TY - JOUR
T1 - A mathematical model of contact tracing during the 2014–2016 west african ebola outbreak
AU - Burton, Danielle
AU - Lenhart, Suzanne
AU - Edholm, Christina J.
AU - Levy, Benjamin
AU - Washington, Michael L.
AU - Greening, Bradford R.
AU - Jane White, K. A.
AU - Lungu, Edward
AU - Chimbola, Obias
AU - Kgosimore, Moatlhodi
AU - Chirove, Faraimunashe
AU - Ronoh, Marilyn
AU - Helen Machingauta, M.
N1 - Funding Information:
Funding: This research was funded in part by the National Science Foundation, grant number 134651, to the MASAMU Advanced Study Institute, and in part by the National Institute for Mathematical and Biological Synthesis, which is funded by the National Science Foundation, grant number DBI-1300426, with additional support from the University of Tennessee, Knoxville. K.A.J.W. was supported in part by an LMS Scheme 5 grant (51710).
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/3/2
Y1 - 2021/3/2
N2 - 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.
AB - 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.
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U2 - 10.3390/math9060608
DO - 10.3390/math9060608
M3 - Article
AN - SCOPUS:85102959844
SN - 2227-7390
VL - 9
JO - Mathematics
JF - Mathematics
IS - 6
M1 - 608
ER -