| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | November 26, 2014 |
| Latest Amendment Date: | November 26, 2014 |
| Award Number: | 1513639 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Wendy Nilsen
wnilsen@nsf.gov (703)292-2568 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | December 1, 2014 |
| End Date: | November 30, 2016 (Estimated) |
| Total Intended Award Amount: | $137,209.00 |
| Total Awarded Amount to Date: | $137,209.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1601 VATTIER STREET MANHATTAN KS US 66506-2504 (785)532-6804 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
2 Fairchild Hall Manhattan KS US 66506-1103 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Information Technology Researc, Smart and Connected Health |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Viruses do not understand borders. If an infectious disease is introduced into the country, it can be a challenge to keep it away from spreading due to the nature of the virus. This spreading can give life to a variety of negative consequences and it can create a major impact on social and economic aspects of the country.
When a disease is observed, we must take multiple measures to stop it at the very early stage and avoid the catastrophic event of an epidemics. One of the most effective measures is contact tracing, where we find and monitor the individuals who have been in close contact with a patient.
The goal of this project was to evaluate the effectiveness of contact tracing efforts for suppressing Ebola within the United States. With an emphasis on the early stage---before a possible epidemic phase---this project aimed at quantitatively studying contact tracing in several scenarios that can help public health authorities suppressing not only the transmission of Ebola but also of other similar diseases.
To this end, a stochastic and patient–centric model was developed for the early stage of Ebola propagation, incorporating contact tracing in a heterogeneous network that could capture the inherent time–varying nature of contagion process in a host population. Then the impact of critical aspects of the implementation of the contact tracing strategy was studied in detail. In addition, the impact of implemented mitigation protocols on Ebola progression in West Africa was also studied, captured by the evolution of the basic reproductive number, a critical index of disease aggressiveness in epidemiology.
The intellectual merit of this project concerns computational epidemiology of infectious diseases and network science, and includes the introduction of patient-centric modeling of infectious disease, the use of activity driven network description of individual-level temporal interaction patterns necessary for contact tracing, and the development of a specificity-sensitivity framework for quantifying contact tracing.
This project has provided results that can be translated into simple guidelines for public health officials facing an emerging outbreak of an infectious disease such as Ebola. Our analysis identified that immediate and accurate implementation of contact tracing protocols and hospitalization could result in the substantial reduction of the total number of infections. For Ebola, due to its incubation period of 5–21 days, more important than immediate contact tracing is immediate hospitalization of infectious patients at early stages, which can dramatically lower basic reproductive number and impede the transmission chain of the Ebola disease spreading.
In addition to public health impacts, this project allowed for training and professional developments of two female MS students who completed their thesis within this project, as well a junior faculty who advised a graduate student for the first time.
Successful implementation of contact-tracing efforts helped to minimize the number of Ebola deaths that could have taken place in the United States. Moreover, it helped the people who were affected with the virus to recover within a short period as it was diagnosed at an initial stage. This project facilitates more quantitative understanding of such contact-tracing efforts towards better preparedness of our national security against emerging diseases threats.
Last Modified: 01/30/2017
Modified by: Caterina Scoglio
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