Publications Details
Transportation Modeling and Global Health
Lacy, Susan L.; Finley, Patrick D.
A patient in the United States has been diagnosed with Ebola. Fear and panic kicks in across the country, and hospitals are inundated with hundreds of people, some infected with the highly contagious disease and others not. Blood tests are needed for positive diagnoses, but the diagnostic labs are overwhelmed with blood samples to test, and staff are overworked and stressed. Infected people need to be quarantined and treated, but it's hard to find rooms to quarantine so many patients. Sick people who need triage and regular care for other emergencies are afraid to go to hospitals for fear of Ebola, which has a 50% fatality rate. And since hospitals are so overwhelmed, sick people often stay home, infecting heathy people around them; the U.S. is now in the grips a full-blown Ebola outbreak. Sandia's high-performance computers simulated such a nightmare scenario recently, and with good reason. An Ebola outbreak in the United States could be devastating if hospitals are not prepared. When an Ebola outbreak in West Africa became a global concern in 2014, health advisers were alarmed at the length of time it took to properly diagnose infected people. In rural areas in Liberia, for example, blood samples from ailing people would be sent to a laboratory for testing, but the closest lab was hundreds of miles away through difficult and sometimes impassable roads. In more urban areas, blood samples would be sent to nearby labs, but those labs were often already overburdened by the sheer volume of samples to test. Staff at some treatment centers were unaware that a lab a little farther away might have the capacity to take in more samples. Meanwhile, undiagnosed infected people were unknowingly spreading the disease to many others around them, worsening the outbreak. The U.S. Defense Threat Reduction Agency (DTRA) and Centers for Disease Control and Prevention (CDC) posed a serious question: how do we improve blood-sample transportation routes in Liberia to ensure that samples taken from ill people are tested as quickly as possible, ensuring a proper diagnosis and faster treatment? Sandia scientists, already experts in transportation modeling for nuclear materials, quickly swarmed on this problem. The Sandia Ebola response team immediately set out to collect data from the region using available maps and local information, and transformed the raw data to GIS maps. Then, applying Sandia transportation routing algorithms, the team identified the optimal routes to get blood samples to the best laboratory for testing, even if that lab was not geographically the closest. The models also showed the best possible locations for mobile diagnostic laboratories that would better support the very rural regions that were most affected by the Ebola outbreak.