Human Centered Decision-Making for COVID-19 Testing Center Location Selection: Tamil Nadu-A Case Study

Area of Science:

• Operations Research
• Public Health Management
• Decision Science

Background:

• Effective placement of COVID-19 testing centers is crucial for public health response.
• Suboptimal site selection can lead to resource wastage and reduced testing accessibility.
• A systematic approach is needed to identify the most suitable locations for new testing facilities.

Purpose of the Study:

• To develop and validate a decision-making framework for selecting optimal COVID-19 testing center locations.
• To ensure testing centers are established in areas with the greatest need and highest impact potential.
• To provide a replicable methodology for public health officials and government agencies.

Main Methods:

• A hybrid approach combining Fuzzy Analytic Hierarchy Process (AHP) for criteria weighting.
• Optimization of weights using the Monkey Search algorithm.
• Ranking of potential locations using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).

Main Results:

• The proposed method successfully ranks potential testing center locations.
• Case study in Tamil Nadu, India, demonstrates the technique's applicability.
• Assigned ranks correlate with key epidemiological data such as patient numbers and death rates.

Conclusions:

• The integrated methodology provides a robust framework for strategic placement of public health infrastructure.
• The approach aids in maximizing the effectiveness of COVID-19 testing resources.
• This decision-support tool can be adapted for selecting sites for other essential health services.