COVID-19 Q&A

On Thursday, March 12, 2020, I was interviewed by a reporter at a newspaper in a mid-sized California city*. The topic was described to me as “a story about the panic associated with the virus — people clearing out stores of toilet paper, bottled water, etc.” I am not a topic expert on COVID-19, but was being interviewed by virtue of my expertise on collective social behavior (I did spend three years as a postdoctoral fellow at Johns Hopkins Med School in the department of Emergency Medicine, where I managed to pick up at least some epidemiology, and I regularly teach modeling contagion).

I was sent a number of questions in advance to prepare, though our conversation was over the phone. When it became apparent that I didn’t think people were overreacting, the reporter indicated that the story would probably be killed rather than reshaped to reflect more accurate information. I urged this person to flip the story and encourage people to adequately respond, but the more we talked, the less likely that seemed. Since the newspaper won’t cover it, I’m posting my brief answers to their questions here. I realize that a lot of people who follow my research will not need this information, but if anyone benefits from it, it seems worth it.

What is driving this behavior?

I think people are responding to a potential threat. There is a lot of uncertainty about what is going on. They are getting some conflicting information, but one common theme is: this is bad, and it is going to get worse before it gets better. From the epidemiological work I’ve managed to survey on COVID-19, I’d say this is accurate. My primary concern is not overreaction on the part of a few stockpilers, it’s underreaction on the part of both individuals and institutions who are not taking this serious. This is shaping up to be the worst pandemic since the 1918 Spanish flu, and could potentially be much worse in terms of both lives lost as well as economic impact. The US needs more measures to ensure social distancing, more and free access to testing and treatment, and better information put out to the public.

Is the panic worse than the threat?

Not by a long shot. This is very serious. We are maybe a couple of weeks behind Italy, and we are showing similar patterns as them and other countries when you control for when the first outbreaks were reported. In fact, the US likely has a lot more infected individuals than the numbers suggest, because of the lack of sufficient testing. In the next few weeks this is likely to get very bad, very quickly. As of today, Italy has over 17,000 confirmed cases with more than 1,200 deaths.

Keep in mind that we are talking about exponential increase. Some of the data from other countries suggest that, at least in the first few weeks, you can approximate the spread as a daily increase of 33%. If you start with just three cases and the number of infected increases by a third every day, in 5 days you have 12 cases. No big deal. In 10 days, you have 52 cases. In 3 weeks, you have over 1,000 cases, and in a month you’ve got 20,000 cases. Two more weeks after that, and you’ve exceeded a million cases. Now obviously there are limits to how high this number can go because of the way populations interact, but the early numbers at least are in line with how the virus has increased in countries that saw earlier outbreaks than us. We had a big lead to prepare for this, and we’ve wasted it.

Why do some people engage in this other behavior while others don’t?

I don’t know. Some people are probably more reactionary, and others are more stubborn. No one likes to have to change or cancel their plans, or be otherwise inconvenienced. Social networks and identities interact with practical and economic concerns.

How does the response to the virus compare to previous public threats (AIDS, 9-11, etc)?

We probably haven’t had a real public threat like this in 100 years. 9/11 was a vicious attack on one place at one time by a group of people who were able to exploit a weakness in a system. Look, I’m a native New Yorker and I lived in NYC in the aftermath of 9/11. The reaction from most people was a mix of solidarity – we’re in this together – and, you know, racism. Most importantly, the threat of it happening again was very small. People seem to dramatically overestimate the threat of terrorism. Even before this pandemic, most people are much more likely to die of disease than of terrorism.

AIDS is caused by a virus, so it’s perhaps more similar to now. During the AIDS crisis, the response was also completely inadequate, both by the public and by the government, and this was largely because it initially was mostly restricted to marginalized populations like gay men. But HIV is relatively difficult to transmit – you can’t catch AIDS from someone if they cough or sneeze on you or something you touch. You can catch Coronavirus that way.

Something else to remember is that the incubation period for something like flu is usually a couple of days. There’s not that much time between when you catch it and when you feel sick. With COVID-19, the time between when you catch it – and can infect others – and start showing symptoms appears to be up to two weeks! I’ve heard people say things like “There are no cases in my town yet” or “there aren’t many cases here.” Two things about this. First, there could be many people infected who aren’t yet symptomatic, who can still infect others. Second, the extent to which the US has failed to adequately test people for COVID-19 cannot be overstated. We need to be testing much, much more. I am confident that if we had an accurate picture of how the infection is spreading here, we’d have justification to be more worried.

Any advice on how not to find the balance between panic and not doing anything?

Don’t panic, but do worry. The best thing you as an individual can do is to avoid crowds, public transportation and airports, and wash your hands well and often. The Coronavirus binds to soap, so soap works better than hand sanitizer. The best thing that society can do is to encourage social distancing. This doesn’t just limit the number of infections. It can dramatically reduce the speed of infection, so that fewer people are sick at any given time. This is really important if we want to avoid overloading our hospitals, our healthcare systems, and to provide more time for new tests and treatments to be developed. It’s completely insane that any large gatherings are happening at all right now.

As for stockpiling – other countries have effectively shut down commerce as the virus has reached peak infection rates. I think it is entirely rational to cache a few weeks worth of food and other supplies. The CDC recommends a month’s worth of supplies.

Stay informed. Social media like Twitter is especially good for this. Follow experts, not pundits or politicians (but hold the politicians accountable).

 

*The name of the paper isn’t important. No one is perfect, and I don’t this is worth calling someone out on.

COVID-19: Modeling the Flattening of the Curve

It appears that we are in the middle of a global pandemic. COVID-19, caused by the SARS-CoV2 Virus (a form of Coronavirus) is spreading rapidly throughout the world. Some estimates suggest that more than half the world’s population will become infected over the next two years or so. This is serious: COVID-19 appears to be both more contagious and more deadly than most influenza strains, and it appears to be particularly dangerous for older people. While it’s important to note that these estimates are based on emerging and incomplete data, epidemiology is a fairly well developed science with strong methods for calculating these sorts of figures.

So, what can we do? Wash your hands. Cough and sneeze into your elbow. Stay home if you have symptoms. Cancel travel plans and avoid crowds and large gatherings.

I’ve noticed that a point of confusion sometimes arises here. If COVID-19 is already a pandemic, if its spread can’t be stopped, then what’s the point? Aren’t we all going to get infected anyway? Might as well get it over with, right? Especially if you’re young and not in a high-risk category, you might not see the point. In my Twitter feed, the point has been hammered repeatedly: flatten the curve. This figure by Esther Kim and Carl Bergstrom illustrates the meaning.

FlattenTheCurve

The left curve is the spread of the disease without interventions. People don’t wash their hands and don’t avoid travel and large gatherings. The disease spreads quickly. So many people are infected at once that hospitals and other healthcare systems are completely overwhelmed. This escalates infection and leads to more deaths among the infected, as well as among those who need care for unrelated illnesses and medical conditions. The right curve is the spread of the disease with interventions. A similar number of people still get infected, but the spread is sufficiently slowed that the number of people infected at a given time is much smaller, hopefully within the capacity of our healthcare systems. Flattening the curve has two major benefits. First, hospitals and other providers are able to handle the number of infected individuals at any given time. And second, there is more time for additional treatments to be developed and tested. Both of these things save lives. We need to flatten the curve.

I think that most people understand the benefits of behaviors like washing your hands and covering your mouth when you sneeze. After all, these are behaviors that help prevent you from getting sick or infecting others. But from talking to some people, it’s not always clear to everyone exactly how collective behaviors like avoiding crowds or canceling travel translates to slowing the spread of disease at the population level. In fact, these things are critically important. I wrote up this post in an attempt to illustrate why.

I teach a class at UC Merced called “Modeling Social Behavior.” And because of that class, I had at the ready a simple model of disease spread. It belongs to a family of models called “SIR models,” where the letters stand for Susceptible (meaning that you are uninfected but susceptible to the disease), Infected (meaning that you are both infected and contagious), and Recovered (meaning that you have either recovered from the illness and are neither susceptible nor contagious, or that you have otherwise been removed from the population). In this model, people (sometimes called “agents”) are situated in and move around on an abstract two-dimensional space. Anytime a susceptible individual is sufficiently close to an infected individual, they become infected with some probability (the transmission rate). An infected individual then recovers with a probability dictated by the disease’s recovery rate. The population looks like this. There are 500 agents. The white ones are susceptible, the red ones are infected, and the grey ones are recovered.

covidmodel

The model is not specific to COVID-19, and ignores aspects like incubation periods. I purposefully did not try to calibrate the transmission or recover rates to COVID-19. You should think about this as a generic model of disease transmission. The model parameter I want to focus on is one related to the agents’ mobility. At each tick of the model’s clock, each agent chooses a random direction to face and takes a step, which allows the agents to mix with each other. In other words, agent movement is just a random walk through space. By controlling the size of the step agents take on each movement, we can control the extent to which they move through social space, and thus the extent of social mixing. Here’s an example with two agents, both of which started in the exact center of the space and took 100 steps, with a line drawn between each location at each tick of the clock. The green agent takes small steps (of size 0.5 units – the entire grid is 51 x 51 units square). The orange agent takes large steps (of size 3 units). As you can see, the orange agent has covered substantially more ground than the green agent in the same amount of time. A population of orange agents, who widely explore their social space, will encounter far more unique individuals in a given time than a comparable population of green agents, who move narrowly and tend to interact with the same individuals over and over.

covid_walks

Whether agents move widely or narrowly in space can dramatically affect the dynamics of disease transmission. I started with a population of 500 uninfected agents and infected three of them at random. I then tracked the number of agents who were infected over time. Here are the results from simulations with narrowly (green) and widely (orange) mobile agents, defined as above as agents with a step size of either 0.5 or 3.0 units, respectively.

spread-fastslow

These look an awful lot like the “flatten the curve” figure at the top of this post! When agents move widely, the disease spreads very fast, and lots of them are infected at the same time. For this simulation, the maximum infection rate for widely mobile agents was 78%. For the exact same disease, with the same transmission rate and recovery rate, restricting agents to narrow mobility not only stretched out the time course of the epidemic, it also substantially reduced the maximum infection rate to only 25.6% — less than a third of what it was under widely mobile agents.

Here, I’ve plotted the maximum infection rates for a range of step sizes, running 30 simulations for each value. These are shown in red (the line connects the means for each step size). I’ve also plotted the proportion of individuals who never become infected over the course of the epidemic (in blue). Note that while this number is positive for very small step sizes (perhaps representing rapid and effective quarantines), it quickly goes to zero, meaning that everyone eventually becomes infected. But this figure also shows that even if everyone becomes infected eventually, reducing mobility and population mixing—by limiting travel and avoiding large gatherings—can dramatically reduce the number of people who are infected at any given time.

covidbatch

The code to run the model and explore it on your own is available here.The model was made with NetLogo, which you can download for free here. You can also upload the model to NetLogoWeb and launch it in your browser window without installing NetLogo on your computer.

UPDATE: You can now access a version of the model that you can run directly in your browser here.

 

Bad science evolves

Richard McElreath and I wrote a paper about how incentives to publish can create conditions for the cultural evolution of low-quality research methods. It’s called The Natural Selection of Bad Science (coming soon to an open access journal near you), and it’s already gotten a few write-ups, for which I’m grateful. I mention this because the Society for Personality and Social Psychology (SPSP)’s Character and Context blog asked me to write a post about the paper, which I did. Check it out.

Bad Science Evolves. Stopping It Means Changing Institutional Selection Pressures.