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Population Size Estimation From Capture-Recapture Studies Using shinyrecap: Design and Implementation of a Web-Based
Anne F McIntyre1, Ian E Fellows1,2, Steve Gutreuter1
1Division of Global HIV & TB, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA, United States.
JMIR Public Health and Surveillance
|April 26, 2022
Summary
This study introduces shinyrecap, a user-friendly R application for estimating population sizes (PSE) in hidden populations using 3-sample capture-recapture (3S-CRC) methods, simplifying complex statistical analyses for field epidemiologists.
Area of Science:
- Epidemiology
- Biostatistics
- Public Health
Background:
- Population size estimates (PSE) are crucial for allocating HIV services to high-risk groups.
- Capture-recapture (CRC) methods are commonly used for estimating sizes of hidden populations.
- Three-sample CRC (3S-CRC) offers more robust estimates but involves complex statistical analysis.
Purpose of the Study:
- To design and describe shinyrecap, a user-friendly interface for generating PSE.
- To provide field epidemiologists with an accessible tool for complex 3S-CRC analyses.
Main Methods:
- shinyrecap is built on the R Shiny framework, integrating with statistical packages like Rcapture, dga, and LCMCR.
- The application supports online access or local installation.
- It includes tools for sample size calculation, data formatting, and supports various methodologies (log-linear, Bayesian).
Main Results:
- The application facilitates sample size calculation via simulation.
- It converts data formats for analysis software.
- Provides diagnostics and model checking for multiple statistical methodologies.
Conclusions:
- shinyrecap simplifies the production of robust PSE using 3S-CRC.
- A use case demonstrated its utility for estimating female sex worker populations in sub-Saharan Africa.
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