Linear regression and back-calculation analyses with applications to AIDS cases in Alabama

K.P. Singh, A. McDaniel, A.A. Bartolucci, T.M. Smoot and R. Holmes

Mathematics and Computers in Simulation (MATCOM), 1997, vol. 43, issue 3, 291-295

Abstract: AIDS case projections are vital to the control and prevention of AIDS. In this paper, we discuss statistical methods of AIDS/HIV infection data. We analyzed the AIDS/HIV infection data for the state of Alabama, USA. We discuss the results in detail. To assist health care planning efforts, projections of future AIDS cases were completed for Alabama for 1993 through 1995 by risk exposure and gender. Additional forecasts were also made for four metropolitan areas (Huntsville, Birmingham, Montgomery and Mobile) and two regional areas (North, South) by risk exposure and gender for the same time period. Two types of prediction methods were used to obtain AIDS projections: back-calculation and regression. Reported AIDS cases were adjusted for reporting delays and all projection estimates were inflated by 15% to account for underreporting. Using goodness of fit tests the curvilinear regression and two back-calculation models provided significant fits to the AIDS data.

Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:43:y:1997:i:3:p:291-295

DOI: 10.1016/S0378-4754(97)00012-8

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