COVID19 Risk Calculator

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COVID 19 Risk Calculator

Age:
Gender: Under Development

Caveat – Underlying Health Conditions
Your risk is likely going to be significantly LOWER if you don’t have the below conditions. Your risk is likely going to be significantly higher if you have underlying conditions below.
The sample includes a mix of people with and without those conditions, therefore the rates are an average.
People with chronic lung disease or moderate to severe asthma
People who have serious heart conditions
People who are immunocompromised
Many conditions can cause a person to be immunocompromised, including cancer treatment, smoking, bone marrow or organ transplantation, immune deficiencies, poorly controlled HIV or AIDS, and prolonged use of corticosteroids and other immune weakening medications


People with severe obesity (body mass index [BMI] of 40 or higher)
People with diabetes
People with chronic kidney disease undergoing dialysis
People with liver disease

Risk Calculator Assumptions

Analysis and predictions are only as good as its assumptions and data, so here we explain the data and assumptions we used to get to our prediction.
The calculation is simply, for each age group:
1) The # of people hospitalized or dead from COVID19
2) The # of people of people estimated to be infected
Divide 1 by 2 to get the rate.
The data on #1 rates is per 100,000 population, so we just multiply by a rate of infection in the population to get the final result.
So for example, for the age 18-44 group… we take the rate of death per 100,000 population in NYC of 16.29, multiply by the estimated infection rate in population of 0.199, divide by 100,000 to get the rate per person, and multiply by 100 to get the %.

Hospitalizations and Deaths – Numerator


Data is sourced from NYC Department of Health:
This repository contains data on coronavirus (COVID-19) in New York City (NYC), updated daily. Data are assembled by the NYC Department of Health and Mental Hygiene (DOHMH) Incident Command System for COVID-19 Response (Surveillance and Epidemiology Branch in collaboration with Public Information Office Branch). You can view these data on the Department of Health’s website. Note that data are being collected in real-time and are preliminary and subject to change as COVID-19 response continues. Information on this page will change as data and documentation are updated.


The data shows hospitalizations and deaths in NYC as of May 4th 2020 as a rate per 100,000 of population. However, this alone doesn’t allow us to calculate risk because we don’t know how many are infected. So we use NY State estimate on # of infected.

Total Infected – Denominator

May 2nd NY State press briefing:
Amid the ongoing COVID-19 pandemic, Governor Andrew M. Cuomo today announced the results of the state’s completed antibody testing study, showing 12.3 percent of the population have COVID-19 antibodies. The survey developed a baseline infection rate by testing 15,000 people at grocery stores and community centers across the state over the past two weeks. Of those tested, 11.5% of women tested positive and 13.1% of men tested positive. A regional breakdown of the results is below:


Data is sourced from NY State Press Briefings.
As of May 2nd 2020, NY State estimates that 19.9% of NYC residents have been infected and recovered.
Caveat: To the extent that people haven’t recovered, this biases infected numbers down very slightly.
Caveat: To the extent the sample size checks people who are out at supermarkets, this biases infected numbers up.

Data Differentials

NYC unfortunately doesn’t release data on a granular level, only rolled up. What we can do, is to use differentials based on overall averages. This is a blunt instrument but that’s what we have available. We did not balance back based on population splits.

Gender

On the hospitalization and mortality side, NYC reports females had 412.52 rate of hospitalization and 122.16 rate of death per 100k population.
Males had 627.14 rate of hospitalization and 208.19 rate of death per 100k population.
This results in a male differential of 627.14/516.54=1.214 for hospitalizations and 208.19/163.41=1.274 for deaths on the numerator.
This results in a female differential of 412.52/516.54=0.799 for hospitalizations and 122.16/163.41=0.748 for deaths on the numerator.
On the infection side, NY State overall found 13.1% of men tested positive and 11.5% of women tested positive. Now when we abstract that to NYC specifically, with an overall 19.9% infection rate, we get 1.065 modifier on male and 0.935 modifier on female. For simplicity, we’re using an equal weighted average.
Combining the two leads to a male/female hospitalization differential of 1.14/0.855 and mortality differential of 1.196/0.8.

Data Sense Check

Imperial College London estimates an IFR of 0.66%, which is in the same ballpark as what’s being calculated here.
IFR is the infection fatality ratio, which is the deaths over all infections including mild and asymptomatic.
Mark H. Ebell, MD, MS, on March 31, 2020. (Source: Verity R, Okell LC, Dorigatti I, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis. [published online March 30, 2020]

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