Challenges in Modeling SARS-CoV-2: Bridging the Best of Both Worlds - - PowerPoint PPT Presentation

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Challenges in Modeling SARS-CoV-2: Bridging the Best of Both Worlds Between Models and Reality

Michael Li - McMaster University

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Background

2 June 26, 2020

Theoretical, statistical and computational approaches to study biology MacTheoBio Infectious diseases Spatial ecology Evolution Math and Statistics

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Background

3 June 26, 2020

Theoretical, statistical and computational approaches to study biology MacTheoBio Infectious diseases Math and Statistics

Malaria Ebola Influenza Canine Rabies HIV etc..

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Background

4 June 26, 2020

Theoretical, statistical and computational approaches to study biology MacTheoBio Infectious diseases Math and Statistics

Malaria Ebola Influenza Canine Rabies HIV etc..

I can read Chinese!

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2019–2020 WuHan Novel Corona Virus Outbreak Part 1

June 26, 2020

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Background

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2019–2020 WuHan Novel Corona Virus Outbreak

• Late December 2019, several

suspicious cases of pneumonia in Wuhan City, Hubei Province of China.

• Unknown virus
• Early January 2020, Chinese

authorities confirmed that they had identified a new virus.

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Data collection

7 June 26, 2020

Jan 21st 24:00 105 new cases, 3 discharge and 3 death 375 Cumulative cases 28 Discharged 9 death

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The Basic Reproductive Number/Ratio (R0)

8 June 26, 2020

• Expected number of new cases per case
• Good index of risk at the population level

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The Basic Reproductive Number/Ratio (R0)

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Most Valuable Piece

• f information in disease modelling

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• Expected number of new cases per case
• Good index of risk at the population level

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WH outbreak R0 Estimates

10 June 26, 2020

Majumder, M.S. and Mandl, K.D., 2020. Early in the epidemic: impact of preprints on global discourse about COVID-19 transmissibility. The Lancet Global Health, 8(5), pp.e627-e630.

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• Exponential growth rate (r)
• Generation Interval

Exponential Fitting Framework

11 June 26, 2020

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• Exponential growth rate (r)
• Generation Interval

Exponential Fitting Framework

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Exponential growth rate (r)

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• Estimate from time series

data

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Exponential growth rate (r)

14 June 26, 2020

• Estimate from time series

data

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Exponential growth rate (r)

15 June 26, 2020

• Estimate from time series

data

X

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Exponential growth rate (r)

16 June 26, 2020

• Estimate from time series

data

• Fitting to incidence data
• Logistic model with

negative binomial noise

• epigrowthfit package in R

Ma, J., Dushoff, J., Bolker, B.M. and Earn, D.J., 2014. Estimating initial epidemic growth rates. Bulletin of mathematical biology, 76(1), pp.245-260.

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• Exponential growth rate (r)
• Generation Interval

Exponential Fitting Framework

17 June 26, 2020

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Generation interval

18 June 26, 2020

• Time between

infections

• Focal individual

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Generation interval

19 June 26, 2020

• Time between

infections

• Focal individual
• Infection are hard to
• bserve
• Serial intervals
• Time between

symptom onsets

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• Exponential growth rate (r)
• Generation Interval

Exponential Fitting Framework

20 June 26, 2020

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• Exponential growth rate (r)
• Generation Interval

Exponential Fitting Framework

21 June 26, 2020

Euler-Lotka equation

Wallinga, J. and Lipsitch, M., 2007. How generation intervals shape the relationship between growth rates and reproductive numbers. Proceedings of the Royal Society B: Biological Sciences, 274(1609), pp.599-604.

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• Exponential growth rate (r)
• Generation Interval (GI)
• Mean GI ( )
• Dispersion ( )

Gamma approximation framework

22 June 26, 2020

Park, S.W., Champredon, D., Weitz, J.S. and Dushoff, J., 2019. A practical generation-interval-based approach to inferring the strength of epidemics from their speed. Epidemics, 27, pp.12-18.

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R0 estimates

23 June 26, 2020

Park, S.W., Bolker, B.M., Champredon, D., Earn, D.J., Li, M., Weitz, J.S., Grenfell, B.T. and Dushoff, J., 2020. Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak. (In press)

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Parameter Uncertainties

24 June 26, 2020

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Parameter Uncertainties

25 June 26, 2020

• Uncertain of R0 comes from these

parameters

• Important to propagate uncertainties

from all the parameters

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Forecasting

26 June 26, 2020

Li, M., Dushoff, J. and Bolker, B.M., 2018. Fitting mechanistic epidemic models to data: A comparison of simple Markov chain Monte Carlo approaches. Statistical methods in medical research, 27(7), pp. 1956-1967.

Reports

• Bayesian Discrete-time SIR
• Dual beta-binomial process
• Transmission and
• bservation
• 2 week projection

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Summary

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• Easy to make a model
• Extremely hard to make models that:
• are informative
• predict well
• work in real time
• Discrepancies between R0 estimates is

hard to understand

• Method
• Data
• Hard to communicate clearly.
• E.g. R0 ~ 3 (2,4)

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Summary

28

• Easy to make a model
• Extremely hard to make models that:
• are informative
• predict well
• work in real time
• Discrepancies between R0 estimates is

hard to understand

• Method
• Data
• Hard to communicate clearly.
• E.g. R0 ~ 3 (2,4)

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• Predictions of the short-term

trajectories are useful

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Moving forward and preparing for the global pandemic

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• Interesting and important to figure out the discrepancies
• What else? What do people want to know?

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Preparing for the global pandemic

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Preparing for the global pandemic

31 June 26, 2020

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Distributions of delays associated with COVID-19 healthcare in Ontario, Canada Part 2

June 26, 2020

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Preparing for the global pandemic

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Distributions of delays associated with COVID-19 healthcare in Ontario, Canada

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Time intervals

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Time intervals

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Isolation time Specimen collection time Reporting time ER time Hospital admission time ICU time

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Chronological Episodes (Symptom onset)

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Days

Delay

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Chronological Episodes (Isolation)

Days Days

Delay

Duration June 26, 2020

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Chronological Episodes (Specimen collection)

Days

Delay

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Chronological Episodes (ER)

Days Days

Delay

Duration June 26, 2020

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Chronological Episodes (Hospitalization)

Days Days

Delay

Duration June 26, 2020

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Chronological Episodes (ICU)

Days Days

Delay

Duration June 26, 2020

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Chronological Episodes (Death)

Days

Delay

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Chronological Episodes (Intubation)

Days Days

Delay

Duration June 26, 2020

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Chronological Episodes (Ventilator)

Days Days

Duration

Delay

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Admissions, Durations and Occupancies

Daily Admissions

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Admissions, Durations and Occupancies

Daily Admissions Durations

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Admissions, Durations and Occupancies

Daily Admissions Durations Occupancy

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Distributions of delays associated with COVID-19 healthcare in Ontario, Canada

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Changes over time

June 26, 2020

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New Confirmations

50 June 26, 2020

Ontario, Canada

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Testing capacity

51 June 26, 2020

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Testing capacity

52 June 26, 2020

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Backlog ratio

53 June 26, 2020

(test/day) (test) Backlog newTests ~ X days to clear the backlogs

Backlog ratio

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Changes in Delays over time

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Backlog ratio

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Summary

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• Early detection is key in controlling the spread of covid
• Reduce delay -> earlier isolation/treatment
• What components we can take back to the modelling world to improve

models

• e.g. Hospitalization data
• Duration spent in treatment
• Combining different data streams to model

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McMaster Pandemic

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• SEIR model
• Including Hospitalization

time series

• Using empirical delay/

duration distributions to parameterize the flow of the compartments

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Additional features

• mobility from google and apple

https://github.com/bbolker/McMasterPandemic

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Distributions of delays associated with COVID-19 healthcare in Ontario, Canada

57 June 26, 2020

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Final remarks

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• Easy to be tunnel visioned in the model world
• Important to get a sense what is happening in reality
• Bridging the knowledge gap in both directions (Public Health and Modelling)

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Final remarks

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• Easy to be tunnel visioned in the model world
• Important to get a sense what is happening in reality
• Bridging the knowledge gap in both directions (Public Health and Modelling)

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• Small piece of the pie

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Acknowledgments

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• Dr. Jonathan Dushoff
• Dr. Ben Bolker
• Dr. David Earn

Sang Woo Park (Princeton University) David Champerdon (University of Western Ontario) Morgan Kain (Stanford University) Irena Papst (Cornell University) MacTheoBio Steve Cygu Chyun Shi Martin Stelmach McMaster University CIHR IIDR @ McMaster U PHAC PHO

June 26, 2020