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The Model

How does the CHIME model work?

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Compartmental Modeling

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​Discrete-time SIR modeling of infections/recovery

The model consists of individuals who are either Susceptible (S), Infected (I), or Recovered (R).

The epidemic proceeds via a growth and decline process. This is the core model of infectious disease spread and has been in use in epidemiology for many years.

The dynamics are given by the following 3 equations.

To project the expected impact to Penn Medicine, we estimate the terms of the model.

To do this, we use a combination of estimates from other locations, informed estimates based on logical reasoning, and best guesses from the American Hospital Association.

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Parameters

The model's parameters, and , determine the severity of the epidemic.

β can be interpreted as the effective contact rate: β=τ×c

which is the transmissibility Ï„ multiplied by the average number of people exposed c. The transmissibility is the basic virulence of the pathogen. The number of people exposed c is the parameter that can be changed through social distancing.

γ is the inverse of the mean recovery time, in days. i.e.: if γ=1/14 then the average infection will clear in 14 days.

An important descriptive parameter is the basic reproduction number, or . This represents the average number of people who will be infected by any given infected person. When is greater than 1, it means that a disease will grow. A higher implies more rapid transmission and a more rapid growth of the epidemic. It is defined as

is larger when

  • the pathogen is more infectious

  • people are infectious for longer periods of time

  • the number susceptible people is higher

A doubling time of 6 days and a recovery time of 14.0 days imply an ​of 2.71.

Effect of social distancing

After the beginning of the outbreak, actions to reduce social contact will lower the parameter . If this happens at time , then the effective reproduction rate is , which will be lower than .

For example, in the model, a 50% reduction in social contact would increase the time it takes for the outbreak to double, to 27.5 days from 6.00 days, with a of 1.36.

Using the model

We need to express the two parameters β and γ in terms of quantities we can estimate.

  • : the CDC recommends 14 days of self-quarantine, we'll use .

  • To estimate directly, we'd need to know transmissibility and social contact rates. Since we don't know these things, we can extract it from known doubling times. The AHA says to expect a doubling time ​ of 7-10 days. That means an early-phase rate of growth can be computed by using the doubling time formula:

  • Since the rate of new infections in the SIR model is and we've already computed , becomes a function of the initial population size of susceptible individuals .

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Initial Conditions

  • The default value for the total size of the susceptible population defaults to the entire catchment area for Penn Medicine entities (HUP, PAH, PMC, CCH)

    • Delaware = 564696

    • Chester = 519293

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Additional references

Discrete-time SIR modeling:

Montgomery = 826075

  • Bucks = 628341

  • Philly = 1581000

  • For other default values, please consult the section.

  • St+1=St−βStItS_{t+1} = S_{t} −βS_{t}I_{t}St+1​=St​−βSt​It​
    It+1​=It+βSt​It​−γIt​I_{t+1}​ = I_{t} + βS_{t}​I_{t}​−γI_{t}​It+1​​=It​+βSt​​It​​−γIt​​
    Rt+1​=Rt+γIt​R_{t+1} ​= R_{t} + γI_{t}​Rt+1​​=Rt​+γIt​​
    β\beta β
    γ\gammaγ
    R0R_{0}R0​
    R0R_{0}R0​
    R0R_{0}R0​
    R0=β/γR_{0}=\beta / \gamma R0​=β/γ
    R0R_{0}R0​
    R0R_{0}R0​
    ccc
    ttt
    RtR_{t}Rt​
    R0R_{0}R0​
    RtR_{t}Rt​
    γ\gammaγ
    γ=1/14\gamma = 1/14γ=1/14
    β\betaβ
    TdT_{d}Td​
    g=21/Td​−1g=2^{1/T_{d}}​−1g=21/Td​​−1
    g=βS−γg=\beta S - \gammag=βS−γ
    γ\gammaγ
    β\betaβ
    β=(g+γ)\beta = (g+\gamma)β=(g+γ)
    https://mathworld.wolfram.com/SIRModel.htmlarrow-up-right
    Data Inputsarrow-up-right