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A proactive/reactive mass screening approach with uncertain symptomatic cases.

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This study optimizes mass screening strategies for heterogeneous populations with limited budgets. It improves disease detection accuracy by balancing proactive and reactive testing, reducing misclassifications by up to 52%.

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Area of Science:

  • Operations Research
  • Public Health
  • Epidemiology

Background:

  • Mass screening is crucial for disease control, exemplified by the COVID-19 pandemic.
  • Limited budgets necessitate efficient allocation between proactive (targeted) and reactive (symptomatic) screening.
  • Heterogeneous populations present unique challenges for optimizing screening strategies.

Purpose of the Study:

  • To develop an optimal framework for mass screening in heterogeneous populations under budget constraints.
  • To integrate population-level risk data for informed proactive and reactive screening decisions.
  • To evaluate the effectiveness of individual and Dorfman group testing schemes within the proposed framework.

Main Methods:

  • Formulated a bilinear optimization problem to determine optimal screening strategies.
  • Leveraged structural properties of the optimization problem to develop efficient solution schemes.
  • Extended the model for customized testing across sub-populations and introduced a heuristic algorithm.

Main Results:

  • Demonstrated significant improvements in screening efficiency and accuracy.
  • Achieved up to a 52% reduction in total misclassifications compared to conventional methods in a COVID-19 case study.
  • Provided managerial insights into budget and measure allocation for proactive and reactive screening.

Conclusions:

  • The proposed framework effectively optimizes mass screening for heterogeneous populations with limited resources.
  • Integrating risk data and employing advanced optimization techniques leads to substantial improvements in disease detection.
  • The findings offer practical guidance for public health policy and resource management during screening campaigns.