z.umn.edu/LINCS

Matt Michalska-Smith

This talk was recorded for the MIDAS Network Annual Meeting as a video presentation on 30 April 2021, and was presented on 10 May. Text here will supplement slide material.

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Marie Gilbertson

Lauren White

Meggan Craft

New York Times, April 2020

A little over a year ago, there were widespred lockdowns across the US. In this map from the New York Times, we see that many states invoked state-wide lockdowns on travel and business. This was a blunt tool to try to avoid a rising catastrophe, but the reasoning behind it was rooted in an understanding of how diseases are transmitted from person to person; if we could prevent disease-spreading contacts, then we could pre-empt the pandemic. It doesn't take a disease ecologist to realize that there is room for improvement in this approach. For instance, what if we could limit our intervention to preventing only those contacts that are most critical to disease spread, leaving other interactions, perhaps even the majority of interactions, intact at the same time.

Network

Disease Model

What is contact?

What makes a contact network realistic?

Home/Family
School
Work
Religious institutions
Hospitals
Nuring homes

image adapted from Monroe et al. 2021

To do this we had to answer a couple of basic questions, such as "What is a contact?" The answer to this question is obviously context specific, but with COVID-19, with its aerosolized transmission, we think about the risk of transmission increasing with the duration of people sharing the same air space.

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But of course the ways in which we are close to other people is also context dependent, leading to the key insight for this project: the structure of our interactions with other people is dependent on the different ways in which we interact with different facets of our social network.

To put it more concretely, we interact with co-workers differently than we interact with people at home, or at a religious institution. The differences in these interactions, including the strength of interaction and the interacting group size, can have consequences for the spread of disease.

Interaction properties

Node properties

So, we begin to assemble our networks: starting with a collection of individuals, whose ages are distributed according to some locality's census data and grouping them into households, based on the empirical distribution of household sizes. We then successively layer additional interaction types, including schools,

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work-places,

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and possibly others (each likewise based on empirical data whenever possible).

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Importantly, because each node has an age associated with it, we can also classify some individuals as being more vulnerable to adverse outcomes from COVID, using age-normalized hospitalization rates. Here, we dichotomize individuals into "Vulnerable" or "Not" for simplicity.

Disease Model

I want to take a minute to run through the underlying disease model, but since I'm sure most of you have seen these types of models explained, and perhaps explained them yourselves, multiple times, I will keep it very brief.

At each timestep in a simulation, every individual in the network has one of six states. They start out as Susceptible to disease and can become infected when they share an edge, representing a social contact, with an infectious individual.

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Upon infection, they enter a latency period and are classified as Exposed, but not yet infectious. Over time, they transition to being I/Infectious, and some fraction will develop symptoms.

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As more time passes, some of these will Recover,

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while others will sadly Die.

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The final piece of the puzzle is that those individuals that we classified as vulnerable have both longer disease courses (slower recovery),

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and are more likely to die, modifying these two parameters as shown.

What does this look like in a single simulation?

Layered Interaction Network
COVID-19 Simulator

Matt Michalska-Smith

Marie Gilbertson

Lauren White

Meggan Craft

New York Times, April 2020

Network

Disease Model

What is contact?

What makes a contact network realistic?

image adapted from Monroe et al. 2021

Interaction properties

Node properties

Disease Model

Layered Interaction Network COVID-19 Simulator

Thank you!

Layered Interaction Network
COVID-19 Simulator