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Prediction of HIV and AIDS Incidence Using a Back-calculation Model in Korea  

Lee, Ju-Young (Division of Epidemiologic Investigation, Department of Infectious Disease Control, National Institute of Health)
Goh, Un-Yeong (Division of Epidemiologic Investigation, Department of Infectious Disease Control, National Institute of Health)
Kee, Mee-Kyung (Division of Epidemiologic Investigation, Department of Infectious Disease Control, National Institute of Health)
Kim, Jee-Yun (Department of Mathematics and Statistics, Inha University)
Hwang, Jin-Soo (Department of Mathematics and Statistics, Inha University)
Publication Information
Journal of Preventive Medicine and Public Health / v.35, no.1, 2002 , pp. 65-71 More about this Journal
Abstract
Objective : To estimate the status of HIV infection and AIDS incidence using a back-calculation model in Korea. Methods : Back-calculation is a method for estimating the past infection rate using AIDS incidence data. The method has been useful for obtaining short-term projections of AIDS incidence and estimating previous HIV prevalence. If the density of the incubation periods is known, together with the AIDS incidence, we can estimate historical HIV infections and forecast AIDS incidence in any time period up to time t. In this paper, we estimated the number of HIV infections and AIDS incidence according to the distribution of various incubation periods Results : The cumulative numbers of HIV infection from 1991 to 1996 were $708{\sim}1,426$ in Weibull distribution and $918{\sim}1,980$ in Gamma distribution. The projected AIDS incidence in 1997 was $16{\sim}25$ in Weibull distribution and $13{\sim}26$ in Gamma distribution. Conclusions : The estimated cumulative HIV infections from 1991 to 1996 were $1.4{\sim}4.0$ times more than notified cumulative HIV infections. Additionally, the projected AIDS incidence in 1997 was less than the notified AIDS cases. The reason for this underestimation derives from the very low level of HIV prevalence in Korea, further research is required for the distribution of the incubation period of HIV infection in Korea, particularly for the effects of combination treatments.
Keywords
Back-calculation; Incubation period distribution; Infection rate; Poisson regression;
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  • Reference
1 국립보건원. HIV 감염자 발생현황，2001
2 Schwartlander B, Stamecki K.A., Brown T., Way P.O., Monasch R. et al. Country-specific estimates and models of HIV and AIDS: methods and limitations. AIDS 1999; 13:2445-2458
3 이순영. 한국의 에이즈 관리 및 감시체계의효과적 운영방안. 1995, 한국보건사회연구원
4 Taylor JM. Models for the HIV infection and AIDS epidemic in the United States, Statistics in Medicine 1989; 8: 45-58   DOI   PUBMED   ScienceOn
5 De Gruttola V, Lagakos SW. Analysis of doubly-censored survival data with applications to AIDS, Biometrics 1989a;45: 1-11   DOI   PUBMED   ScienceOn
6 O' sullivan F. A Statistical perspective on ill-posed inverse problems. Statistical Science 1986; 1: 502-27   DOI   ScienceOn
7 Brookmeyer R, Liao J. Statistical Methods for reconstructing infection curves. In Jewell N, Dietz K, Farewell V(eds), AIDS Epidemiology: Methodo-logic Issues, 1992, pp 39-60. Boston:Birkh$\"{a}$user
8 Brookmeyer R, Gail MH. Minimum size of the acquired immunodeficiency syndrome(AIDS) epidemic in the United States. Lancet 1986: 2: 1320-22   PUBMED
9 Brookmeyer R, Damiano A. Statistical methods for short-term projections of AIDS incidence, Statistics in Medicine 1989; 8: 23-34   DOI   ScienceOn
10 Karon JM, Dondero TJ Jr, Curran JW. The projected incidence of AIDS and estimated prevalence of HIV infection in the United States. J Acquired Immune Deficiency Syndrome 1988; 1(6):542-50
11 Isham V. Estimation of the incidence of HIV infection, Philosopical Transaction of the Royal Society of London. Series B, 1989; 325: 113-21
12 Brookmeyer R, Gail MH. AIDS Epide-miology: A Quantitative Approach. Ox-ford university Press, 1993
13 UNAIDS, Report on the global HIV/AI-DS epidemic. June. 2000
14 Brookmeyer R, Gail MH. A method of obtaining short-term projections and lower bounds on the size of the AIDS epidemic. JASA, 1988; 83: 301-08   DOI   ScienceOn
15 Commenges D, Etcheverry B. An empi-rical Bayes approach to the estimation of the incidence curve of HIV infection. Statistics in Medicine 1993; 12(14):1317-24   DOI   ScienceOn
16 Brookmeyer R. Reconstruction and future trends of the AIDS epidemic in the United States. Science 1991; 253: 37-42   DOI   PUBMED
17 Bacchetti P, Segal M, Jewell NP. Back-calculation of HIV infection rates(with discussion), Statistical Science, 1993
18 Down AM, Heisterkamp SH, Brunet JB, Hamers FF. Reconstruction and predic-tion of HIV/AIDS epidemic among adults in the European Union in the low prevalence countries of central and eas-tern Europe. AIDS 1997; 11(5): 649-62