Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC


  • Boseung Choi Department of National Statistics, Korea University Sejoung Campus, Seoul, Republic of Korea
  • Sydney Busch Augsburg University
  • Dieudonne Kazadi Ministry of Health, Democratic Republic of Kongo, Kinshasa, DRC
  • Benoit Kebela Department of Public Health, University of Kinshasa, Kinshasa, DRC
  • Emile Okitolonda Department of Public Health, University of Kinshasa, Kinshasa, DRC
  • Yi Dai Division of Biostatistics, The Ohio State University
  • Robert M Lumpkin Department of Statistics, The Ohio State University
  • Wasiur Rahman Khuda Bukhsh Mathematical Biosciences Institute, The Ohio State University
  • Omar Saucedo Mathematical Biosciences Institute, The Ohio State University
  • Marcel Yotebieng Division of Epidemiology The Ohio State University
  • Joe Tien Department of Mathematics The Ohio State University
  • Eben B Kenah Division of Biostatistics The Ohio State University
  • Grzegorz A Rempala Department of Mathematics, Division of Biostatistics and Mathematical Biosciences Institute, The Ohio State University



parameter estimation, branching process, Markov Chain Monte-Carlo methods, survival dynamical system


We describe two approaches to modeling data from a small to moderate-sized epidemic outbreak. The first approach isВ based on a branching process approximation and direct analysis of the transmission network, whereas the second one is based on a survival model derived from the classical SIR equations with no explicit transmission information. We compare these approaches using data from a 2012 outbreak of Ebola virus disease caused byВ Bundibugyo ebolavirusВ in city of Isiro, Demo- cratic Republic of the Congo. The branching process model allows for a direct comparison of disease transmission across different environments, such as the general community or the Ebola treatment unit. However, the survival model appears to yield parameter estimates with more accuracy and better precision in some circumstances.

Author Biography

Grzegorz A Rempala, Department of Mathematics, Division of Biostatistics and Mathematical Biosciences Institute, The Ohio State University

Professorof Mathematics and Biostatistics, Former Interim Director, В Mathematical Biosciences Institute


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