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[Indirect methods to estimate hidden population].

Rocío Lorenzo Ortega1,2, Michela Sonego3,4, José Pulido3,5,6

  • 1Servicio de Medicina Preventiva. Hospital Virgen de la Victoria. Málaga. España.

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Summary
This summary is machine-generated.

Estimating hidden populations is difficult due to sensitive behaviors. This review examines indirect methods for hard-to-reach populations, highlighting data needs and bias risks for accurate prevalence estimation.

Keywords:
Data CollectionEpidemiologic Study Characteristics as TopicEpidemiological MonitoringSpainVulnerable Populations

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Area of Science:

  • Epidemiology
  • Social Sciences
  • Biostatistics

Background:

  • Estimating the size of hidden populations is challenging due to difficulties in identifying individuals with socially sanctioned or illegal behaviors.
  • These populations often engage in activities that make direct enumeration impossible, necessitating indirect estimation techniques.

Purpose of the Study:

  • To critically review widely used indirect methods for estimating the size of hard-to-reach populations.
  • To discuss the data requirements, potential biases, and selection criteria for these estimation methods.

Main Methods:

  • The study provides a critical review of indirect demographic estimation methods.
  • Focuses on methods relying on incomplete data sources for prevalence estimation.

Main Results:

  • No single indirect method is universally superior; method choice depends on available data.
  • Each method has specific requirements and is susceptible to distinct biases.
  • Simultaneous use of multiple methods is recommended for result validation.

Conclusions:

  • Accurate evaluation of available data is crucial for selecting the most appropriate estimation method.
  • Cross-validation using multiple methods enhances the reliability of prevalence estimates for hidden populations.
  • Understanding method-specific risks of bias is essential for robust population size estimation.