Controlling infectious disease outbreaks: A deterministic allocation-scheduling model with multiple discrete...

Area of Science:

• Public Health
• Operations Research
• Epidemiology

Background:

• Infectious disease outbreaks are recurrent and pose significant future risks.
• Effective resource allocation and scheduling are critical during outbreaks.
• Existing methods may not fully address the complexities of parallel resource deployment across multiple infected zones.

Purpose of the Study:

• To propose a novel heuristic algorithm for optimizing resource allocation and scheduling in infectious disease outbreaks.
• To address the challenge of managing limited, parallel resources across several infected areas.
• To provide a practical methodology for enhancing outbreak response strategies.

Main Methods:

• Development of a heuristic algorithm building upon established works by Shih (1974) and Pappis & Rachaniotis (2010).
• Application of the algorithm to a simulated influenza outbreak scenario.
• Numerical example to demonstrate the methodology's implementation and effectiveness.

Main Results:

• The proposed heuristic algorithm effectively addresses the problem of allocating and scheduling diverse resources in parallel across multiple infected regions.
• A numerical example using influenza data illustrates the practical application and potential benefits of the methodology.
• The algorithm demonstrates a viable approach for optimizing resource management during public health emergencies.

Conclusions:

• The developed heuristic methodology offers significant value for improving infectious disease outbreak response.
• This approach can inform the creation of robust contingency plans and healthcare policy agendas.
• Efficient resource management is key to mitigating the impact of future epidemics.