Limited cross-border infections in patients newly diagnosed with HIV in Europe
- Dineke Frentz1,
- Annemarie M J Wensing2,
- Jan Albert3, 4,
- Dimitrios Paraskevis5,
- Ana B Abecasis6,
- Osamah Hamouda7,
- Louise B Jørgensen8,
- Claudia Kücherer7,
- Daniel Struck9,
- Jean-Claude Schmit9, 10,
- Birgitta Åsjö11,
- Claudia Balotta12,
- Danail Beshkov13,
- Ricardo J Camacho6, 14,
- Bonaventura Clotet15,
- Suzie Coughlan16,
- Stéphane De Wit17,
- Algirdas Griskevicius18,
- Zehava Grossman19,
- Andrzej Horban20,
- Tatjana Kolupajeva21,
- Klaus Korn22,
- Leondios G Kostrikis23,
- Kirsi Liitsola24,
- Marek Linka25,
- Claus Nielsen8,
- Dan Otelea26,
- Roger Paredes16,
- Mario Poljak27,
- Elisabeth Puchhammer-Stöckl28,
- Anders Sönnerborg4, 29,
- Danica Stanekova30,
- Maja Stanojevic31,
- Anne-Mieke Vandamme6, 32,
- Charles A B Boucher1,
- David A M C Van de Vijver1Email author and
- SPREAD Programme
© Frentz et al.; licensee BioMed Central Ltd. 2013
Received: 10 October 2012
Accepted: 8 March 2013
Published: 3 April 2013
International travel plays a role in the spread of HIV-1 across Europe. It is, however, not known whether international travel is more important for spread of the epidemic as compared to endogenous infections within single countries. In this study, phylogenetic associations among HIV of newly diagnosed patients were determined across Europe.
Data came from the SPREAD programme which collects samples of newly diagnosed patients that are representative for national HIV epidemics. 4260 pol sequences from 25 European countries and Israel collected in 2002–2007 were included.
We identified 457 clusters including 1330 persons (31.2% of all patients). The cluster size ranged between 2 and 28. A number of 987 patients (74.2%) were part of a cluster that consisted only of patients originating from the same country. In addition, 135 patients (10.2%) were in a cluster including only individuals from neighboring countries. Finally, 208 patients (15.6%) clustered with individuals from countries without a common border. Clustering with patients from the same country was less prevalent in patients being infected with B subtype (P-value <0.0001), in men who have sex with men (P-value <0.0001), and in recently infected patients (P-value =0.045).
Our findings indicate that the transmission of HIV-1 in Europe is predominantly occurring between patients from the same country. This could have implications for HIV-1 transmission prevention programmes. Because infections through travelling between countries is not frequently observed it is important to have good surveillance of the national HIV-1 epidemics.
KeywordsEurope HIV-1 Transmission Clusters
Travel and migration have contributed to the world-wide spread of HIV-1. For instance, HIV was introduced in the America’s through travel and migration from Africa and Haiti in the 1960s . Travel has also played a role in the early spread of HIV in East-Africa. A phylogenetic study that included geographic information found that the HIV epidemic spread more rapidly in areas in East-Africa with a good infrastructure that facilitates traveling . Moreover, we recently showed that within Europe Mediterranean countries are a source of HIV-1 subtype B infections for other European countries .
Although travel and migration played a key role in the early spread of HIV, it is not known to what extent travel explains current transmission of HIV. On the one hand, the importance of travel may have declined over the years, because travel from sub-Saharan Africa may have decreased due to stricter European immigration laws. But also among native-born Europeans, travel may have become less important for the spread of HIV. In Europe, the HIV prevalence is generally low, and stable at 0.2% over the last decade  and is concentrated mainly in specific risk groups (men who have sex with men (MSM) and injection drug users) . Because the HIV epidemic is well-spread in all European countries, many transmissions could take place within a country. On the other hand, the role of travel in transmission of HIV-1 may also have increased further in recent years. International travelling has become easier within Europe in the last decade because of low cost airlines and the absence of border control between most countries.
In this study we used data from the pan-European SPREAD project. SPREAD includes individuals newly diagnosed with a HIV-1 infection that are representative for the risk group and geographical distribution of the HIV epidemic in participating countries [6, 7]. By performing phylogenetic analyses on this data we estimated the proportion of individuals newly diagnosed with HIV that was infected within their own country.
Characteristics of patients
Continent of Origin, no. (%)
Eastern Europe & Central Asia
HIV-RNA load, mean (IQR), log copies/ml
CD4 cell count, median (IQR), cells/mm3
Age, mean years (IQR)
Gender, no. (%)
Risk group, no. (%)
Men having Sex with Men (MSM)
Injection drug use
CDC stage, no. (%)
A and B
Subtype, no. (%)
Duration of infection, no. (%)
TDRM, no. (%)
Comparison of the proportional HIV risk group distribution in the participating countries of the SPREAD study with proportional HIV risk group distribution collected in 2007 by the European Centres for Disease Prevention and Control (ECDC)
Men having Sex with Men(MSM)
Injecting drug users
More than half of all patients (55%) originated from Western Europe, followed by patients originating from Eastern Europe and Central Asia (22%) and from Sub-Saharan Africa (11%). A total of 3322 (77%) patients, were originating from a country in Europe. A number of 3035 (70%) patients were living in their country of origin. This ranged between 40.3% to 100%. The lowest proportions of people living in their country of origen were found in Israel (40.3%; 44% from Ethiopia), Sweden (48.2%; 4.5% from Thailand and 4.2% from Ethiopia), Norway (50.0%; 9.3% from Thailand and 5.9% in Ethiopia), and 51.1% in Ireland (7.6% from both the United Kingdom and Zimbabwe).
We found numerous differences between patients infected with a subtype B virus and patients infected with a non-B subtype virus. Not surprisingly, patients infected with a subtype B virus were less often originating from Sub-Saharan countries (0.7%) as compared to 31.7% in non-B subtype strains (P-value <0.0001). From this it follows that individuals harboring a subtype B strain were more often originating from European countries (89.8%) compared to 50.9% of individuals infected with a non-B strains (P-value <0.0001). Furthermore, patients with subtype B strains were more often MSM (71.9%) and recently infected (34.9%), than patients infected with a non-B subtype virus (13.6% and 15.9%, respectively) (both P-values <0.0001).
Patients that were part of a phylogenetic cluster had different characteristics as compared to patients that were not in a cluster. First, patients included in any cluster were more frequently infected through MSM (63.2% in a cluster vs. 41.3% of individuals that did not cluster, P-value <0.0001). Patients that were part of a cluster were more frequently infected with subtype B (82.5%; P-value <0.0001), recently infected (39.5%; P-value <0.0001) and harbouring a transmitted drug resistance mutation (10.4%, P-value =0.03) as compared to non-clustering patients (58.8%, 23.9%, and 8.3%, respectively). We observed a significant increase in cluster frequency among recently infected individuals from 33% in 2002 to 48% in 2007 (P-value = 0.002).
Of the clustering patients infected with a subtype B virus, 1013 (92.1%) patients were originating from a European country. In patients infected with a non-B subtype that were clustering, a smaller percentage of 63.5% originated from Europe (P-value <0.0001). Nonetheless, we found high proportions of patients originating from Europe in clustering patients infected with subtype F (25 out of 26, 96.2%), subtype A (44 out of 61, 72.1%) and subtype G (12 out of 19, 63.2%). Most of these patients infected with subtype F were living in Romania (n = 10) and Italy (n = 10) and were heterosexually infected (n = 17). Most of these patients infected with subtype A strains were living in Greece (n = 12), Latvia (n = 8), Cyprus (n = 6) and Austria (n = 6). In these patients, transmission through MSM was the most common route of transmission in patients from Greece (11 out of 12) and from Cyprus (3 out of 6), whereas in the other countries subtype A viruses were mostly transmitted among heterosexual patients. The 12 patients that were part of a cluster and were infected with subtype G were living in many different countries and were mainly heterosexual patients (n = 10).
Most patients (a number of 987, 74.2%) were part clusters that consisted only of patients originating from the same country of residence. The largest clusters were found in Poland (n = 15), Germany (n = 12 and 11), and the Czech Republic (n = 10). Among the remaining international clusters containing 343 patients, 135 (10.2%) of patients were in a cluster including only individuals from neighboring countries (the largest had 10 individuals from Denmark and Germany). Finally, 208 patients (15.6%) clustered with individuals from countries without a common border (including the largest cluster of 28 patients). The cluster size of 28 contained patients mostly living in the Czech Republic (n = 25) with two patients living in Slovakia and one patient living in Italy. Of these 28 patients, 24 patients reported to be MSM. In the 46 international clusters without a common border, most involved patients living in Spain (n = 18) or Germany (n = 15).
Characteristics of clusters and patients
All clusters, n
Clusters with one country of residence, n (%)
Clusters with neighbouring countries, n (%)
International clusters, n (%)
Characteristics of clusters
Characteristics of patients in clusters
Sensitivity analysis for cluster determination
Sensitivity analyses on proportion of clusters containing individuals with the same country of residence
Within one country
Without common border
Within one country
Without common border
In this large collection of sequences sampled from newly diagnosed individuals considering representativeness and large coverage across Europe, we found phylogenetic relationships (clusters) between isolates in one third of the study individuals. In these clusters, the vast majority of sequences were sampled from persons living in the same country. This suggests that a large part of the spread of HIV-1 in Europe can be explained by transmission of infections taking place between patients within the same country.
A strength of our study is the data collection that is performed within the SPREAD programme. The SPREAD programme is a large and sufficiently powered pan- European study that has been running since 2002. During this time the programme included patients newly diagnosed with HIV using a predefined strategy. This strategy allowed us to include patients considering representativeness for the national HIV epidemic in participating countries.
However, even though we achieved a very good overall representativeness of the European HIV-1 epidemic, we need to acknowledge that it is difficult to exclude the existence of minor sampling biases in specific countries and transmission groups. We assessed the representativeness by comparing the distribution of the transmission groups in all countries included in SPREAD with the HIV surveillance data from the European Centre for Disease prevention and Control (ECDC) (Table 2) and found that the proportional distribution of the different transmission groups was very comparable. However, compared to the data from ECDC, MSM were somewhat over-represented in some of the countries participating in SPREAD. In this study, we found MSM having a lower proportion of clustering patients from one country. An overrepresentation of MSM would therefore have resulted in a lower overall proportion of clustering patients from one country. This confirms our finding that HIV is mainly spreading within a country.
The results of this study are in agreement with phylogenetic studies performed in single European countries [9, 10]. First, a phylogenetic transmission study performed in Belgium found that local onward transmission of subtype B virus contributes to an important extent to the epidemic as virtually all patients part of a transmission cluster were of Caucasian origin . Second, a study from Switzerland found that clustering was segregated between different regions in the country, as transmission events occurred preferentially within the same Swiss region .
Our study found that patients infected with a non-B subtype virus were less often found in phylogenetic clusters (17.5%) as compared to patients infected with a subtype B virus (39.2%). This finding reflects differences between patients infected with HIV of non-B subtypes and patients infected with a B subtype. First, a much higher proportion of migrants originating from Sub-Saharan countries are infected with a non-B subtype. A Dutch modeling study showed that the migrant groups did not have a large influence on the Dutch HIV epidemic, due to the small number of migrants, their relatively moderate sexual risk behavior and low mixing with the Dutch heterosexuals . This is in concordance with phylogenetic studies in Switzerland which showed that non-B subtypes are a combined result of both migration and domestic transmission  whereas the subtype B epidemic is mainly driven by within country transmission . Second, patients infected with a non-B subtype are less frequently recently infected (<1 yr) as compared to patients infected with a subtype B virus, thus suggesting the possibility to became infected before they moved to Europe. Because non-B subtype patients are often chronically infected at time of diagnosis and have originated from many different countries, the chance of phylogenetic clustering in these patients is smaller. Also, patients infected with a non-B subtype are more often heterosexually infected. Compared to MSM, heterosexual individuals less frequently receive a HIV test. As a consequence HIV infections are less likely to be identified in a timely manner in heterosexually infected patients.
In all HIV risk groups, clustering was found mainly between patients with the same country of residence. However, differences were seen between the risk groups. MSM did less often cluster with patients from the same country than heterosexuals and injection drug users. This is also reflected in the lower percentage of seroconverters clustering within a country compared to the non-seroconverters, which could be ascribed to the fact that HIV-infected MSM are often diagnosed at an earlier stage of infection . The less frequently clustering MSM suggests that MSM more often get infected during travels to other European countries whereas heterosexuals and injection drug users get infected near home. This is supported by studies reporting an association of transmission of HIV-1 in injection users with extensive local epidemics [14, 15].
Sensitivity analyses showed that our findings were not distorted by the arbitrary cut-off values that were used for the bootstrap values and for the genetic distance. Using a more stringent genetic distance increased the percentage of patients clustering with patients living in the same country. Therefore, the percentage of patients clustering with patients living in the same country is at least 83.2% or higher, because the initial genetic distance used in the main analyses was taken very wide. Larger bootstrap values did not change the results in our study. Therefore, these results are generally robust and not influenced by the level of bootstrap values used in the cluster definition.
We did not have access to dense samples in which sequences from virtually all newly diagnosed HIV-infected individuals in a particular country are included. We may therefore have underestimated the size of the clusters or missed individuals for whom we currently did not identify a phylogenetically related sequence. This is the reason also why we probably estimated a large number of small clusters. Nonetheless, we still found that one out of three individuals was part of a cluster. In addition, dense sampling is expected not to have changed the results to a great extent as we achieved a very good overall representativeness of the European HIV-1 epidemic.
Our findings indicate that the transmission of HIV-1 in Europe is for a large part occurring between patients from the same country. These findings have significant public health implication, as they show that a large part of all HIV-1 infections in Europe could possibly be prevented by local interventions.
Ethical requirements are fulfilled according to the procedure described in the EC contract. The procedure differs among the 32 countries in the network according to national legislation. Briefly, for each participating hospital or collection center, approval was obtained by the institutional medical ethical review committee. Additionally, a written informed consent was obtained for each patient. In countries where a mandatory surveillance system was already established, legally no informed consent was needed. All surveillance data were made anonymous and coded at national level.
Data came from the SPREAD programme which included newly diagnosed HIV-1 infected patients of 18 years and older who had never been exposed to antiretroviral drugs from 2002–2007. A blood sample had to be collected from each patient within six months after diagnosis. The sampling strategies were defined in close collaboration with the national public health institutes in the participating countries that had access to the latest information on national HIV epidemics. To obtain representative samples from every country, the investigators selected individuals randomly or according to the national distribution of transmission risk groups and the geographical distribution of patients with new diagnoses of HIV-1 infection. Epidemiological, clinical, and behavioral data were collected using a standardized questionnaire within six months of diagnosis. More details on the sampling strategy are provided in previous publications from the SPREAD Programme [6, 7]. Within the SPREAD study, we defined patients as recently infected when patients had a duration of infection of less than one year. The duration of infection could be calculated when a last negative HIV-test was available 3 years before diagnosis. In these patients, the date of infection was estimated as the midpoint between the date of the last negative and first positive test. In addition, individuals were defined as recently infected if they had documented negative or indeterminate HIV-1 serological results up to 12 months prior to confirmation of diagnosis by western blot.
The GenBank accession numbers for the sequences used in this analysis are listed in the Appendix.
HIV-1 subtypes were determined by the Rega subtyping tool (version 2.0) . The Rega subtyping tool assesses HIV-subtypes by the construction of phylogenetic trees with group M pure reference sequences for subtypes A-D, F-H, J and K. A sequence is classified as a particular subtype when bootstrap values are >70% without recombination in the bootscan, and when they do not cluster with a circulation recombinant form with bootstrap >70%.
Isolates suggestive of intersubtype recombination in protease and reverse transcriptase fragments were analyzed by SimPlot 3.5.1 software . All sequences were aligned to consensus sequences from the Los Alamos Sequence Database using Clustal W as implemented in the BioEdit software . Sequences were then trimmed to equal length and the gaps were removed. In order to remove the influence of convergent evolution at antiretroviral drug resistance mutations on the phylogenetic analysis, we excluded all sites associated with major resistance according to the International AIDS Society-USA . In protease these positions are 30, 32, 33, 46, 47, 48, 50, 54, 58, 74, 76, 82, 84, 88, and 90. In reverse transcriptase the following positions were excluded: 41, 62, 65, 67, 69, 70, 74, 75, 77, 100, 101, 103, 106, 108, 115, 116, 151, 181, 184, 188, 190, 210, 215, 219 and 225. This resulted in 920 nucleotides that were used for phylogenetic analysis.
Phylogenetic analyses are computationally intensive. We therefore created two different datasets in order to analyse subtype B sequences (which is the most common subtype in Europe [6, 7]) separately from non-B subtype sequences. Subtype C was chosen as out-group for analysis of sequences of subtype B. Similarly, subtype B was taken as an out-group for the analysis of non-B subtypes. Phylogenetic trees were constructed using the MEGA5 integrated analysis software  by maximum likelihood methods under the general time-reversible model. The reliability of the maximum likelihood tree was determined using bootstrapping with 1000 replicates. To identify transmission clusters, the novel methodology for large-scale phylogeny partition was used . This method identifies transmission chains by conjugating the evaluation of node reliability, tree topology and patristic distance analysis and was validated in a large Italian cohort .
Clustering was based on high bootstrap values (>98%) and intra-cluster average branch lengths less than 0.03 nucleotide substitutions per site . We feel that these criteria are suitable for our epidemiological questions, but we acknowledge that there is no consensus on the definition of clusters. For this reason and because the cut-offs for bootstrap values and genetic distances could impact on clustering, we performed a sensitivity analysis in which clusters were defined using a less strict bootstrap value of 90%. In addition, we also did a sensitivity analysis using stricter cut-off values for the genetic distances of 0.02 and 0.01.
To study the demographics of the transmission clusters, we divided the clusters into clusters containing patients from the same country of residence, clusters with patients from countries of residence with a common border, and clusters with patients from different countries of residence which do not share a common border. We also divided Europe into three region: Central & East (Bulgaria, Croatia, Czech Republic, Latvia, Lithuania, Poland, Romania, Serbia, Slovakia, and Slovenia), West (Austria, Belgium, Denmark, Finland, Germany, Ireland, Luxembourg, the Netherlands, Norway, and Sweden), and South (Cyprus, Greece, Italy, Israel, Portugal, and Spain) to study the demographics of the transmission clusters geographically.
Categorical data were compared using the chi-square test. Multivariate analyses as well as the time trend analysis were performed with logistic regression. The univariate analyses where included in the multivariate analyses by the forward stepwise method in the SPSS programme.
GenBank Accession Numbers:
AJ971093, AJ971102, AJ971103, AJ971106, AJ971107, AJ971109, AJ971114, AJ971117, AJ971122, AJ971140, AJ971143, AJ971144, AY694290, AY694313, AY694317, AY694318, AY694321, AY694322, AY694324, AY694328-AY694330, AY694338, AY694339, AY694343-AY694345, AY694350, AY694353, AY694361, AY694362, AY694377, AY694382, AY938439, AY938441-AY938447, AY938453, AY938455, AY938460, AY938463-AY938465, AY938475, AY938476, AY938482, AY938487, AY938488, AY938490, AY938492, AY938510, AY938512, AY938513, AY938517, AY938521, AY938523, AY938531, DQ974841, DQ974844, DQ974845, DQ974847, DQ974848, DQ974850, DQ974853, DQ974854, DQ974857, DQ974858, DQ974863-DQ974865, DQ974867-DQ974873, DQ974875-DQ974877, DQ974880-DQ974882, DQ974887, DQ974890, DQ974892, DQ974893, DQ974895-DQ974897, DQ974899, DQ974902-DQ974906, DQ974908, DQ974910-DQ974912, DQ974922-DQ974924, DQ974927-DQ974929, DQ974931, DQ974932, DQ974941, DQ974944, DQ974945-DQ974947, DQ974951-DQ974953, DQ974955-DQ974963, DQ974965, DQ974966, DQ974968, DQ974982-DQ974991, DQ974996-DQ974998, DQ975003, DQ975011-DQ975015, DQ975018-DQ975021, DQ975024, DQ975032, DQ975034-DQ975036, DQ975044, DQ975136, DQ975139-DQ975147, DQ975156-DQ975159, DQ975161-DQ975163, DQ975165, DQ975169, DQ975172, DQ975173, DQ975187, EU248291-EU248297, EU248299, EU248300, EU248302, EU248303, EU248305-EU248307, EU248309, EU248310, EU248312, EU248314, EU248315, EU248317, EU248320-EU248323, EU248325, EU248327, EU248329, EU248331-EU248337, EU248340, EU248341, EU248343-EU248345, EU248347-EU248360, EU248363-EU248365, EU248368, EU248371-EU248373, EU248376-EU248378, EU248382, EU248383, EU248385-EU248387, EU248389, EU248392, EU248393, EU248396, EU248399-EU248401, EU248403, EU248404, EU248406-EU248408, EU248410-EU248412, EU248415-EU248419, EU248421-EU248426, EU248428, EU248431, EU248432, EU248435, EU248439-EU248444, EU248446, EU248448, EU248449, EU248451, EU248453, EU248455-EU248457, EU248459-EU248461, EU248463-EU248466, EU248468-EU248474, EU248476, EU248477, EU248479, EU248480, EU248483, EU248485, EU248487-EU248490, EU248492, EU248494-EU248498, EU248500-EU248505, EU248507, EU248509, EU248512, EU248515, EU248517-EU248521, EU248523, EU248526-EU248569, EU248571-EU248582, EU248584-EU248588, EU673374-EU673397, FJ030767, FJ030769, FJ030771, FJ030772, FJ185113-FJ185120, FJ185122, FJ185124, FJ185125, FJ185127, GQ398826-GQ399141, GQ399143-GQ399892, GQ399894-GQ400280, GQ400282-GQ400615, GQ400617-GQ400625, GQ400627-GQ400682, GQ400684-GQ400905, GQ400907-GQ400913, GQ400915-GQ401008, GQ401010-GQ401023, JX299533-JX299579, JX299581-JX299666, JX299668-JX299780, JX299782-JX301162.
We thank the patients and doctors throughout Europe, for their consent and support for the study.
ESAR Coordination Office: A. van Kessel
SPREAD Programme investigators (Strategy to Control the Spread of HIV-1). Austria: E. Puchhammer-Stockl (national coordinator), M. Sarcletti, B. Schmied,M. Geit, and G. Balluch. Belgium: A.-M. Vandamme (national coordinator), J. Vercauteren, I. Derdelinckx, A. Sasse, M. Bogaert, H. Ceunen, A. De Roo, S. De Wit, F. Echahidi, K. Fransen, J.-C. Goffard, P. Goubau, E. Goudeseune, J.-C. Yombi, P. Lacor, C. Liesnard, M. Moutschen, D. Pierard, R. Rens, Y. Schrooten, D. Vaira, L.P.R. Vandekerckhove, A. Van den Heuvel, B. Van Der Gucht, M. Van Ranst, E. Van Wijngaerden, B. Vandercam, M.Vekemans, C. Verhofstede, N. Clumeck, and K. Van Laethem. Cyprus: L. Kostrikis (national coordinator), I. Demetriades, I. Kousiappa, V. Demetriou, and J. Hezka. Czech Republic: M. Bruckova (national coordinator), M. Linka, and L. Machala. Denmark: C. Nielsen (national coordinator), L. B. Jørgensen, J. Gerstoft, L. Mathiesen, C. Pedersen, H. Nielsen, A. Laursen, and B. Kvinesdal. Finland: M. Salminen (national coordinator), M. Ristola, K. Liitsola, J. Suni, and J. Sutinen. Germany: K. Korn (national coordinator), C. Kücherer, T. Berg, P. Braun, G. Poggensee, M. Däumer, J. Eberle, O. Hamouda, H. Heiken, R. Kaiser, H. Knechten, H. Müller, S. Neifer, B. Schmidt, H. Walter, B. Gunsenheimer-Bartmeyer, and T. Harrer. Greece: D. Paraskevis (national coordinator), A. Hatzakis, E. Magiorkinis, E. Hatzitheodorou, C. Haida, A. Zavitsanou, G. Magiorkinis, M. Lazanas, M. Chini, N. Magafas, N. Tsogas, V. Paparizos, S. Kourkounti, A. Antoniadou, A. Papadopoulos, P. Panagopoulos, G. Poulakou, V. Sakka, G. Chryssos, S. Drimis, P. Gargalianos, M. Lelekis, G. Chilomenos, M. Psichogiou, G. L. Daikos, G. Panos, G. Haratsis, T. Kordossis, A. Kontos, G. Koratzanis, M. Theodoridou, G. Mostrou, and V. Spoulou. Ireland: S. Coughlan (national coordinator), C. De Gascun, C. Byrne, M. Duffy, C. Bergin, D. Reidy, G. Farrell, J. Lambert, E. O’Connor, A. Rochford, J. Low, P. Coakely, S. O’Dea and W. Hall. Israel: Z. Grossman (national coordinator), I. Levi, and D. Chemtob. Italy: C. Balotta (national coordinator), M. Franzetti, A. Lai, F. Binda, F. Tramuto, M. Ciccozzi, C. Mussini, G. Angarano, and G. Rezza. Luxembourg: J. C. Schmit (national coordinator), D. Struck, R. Hemmer, V. Arendt, T. Staub, F. Schneider, and F. Roman. The Netherlands: A. M. J. Wensing (national coordinator), C. A. B. Boucher (national coordinator), D. A. M. C. van de Vijver, A. van Kessel, P. H. M. van Bentum, K. Brinkman, E. L. op de Coul, M. E. van der Ende, I. M. Hoepelman, M. van Kasteren, J. Juttmann, M. Kuipers, N. Langebeek, C. Richter, R. M. W. J. Santegoets, L. Schrijnders-Gudde, R. Schuurman, and B. J. M. van de Ven. Norway: B. Åsjö (national coordinator), V. Ormaasen, and P. Aavitsland. Poland: A. Horban (national coordinator), J. J. Stanczak, G. P. Stanczak, E. Firlag-Burkacka, A. Wiercinska-Drapalo, E. Jablonowska, E. Małolepsza, M. Leszczyszyn-Pynka, and W. Szata. Portugal: R. Camacho (national coordinator), C. Palma, F. Borges, T. Paixão, V. Duque, and F. Araújo on behalf of the Portuguese SPREAD Network. Republic of Serbia: M. Stanojevic (national coordinator), Dj. Jevtovic, and D. Salemovic. Slovakia: D. Stanekova (national coordinator), M. Habekova, M. Mokras, and P. Truska. Slovenia: M. Poljak (national coordinator), M. Lunar, D. Babic, J. Tomazic, L. Vidmar, T. Vovko and P. Karner. Spain: B. Clotet (national coordinator), P. Domingo, M. J. Galindo, C. Miralles, M.A. del Pozo, E. Ribera, J. A. Iribarren, L. Ruiz, J. de la Torre, F. Vidal, F. Garcia and R. Paredes. Sweden: J. Albert (national coordinator), A. Heidarian, K. Aperia-Peipke, M. Axelsson, M. Mild, A. Karlsson, A. Sönnerborg, A. Thalme, L. Navér, G. Bratt, A. Karlsson, A. Blaxhult, M. Gisslén, B. Svennerholm, I. Bergbrant, P. Björkman, C. Säll, Å. Mellgren, A. Lindholm, N. Kuylenstierna, R. Montelius, F. Azimi, B. Johansson, M. Carlsson, E. Johansson, B. Ljungberg, H. Ekvall, A. Strand, S. Mäkitalo, S. Öberg, P. Holmblad, M. Höfer, H. Holmberg, P. Josefson, U. Ryding.
The work has been partially funded by the European Commission (grant QLK2-CT-2001-01344, fifth framework; grant LSHP-CT-2006-518211, sixth framework, grant DynaNets no. 233847), seventh framework; Belgian AIDS Reference Laboratory Fund, Belgian Fonds voor Wetenschappelijk Onderzoek (grant G.0611.09); Interuniversitaire Attractiepolen (Belgium; grant P6/41); Cyprus Research Promotion Foundation (grant Health/0104/22); Danish AIDS Foundation; Ministry of Health (Germany; grant 1502-686-18); Ministry of Education and Research (Germany; grant 01KI501); Fifth National Program on HIV/AIDS, Istituto Superiore di Sanità (Italy; grants N 40 F.56 and 20D.1.6); Fondation Recherche sur le SiDA; Ministry of Health (Luxembourg); Swedish Research Council; Swedish Civil Contingencies Agency; CHAIN, Collaborative HIV and Anti-HIV Drug Resistance Network’, Integrated Project no. 223131, funded by the European Commission Framework 7 Program; Ministry of Education and Science (Republic of Serbia; grant 175024). ABA is supported by Fundação para a Ciência e Tecnologia (grant no. SFRH / BPD / 65605 / 2009), Slovak Ministry of Health (Bratislava, grant 2005/37-SZU-15).
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