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Phil Sahm

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Jun 25, 2015 3:01 PM

Damon J.A. Toth, Ph.D.
Damon J.A. Toth, Ph.D.

(SALT LAKE CITY)—When two Texas nurses contracted Ebola in 2014 after being infected by a man who’d acquired it in West Africa and then came to the United States, health system and hospital officials quickly contained the virus from spreading.

While the response prevented an outbreak once the virus was transmitted to the nurses, a new University of Utah and Department of Veterans Affairs Salt Lake City Health Care System study concludes that the United States and other countries should place “paramount importance” on developing surveillance systems to identify incoming travelers who may have Ebola before they infect someone in the nation they’re entering. Early identification in tandem with enhanced control measures for preventing the transmission of Ebola would provide the best defense against an outbreak of the virus.

“The risk of a substantial outbreak in a new country really increases if the first patient transmits infection to a lot of other people,” says applied mathematician Damon J.A. Toth, Ph.D., research assistant professor of internal medicine at the University of Utah School of Medicine and first author on the study. “An outbreak of even 10 cases would be considered unacceptable in many countries, and 100 cases would be considered a disaster.  Identifying incoming travelers with Ebola can have the most impact to reduce larger outbreaks or worst-case scenarios.”

The Ebola outbreak, which started in the West African nation of Guinea in late 2013 and spread to Sierra Leone and Liberia in 2014, is the largest since the virus was discovered in 1976. Although it currently isn’t grabbing front-page headlines, the outbreak continues in Guinea and Sierra Leone and has caused more than 11,000 deaths, according to the Centers for Disease Control and Prevention. 

A Continuing Risk

The continuing outbreak means the United States and other countries remain at risk for someone in the outbreak area transmitting the disease when they travel.

“Modeling gives you the ability to explore the trade-offs associated with alternative control strategies, which is useful for policy-makers and public health agencies,” says Matthew H. Samore, M.D., professor of internal medicine, chief of the Division of Epidemiology at the U of U medical school, Director of the Center of Innovation (IDEAS Center) at the VA Salt Lake City Health Care System, and senior author on the study published June 23, 2015, in the Centers for Disease Control and Prevention’s journal Emerging Infectious Diseases.

This type of modeling also can be used to track other viruses and disease outbreaks such as MERS (Middle East Respiratory Syndrome), the researchers say. MERS was first reported in Saudia Arabia in 2012, but the virus has spread to other countries outside of the Middle East, including the United States. In May, South Korea reported an outbreak, the largest one outside of the Arabian Peninsula.

Toth, Samore and their colleagues used data from the current outbreak to analyze the probabilities of Ebola spreading after a new introduction in various scenarios. They gathered information on 56 documented Ebola patients who spent part or all of their infectious period in the United States, Nigeria, Mali or nine other countries where the virus appeared but was contained relatively quickly. The researchers assigned the data to one of three categories: patients who traveled to one of the 12 countries when the virus was incubating; patients evacuated for treatment from Sierra Leone, Liberia or Guinea; people who acquired the virus after it was introduced into a new country by an infected incoming traveler or evacuee.

Among those three groups, seven infected travelers transmitted the virus to 19 people total, while only one transmission occurred from 20 evacuees. Those transmissions from travelers and evacuees led to nine additional transmissions among the local patients.

Using a mathematical theory known as branching process, the researchers analyzed the Ebola transmission data to determine the risk for an outbreak using different parameters and assumptions in which the virus is controlled either immediately or after a delay. Those situations depend on whether health officials are aware of an infected patient entering a country and whether those countries have enhanced control measures for preventing Ebola transmissions.

“Our analysis clearly showed that identifying the first case of Ebola entering a country has a bigger effect on the risk for a large outbreak than preparing to prevent transmission of the virus once it has been passed to someone in a new country,” Toth says.   

Worst-Case Scenarios

The mathematical model predicts the size of a worst-case scenario outbreak, one that would occur one in 10,000 times, for example. When an undiagnosed Ebola carrier enters a country that doesn’t use enhanced infection control—the model predicts a worst-case outbreak size of 240 new cases. This result decreases to 180 with enhanced infection control. The predicted size of a worst-case outbreak drops more substantially when an Ebola carrier is identified upon entering a country, measuring 40 without enhanced infection control and only 10 with enhanced control.

“Several countries have demonstrated an ability to greatly reduce transmission probabilities, once infected patients are identified,” Toth says, “but it may not always be possible to identify incoming patients immediately, especially if the infected person doesn’t cooperate with health officials.”

The higher worst-case outbreak sizes predicted by the model depend on assuming a relatively high probability of superspreading—one patient transmitting infection to a much-higher-than-average number of others. A patient in Nigeria, for example, transmitted the virus to 13 others, while the average number of transmissions from all travelers was less than three. Superspreading could be caused by a number of different factors—a patient could be unusually contagious, have an unusually high number of contacts with others, or be unwilling or unable to seek medical attention while experiencing symptoms.

The model results give reason to be optimistic that a combination of traveler surveillance and enhanced infection control can reduce the risk to all but a handful of transmissions to negligible levels. The results also give reason for caution—infected travelers who slip through the cracks could conceivably cause larger outbreaks than we have seen to date in countries outside of West Africa. “The mathematics allow us to explore the likelihood of events that we hope never happen,” Toth says.

Study co-authors are: Adi V. Gundlapalli; Karim Kader; Warren B.P. Pettey, Michael A. Rubin; Frederick R. Adler.


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