Dataset Information

Improving Underestimation of HIV Prevalence in Surveys Using Time-Location Sampling.

ABSTRACT: We sought to find a method that improves HIV estimates obtained through time-location sampling (TLS) used to recruit most-at-risk populations (MARPs). The calibration on residuals (CARES) method attributes weights to TLS sampled individuals depending on the percentile to which their logistic regression residues belong. Using a real country database, provided by EMIS-2010, with 9591 men who have sex with men (MSM) and an HIV prevalence of 12.1%, we simulated three populations (termed "pseudo-populations") with different levels of HIV. From each pseudo-population, 1000 TLS samples were drawn, and the HIV prevalence estimated by the TLS method and by the CARES method were recorded and compared with the HIV prevalence of the 9591 men. Results showed that the CARES method improves estimates given by the TLS method by getting closer to the real HIV prevalence.

SUBMITTER: Barros AB

PROVIDER: S-EPMC8382794 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Improving Underestimation of HIV Prevalence in Surveys Using Time-Location Sampling.

Barros Ana B AB Martins Maria Rosario O MRO

Journal of urban health : bulletin of the New York Academy of Medicine 20210801 4

We sought to find a method that improves HIV estimates obtained through time-location sampling (TLS) used to recruit most-at-risk populations (MARPs). The calibration on residuals (CARES) method attributes weights to TLS sampled individuals depending on the percentile to which their logistic regression residues belong. Using a real country database, provided by EMIS-2010, with 9591 men who have sex with men (MSM) and an HIV prevalence of 12.1%, we simulated three populations (termed "pseudo-popu ...[more]

PMID: 31898200

Similar Datasets

Project description:IntroductionHIV prevalence and sexual risk have been estimated very high for transgender people. However, the limited sampling and data collection methods used in current research on transgender people potentially led to overrepresentation and generalisation of people at risk for HIV. Current HIV prevalence estimates in transgender populations are generalised from studies mainly focusing on transgender women engaging in sex work. Moreover, studies focusing on non-binary people, who identify with a broad range of identities beyond the traditional male and female gender identities, are scarce.ObjectivesTo estimate the HIV prevalence rate in the Flemish and Brussels (Belgium) transgender population, including transgender women, transgender men and non-binary people, and to identify the associated risk factors.MethodsIn this community-based cross-sectional study, self-identified transgender and non-binary (TGNB) people will be recruited through a two-stage time-location sampling approach. First, community settings in which TGNB people gather will be mapped to develop an accurate sampling frame. Secondly, a multistage sampling design is applied involving a stratification based on setting type (healthcare facilities vs outreach events), a selection of clusters by systematic sampling and a simple random selection of TGNB people within each cluster. Participants will complete an electronic self-reported survey to measure sociological, sexual and drug-using behaviors (risk factors) and oral fluid aliquots will be collected and tested for HIV antibodies. Logistic regression models will be used to evaluate risk factors independently associated with HIV infection. The presented study is registered at ClinicalTrials.gov (NCT04930614).DiscussionThis study will be the first to investigate the HIV prevalence rates and associated risk behaviors in an accurate representation of the TGNB population in a Western European country. The findings will globally serve as a knowledge base for identifying subgroups at risk for becoming infected with HIV within TGNB people and to set up targeted prevention programs.

Project description:BackgroundThis study aims to investigate the measurement of breastfeeding prevalence indicators using Demographic and Health Surveys (DHS) data, focusing on early initiation, exclusive breastfeeding, and continued breastfeeding indicators as reported by the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF) and on the discrepancies arising from small changes in their definition.MethodsTwo hundred sixty DHS samples from 78 countries were analyzed to re-calculate usual indicators reported by WHO and UNICEF: early initiation of breastfeeding (EIB), exclusive breastfeeding under 6 months (EBF), and continued breastfeeding between 1 and 2 years (CBF12 and CBF24). Additionally, alternative estimates of the same indicators, slightly changing their definition, were calculated to test their robustness.ResultsThe WHO and UNICEF indicators for early initiation (EIB) primarily capture cases where breastfeeding is initiated "immediately" after birth, omitting those initiated within 0 or 1 hour. This discrepancy leads to substantial underestimation of levels in some regions, particularly South Asia, and in trends. Furthermore, sizable discrepancies between exclusive breastfeeding (EBF) indicators arise from the inclusion or exclusion of plain water in the definition, with significant variations across regions, especially in West and Middle Africa. However, continued breastfeeding indicators showed consistency across definitions, proving them robust for international comparisons and time trend estimations.ConclusionThis study highlights the importance of understanding how breastfeeding indicators are defined and calculated using DHS data. Researchers should be cautious when using WHO and UNICEF indicators for early initiation and exclusive breastfeeding, as they may underestimate prevalence due to their narrow definition. Continued breastfeeding indicators, on the other hand, are less affected by small changes in definitions and provide reliable measures for cross-country comparisons and trend analyses. These findings underscore the need for standardized robust definitions and transparent reporting of breastfeeding indicators in global health assessments.

Project description:Occupancy methods propelled the quantitative study of species distributions forward by separating the observation process, or the imperfect detectability of species, from the ecological processes of interest governing species distributions. Occupancy studies come at a cost, however: the collection of additional data to account for nondetections at sites where the species is present. The most common occupancy designs (repeated-measures designs) require repeat visits to sites or the use of multiple observers or detection methods. Time-to-detection methods have been identified as a potentially efficient alternative, requiring only one visit to each site by a single observer. A comparison of time-to-detection methods to repeated-measures designs for visual encounter surveys would allow researchers to evaluate whether time-to-detection methods might be appropriate for their study system and can inform optimal survey design. We collected time-to-detection data during two different repeated-measures design occupancy surveys for four amphibians and compared the performance of time-to-detection methods to the other designs using the location (potential bias) and precision of posterior distributions for occurrence parameters. We further used results of time-to-detection surveys to optimize survey design. Time-to-detection methods performed best for species that are widespread and have high detection probabilities and rates, but performed less well for cryptic species with lower probability of occurrence or whose detection was strongly affected by survey conditions. In all cases, single surveys were most efficient in terms of person-hours expended, but under some conditions the survey duration required to achieve high detection probabilities would be prohibitively long for a single survey. Regardless of occupancy survey design, time-to-detection methods provide important information that can be used to optimize surveys, allowing researchers and resource managers to efficiently achieve monitoring and conservation goals. Collecting time-to-detection data while conducting repeated-measures occupancy surveys requires only small modifications to field methods but could have large benefits in terms of time spent surveying in the long term.

Dataset Information

Improving Underestimation of HIV Prevalence in Surveys Using Time-Location Sampling.

Publications

Improving Underestimation of HIV Prevalence in Surveys Using Time-Location Sampling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets