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What is the purpose of inoculating the pigs in both isolators 1 and 2? Seems like the isolator 3 pigs could have been infected by either set of inoculated pigs, & this was a missed opportunity to test aerosol transmission distance limits/sensitivity.

Thanks to the Delphi Group at Carnegie Mellon for sharing their survey data!

And thanks to you, dear reader, for making it this far! 😅

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We still need additional contact surveys in the US, esp. focused on
🚸 children
👭 assortative mixing patterns (when people interact w/ others w/ similar characteristics)
📅 individual behavior change over time

Our pandemic & baseline contact estimates are available at github.com/bansallab/re...

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3️⃣ During the pandemic & at baseline, younger adults, men, & Hispanic & Black individuals have more contacts & are at greater disease risk

These geographic & social differences in risk can help target public health resources & surveillance 📢

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2️⃣ Contact patterns vary across US counties regardless of disease 🌎

Based on population density, we expected urban counties 🏙️ to have higher contact rates than rural ones 🚜

This is true at baseline, but not during the pandemic, when urban areas were more responsive to gathering restrictions

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If contact rates aren’t changing much over time, then increased winter respiratory infections may be driven more by where contact is happening (indoors 🏢 vs outdoors ⛰️ ) rather than by an increase in overall contacts

See @zsusswein.bsky.social's paper for more on this: doi.org/10.7554/eLif...

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1️⃣ Early in the pandemic, contact varied over time 📆

However, contact and COVID-19 incidence were anti-correlated during this period (when disease went ⬆️, contacts went ⬇️)

Thus, after controlling for disease, there was no longer any systematic variation in contact over time

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I know what you're thinking

"These survey data are from early in the pandemic, and it's 2025... 🙄 Is this even relevant?"

We got you! 🫡

By controlling for the effect of cases, vaccines & pandemic policies on contact, we inferred baseline contact patterns in the US 🎉

So what did we find?

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Here, we tackle these questions using a large survey in the US from June 2020 to April 2021 📝

Contacts are defined as either:
🗣️ conversations >5 mins long w/ someone <6 ft away
or
🫂 physical contact

We analyze the average # of contacts in each county for each week in the study period

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Hopefully, you're convinced that contact patterns are important by this point.

Yet we know relatively little about them in the US! 😧

🗺️ Do contact rates differ across counties?
☃️ Are contact rates ⬆️ in winter, driving resp. infections, like flu?
👵 How do contacts vary with age, gender, & race?

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For this reason, we model disease spread on networks, where some people have more connections than others.

And theory suggests that the people with more contacts are more likely to get infected 🤒

Thus, understanding contact patterns can help us better estimate individual & population risk!

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Initially, disease models relied on the homogeneous mixing assumption, where each person has the same number of contacts 👯‍♀️ #twins

But from past surveys (eg POLYMOD) we know that there's actually lots of variation in # of contacts across individuals & this heterogeneity affects disease spread! 🤓

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Interactions between individuals (contacts) provide opportunities for respiratory infectious disease transmission 🦠

By studying these interactions and incorporating them into mathematical models, we can better predict how far and fast diseases can spread 📈

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