Using real-time modelling to inform the 2017 Ebola outbreak response in DR Congo.

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health Policy

Background:

• Ebola outbreaks pose significant public health challenges, necessitating effective interventions.
• Decisions regarding the timing and removal of resource-intensive interventions are critical during outbreaks.

Purpose of the Study:

• To assess the effectiveness of the Ebola Response Team (ERT) during the 2017 Ebola outbreak in Likati Health Zone, DRC.
• To determine the optimal timing for the withdrawal of the ERT using mathematical modeling.

Main Methods:

• Utilized a branching process model to estimate the reproduction number (R) before and after ERT deployment.
• Calculated the risk of ongoing transmission and future cases under different intervention scenarios.

Main Results:

• Pre-ERT arrival, the estimated reproduction number was R = 1.49, with a 97% risk of further cases.
• Post-ERT arrival, no further cases occurred, indicating effective transmission control.
• By the ERT withdrawal date, the estimated risk of future cases was reduced to 0.01, signifying a safe withdrawal.

Conclusions:

• The ERT's interventions were effective in controlling the 2017 Ebola outbreak in the Likati Health Zone.
• Mathematical modeling provided a reliable framework for assessing intervention effectiveness and guiding safe withdrawal decisions.
• The developed modeling framework can inform future outbreak response strategies and intervention management.