Estimating the size of the MSM populations for 38 European countries by calculating the survey-surveillance discrepancies (SSD) between self-reported new HIV diagnoses from the European MSM internet survey (EMIS) and surveillance-reported HIV diagnoses among MSM in 2009
1 Department of Infectious Disease Epidemiology, Robert Koch Institute, P.O. Box 650261, 13302 Berlin, Germany
2 Sigma Research, London School of Hygiene and Tropical Medicine, London, UK
BMC Public Health 2013, 13:919 doi:10.1186/1471-2458-13-919Published: 3 October 2013
Comparison of rates of newly diagnosed HIV infections among MSM across countries is challenging for a variety of reasons, including the unknown size of MSM populations. In this paper we propose a method of triangulating surveillance data with data collected in a pan-European MSM Internet Survey (EMIS) to estimate the sizes of the national MSM populations and the rates at which HIV is being diagnosed amongst them by calculating survey-surveillance discrepancies (SSD) as a measure of selection biases of survey participants.
In 2010, the first EMIS collected self-reported data on HIV diagnoses among more than 180,000 MSM in 38 countries of Europe. These data were compared with data from national HIV surveillance systems to explore possible sampling and reporting biases in the two approaches. The Survey-Surveillance Discrepancy (SSD) represents the ratio of survey members diagnosed in 2009 (HIVsvy) to total survey members (Nsvy), divided by the ratio of surveillance reports of diagnoses in 2009 (HIVpop) to the estimated total MSM population (Npop). As differences in household internet access may be a key component of survey selection biases, we analysed the relationship between household internet access and SSD in countries conducting consecutive MSM internet surveys at different time points with increasing levels of internet access. The empirically defined SSD was used to calculate the respective MSM population sizes (Npop), using the formula Npop = HIVpop*Nsvy*SSD/HIVsvy.
Survey-surveillance discrepancies for consecutive MSM internet surveys between 2003 and 2010 with different levels of household internet access were best described by a potential equation, with high SSD at low internet access, declining to a level around 2 with broad access. The lowest SSD was calculated for the Netherlands with 1.8, the highest for Moldova with 9.0. Taking the best available estimate for surveillance reports of HIV diagnoses among MSM in 2009 (HIVpop), the relative MSM population sizes were between 0.03% and 5.6% of the adult male population aged 15–64. The correlation between recently diagnosed (2009) HIV in EMIS participants and HIV diagnosed among MSM in 2009 as reported in the national surveillance systems was very high (R2 = 0.88) when using the calculated MSM population size.
Npop and HIVpop were unreliably low for several countries. We discuss and identify possible measurement errors for countries with calculated MSM population sizes above 3% and below 1% of the adult male population. In most cases the number of new HIV diagnoses in MSM in the surveillance system appears too low. In some cases, measurement errors may be due to small EMIS sample sizes. It must be assumed that the SSD is modified by country-specific factors.
Comparison of community-based survey data with surveillance data suggests only minor sampling biases in the former that – except for a few countries - do not seriously distort inter-country comparability, despite large variations in participation rates across countries. Internet surveys are useful complements to national surveillance systems, highlighting deficiencies and allowing estimates of the range of newly diagnosed infections among MSM in countries where surveillance systems fail to accurately provide such data.