Model Comparison and Assessment for Closed Capture-recapture Models for Estimate Opioid Use Disorders

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Ratchadaporn Ungcharoen
Lily Ingsrisawang
Matthew Law

Abstract

A popular method for dealing with an unknown population size is the capture-recapture method (CRC). Then capture-recapture models were applied in the adjustment of epidemiology data. The aim of study was to compare the estimator of capture-recapture models in the closed population for estimation the number of opioid use disorders (OUD). The data of opioid use disorders in 2014, in New South Wales, Australia. The CRC was use to estimate the number of OUD cases based on three data sources, including patient department, emergency department, and national death index. The data were analyzed using the Rcapture package. The model used M0, Mt, Mh, and Mb to compare the assessment of OUD data. The minimum Akaike’s Information Criterion (AIC) value was used to select the best model. The three data sources were: 87 patients at the Patient Department, 407 cases from Emergency Department, and 15 cases from the National Death Index. The overlapping of the three data sources involved 54 cases. The results showed that the estimates obtained were 666 cases from M0 model and Mh Chao (LB), 465 cases from Mt model, 433 cases from Mh Poisson 2, 351 cases from Mh Gamma 3.5 and 503 cases from Mb model. The smallest AIC was obtained for the Mt model (AIC = 51.962). With the Mt model more suitable for OUD were estimated. This model should be able to apply to any setting with similar context. The method provided a simple, quick method to estimate the numbers of OUD.

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