Literature DB >> 19036911

Modelling and calibration of the hepatitis C epidemic in Australia.

K Razali1, J Amin, G J Dore, M G Law.   

Abstract

Hepatitis C virus (HCV) infection in Australia is predominantly transmitted through injecting drug use. A reduction in the heroin supply in Australia in late 2000 and early 2001 may have impacted the number of injecting drug users (IDUs) and the number of new hepatitis C infections. This paper updates estimates of HCV incidence between 1960 and 2005 and models long-term sequelae from infection. Outcomes among those with HCV were also recently assessed in a linkage study assessing cancer and causes of death following HCV diagnosis in New South Wales. Linkage study outcomes have been used here to calibrate modelled outcomes. Mathematical models were used to estimate HCV incidence among IDUs, migrants to Australia from high HCV-prevalence countries, and other HCV exposure groups. Recent trends in numbers of IDUs were based on indicators of injecting drug use. A natural history of HCV model was applied to estimate the prevalence of HCV in the population. Model predicted endpoints that were calibrated against the NSW linkage data over the period 1995-2002 were: (i) incident hepatocellular carcinoma (HCC); (ii) opioid overdose deaths; (iii) liver-related deaths; and (iv) all-cause mortality. Modelled estimates and the linkage data show reasonably good calibration for HCC cases and all-cause mortality. The estimated HCC incidence was increased from 70 cases in 1995 to 100 cases in 2002. All-cause mortality estimated at 1000 in 1995 increased to 1600 in 2002. Comparison of annual opioid deaths shows some agreement. However, the models underestimate the rate of increase observed between 1995 and 1999 and do not entirely capture the rapid decrease in overdose deaths from 2000 onwards. The linkage data showed a peak of overdose deaths at 430 in 1999 compared to 320 estimated by the models. Comparison of observed liver deaths with the modelled numbers showed poor agreement. A good agreement would require an increase in liver deaths from the assumed 2 to 5% per annum following cirrhosis in the models. Mathematical models suggest that HCV incidence decreased from a peak of 14,000 infections in 1999 to 9700 infections in 2005, largely attributable to a reduction in injecting drug use. The poor agreement between projected and linked liver deaths could reflect differing coding of causes of deaths, underestimates of the numbers of people with cirrhosis following HCV, or underestimates of rates of liver death following cirrhosis. The reasonably good agreement between most of the modelled estimates with observed linkage data provides some support for the assumptions used in the models.

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Year:  2008        PMID: 19036911     DOI: 10.1177/0962280208094689

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  4 in total

1.  Modelling the combined impact of interventions in averting deaths during a synthetic-opioid overdose epidemic.

Authors:  Michael A Irvine; Margot Kuo; Jane A Buxton; Robert Balshaw; Michael Otterstatter; Laura Macdougall; M-J Milloy; Aamir Bharmal; Bonnie Henry; Mark Tyndall; Daniel Coombs; Mark Gilbert
Journal:  Addiction       Date:  2019-06-28       Impact factor: 6.526

2.  Historical Trends in the Hepatitis C Virus Epidemics in North America and Australia.

Authors:  Chaturaka Rodrigo; Auda A Eltahla; Rowena A Bull; Jason Grebely; Gregory J Dore; Tanya Applegate; Kimberly Page; Julie Bruneau; Meghan D Morris; Andrea L Cox; William Osburn; Arthur Y Kim; Janke Schinkel; Naglaa H Shoukry; Georg M Lauer; Lisa Maher; Margaret Hellard; Maria Prins; Chris Estes; Homie Razavi; Andrew R Lloyd; Fabio Luciani
Journal:  J Infect Dis       Date:  2016-08-28       Impact factor: 5.226

3.  Modeling the initiation of others into injection drug use, using data from 2,500 injectors surveyed in Scotland during 2008-2009.

Authors:  Simon R White; Sharon J Hutchinson; Avril Taylor; Sheila M Bird
Journal:  Am J Epidemiol       Date:  2015-03-18       Impact factor: 4.897

4.  Hepatitis C virus prevalence in The Netherlands: migrants account for most infections.

Authors:  H J Vriend; M G Van Veen; M Prins; A T Urbanus; H J Boot; E L M Op De Coul
Journal:  Epidemiol Infect       Date:  2012-09-11       Impact factor: 4.434

  4 in total

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