Literature DB >> 8286495

Assessing the extent of the Australian HIV epidemic from AIDS surveillance data.

N G Becker1, L F Watson, I C Marschner, M Motika, S V Newstead, J B Carlin.   

Abstract

Current knowledge about human immunodeficiency virus (HIV) disease is used to assess past and future trends in Australian HIV/AIDS (acquired immune deficiency syndrome) incidence, focusing on the precision with which such assessments can be made. The statistical method of back-projection is applied to reconstruct the past pattern of HIV incidence from surveillance data on AIDS incidence to June 1992. The results indicate that HIV incidence rose rapidly in the early 1980s to peak in 1983-1984, followed by a sharp decline. This finding is insensitive to plausible variations from the assumptions made, and is consistent with both success in preventive strategies and high levels of infection in a subgroup having a high probability of exposure. Cumulative HIV incidence to the end of 1987 is estimated with a 90 per cent confidence interval from 9,350 to 10,350. Estimation of the cumulative HIV incidence to June 1992 is less precise, with a 90 per cent confidence interval of 12,900 to 17,800. After adjustment for underreporting the incidence could be as high as 22,000, but only if recent infection rates, which cannot be quantified accurately, were very high. Based on data to June 1992, the estimated trend in AIDS incidence indicates 680 new cases in 1993, rising gradually to 695 in 1995. The estimated rate of increase in AIDS incidence over the recent past and near future is significantly less than that observed earlier in the epidemic. This is a consequence of both the earlier peak in HIV incidence and the effect of therapy.

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Year:  1993        PMID: 8286495     DOI: 10.1111/j.1753-6405.1993.tb00140.x

Source DB:  PubMed          Journal:  Aust J Public Health        ISSN: 1035-7319


  2 in total

1.  Characterizing trends in HIV infection among men who have sex with men in Australia by birth cohorts: results from a modified back-projection method.

Authors:  Handan Wand; David Wilson; Ping Yan; Andrea Gonnermann; Ann McDonald; John Kaldor; Matthew Law
Journal:  J Int AIDS Soc       Date:  2009-09-18       Impact factor: 5.396

2.  Back-projection of COVID-19 diagnosis counts to assess infection incidence and control measures: analysis of Australian data.

Authors:  I C Marschner
Journal:  Epidemiol Infect       Date:  2020-05-18       Impact factor: 2.451

  2 in total

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