Responding to an Ebola disease outbreak within a slum

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A model created by Yao Houkpati in partial fulfillment of the requirements for the degree of Master of Arts in Interdisciplinary Studies: Computational Social Science Concentration.

Quarantine was used as epidemic control measure in West Point Slum, Liberia during the 2014-2015 Ebola outbreak in West Africa. However, its use was largely criticized in the public press with regards to its effectiveness. West Point quarantine represents an opportunity to understand the potential benefits and limitations of quarantine when used in slums. By integrating agent-based modelling (ABM) with geographic information systems (GIS), I constructed a model calibrated with publicly available data on the study area that assessed the risks associated with the spread of Ebola in the slum by tracing the population movements during daily activities between West Point (WP) and its immediate neighbor Central Monrovia A (CMA), an upscale zone. The results show that with no movement restrictions, 74.13% (95% CI: 64.72 – 83.53) of CMA transmissions originated from WP whereas only 11% (95% CI: 5.84 – 17.17) of WP transmissions originated from CMA. 74.36 % (95% CI: 65.09 – 83.63) of WP population acquired the disease whereas only 45.14 % (95% CI: 32.50– 57.78) of CMA population were exposed. At global level, transmission rate was 62.67% (95% CI: 52.20 – 73.14). Under quarantine, the transmission rate in the total population was 47.39%. At zone level, the transmission rates were 71.66% and 8.22% respectively in WP and CMA. Model simulations suggest that WP represents a risk hotspot and a catalyst for the spread of Ebola, provoking 74% of CMA transmissions and having a transmission rate of 71.66%. Furthermore, the results indicate that quarantine is effective in halting the spread of Ebola at global level and in CMA, reducing the transmissions rates by 15.28% and 36.92% respectively. However, quarantine is less effective in quelling the transmission dynamics in WP, reducing the transmission rate by only 2.7%. This model lays the foundation to studying Ebola from an ABM perspective where one can test ideas in a simulated computer environment.


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