An Epidemic Simulation At The U.S. Naval War College Provides Lessons For The Coronavirus Pandemic

by

A deadly disease caused paralysis in decision-making at the top and misinformation to spread on social media—in a simulated epidemic from September 2019 that provides hard lessons for today.


https://specials-images.forbesimg.com/imageserve/5ed132df7f63de00066e0167/960x0.jpg?cropX1=0&cropX2=1280&cropY1=118&cropY2=838
Benjamin Davies led an epidemic simulation in September 2019 that has eerie parallels to the current ... [+] pandemic.Benjamin Davies

In September 2019, Benjamin Davies, who creates war games for the U.S. Naval War College, designed a simulated epidemic to improve crisis management among experts who combat similar situations in real life. In the simulation, an infectious disease spread through a densely populated city with 21 million people and pockets of inequality that became a hotbed for contagion. Those who contracted the virus suffered a cough and a raging fever that led to respiratory failure. Even when a cure was developed, authorities couldn’t prevent a cascade of failures.

Of course, Davies wasn’t thinking of the current coronavirus pandemic when he created the game. He had another infectious disease in mind, namely Ebola. But the results of that simulation provide insight into what’s going wrong in the response to the Covid-19.

The simulation’s goal was for participants to act as they would in their real-life roles in the event of a similar threat. To make it as accurate as possible, the US Naval War College teamed up with the National Center for Disaster Medicine and Public Health and the Johns Hopkins Applied Physics Laboratory and brought together 50 stakeholders from organizations, many of which are now responding to the Covid-19 pandemic. Experts from the State Department, the US Health and Human Services and the Centers for Disease Control and Prevention (CDC) came to Laurel, Maryland for the two-day workshop in September, along with representatives of the private sector and NGOs.

“We wanted to identify risks and come up with ideas to remedy decision paralysis,” Davies says.

No one expected the war game become reality so soon. “The timing is uncanny,” says Captain Alexander Soukhanov, director of Moran Cyber Shipping and a simulation participant.

What the simulation unearthed was a dynamic that hampered effective crisis management: a preference for inaction.

The idea of the “Urban Outbreak 2019” simulation came to Davies and his colleagues at a civilian-military humanitarian workshop, when they realized there was surprisingly little written about disaster response in big cities. Response to epidemics has been professionalized for rural environments, but cities create a unique challenge because they operate in some ways like a living organism, where different organs interact. The simulation’s aim was to identify risks in such a dangerous scenario and work out ideas to overcome them.

The simulation began with the World Health Organization (WHO) declaring a Public Health Emergency of International Concern. A fictional virus called P.ashlii spread with a high reproduction value, induced flu-like symptoms and caused a small part of the population to wind up in intensive care. Over 90,000 infected with P.ashlii died. Ironically, some experts invited to the war game found this storyline unrealistic, and so the war game had to be toned down before the simulation began.

Months later, it has become clear to these researchers that a learning opportunity to prepare for a pandemic was lost.

Phase One: A Chaotic Response

The first weeks of the simulation were geared to be the time for relevant agencies and organizations to gather information and work out who is in charge. “The first five steps in mitigating an outbreak are far more important, than the last 50 moves,” says Davies.

What the simulation unearthed instead was a dynamic that hampered effective crisis management: a preference for inaction. Players from the military and government agencies were quick to provide reasons why they could not act, according to a summary report of the simulation. They also avoided getting involved with the affected population, preferring instead to work on coordination with each other, notes Davies.

“The big fear was that we wouldn't coordinate enough, or we wouldn't follow the right command and control structure, or we wouldn't be creating a great common operating picture,” he says.

Representatives of the CDC, the US Department of Health and Human Services (HHS) and the US Agency for International Development (USAID) were more concerned with “nebulous high-level policy issues,” according to the summary report, and focused more on details about the command structure. These representatives actively avoided discussing how to distribute the antibiotics needed to heal the disease in favor of bureaucratic issues.

Frontline healthcare workers and first responders participating in the simulation, were considered to be a better source of realistic assessment, according to Davies, and were frustrated with the response of the military and USAID. “Health care workers don’t need to waste time discussing coordination – our mission is the population in front of us,” humanitarians said in the summary report.

Phase Two: Misinformation And Supply Shortages

“The bug exploded in the second phase” of the exercise, Davies says, which simulated the third month of the outbreak. By this time misinformation was spreading in the population about the fictional disease. One element designed by the researcher was that many in the public believed the government was using the outbreak to kill slum dwellers and take back land.

Short supplies in medical equipment and the failing medical system created ripple effects in the simulation, both good and bad. For example, there was a lot of generosity and donations among the simulated public. But the outbreak exacerbated existing deficiencies, too. Debt, spousal abuse and drug problems ticked up. Health systems and supply chains started to collapse, public services became intermittent, and hoarding and theft led to extremely lucrative black markets.

Participants had to rely on themselves when there was no guidance or authority coming from the federal government.

As a consequence, the risk for certain population groups would rise. Within the simulation, Davies constructed game scenarios which sound realistic in the current pandemic. If ambulances couldn’t handle the high number of emergency calls, people started taking informal transportation and cabs to get to the hospital. But cab drivers didn’t necessarily want to serve as ambulances, so only a handful were simulated to be willing to take the risk, though the number grew as it became more lucrative to give rides.  “It’s a race to the bottom in terms of risk for the cab driver,” Davies says.

Davies observed another behavior that he’s seeing again in the current pandemic. While professionals in charge of responding to an outbreak are the best in their field, they don’t feel confident about making large scale decisions affecting so many levels. “The hard part about a pandemic is that it requires us all to get out of our expertise,” he says. An epidemiologist doesn’t just make strictly medical decisions, but also has to consider their feasibility and economic implications. If those decisions don’t get made, a leadership vacuum can emerge, leading to hesitation and confusion.

As the simulation progressed, Davies observed that national government agencies “pretty much abdicated any interest in this city out of political paralysis.” Within the gameplay, this meant that participants had to rely on themselves when there was no guidance or authority coming from the federal government.

“The truly scary thing for many people is probably that they themselves are the best response there is,” says Davies.

Government paralysis made non-governmental organizations and the private sector stand out in the game, because it was clear that they couldn’t do their work without engaging those, who were affected by the outbreak. “NGOs are used to being independent and making decisions with little or no support,” says Davies.

For Alex Soukhanov, a long-time logistics professional, exercises such as this are nothing out of the ordinary. He and his company’s global network don’t only meet in times of crisis. Many industries have built up global networks which are regularly mobilized to mitigate risks, he says. “If there is a risk for one member, there is a risk for all,” he says about the security of supply chains.

Phase Three: Aftermath

When the disease finally stopped spreading,  participants were left working to recover the economy, coping with still-ongoing public health emergencies, burying their dead.

Davies was surprised to see that players blindly accepted the data they were given. 

In the end phase of the simulation, there were 90,000 bodies in one city that needed to be buried or disposed of. “Everyone just took it as given, that people could do this,” says Davies. The Red Cross Movements took the role of mortuary affairs, but they had never been asked to dispose of 90,000 bodies in three months. This showed that even an established organization may not be able to scale its capacity in the extreme circumstances created by an outbreak.

In the final round, the reported number of infections fell dramatically. Though the reports given the players never clearly indicated the reason for this decline, many of them thought this reflected their successful response. Davies expected players to question the reliability of the numbers, and was surprised to see that players blindly accepted the data they were given. 

What The Simulation Teaches Us

https://specials-images.forbesimg.com/imageserve/5ed1350bd7ac8c00062b470a/960x0.jpg?cropX1=32&cropX2=1214&cropY1=116&cropY2=781
Davies was surprised that the simulation revealed players blindly accepting data, and that people in ... [+] charge had a preference for inaction.Benjamin Davies

The scale of the Urban Outbreak 2019 in the mythical city of Olympia cannot be compared to a real-life pandemic like Covid-19. The phases of crisis management and dynamics of response in the game, however, can help participants better understand what affected countries are going through. One problem that Davies took away from this is: “We’re too networked.”

What he means is that unlike the “Urban Outbreak 2019” or other humanitarian crisis that might be localized, the high number of countries affected by Covid-19 creates a unique situation. According to Davies, the usual progression of humanitarian response assumes an overwhelmed country can request support from somewhere else. That assumption breaks down when a crisis is global.  

“Under the current circumstances everybody is for themselves,” he says. Italy’s first desperate requests for medical supplies in mid-March remained unheard by its European neighbors, who feared shortages of masks and ventilators in their countries. While the Italian government eventually received help from some states, this experience goes to show that countries can’t necessarily rely on international partners to step in and help during a pandemic.

Despite all this, Davies sees a grim silver lining to Covid-19. According to data from the World Health Organization, previous epidemics have involved diseases that kill at a far higher rate: Ebola has an approximate case-fatality rate of 50%, MERS has a 34% case-fatality rate and smallpox kills 30% of the infected and is more contagious than the Covid-19. With those numbers in his head, Davies says the current crisis could have been worse. “I am happy we’re not facing a pandemic with an even deadlier virus,” he says.

Full coverage and live updates on the Coronavirus