Quantifying the impact of early-stage contact tracing on controlling Ebola diffusion

  • Received: 15 September 2017 Revised: 27 January 2018 Published: 01 October 2018
  • MSC : Primary: 92B05, 68U20; Secondary: 65C20

  • Recent experience of the Ebola outbreak in 2014 highlighted the importance of immediate response measure to impede transmission in the early stage. To this aim, efficient and effective allocation of limited resources is crucial. Among the standard interventions is the practice of following up with the recent physical contacts of the infected individuals -- known as contact tracing. In an effort to understand the effects of contact tracing protocols objectively, we explicitly develop a model of Ebola transmission incorporating contact tracing. Our modeling framework is individual-based, patient-centric, stochastic and parameterizable to suit early-stage Ebola transmission. Notably, we propose an activity driven network approach to contact tracing, and estimate the basic reproductive ratio of the epidemic growth in different scenarios. Exhaustive simulation experiments suggest that early contact tracing paired with rapid hospitalization can effectively impede the epidemic growth. Resource allocation needs to be carefully planned to enable early detection of the contacts and rapid hospitalization of the infected people.

    Citation: Narges Montazeri Shahtori, Tanvir Ferdousi, Caterina Scoglio, Faryad Darabi Sahneh. Quantifying the impact of early-stage contact tracing on controlling Ebola diffusion[J]. Mathematical Biosciences and Engineering, 2018, 15(5): 1165-1180. doi: 10.3934/mbe.2018053

    Related Papers:

  • Recent experience of the Ebola outbreak in 2014 highlighted the importance of immediate response measure to impede transmission in the early stage. To this aim, efficient and effective allocation of limited resources is crucial. Among the standard interventions is the practice of following up with the recent physical contacts of the infected individuals -- known as contact tracing. In an effort to understand the effects of contact tracing protocols objectively, we explicitly develop a model of Ebola transmission incorporating contact tracing. Our modeling framework is individual-based, patient-centric, stochastic and parameterizable to suit early-stage Ebola transmission. Notably, we propose an activity driven network approach to contact tracing, and estimate the basic reproductive ratio of the epidemic growth in different scenarios. Exhaustive simulation experiments suggest that early contact tracing paired with rapid hospitalization can effectively impede the epidemic growth. Resource allocation needs to be carefully planned to enable early detection of the contacts and rapid hospitalization of the infected people.


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    [1] [ C. Browne,H. Gulbudak,G. Webb, Modeling contact tracing in outbreaks with application to Ebola, Journal of Theoretical Biology, 384 (2015): 33-49.
    [2] [ G. Chowell,C. Viboud, Is it growing exponentially fast?-Impact of assuming exponential growth for characterizing and forecasting epidemics with initial near-exponential growth dynamics, Infectious Disease Modelling, 1 (2016): 71-78.
    [3] [ O. Diekmann,J. A. P. Heesterbeek,J. A. J. Metz, On the definition and the computation of the basic reproduction ratio $R_{0}$ in models for infectious diseases in heterogeneous populations, Journal of Mathematical Biology, 28 (1990): 365-382.
    [4] [ M. G. Dixon,I. J. Schafer, Ebola Viral Disease Outbreak - West Africa, 2014, MMWR Morb Mortal Wkly Rep, 63 (2014): 548-551.
    [5] [ K. T. Eames,M. J. Keeling, Contact tracing and disease control, Proceedings of the Royal Society of London B: Biological Sciences, 270 (2003): 2565-2571.
    [6] [ F. O. Fasina, A. Shittu, D. Lazarus, O. Tomori, L. Simonsen, C. Viboud and G. Chowell, Transmission dynamics and control of Ebola virus disease outbreak in Nigeria, July to September 2014, Eurosurveillance, 19 (2014), 20920.
    [7] [ M. Greiner,D. Pfeiffer,R. D. Smith, Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests, Preventive Veterinary Medicine, 45 (2000): 23-41.
    [8] [ J. M. Heffernan,R. J. Smith,L. M. Wahl, Perspectives on the basic reproductive ratio, Journal of the Royal Society Interface, 2 (2005): 281-293.
    [9] [ M. J. Keeling and P. Rohani, Modeling Infectious Diseases in Humans and Animals, Princeton University Press, Princeton, NJ, 2008.
    [10] [ I. Z. Kiss,D. M. Green,R. R. Kao, Disease contact tracing in random and clustered networks, Proceedings of the Royal Society of London B: Biological Sciences, 272 (2005): 1407-1414.
    [11] [ D. Klinkenberg,C. Fraser,H. Heesterbeek, The effectiveness of contact tracing in emerging epidemics, PloS One, 1 (2006): e12.
    [12] [ S. Liu,N. Perra,M. Karsai,A. Vespignani, Controlling contagion processes in activity driven networks, Physical review letters, 112 (2014): 118702.
    [13] [ A. S. da Mata and R. Pastor-Satorras, Slow relaxation dynamics and aging in random walks on activity driven temporal networks, The European Physical Journal B, 88 (2015), Art. 38, 8 pp.
    [14] [ N. Perra, B. Gonçalves, R. Pastor-Satorras and A. Vespignani, Activity Driven Modeling of Time Varying Networks, Scientific Reports, 2012.
    [15] [ N. Perra,A. Baronchelli,D. Mocanu,B. Gonc'calves,R. Pastor-Satorras,A. Vespignani, Random walks and search in time-varying networks, Physical review letters, 109 (2012): 238701.
    [16] [ A. Rizzo,B. Pedalino,M. Porfiri, A network model for Ebola spreading, Journal of theoretical biology, 394 (2016): 212-222.
    [17] [ A. Rizzo,M. Frasca,M. Porfiri, Effect of individual behavior on epidemic spreading in activity-driven networks, Physical Review E, 90 (2014): 042801.
    [18] [ A. Rizzo and M. Porfiri, Toward a realistic modeling of epidemic spreading with activity driven networks, in Temporal Network Epidemiology (N. Masuda and P. Holme), Springer, (2017), 317-319.
    [19] [ N. M. Shahtori,C. Scoglio,A. Pourhabib,F. D. Sahneh, Sequential Monte Carlo filtering estimation of Ebola progression in West Africa, American Control Conference(ACC), null (2016): 1277-1282.
    [20] [ M. D. Shirley,S. P. Rushton, The impacts of network topology on disease spread, Ecological Complexity, 2 (2005): 287-299.
    [21] [ F. Shuaib,R. Gunnala,E. O. Musa,F. J. Mahoney,O. Oguntimehin,P. M. Nguku,S. B. Nyanti,N. Knight,N. S. Gwarzo,O. Idigbe,A. Nasidi,J. F. Vertefeuille, Ebola virus disease outbreak-Nigeria, July-September 2014, MMWR Morb Mortal Wkly Rep, 63 (2014): 867-872.
    [22] [ M. Starnini,R. Pastor-Satorras, Temporal percolation in activity-driven networks, Physical Review E, 89 (2014): 032807.
    [23] [ M. Starnini,R. Pastor-Satorras, Topological properties of a time-integrated activity-driven network, Physical Review E, 87 (2013): 062807.
    [24] [ K. Sun, A. Baronchelli and N. Perra, Contrasting effects of strong ties on SIR and SIS processes in temporal networks, The European Physical Journal B, 88 (2015), Art. 326, 8 pp.
    [25] [ L. Zino,A. Rizzo,M. Porfiri, Continuous-Time Discrete-Distribution Theory for Activity-Driven Networks, Physical Review Letters, 117 (2016): 228302.
    [26] [ Cases of Ebola Diagnosed in the United States, 2014. Available from: https://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/united-states-imported-case.html.
    [27] [ Implementation and Management of Contact Tracing for Ebola Virus Disease, Emergency Guideline by the World Health Organization, 2015. Available from: https://www.cdc.gov/vhf/ebola/pdf/contact-tracing-guidelines.pdf.
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