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.
