Key population size estimation in Nigeria: applying novel Bayesian methods for analysis of three-source capture-recapture data (Preprint)

2021 ◽  
Author(s):  
Anne F. McIntyre ◽  
Andrew Mitchell ◽  
Kristen A. Stafford ◽  
Samuel U. Nwafor ◽  
Julia Lo ◽  
...  
Keyword(s):  
Population Size ◽  
Latent Class ◽  
Latent Class Models ◽  
Population Size Estimation ◽  
Size Estimation ◽  
Bayesian Nonparametric ◽  
Population Size Estimates ◽  
Social Visibility ◽  
Capture Recapture ◽  
Class Models

BACKGROUND Nigeria has the fourth largest burden of HIV globally. Key populations (KP) including female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID) often have poor social visibility and are more vulnerable to HIV than the general population due to stigma, discrimination, and criminalization of KP-defining behaviors. Reliable, empirical population size estimates (PSE) are needed to guide focused and appropriately scaled HIV epidemic response efforts for KP. We used novel approaches to sampling and analysis to calculate PSE in Nigeria. OBJECTIVE We sampled the population using three-source capture-recapture (3S-CRC) and analyzed results using Bayesian nonparametric latent-class models to generate median PSE with 80% highest density intervals. METHODS During October–December 2018, we used three-source capture-recapture (3S-CRC) to estimate the size of KP in seven United States President’s Emergency Plan for AIDS Relief (PEPFAR) priority states in Nigeria. Hotspots were mapped before 3S-CRC started. We sampled FSW, MSM, and PWID during three independent captures approximately one week apart. During encounters in KP hotspots, distributors offered inexpensive and memorable objects to KP, unique to each capture round and KP type. In subsequent rounds, participants were offered an object and asked to produce or identify objects received during previous rounds (if any); affirmative responses were tallied upon producing or identifying the correct object. Distributors recorded responses on tablets and uploaded to a secure server after each encounter. Data were aggregated by KP and state for analysis. Median PSE were derived using Bayesian nonparametric latent-class models with 80% highest density intervals for precision. RESULTS We sampled approximately 310,000 persons at 9,015 hotspots during three independent captures in all seven states. Overall, FSW PSE ranged from 14,500-64,300; MSM PSE, 3,200-41,400; and PWID PSE, 3,400-30,400. CONCLUSIONS This study represents the first implementation of these 3S-CRC sampling and novel analysis methods for large-scale population size estimation in Nigeria. Overall, our estimates were larger than previously documented for each KP in all states. The current Bayesian models account for factors (i.e., social visibility and stigma) that influence heterogeneous capture probabilities resulting in more reliable PSE. The larger estimates suggest a need for programmatic scale-up to reach these populations at highest risk for HIV.

scholarly journals Population Size Estimation Using Multiple Incomplete Lists with Overcoverage

2018 ◽  
Vol 34 (2) ◽  
pp. 557-572 ◽  
Author(s):  
Davide Di Cecco ◽  
Marco Di Zio ◽  
Danila Filipponi ◽  
Irene Rocchetti
Keyword(s):  
Population Size ◽  
Latent Class ◽  
Latent Class Models ◽  
Size Estimation ◽  
Administrative Information ◽  
Capture Recapture ◽  
Incomplete Lists ◽  
Class Models ◽  
Different Sources

Abstract The quantity and quality of administrative information available to National Statistical Institutes have been constantly increasing over the past several years. However, different sources of administrative data are not expected to each have the same population coverage, so that estimating the true population size from the collective set of data poses several methodological challenges that set the problem apart from a classical capture-recapture setting. In this article, we consider two specific aspects of this problem: (1) misclassification of the units, leading to lists with both overcoverage and undercoverage; and (2) lists focusing on a specific subpopulation, leaving a proportion of the population with null probability of being captured. We propose an approach to this problem that employs a class of capturerecapture methods based on Latent Class models. We assess the proposed approach via a simulation study, then apply the method to five sources of empirical data to estimate the number of active local units of Italian enterprises in 2011.

shinyrecap: A Shiny Application for Population Size Estimation from Capture-Recapture Data (Preprint)

2021 ◽  
Author(s):  
Anne F. McIntyre ◽  
Ian E. Fellows ◽  
Steve Gutreuter ◽  
Wolfgang Hladik
Keyword(s):  
Population Size ◽  
Sex Workers ◽  
Female Sex Workers ◽  
Population Size Estimation ◽  
Sub Saharan Africa ◽  
Size Estimation ◽  
Female Sex ◽  
Populations At Risk ◽  
Population Size Estimates ◽  
Capture Recapture

BACKGROUND Capture-recapture is often used to estimate the size of populations at risk for HIV, including female sex workers, men who have sex with men, and people who inject drugs. These population size estimates are critical in determining resource allocation for HIV services geared toward these communities. OBJECTIVE Compared to the commonly used two-source capture-recapture, capture-recapture relying on three (or more) samples can provide more robust PSE but involve far more complex statistical analysis. shinyrecap is designed to provide a user-friendly interface for the field epidemiologist. METHODS shinyrecap is built on the Shiny web application framework for R. This allows it to seamlessly integrate with the sophisticated CRC statistical packages. Additionally, the application may be accessed online or run locally on the user’s machine. RESULTS The application enables users to engage in sample size calculation based on a simulation framework. It assists in the proper formatting of collected data by providing a tool to convert commonly used formats to that used by analysis software. A wide variety of methodologies are supported by the analysis tool, including log-linear, Bayesian model averaging, and Bayesian latent class models. For each methodology, diagnostics and model checking interfaces are provided. CONCLUSIONS Through a use case, we demonstrate the broad utility of this powerful tool with three-source capture-recapture data to produce population size estimation for female sex workers in a subnational unit of a country in sub-Saharan Africa.

scholarly journals Estimating the Size of Key Populations in Kampala, Uganda: 3-Source Capture-Recapture Study (Preprint)

2018 ◽  
Author(s):  
Reena H Doshi ◽  
Kevin Apodaca ◽  
Moses Ogwal ◽  
Rommel Bain ◽  
Ermias Amene ◽  
...  
Keyword(s):  
Population Size ◽  
Latent Class ◽  
Latent Class Model ◽  
Key Populations ◽  
Size Estimation ◽  
Public Health Response ◽  
Hiv Epidemic ◽  
Population Size Estimates ◽  
Capture Recapture ◽  
Size Estimates

BACKGROUND Key populations, including people who inject drugs (PWID), men who have sex with men (MSM), and female sex workers (FSW), are disproportionately affected by the HIV epidemic. Understanding the magnitude of, and informing the public health response to, the HIV epidemic among these populations requires accurate size estimates. However, low social visibility poses challenges to these efforts. OBJECTIVE The objective of this study was to derive population size estimates of PWID, MSM, and FSW in Kampala using capture-recapture. METHODS Between June and October 2017, unique objects were distributed to the PWID, MSM, and FSW populations in Kampala. PWID, MSM, and FSW were each sampled during 3 independent captures; unique objects were offered in captures 1 and 2. PWID, MSM, and FSW sampled during captures 2 and 3 were asked if they had received either or both of the distributed objects. All captures were completed 1 week apart. The numbers of PWID, MSM, and FSW receiving one or both objects were determined. Population size estimates were derived using the Lincoln-Petersen method for 2-source capture-recapture (PWID) and Bayesian nonparametric latent-class model for 3-source capture-recapture (MSM and FSW). RESULTS We sampled 467 PWID in capture 1 and 450 in capture 2; a total of 54 PWID were captured in both. We sampled 542, 574, and 598 MSM in captures 1, 2, and 3, respectively. There were 70 recaptures between captures 1 and 2, 103 recaptures between captures 2 and 3, and 155 recaptures between captures 1 and 3. There were 57 MSM captured in all 3 captures. We sampled 962, 965, and 1417 FSW in captures 1, 2, and 3, respectively. There were 316 recaptures between captures 1 and 2, 214 recaptures between captures 2 and 3, and 235 recaptures between captures 1 and 3. There were 109 FSW captured in all 3 rounds. The estimated number of PWID was 3892 (3090-5126), the estimated number of MSM was 14,019 (95% credible interval (CI) 4995-40,949), and the estimated number of FSW was 8848 (95% CI 6337-17,470). CONCLUSIONS Our population size estimates for PWID, MSM, and FSW in Kampala provide critical population denominator data to inform HIV prevention and treatment programs. The 3-source capture-recapture is a feasible method to advance key population size estimation.

scholarly journals Estimating the Size of Key Populations in Kampala, Uganda: 3-Source Capture-Recapture Study

10.2196/12118 ◽  
2019 ◽  
Vol 5 (3) ◽  
pp. e12118 ◽  
Author(s):  
Reena H Doshi ◽  
Kevin Apodaca ◽  
Moses Ogwal ◽  
Rommel Bain ◽  
Ermias Amene ◽  
...  
Keyword(s):  
Population Size ◽  
Latent Class ◽  
Latent Class Model ◽  
Key Populations ◽  
Size Estimation ◽  
Public Health Response ◽  
Hiv Epidemic ◽  
Population Size Estimates ◽  
Capture Recapture ◽  
Size Estimates

Background Key populations, including people who inject drugs (PWID), men who have sex with men (MSM), and female sex workers (FSW), are disproportionately affected by the HIV epidemic. Understanding the magnitude of, and informing the public health response to, the HIV epidemic among these populations requires accurate size estimates. However, low social visibility poses challenges to these efforts. Objective The objective of this study was to derive population size estimates of PWID, MSM, and FSW in Kampala using capture-recapture. Methods Between June and October 2017, unique objects were distributed to the PWID, MSM, and FSW populations in Kampala. PWID, MSM, and FSW were each sampled during 3 independent captures; unique objects were offered in captures 1 and 2. PWID, MSM, and FSW sampled during captures 2 and 3 were asked if they had received either or both of the distributed objects. All captures were completed 1 week apart. The numbers of PWID, MSM, and FSW receiving one or both objects were determined. Population size estimates were derived using the Lincoln-Petersen method for 2-source capture-recapture (PWID) and Bayesian nonparametric latent-class model for 3-source capture-recapture (MSM and FSW). Results We sampled 467 PWID in capture 1 and 450 in capture 2; a total of 54 PWID were captured in both. We sampled 542, 574, and 598 MSM in captures 1, 2, and 3, respectively. There were 70 recaptures between captures 1 and 2, 103 recaptures between captures 2 and 3, and 155 recaptures between captures 1 and 3. There were 57 MSM captured in all 3 captures. We sampled 962, 965, and 1417 FSW in captures 1, 2, and 3, respectively. There were 316 recaptures between captures 1 and 2, 214 recaptures between captures 2 and 3, and 235 recaptures between captures 1 and 3. There were 109 FSW captured in all 3 rounds. The estimated number of PWID was 3892 (3090-5126), the estimated number of MSM was 14,019 (95% credible interval (CI) 4995-40,949), and the estimated number of FSW was 8848 (95% CI 6337-17,470). Conclusions Our population size estimates for PWID, MSM, and FSW in Kampala provide critical population denominator data to inform HIV prevention and treatment programs. The 3-source capture-recapture is a feasible method to advance key population size estimation.

Estimating the population size of people who inject drugs in Ho Chi Minh City, Vietnam: A two-survey capture-recapture exercise (Preprint)

2019 ◽  
Author(s):  
Abu Abdul-Quader
Keyword(s):  
Population Size ◽  
Illicit Drugs ◽  
People Who Inject Drugs ◽  
Care Service ◽  
Ho Chi Minh City ◽  
Size Estimation ◽  
Population Size Estimates ◽  
Capture Recapture ◽  
The City ◽  
Size Estimates

BACKGROUND Population size estimation of people who inject drugs (PWID) in Ho Chi Minh City (HCMC), Vietnam relied on the UNAIDS Estimation and Projection Package and reports from the city police department. The two estimates vary widely. OBJECTIVE To estimate the population size of people who inject drugs in Ho Chi Minh City, Vietnam METHODS Using Respondent-driven sampling (RDS), we implemented two-source capture-recapture method to estimate the population size of PWID in HCMC in 2017 in 7 out of 24 districts. The study included men or women aged at least 18 years who reported injecting illicit drugs in the last 90 days and who had lived in the city the past six months. We calculated two sets of size estimates, the first assumed that all participants in each survey round resided in the district where the survey was conducted, the second, used the district of residence as reported by the participant. District estimates were summed to obtain an aggregate estimate for the seven districts. To calculate the city total, we weighted the population size estimates for each district by the inverse of the stratum specific sampling probabilities. RESULTS The first estimate resulted in a population size of 19,155 (95% CI: 17,006–25,039). The second one generated a smaller population size estimate of 12,867 (95% CI: 11,312–17,393). CONCLUSIONS The two-survey capture-recapture exercise provided two disparate estimates of PWID in HCMC. For planning HIV prevention and care service needs among PWID in HCMC, both estimates may need to be taken into consideration together with size estimates from other sources.

Bayesian nonparametric latent class model for longitudinal data

2020 ◽  
Vol 29 (11) ◽  
pp. 3381-3395
Author(s):  
Wonmo Koo ◽  
Heeyoung Kim
Keyword(s):  
Longitudinal Data ◽  
Latent Class ◽  
Latent Class Model ◽  
Latent Class Models ◽  
Model Parameters ◽  
Latent Classes ◽  
Bayesian Nonparametric ◽  
Class Model ◽  
Proposed Model ◽  
Class Models

Latent class models have been widely used in longitudinal studies to uncover unobserved heterogeneity in a population and find the characteristics of the latent classes simultaneously using the class allocation probabilities dependent on predictors. However, previous latent class models for longitudinal data suffer from uncertainty in the choice of the number of latent classes. In this study, we propose a Bayesian nonparametric latent class model for longitudinal data, which allows the number of latent classes to be inferred from the data. The proposed model is an infinite mixture model with predictor-dependent class allocation probabilities; an individual longitudinal trajectory is described by the class-specific linear mixed effects model. The model parameters are estimated using Markov chain Monte Carlo methods. The proposed model is validated using a simulated example and a real-data example for characterizing latent classes of estradiol trajectories over the menopausal transition using data from the Study of Women’s Health Across the Nation.

scholarly journals Population Size Estimation and Linkage Errors: the Multiple Lists Case

2018 ◽  
Vol 34 (4) ◽  
pp. 889-908 ◽  
Author(s):  
Loredana Di Consiglio ◽  
Tiziana Tuoto
Keyword(s):  
Data Integration ◽  
Population Size ◽  
Population Size Estimation ◽  
Population Estimates ◽  
Size Estimation ◽  
Multiple Sources ◽  
Official Statistics ◽  
Linkage Error ◽  
Capture Recapture ◽  
Error Probabilities

Abstract Data integration is now common practice in official statistics and involves an increasing number of sources. When using multiple sources, an objective is to assess the unknown size of the population. To this aim, capture-recapture methods are applied. Standard capture-recapture methods are based on a number of strong assumptions, including the absence of errors in the integration procedures. However, in particular when the integrated sources were not originally collected for statistical purposes, this assumption is unlikely and linkage errors (false links and missing links) may occur. In this article, the problem of adjusting population estimates in the presence of linkage errors in multiple lists is tackled; under homogeneous linkage error probabilities assumption, a solution is proposed in a realistic and practical scenario of multiple lists linkage procedure.

scholarly journals Using Unmanned Aerial Vehicles (UAV) for free-roaming dog population size estimation

2019 ◽  
Author(s):  
Charlotte Warembourg ◽  
Monica Berger-González ◽  
Danilo Alvarez ◽  
Filipe Maximiano Sousa ◽  
Alexis López Hernández ◽  
...  
Keyword(s):  
Statistical Model ◽  
Unmanned Aerial Vehicles ◽  
Population Size ◽  
Census Data ◽  
Population Size Estimation ◽  
Domestic Dog ◽  
Estimation Methods ◽  
Size Estimation ◽  
Aerial Vehicles ◽  
Capture Recapture

AbstractPopulation size estimation is performed for several reasons including disease surveillance and control, for example to design adequate control strategies such as vaccination programs or to estimate a vaccination campaign coverage. In this study, we aimed at assessing the benefits and challenges of using Unmanned Aerial Vehicles (UAV) to estimate the size of free-roaming domestic dog (FRDD) populations and compare the results with two regularly used methods for population estimations: a Bayesian statistical model based on capture-recapture data and the human:dog ratio estimation. Three studies sites of one square kilometer were selected in Petén department, Guatemala. UAV flight were conducted twice during two consecutive days per study site. The UAV’s camera was set to regularly take pictures and cover the entire surface of the selected areas. A door-to-door survey was conducted in the same areas, all available dogs were marked with a collar and owner were interviewed. Simultaneously to the UAV’s flight, transect walks were performed and the number of collared and non-collared dogs were recorded. Data collected during the interviews and the number of dogs counted during the transect walks informed a Bayesian statistical model. The number of dogs counted on the UAV’s pictures and the estimates given by the Bayesian statistical model, as well as the estimates derived from using a 5:1 human:dog ratio were compared to dog census data. FRDD could be detected using the UAV’s method. However, the method lacked of sensitivity, which could be overcome by choosing the flight timing and the study area wisely, or using infrared camera or automatic detection of the dogs. We also suggest to combine UAV and capture-recapture methods to obtain reliable FRDD population size estimated. This publication may provide helpful directions to design dog population size estimation methods using UAV.

scholarly journals Population Size Estimation of Venue-Based Female Sex Workers in Ho Chi Minh City, Vietnam: Capture-Recapture Exercise

10.2196/10906 ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. e10906 ◽  
Author(s):  
Giang Le ◽  
Nghia Khuu ◽  
Van Thi Thu Tieu ◽  
Phuc Duy Nguyen ◽  
Hoa Thi Yen Luong ◽  
...  
Keyword(s):  
Population Size ◽  
Sex Workers ◽  
Female Sex Workers ◽  
Population Size Estimation ◽  
Ho Chi Minh City ◽  
Size Estimation ◽  
Female Sex ◽  
Capture Recapture
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