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Disease models & differential equations: connecting geographies with time series clustering

May 2, 2020 by Carlo Bailey
To explore more on COVID-19, please go to covid19.topos.com

Topos
Topos
May 2 · 8 min read
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Animation of an SIRD model with changing parameters (from Wikipedia)

What are disease models?

The mechanics of an SIRD model

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Animation of an SIRD model with changing rho parameter

Curve fitting and parameter extraction

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Example of output from polynomial regression showing values of the three parameters and the curve fitted to real world data for the Los Angeles county

Relationship between model parameters and spatial features

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Selected correlates of the extracted Rho parameter (capturing the effectiveness of social distancing)
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Selected correlates of the extracted contact-rate parameter Beta*Rho

Clustering geographies based on curves

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Total number of cases over time by cluster.
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Growth in new infections versus population per square mile, sized according to total cases and colored by cluster.
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Left: Counties that are seeing above average growth in new cases with below average density (people per square mile). Right: Counties with below average growth in new cases with above average density (as of 23rd April 2020)
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Downtown Virginia Beach City, VA
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Percentage of the population staying at home over the last 7 days
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Five Clusters displayed on the map


To explore more data on Covid-19, please go to covid19.topos.com

topos.ai

topos.ai

Topos

Written by

Topos

Transforming the way we understand cities with Artificial Intelligence | @topos_ai

topos.ai

topos.ai

topos.ai

Topos

Written by

Topos

Transforming the way we understand cities with Artificial Intelligence | @topos_ai

topos.ai

topos.ai

topos.ai

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