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

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  • 1Department of Information Technology, Mepco Schlenk Engineering College, Sivakasi, 626005 Tamil Nadu, India.

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This study introduces a novel method for selecting optimal COVID-19 testing center locations. The approach effectively ranks sites based on public health needs, ensuring efficient resource allocation.

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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.