兔子先生传媒文化作品

兔子先生传媒文化作品 researcher Daniel Larremore has never held a nasal swab and doesn鈥檛 wear scrubs. Instead, he relies on math to track the spread of human diseases.听

This week, Larremore and several colleagues from Colorado joined a nationwide study that seeks to use social media data to better understand how coronavirus cases might grow and travel in the coming weeks.听

The will draw on huge volumes of anonymized location information supplied by Facebook to follow how groups of people move from spot to spot over time. That will allow researchers like Larremore, an assistant professor in the Department of Computer Science and in the BioFrontiers Institute, to build maps that show where people are still traveling in the age of social distancing.听

It鈥檚 totally anonymous and designed with privacy as a top priority, he said.听

鈥淵ou can鈥檛 tell anything about individual mobility since Facebook gives us only anonymized and aggregated data,鈥� said Larremore. 鈥淏ut we will be able to see, for example, how many people went from Jefferson County to Boulder County last week and compare it to how many people made the same trip several weeks ago.鈥�

He and his colleagues will soon provide these maps to local public health leaders on a daily basis so that they can craft more efficient policies around how to slow the spread of the virus. 听

The Colorado team includes Ryan Layer, an assistant professor in computer science at 兔子先生传媒文化作品; Bailey Fosdick of Colorado State University; and Paul Doherty of the National Alliance for Public Safety GIS (NAPSG). The overall effort is led by researchers at the Harvard School of Public Health, Harvard Medical School and Direct Relief and includes scientists from across the country.

Larremore talked with 兔子先生传媒文化作品 Today about what complex mathematical equations, or numerical 鈥渕odels,鈥� can reveal about pathogens, and what may lie in store for Colorado.

You approach human diseases from a different angle than people might normally expect鈥攖hrough the lens of mathematics. What can this approach tell us about epidemics?

Historically, the math has helped us to understand the mechanisms by which diseases are spread. With Ebola, for example, the models helped us understand how transmission was occurring鈥攊n that case, through bodily fluids. With malaria, researchers named Ronald Ross and George Macdonald discovered that the disease spread through mosquitoes. They wrote down the model that still helps us understand mosquito populations and their role in malaria today.

What do those same types of calculations tell us about COVID-19?

They show that early on in an epidemic, growth is exponential鈥擨 think that鈥檚 the scariest part鈥攚hich means that it looks like a 鈥渉ockey stick.鈥� It feels far off, and then suddenly you鈥檙e in the middle of it. [Ed. note: This interview was conducted on March 24]

You鈥檝e compared COVID preparations to preparing for natural disasters. How so?

Early on, it鈥檚 kind of like when the government tells Florida citizens that a hurricane is eight days away. You look outside, and you say, 鈥榃hat are you talking about? I don鈥檛 see any clouds in the sky.鈥� But the models help you to see the storm beyond the horizon.

In this case, it鈥檚 different because we are the hurricane. We can do the social distancing and stop the spread, stop that approaching storm in its tracks.

What is it like being a researcher in the middle of a pandemic?

It鈥檚 really sad that these skills are needed. Everyone I know who does targeted epidemiological forecasts and modeling is working 24/7, minus whatever hours they get to sleep. It鈥檚 bizarre and, in some ways, exciting to be involved directly, but, also,听I wish it were under better circumstances.

What would you say to Coloradans who might be seeing that hurricane on the horizon and aren鈥檛 sure of what to do?

We need to buckle our seatbelts because it鈥檚 going to get worse before it gets better. Social distancing only works if you actually do it. If you have half the population self-quarantining and taking it seriously, and the other half don鈥檛鈥攖hey go hiking in a big group, or they crowd the bike paths鈥攊t doesn鈥檛 work. It鈥檚 not that it doesn鈥檛 work for them. It doesn鈥檛 work for anyone, and the time we spend in this awkward, half-social distancing process just gets drawn out.