, as some are more complex than others.
Definitions
We define the following metrics for each day in our output schema:
| Metric |
Description |
Mild |
Current number of mild cases on this day |
ILI |
Current number of influenza-like illness cases on this day (assume represents GP demand) |
SARI |
Current number of Severe Acute Respiratory Illness cases on this day (assume represents hospital demand) |
Critical |
Current number of critical cases on this day (assume represents ICU demand) |
CritRecov |
Current number of critical cases on this day who are well enough to leave the ICU but still need a hospital bed |
R |
R-number on this day |
incDeath |
Number of deaths occurring on this day |
For the first five, we also define cumulative versions representing total numbers since the start of the pandemic (cumMild, cumILI, cumSARI, cumCritical & cumCritRecov).
By taking the difference between two consecutive days, the UI also determines the numbers of new cases on a given day (which I'll refer to as incMild, incILI, incSARI, incCritical & incCritRecov).
With covid-policy-modelling/covid-policy-modelling#56, we released a first draft of an export. There are a number of metrics that we omitted however, that we should now investigate adding:
prevalenceMild+ILI+SARI+Critical+CritRecov/ population (which we'd have to lookup)?prevalence_mtpprevalanceweekly_cases_per_100kincMild+incILI+incSARI+incCritical+incCritRecovfor the last week * 100000 / population?community_prevMild+ILI+SARI+Critical+CritRecov, although unsure if there is some meaning to "community", e.g. may be justMild+ILI?type28_death_inc_linenum_positive_testsincidenceincMild+incILI+incSARI+incCritical+incCritRecov, although it's not clear from the description if this should then be given as a proportion, e.g. of populationmean_generation_timevar_generation_timekappavar_generation_time?growth_rateexp[(R-1)/mean_generation_time], but that might not be universaldoubling_timelog2 * genTime / (R-1), but that might not be universalI do not think we need to support all the values.
If there is one that we do not have the information in the output schema to produce (and it can't be looked up from some data source like population), we can decide whether we need to update our schema, or just choose to ignore that value.
We can potentially go back to ask questions about the external schema if things aren't clear, although I don't know how quickly we'd get a response.
This may get split into separate issues, as some are more complex than others.
Definitions
We define the following metrics for each day in our output schema:
MildILISARICriticalCritRecovRincDeathFor the first five, we also define cumulative versions representing total numbers since the start of the pandemic (
cumMild,cumILI,cumSARI,cumCritical&cumCritRecov).By taking the difference between two consecutive days, the UI also determines the numbers of new cases on a given day (which I'll refer to as
incMild,incILI,incSARI,incCritical&incCritRecov).