As mentioned in my previous blog post, Ebola has the potential to be one of the deadliest epidemics in a century, but the primary area of concern is Western Africa, where the virus is most prevalent. However, as cases pop up in the U.S., concerns are rising, as evidenced by the acute media analysis and discussion around the first case in New York, for example.
Based on RMS modeling, we estimate that there will be between 15 and 130 cases in the U.S. between now and the end of the year—less than 1 case for every 2 million people. Our calculations assume that American medical professionals working with infected people in West Africa will account for the majority of cases. We simulated the number of new U.S. cases based on the existing infection rates among the American medical workers; this technique incorporates our projections for future West African caseloads and medical staff on the ground in the next two months, based on RMS’s epidemic scenario model. We then further modeled the virus’s spread once back in the U.S., taking into account the preparedness and higher quality of treatment facilities here versus the affected countries in West Africa.
The high end of the range is likely a slight overestimate as our calculations exclude automatic quarantining measures that some areas of the US are implementing. These measures can both reduce the number of contacts (people who come into contact with the infected person) for the imported cases, as well as increase the travel burden on U.S. volunteers planning to support the effort in Africa; this in turn could potentially reduce the number of people who actually make it over to the affected region.
The U.S. is prepared to handle the caseload even if it hits the upper range of 130 new cases. At any given time between now and December, specialized Ebola biocontainment facilities will have 11 beds available, which is enough to cope with the maximum weekly caseload in most of (but not all) of our modeled projections. In the more extreme scenarios, we still expect hospitals nationwide that have at least one Ebola treatment bed in place to handle overflow. Even if the reality over the next few months resembles a very pessimistic situation, it will be manageable given the U.S.’s higher capacity for managing cases.
Catastrophe modeling is an art and a science. The interesting, albeit challenging, part about calculating a range for something like this is that so much is contingent on estimates. The very nature of the virus and the exponential way the epidemic spreads means our estimates of the uncertainty in the variables are amplified in the number of cases. Our estimate is largely dependent on when affected regions reach the tipping point, where the number of new daily cases declines rather than increases. Everything is interconnected – the pace at which the epidemic spreads directly affects the tipping point, which then affects the need for treatment and number of professionals, which in turn affects the potential number of cases that can be imported back to the U.S.
As with all catastrophes we model, understanding risk is the first step toward mitigating and managing it.