Drug-related infectious diseases
Drug-related infectious diseases such as HIV and hepatitis B and C are among the most serious health consequences of drug use. They may have the largest economic impact on health care systems of all consequences of drug use, even in countries where HIV prevalence in injecting drug users (IDUs) is low. These are the target group for measuring prevalence of drug-related infections defined as any person who has ever in their lifetime injected a drug for non-medical purposes.
The EMCDDA is systematically monitoring HIV and hepatitis B and C (prevalence of antibodies, or other specific markers in the case of hepatitis B) among injecting drug users as a complement to existing notification and case reporting systems that follow trends in counts of cases. National notification data are often unreliable due to under-reporting of large proportions of asymptomatic or chronic cases (hepatitis B/C), while HIV case reporting has not been implemented in some of the most affected countries. Other infections may in the future be added to the EMCDDA monitoring system (e.g. sexually transmitted infections, tuberculosis) while a rapid alert system is being maintained to report outbreaks of serious infections such as tetanus and wound botulism that may be related to infected batches of injectable drugs.
To improve HIV and hepatitis B/C monitoring in IDUs the EMCDDA follows two lines of work:
1) Collecting existing prevalence (HIV and hepatitis B/C) and notification data (hepatitis B/C only – HIV case reports are obtained from EuroHIV in aggregate format using a standard data reporting form;
2) Stimulating new sero-behavioural studies in injecting drug users, by maintaining an expert network to discuss methods and work towards common protocols.
The EMCDDA has developed draft guidelines (106KB) for the national focal points to collect the existing prevalence and notification data and it is working on a toolkit for seroprevalence studies based on a draft consensus protocol prepared on the basis of an expert network of longitudinal (cohort) studies.
To further improve the comparability of prevalence data in IDUs, data are collected and reported on prevalence of HIV and hepatitis in young IDUs (under age 25) and new IDUs (who have injected less than 2 years). These indicators, and especially the data for new IDUs, are more sensitive to changes in incidence than is prevalence in all IDUs. In practice the target group differs slightly between settings: sero-prevalence data from needle exchanges by definition refer to current injectors (defined as having injected in the last 12 months) while data from hepatitis notifications or public health laboratories may be partly based on ex-injectors, so additional methodological data such as service setting are also collected.
The aggregate prevalence data collection through the standard reporting form has been successful. In few years time a general overview could be given of HIV and hepatitis B/C prevalence among IDUs in all EU Member States, going back to 1996 and in part even before. Many countries are able to provide up to date data with national coverage and in many cases there is regional breakdown or data from key regions or cities, often unpublished and recent. For example for HCV, data for 1996-2002 have been reported from 63 sources and 111 study sites in 14 countries, including in total 58 time series and 233 prevalence estimates. Similar data are available for HIV and HBV. Several countries are also providing hepatitis B/C notification data for IDUs. These data have proven useful to provide a general overview of the situation, showing regional variation in levels and trends. Although in general they show a stable prevalence of HIV and hepatitis among IDUs, they served to signal some increases in HIV or hepatitis among subgroups of IDUs in some countries.
However, the data are subject to important limitations: the use of varying source-types/settings (drug treatment, low-threshold, prisons etc.) that may result in different biases, in some cases non-adherence to the basic case definition of ‘ever-IDUs’ that by inclusion of non-IDUs may lead to severe downward bias, small sample sizes and other problems. Improving data quality and comparability proves difficult, as this depends on influencing often well-established data producing systems. Also, to get quality information on trends over time from routine diagnostic data (as opposed to well-defined prevalence studies) it is necessary to understand selection procedures for being tested, and if possible to work towards more standardisation in the criteria for screening IDUs in contact with services.
For more information see http://www.emcdda.europa.eu/?nnodeid=1375