Effectiveness of contact tracing for detection of Ebola risk during early introduction of the virus within the USA

The current outbreak of Ebola is the largest thus far, with more than 13,000 reported cases to date in West Africa. Secondary infections have also been reported in Spain and the United States, raising concerns about training of medical personnel and safety of the entire population. In an effort to stop the transmission of the virus within the USA during its very early stage, the Center for Disease Control and Prevention is adopting a "contact tracing" approach — finding all individuals who have had close contact with an Ebola patient and monitoring the health status of those people for 21 days. This approach requires careful data collection, and is labor and cost intensive. A quantitative measure to evaluate the effectiveness of contact tracing is currently missing, due to the lack of previous experience of Ebola in the USA and insufficient supporting data from current cases. The goal of this project is to evaluate risk detection capabilities of contact tracing efforts for Ebola before the epidemic phase, and estimate the associated cost in potential scenarios. Not only will understanding the effectiveness of contact tracing be important for the current Ebola epidemic, but this project will also provide information for developing contact tracing guidelines and identifying critical circumstances hampering effective contact tracing in possible future epidemic threats.

This project will develop a network-based stochastic modeling framework of Ebola transmission for the local contact network of infected individuals (household, workplace, hospital, airplane, etc.). This simulation framework will allow investigators to synthesize scenarios and activities compatible with daily news about Ebola. "Missed- detection probability" versus "contact tracing cost" will be estimated through extensive simulations. Missed-detection probability, in this case, denotes the probability that a secondary infected individual is not detected before transmitting the infection to others. The team will perform sensitivity analysis to account for inherent uncertainties in different scenarios. The in-silico analysis will allow the following: 1) test performance and associated cost of contact tracing efforts in multiple realistic scenarios and different parameter spaces, 2) propose contact tracing guidelines under limited resources, and 3) identify critical circumstances for which contact tracing is not fully effective. A successful implementation of this project will have immediate benefits to USA public health and security against infectious disease.


Duration December 1 2014 - November 30 2015

Investigators

Faculty

Caterina Scoglio (Google Profile)

Faryad Darabi Sahneh (Google Profile)

Student

Narges Montazeri Shahtori (Ph.D.)

Products

  • C. Scoglio, A. Ahmadi Fard, F. Darabi Sahneh, "Modeling Ebola Risk during Early Introduction of the Virus", Poster presented at 7th International Symposium on Filoviruses; Ebola: West Africa and Recent Developments, Washington DC, March 25-28 2015.
  • C. Scoglio, F. Darabi Sahneh, N. Montazeri Shahtori “Effectiveness of Contact Tracing for Detection of Ebola Risk during Early Introduction of the Virus within the USA” NSF Smart and Connected Health (SCH) Principal Investigators Workshop, Arlington VA, June 30-July 1, 2015.
  • N. Montazeri Shahtori, C. Scoglio , A. Pourhabib , F. Darabi Sahneh “Sequential Monte Carlo Filtering Estimation of Ebola Progression in West Africa”, submitted 2015.

EpiModeling Software

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Supported by National Science Foundation under Award IIS-1513639. Any opinions, findings, and conclusions or recommendations expressed in this website are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.