Interactive Projection Tool for COVID-19 Interventions

Specify data to compare model outcomes against

What data are you entering?

Instructions

Enter data in the data table to compare with model outcomes.

Daily observed data entered will be automatically cumulated and available for visualization as daily and cumulative outcomes in the Comparison to Data tab.

Feel free to tune the model parameters to reflect what you believe best represents the trend in the data.

Where can I find data to use here?

Check out sources such as:

covidtracking.com
Johns Hopkins CSSE Repository
New York Times Data Repository
U.S. CDC - COVID-19 Cases in U.S.

Enter observed data in the Data Input page and compare model outcomes against it here.

Select the Comparison Data Set

Outcomes format:

Select Compartments Shown

Susceptible

Exposed

Asymptomatic

Symptomatic

Recovered

Download Compartment Flows Data

Outcomes format:

Download Cases Data

Outcomes format for deaths:

Download Deaths Data Download New Case Ratio Data

Outcomes format:

Download Advanced Cases Data Download Symptoms Data

Model Structure

Similar Work

See similar projects, such as:

About C-SPEC

Please feel free to reach out to us with any questions at c19spec@gmail.com

How can I find out more?

Learn more about us at our website https://covid-spec.org.

Visit the GitHub repository for this project at https://github.com/abilinski/COVID19.

Read our technical documentation, linked below for download.

Download our Technical Documentation

Base case parameters

simulation time (days)

p: Pr(transmission per contact)

Disease Free Equilibrium Doubling Time

δ: 1/(dur of incub)

γ: 1/(dur of infectious)

ongoing infections at day 1

n: total population

Symptomatic detection rate

Asymptomatic detection rate

k_det_c: rel. rate of transmission for detected

Download parameters

s: Frc socially distanced

e: Social distance multiplier

κ: rel. Pr(trans) for asymp

m1: mortality yng

m2: mortality med

m3: mortality old

k_report: rel rep rate for yng

hosp: hospitalization rate for infected

resp: rate of needing respirator for infected

α1: Pr(asymp) yng

α2: Pr(asymp) med

α3: Pr(asymp) old

Frc youth

Frc adults

Frc older adults

k_inf: rel infectiousness for yng

k_susp: rel. suscep for yng

Contact Rates (not-socially-distanced)

[0,20) [0,20)

[0,20) [20,65)

[0,20) 65+

[20,65) [0,20)

[20,65) [20,65)

[20,65) 65+

65+ [0,20)

65+ [20,65)

65+ 65+

Contact Rates (socially-distanced)

[0,20) [0,20)

[0,20) [20,65)

[0,20) 65+

[20,65) [0,20)

[20,65) [20,65)

[20,65) 65+

65+ [0,20)

65+ [20,65)

65+ 65+

* Please note that the estimated doubling time and Re are only sensible during exponentail growth period.

Intervention parameters

p: Pr(transmission per contact)

Disease Free Equilibrium Doubling Time

δ: 1/(dur of incub)

γ: 1/(dur of infectious)

ongoing infections at day 1

n: total population

Symptomatic detection rate

Asymptomatic detection rate

k_det_c: rel. rate of transmission for detected

Download parameters

s: Frc socially distanced

e: Social distance multiplier

κ: rel. Pr(trans) for asymp

m1: mortality yng

m2: mortality med

m3: mortality old

k_report: rel rep rate for yng

hosp: hospitalization rate for infected

resp: rate of needing respirator

α1: Pr(asymp) yng

α2: Pr(asymp) med

α3: Pr(asymp) old

Frc youth

Frc adults

Frc older adults

k_inf: rel infectiousness for yng

k_susp: rel. suscep for yng

Contact Rates (not-socially-distanced)

[0,20) [0,20)

[0,20) [20,65)

[0,20) 65+

[20,65) [0,20)

[20,65) [20,65)

[20,65) 65+

65+ [0,20)

65+ [20,65)

65+ 65+

Contact Rates (socially-distanced)

[0,20) [0,20)

[0,20) [20,65)

[0,20) 65+

[20,65) [0,20)

[20,65) [20,65)

[20,65) 65+

65+ [0,20)

65+ [20,65)

65+ 65+