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HIV, HCV, and HBV in injecting drug users in Europe

EMCDDA conference. May 2009. HIV, HCV, and HBV in injecting drug users in Europe. Mirjam Kretzschmar Centre for Infectious Disease Control, RIVM, and Julius Center for Health Sciences & Primary Care University Medical Centre Utrecht, The Netherlands.

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HIV, HCV, and HBV in injecting drug users in Europe

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  1. EMCDDA conference May 2009 HIV, HCV, and HBV in injecting drug users in Europe Mirjam Kretzschmar Centre for Infectious Disease Control, RIVM, and Julius Center for Health Sciences & Primary Care University Medical Centre Utrecht, The Netherlands

  2. HIV infections newly diagnosed in injecting drug users, by year of report, by country, cases per million, 1996–2006. Source: EMCDDA website

  3. HIV prevalence among injecting drug users — studies with national and subnational coverage. 100% 75% All injecting drug users, 2005 and 2006 Young injecting drug users (under age 25), 2005 to 2006 Black dots: national Blue dots: subnational Source: EMCDDA website

  4. Estimated HCV antibody prevalence among injecting drug users — studies with national and subnational coverage 100% 100% Young injecting drug users (under age 25), 2005 to 2006 All injecting drug users, 2005 and 2006 Source: EMCDDA website

  5. Prevalence of markers of HBV infection estimated among national and subnational samples of injecting drug users 2005 to 2006, where data are available 100% 16% Percentage positive for current infection (HBsAg) Percentage positive for ever infected (antiHBc) Source: EMCDDA website

  6. Questions • How are HIV and HCV prevalence related? • And HBV? • How do these prevalences depend on risk behaviour, duration of injecting, intervention? • What is the impact of harm reduction on incidence and prevalence? Use statistical methods and mathematical modelling to get some answers

  7. Project • First project: Sept. 2006 – Nov. 2007 tendered by EMCDDA and conducted as a collaboration between EMCDDA and School of Public Health, University of Bielefeld • Set up team of modellers to work on analysis of European data • Produce 5 draft papers for publication in international journals • Resulted in collaboration with epidemiologists (the ‘Study group‘) • Second phase: Collaboration with WHO Europe project: ‘Review statistical methods for estimating HIV incidence in countries with concentrated epidemics’ • Discuss other modelling issues and approaches • Continue EMCDDA work, link with WHO interests • Background: EMCDDA EU network on drug related infectious diseases (HIV, hepatitis B/C in IDUs: experts, national focal points in 30 countries

  8. Relationships between HIV and HCV prevalence HIV and HCV prevalence data for 310 regions from published studies Thresholds? Vickerman et al. submitted

  9. Force of infection links incidence and prevalence • Force of infection (FOI): • risk per time unit for a susceptible person to become infected • depends on exposure and therefore on prevalence • can be different for different groups of IDU • can change during drug use career λ B susceptible μ

  10. Link between FOI and heterogeneity Sutton et al. J Viral Hepatitis 2008 Estimates of force of infections from seroprevalence studies in different populations Frailty function indicates heterogeneity with respect to exposure

  11. Force of infection as a function of time since start of injecting: Exposure duration • Caveats: • steady state assumption • impact of intervention? Hamata et al; in preparation

  12. How effective have NEPs been? Hurley et al Lancet 1997 Amundsen et al Eur J Pub Health 2003 How can we interpret ecological studies?

  13. Decline HIV and HCV incidence in ACS 1985-2005 Amsterdam Cohort Studies among drug users • Prospective HIV testing • Retrospectively tested for HCV antibodies • 952 ever injecting DU 58 HCV infections 90 HIV infections 30 HCV 0 10 HIV 0 Van den Berg et al. Eur J Epidemiol 2007 1985 - 2004

  14. Is it all really the effect of harm reduction? Possible other explanation: Demographic changes in IDU population (e.g., ageing) Disease related mortality in those groups at highest risk of infections in the first decade of the HIV epidemic might have led to a change in the composition of the IDU population with less risk behaviour and lower transmission rates at the population level over calendar time. Smit et al, JAIDS 2008

  15. Conclusions • Epidemiology of HIV and HCV is closely related, but need to understand better thresholds and transmission dynamics • Force of infection links incidence and prevalence, can say something about heterogeneity if we have data about more than on infection • The impact of calender time on these relationships is not yet clear, need cohort studies to analyse that • We need to disentangle impact of harm reduction from other influences – demographic changes, behaviour changes

  16. Acknowledgements • Lucas Wiessing • Peter Vickerman • Ziv Shkedy • Emma White • Andrew Sutton • Viktor Mravcik • Cathy Matheï • Maria Prins • Fernando Vallejo • Barbara Suligoi • Lillebil Norden and all other members of the study group

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