Design and Weighting Methods for a Nationally Representative Sample of HIV-infected Adults Receiving Medical Care in the United States-Medical Monitoring Project



Ronaldo Iachan1, Christopher H. Johnson*, 2, Richard L. Harding1, Tonja Kyle1, Pedro Saavedra1, Emma L. Frazier2, Linda Beer2, Christine L. Mattson2, Jacek Skarbinski2
1 ICF International, Inc., Calverton, MD, USA
2 Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA


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© Iachan et al.; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at the Division of HIV/AIDS Prevention, NCHHSTP, Centers for Disease Control and Prevention, 1600 Clifton Road, Mail Stop E-47, Atlanta, GA 30333, USA; Tel: (404) 639-2989; Fax: (404) 639-8642; E-mail: chj0@cdc.gov


Abstract

Background:

Health surveys of the general US population are inadequate for monitoring human immunodeficiency virus (HIV) infection because the relatively low prevalence of the disease (<0.5%) leads to small subpopulation sample sizes.

Objective:

To collect a nationally and locally representative probability sample of HIV-infected adults receiving medical care to monitor clinical and behavioral outcomes, supplementing the data in the National HIV Surveillance System. This paper describes the sample design and weighting methods for the Medical Monitoring Project (MMP) and provides estimates of the size and characteristics of this population.

Methods:

To develop a method for obtaining valid, representative estimates of the in-care population, we implemented a cross-sectional, three-stage design that sampled 23 jurisdictions, then 691 facilities, then 9,344 HIV patients receiving medical care, using probability-proportional-to-size methods. The data weighting process followed standard methods, accounting for the probabilities of selection at each stage and adjusting for nonresponse and multiplicity. Nonresponse adjustments accounted for differing response at both facility and patient levels. Multiplicity adjustments accounted for visits to more than one HIV care facility.

Results:

MMP used a multistage stratified probability sampling design that was approximately self-weighting in each of the 23 project areas and nationally. The probability sample represents the estimated 421,186 HIV-infected adults receiving medical care during January through April 2009. Methods were efficient (i.e., induced small, unequal weighting effects and small standard errors for a range of weighted estimates).

Conclusion:

The information collected through MMP allows monitoring trends in clinical and behavioral outcomes and informs resource allocation for treatment and prevention activities.

Keywords: HIV infection, Nonresponse, Probability sampling, Surveillance, Survey methodology, Weighting.