Real-time predictions of the 2018–2019 Ebola virus disease outbreak in the Democratic Republic of the Congo using Hawkes point process models
J. Daniel Kelly,
Junhyung Park,
Ryan J. Harrigan,
Nicole A. Hoff,
Sarita D. Lee,
Rae Wannier,
Bernice Selo,
Mathias Mossoko,
Bathe Njoloko,
Emile Okitolonda-Wemakoy,
Placide Mbala-Kingebeni,
George W. Rutherford,
Thomas B. Smith,
Steve Ahuka-Mundeke,
Jean Jacques Muyembe-Tamfum,
Anne W. Rimoin,
Frederic Paik Schoenberg
Affiliations
J. Daniel Kelly
Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA; F.I. Proctor Foundation, University of California, San Francisco, CA USA; Corresponding author at: Box 0886 3rd Floor, 550 16th Street, San Francisco, CA 94143, USA.
Junhyung Park
Department of Statistics, University of California, Los Angeles, CA, USA
Ryan J. Harrigan
Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, CA, USA
Nicole A. Hoff
Department of Epidemiology, University of California, Los Angeles, CA, USA
Sarita D. Lee
Department of Statistics, University of California, Los Angeles, CA, USA
Rae Wannier
Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
Bernice Selo
Ministry of Health, Kinshasa, Congo
Mathias Mossoko
Ministry of Health, Kinshasa, Congo
Bathe Njoloko
Ministry of Health, Kinshasa, Congo
Emile Okitolonda-Wemakoy
School of Public Health, University of Kinshasa, Kinshasa, Congo
Placide Mbala-Kingebeni
Institut National de Recherche Biomedicale, Kinshasa, Congo
George W. Rutherford
Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
Thomas B. Smith
Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, CA, USA
Steve Ahuka-Mundeke
Institut National de Recherche Biomedicale, Kinshasa, Congo
Jean Jacques Muyembe-Tamfum
Institut National de Recherche Biomedicale, Kinshasa, Congo
Anne W. Rimoin
Department of Epidemiology, University of California, Los Angeles, CA, USA
Frederic Paik Schoenberg
Department of Statistics, University of California, Los Angeles, CA, USA
As of June 16, 2019, an Ebola virus disease (EVD) outbreak has led to 2136 reported cases in the northeastern region of the Democratic Republic of the Congo (DRC). As this outbreak continues to threaten the lives and livelihoods of people already suffering from civil strife and armed conflict, relatively simple mathematical models and their short-term predictions have the potential to inform Ebola response efforts in real time. We applied recently developed non-parametrically estimated Hawkes point processes to model the expected cumulative case count using daily case counts from May 3, 2018, to June 16, 2019, initially reported by the Ministry of Health of DRC and later confirmed in World Health Organization situation reports. We generated probabilistic estimates of the ongoing EVD outbreak in DRC extending both before and after June 16, 2019, and evaluated their accuracy by comparing forecasted vs. actual outbreak sizes, out-of-sample log-likelihood scores and the error per day in the median forecast. The median estimated outbreak sizes for the prospective thee-, six-, and nine-week projections made using data up to June 16, 2019, were, respectively, 2317 (95% PI: 2222, 2464); 2440 (95% PI: 2250, 2790); and 2544 (95% PI: 2273, 3205). The nine-week projection experienced some degradation with a daily error in the median forecast of 6.73 cases, while the six- and three-week projections were more reliable, with corresponding errors of 4.96 and 4.85 cases per day, respectively. Our findings suggest the Hawkes point process may serve as an easily-applied statistical model to predict EVD outbreak trajectories in near real-time to better inform decision-making and resource allocation during Ebola response efforts. Keywords: Ebola virus disease, Hawkes point process, Mathematical modeling, Democratic Republic of Congo, Compartmental models
