Faculty Creates Modeling Tool to Help Predict the Coronavirus Pandemic’s Impact
Many of the students in Alex Hoyt’s Doctor of Nursing Practice class manage large health care systems, and the COVID-19 pandemic has been dominating their work over the past two months. To help students get a handle on the scope of the pandemic, Hoyt, PhD, RN, developed a hands-on Excel tool allowing these nurse leaders and other health care administrators to model the spread of the virus and measure the impact of community mitigation efforts like school closures and social distancing. How many daily ER admissions will happen in three months if the quarantine is lifted in two months? How many additional ER beds will be needed and by when? The answers to these questions will guide not only government policy but just as importantly, the logistics of public health systems across the country.
The Numbers, In a Nutshell
The statistics for COVID-19 are changing on a daily basis as new data is released and social distancing increases; this is why it is helpful for nurse leaders to be able to tweak their own models to test a range of assumptions and show different scenarios. “We are all looking for a way to flatten the curve of infection and not overwhelm health care systems,” says Hoyt.
Hoyt has spent the past 10 years providing doctoral education for nurse leaders who manage emergency room departments, primary care facilities, and many other health care sites. Right now, he is seeing his work play out in real time.
His tool applies a Susceptible-Infected-Recovered (SIR) model to COVID-19 and works by projecting the number of people who are susceptible, infected, and recovered (immune) based on the transmissibility of the virus, the contact between those in the susceptible and infected groups, and time it takes to move from the infected to the recovered group. Similar models are used by governments to forecast the peak. Hoyt explains, "The Excel version is a less sophisticated model presented in a more accessible format." He also developed a video for his class to help explain his SIR model and Excel tool.
Policies and recommendations around COVID-19 are shifting daily, and the Excel tool allows one to project the impact. “Though the specifics are constantly changing, the general takeaway is that, were we to completely lift the quarantine in one month or two months, we would essentially be starting from scratch,” explains Hoyt. “Some sort of distancing will be necessary to keep cases from rising exponentially.” Based on the characteristics of the virus, Hoyt says, the growth in new cases will not go down on its own until about half the population has immunity by either recovering from infection or getting vaccinated.
Some Room for Optimism
“What we don’t know stands out almost as starkly as what we do, but there is room for hope,” says Hoyt. First, there is evidence that social distancing is working. "There are more new cases every day, but the rate of growth has fallen," says Hoyt. Second, better testing is becoming available. “Due to a lack of antibody testing, we don’t know who is susceptible to the virus and who is immune because they had mild symptoms and recovered.”
When antibody testing becomes available, we will know whether someone has already recovered, rather than only knowing whether or not they are currently infected. This testing will allow better targeting of quarantine and allow some sectors of the economy to reopen, staffed by workers who have already recovered from the disease and are now immune.
That, says Hoyt, is his main takeaway from the data. “We need some sort of bridge between now and when we develop the vaccine. We can be more targeted when antibody testing is available, but right now we cannot responsibly lift quarantines or we will be right back to where we started.”