A Mathematical Model of Contact Tracing during the 2014–2016 West African Ebola Outbreak

Danielle Burton, Suzanne Lenhart, Christina J. Edholm, Benjamin Levy, Michael L. Washington, Bradford R. Greening, K. A. Jane White, Edward Lungu, Obias Chimbola, Moatlhodi Kgosimore, Faraimunashe Chirove, Marilyn Ronoh and M. Helen Machingauta
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Danielle Burton: Department of Mathematics, University of Wisconsin, Madison, WI 53706, USA
Suzanne Lenhart: Department of Mathematics, University of Tennessee, Knoxville, TN 37996, USA
Christina J. Edholm: Mathematics Department, Scripps College, Claremont, CA 91711, USA
Benjamin Levy: Department of Mathematics, Fitchburg State University, Fitchburg, MA 01420, USA
Michael L. Washington: Centers for Disease Control and Prevention, Atlanta, GA 30333, USA
Bradford R. Greening: Centers for Disease Control and Prevention, Atlanta, GA 30333, USA
K. A. Jane White: Department of Mathematical Sciences, University of Bath, Bath BA2 7AY, UK
Edward Lungu: Department of Mathematical & Statistical Sciences, Botswana International University of Science & Technology, Palapye, Botswana
Obias Chimbola: Department of Mathematical & Statistical Sciences, Botswana International University of Science & Technology, Palapye, Botswana
Moatlhodi Kgosimore: Department of Biometry & Mathematics, Botswana University of Agriculture and Natural Sciences, Gaborone, Botswana
Faraimunashe Chirove: Department of Applied Mathematics, University of Johannesburg, Johannesburg 2092, South Africa
Marilyn Ronoh: School of Mathematics, University of Nairobi, Nairobi, Kenya
M. Helen Machingauta: Department of Mathematical & Statistical Sciences, Botswana International University of Science & Technology, Palapye, Botswana

Mathematics, 2021, vol. 9, issue 6, 1-21

Abstract: The 2014–2016 West African outbreak of Ebola Virus Disease (EVD) was the largest and most deadly to date. Contact tracing, following up those who may have been infected through contact with an infected individual to prevent secondary spread, plays a vital role in controlling such outbreaks. Our aim in this work was to mechanistically represent the contact tracing process to illustrate potential areas of improvement in managing contact tracing efforts. We also explored the role contact tracing played in eventually ending the outbreak. We present a system of ordinary differential equations to model contact tracing in Sierra Leonne during the outbreak. Using data on cumulative cases and deaths, we estimate most of the parameters in our model. We include the novel features of counting the total number of people being traced and tying this directly to the number of tracers doing this work. Our work highlights the importance of incorporating changing behavior into one’s model as needed when indicated by the data and reported trends. Our results show that a larger contact tracing program would have reduced the death toll of the outbreak. Counting the total number of people being traced and including changes in behavior in our model led to better understanding of disease management.

Keywords: ebola contact tracing; differential equations; parameter estimation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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