RESEARCH ARTICLE


A Probability Sample for Monitoring the HIV-infected Population in Care in the U.S. and in Selected States



Martin R Frankel1, AD McNaghten*, 2, Martin F Shapiro 3, 4, Patrick S Sullivan 5, Sandra H Berry 3, Christopher H Johnson 2, Elaine W Flagg 2, Sally Morton 6, Samuel A Bozzette 3, 7
1 Baruch College, The City University of New York, New York City, New York, USA
2 Centers for Disease Control and Prevention, Atlanta, Georgia, USA
3 The RAND Corporation, Santa Monica, California, USA
4 University of California, Los Angeles, Los Angeles, California, USA
5 Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
6 Research Triangle Institute, Research Triangle, North Carolina, USA
7 The University of California, San Diego, San Diego, California, USA


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Creative Commons License
© Frankel 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 License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at Emory University, Rollins School of Public Health, Department of Epidemiology, 1518 Clifton Road NE, Atlanta, GA 30322, USA; Tel: +1 404 727-8750; Fax: +1 404 712-8392; E-mail: a.d.mcnaghten@emory.edu


Abstract

Epidemiologic and clinical changes in the HIV epidemic over time have presented a challenge to public health surveillance to monitor behavioral and clinical factors that affect disease progression and HIV transmission. The Medical Monitoring Project (MMP) is a supplemental surveillance project designed to provide representative, population-based data on clinical status, care, outcomes, and behaviors of HIV-infected persons receiving care at the national level. We describe a three-stage probability sampling method that provides both nationally and state-level representative estimates.

In stage-I, 20 states, which included 6 separately funded cities/counties, were selected using probability proportional to size (PPS) sampling. PPS sampling was also used in stage-II to select facilities for participation in each of the 26 funded areas. In stage-III, patients were randomly selected from sampled facilities in a manner that maximized the possibility of having overall equal selection probabilities for every patient in the state or city/county. The sampling methods for MMP could be adapted to other research projects at national or sub-national levels to monitor populations of interest or evaluate outcomes and care for a range of specific diseases or conditions.

Keywords: HIV, sampling, representative, surveillance..