Literature DB >> 28835116

Estimation of the Percentage of Newly Diagnosed HIV-Positive Persons Linked to HIV Medical Care in CDC-Funded HIV Testing Programs.

Guoshen Wang1, Yi Pan1, Puja Seth1, Ruiguang Song1, Lisa Belcher1.   

Abstract

Missing data create challenges for determining progress made in linking HIV-positive persons to HIV medical care. Statistical methods are not used to address missing program data on linkage. In 2014, 61 health department jurisdictions were funded by Centers for Disease Control and Prevention (CDC) and submitted data on HIV testing, newly diagnosed HIV-positive persons, and linkage to HIV medical care. Missing or unusable data existed in our data set. A new approach using multiple imputation to address missing linkage data was proposed, and results were compared to the current approach that uses data with complete information. There were 12,472 newly diagnosed HIV-positive persons from CDC-funded HIV testing events in 2014. Using multiple imputation, 94.1% (95% confidence interval (CI): [93.7%, 94.6%]) of newly diagnosed persons were referred to HIV medical care, 88.6% (95% CI: [88.0%, 89.1%]) were linked to care within any time frame, and 83.6% (95% CI: [83.0%, 84.3%]) were linked to care within 90 days. Multiple imputation is recommended for addressing missing linkage data in future analyses when the missing percentage is high. The use of multiple imputation for missing values can result in a better understanding of how programs are performing on key HIV testing and HIV service delivery indicators.

Entities:  

Keywords:  HIV testing; estimation; linkage to care; multiple imputation; program evaluation

Mesh:

Year:  2017        PMID: 28835116     DOI: 10.1177/0163278717725372

Source DB:  PubMed          Journal:  Eval Health Prof        ISSN: 0163-2787            Impact factor:   2.651


  1 in total

1.  Systems Biology Analysis of the Antagonizing Effects of HIV-1 Tat Expression in the Brain over Transcriptional Changes Caused by Methamphetamine Sensitization.

Authors:  Liana V Basova; James P Kesby; Marcus Kaul; Svetlana Semenova; Maria Cecilia Garibaldi Marcondes
Journal:  Viruses       Date:  2020-04-09       Impact factor: 5.048

  1 in total

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