Title: Optimising workforce distribution for case investigation and contact tracing: a web-based interactive approach utilising machine learning

Authors: AbdAllah M.A. Elsheikh; Bijan Farhoudi; Moushir M. El-Bishouty; Daniela Robu

Addresses: Innovation and Business Intelligence, Alberta Health Services, T2W 1S7, Calgary, Alberta, Canada ' Innovation and Business Intelligence, Alberta Health Services, T2W 1S7, Calgary, Alberta, Canada ' Innovation and Business Intelligence, Alberta Health Services, T2W 1S7, Calgary, Alberta, Canada ' Innovation and Business Intelligence, Alberta Health Services, T2W 1S7, Calgary, Alberta, Canada

Abstract: In recent years, the COVID-19 pandemic has challenged public health agencies around the globe. Managing the spread of the virus involves case investigation and contact tracing efforts, which rely heavily on the availability of trained personnel. A cross-functional team has developed an interactive web-based platform leveraging machine learning algorithms to optimise workforce distribution for case investigation and contact tracing activities. The system has two components: an automated solution for assigning contact tracing personnel based on skillset and an interactive prediction engine powered by machine learning and business rules from domain knowledge to generate adaptable workforce plans. Experiments on public datasets demonstrated the feasibility and effectiveness, achieving promising accuracy and usability results. The findings of this research contribute to the growing literature exploring the integration of artificial intelligence and public health policies, for more robust and responsive crisis management strategies.

Keywords: pandemic; COVID-19; case investigation; contact tracing; workforce distribution; machine learning; interactive; web-based platform; public health policy.

DOI: 10.1504/IJHTM.2024.149020

International Journal of Healthcare Technology and Management, 2024 Vol.21 No.3/4, pp.213 - 232

Received: 13 Dec 2023
Accepted: 18 Nov 2024
Published online: 09 Oct 2025 *

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