Agustí et al. BMC Public Health (2020) 20:1533 https://doi.org/10.1186/s12889-020-09603-7 RESEARCH ARTICLE Open Access The role of socio-demographic determinants in the geo-spatial distribution of newly diagnosed HIV infections in small areas of Catalonia (Spain) Cristina Agustí1,2,3* , Núria Font-Casaseca4, Francesc Belvis5,6,7, Mireia Julià5,8, Núria Vives2,8, Alexandra Montoliu2,7, Juan M. Pericàs5,6,9,10, Jordi Casabona1,2,3,11 and Joan Benach5,6,12 Abstract Background: Spatial visualization of HIV surveillance data could improve the planning of programs to address the HIV epidemic. The objectives of the study were to describe the characteristics and the spatial distribution of newly diagnosed HIV infection in Catalonia and to identify factors associated with HIV infection rates. Methods: Surveillance data from the national registry were presented in the form of descriptive and ring maps and used to study the spatial distribution of new HIV diagnoses in Catalonia (2012–2016) and associated risk factors at the small area level (ABS, acronym for “basic health area” in Catalan). Incident cases were modeled using the following as predictors: type of municipality, prevalence of young men and migrant groups, GBMSM activity indicators, and other variables at the aggregated level. Results: New HIV diagnoses are heterogeneously distributed across Catalonia. The predictors that proved to be significantly associated with a higher rate of new HIV diagnoses were ABS located in the city of Barcelona (IRR, 2.520; P < 0.001), a higher proportion of men aged 15–44 years (IRR, 1.193; P = 0.003), a higher proportion of GBMSM (IRR, 1.230; P = 0.030), a higher proportion of men from Western Europe (IRR, 1.281; P = 0.003), a higher proportion of men from Latin America (IRR, 1.260; P = 0.003), and a higher number of gay locations (IRR, 2.665; P < 0.001). No association was observed between the HIV diagnosis rate and economic deprivation. Conclusions: Ring maps revealed substantial spatial associations for the rate of new HIV diagnoses. New HIV diagnoses are concentrated in ABS located in urban areas. Our results show that, in the case of HIV infection, the socioeconomic deprivation index on which the Catalan government bases its budget allocation policies among the ABS should not be the only criterion used. Keywords: HIV, Small areas, Income inequality, Neighborhood environment * Correspondence: cagusti@iconcologia.net 1 Centre d’Estudis Epidemiològics sobre les Infeccions de Transmissió Sexual i Sida de Catalunya (CEEISCAT), Agència de Salut Pública de Catalunya (ASPC), Generalitat de Catalunya, Edifici Muntanya, Ctra Can Ruti, Cami de les Escoles s/n, 08916 Badalona, Barcelona, Spain 2 Centro de Investigación Biomédica en Red de Epidemiologia y Salud Pública CIBERESP, Madrid, Spain Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Agustí et al. BMC Public Health (2020) 20:1533 Page 2 of 10 Background income inequality, low income, high unemployment, and The World Health Organization recommends that not high poverty correlate positively with the incidence of only should health outcomes, but also their societal dis- HIV. However, the relative importance of these factors tribution and determinants, be taken into account in differed with the population at risk: rates of infection by public health monitoring in order to inform policies, heterosexual contact were more significantly associated programs, and practices aimed at improving the health with income inequality and poverty, whereas GBMSM- of the population and achieving health equity [1]. Know- linked cases were not significantly associated with socio- ledge of the spatial incidence of HIV and associated vari- economic indicators [18]. ables can be of interest for the allocation of resources Catalonia, in the northeast of Spain has one of the and the design of health policies, as well as for generat- highest rates of new HIV diagnoses in the country. In ing theories concerning transmission pathways. 2017, a total of 578 new diagnoses were reported, that is, Factors associated with the incidence of HIV infection 8.1 per 100,000 persons [19], which is higher than the have proven to be diverse and distributed both world- European Union median (6.4 cases per 100,000 popula- wide and within countries and transmission groups. Pre- tion) [20]. Men account for 86% of cases. Half of the vious studies have revealed statistically significant diagnoses reported were in GBMSM (54%). Of these, differences in the distribution of new diagnoses by 47% were diagnosed in people born outside Spain. More demographic characteristics and urban setting, with HIV than half (58%) of all new diagnoses were made in the positivity rates being higher in urban areas [2]. On the city of Barcelona. The median age of the cases was 36 other hand, rural residents at risk for or living with HIV years. Of all new HIV diagnoses in 2017, 38% were aged infection face unique challenges [2, 3], namely, they are 30–39 years, 29% were ≥ 40 years, and 33% were under less likely to have been tested for HIV or have been 30 years [19]. In Spain, studies on the effect of the geo- tested in the past year than urban residents [4]. graphical and socioeconomic context in the distribution Population mobility is also a key driver of the HIV epi- of new HIV diagnoses are lacking. demic [5] and is linked to a higher incidence of infection The objectives of this study were to describe the char- [6]. Although attention in recent years has focused on acteristics and the spatial distribution of new HIV diag- migrants from high-prevalence countries with general- noses in Catalonia using ring maps and to identify ized epidemics, there is evidence that in Europe, specific factors that are potentially associated with HIV infection migrant groups from other regions with more concen- rates at the small area level. trated epidemics, such as gay, bisexual, and other men who have sex with men (GBMSM) from Latin America Methods and Western Europe, are also highly vulnerable to HIV We performed a cross-sectional ecological study using infection [7]. the “basic health area” (ABS [acronym in Catalan]) as Individual-level adverse health outcomes may be influ- the geographical study unit. The ABS is the regional de- enced directly or indirectly by the environment where a marcation used by the Catalan Health Service to person lives [8–10]. Gay neighborhoods have been asso- organize primary healthcare services. An ABS includes a ciated with HIV infection [11, 12], although there is reference territory of a primary health care team and its some debate over whether living in a gay neighborhood population, which comprises 5000–25,000 people. Those is a risk factor or protective factor. Tieu et al. [9] associ- ABSs with fewer than 5000 people were merged with ated living in a gay neighborhood with safer sex behav- bordering ABSs in order to protect the patient anonym- iors such as more frequent condom use for receptive ity. During the study period, the limits of the ABSs were and insertive anal sex. This agrees with the fact that in- sometimes modified (basically ABS splits); this problem dividuals who perceive a higher sense of community and was solved by maintaining the original division and ag- neighborhood participation are more likely to report gregating the data. Thus, we obtained a fixed number of fewer risk behaviors [9]. In contrast, living in a gay 355 ABSs. neighborhood has been associated with the use of drugs to enhance sexual experiences [11, 13]. New diagnoses of HIV data Studies performed in the United States of America We retrieved data on new HIV diagnoses reported from have reported that increased poverty and inequality are 2012 to 2016 in the Catalan HIV Surveillance Registry. associated with the diagnosis of HIV and other sexually The Registry is a population-based information system transmitted infections [14–16]. In contrast, a study per- of all persons residing in Catalonia at diagnosis of HIV formed in the United Kingdom showed an increased in- infection since 2001. The Registry provides the postal cidence of viral hepatitis and sexually transmitted code, sex, country of birth, age, and transmission mode. infections but not HIV infection in deprived areas in the We calculated five-year aggregated new HIV diagnoses north of England [17]. Buot et al. [18] reported that high for each ABS. Multiple-year counts provide more stable Agustí et al. BMC Public Health (2020) 20:1533 Page 3 of 10 estimates of HIV diagnoses, particularly in ABSs with provided by the Agency of Health Quality and Evalu- small populations. New diagnosis rates per 100,000 per- ation of Catalonia (AQuAS) and the Information System sons were calculated by dividing the incident case count for the Development of Research in Primary Care (SIDI by the five-year sum of the population assigned yearly to AP). each ABS. Finally, to identify the gay neighborhoods, all gay loca- tions (eg, bars, discotheques, saunas, hotels, shops, sex Exposure variables clubs, and travel agencies) located in Catalonia were re- To reflect territorial differentiation in Catalonia the ABSs trieved from the Spartacus Guide and Universo Gay were classified into five categories based on the character- (2018 editions) and later georeferenced to their corre- istics of the municipality where each ABS is located, sponding ABS. A total of 239 gay locations were namely, geographical location (Barcelona and its metro- mapped. politan area and rest of the territory), population (munici- palities with less than 10,000 inhabitants, 10,000–20,000 Spatial visualization methods and more than 20,000 inhabitants) and population density Multivariate ring maps based on Huang et al. and (inhabitants/km2 of the municipality or municipalities López-De-Fede et al. [15, 23] were constructed. A ring where the ABS is located). When the ABS included more map is a map surrounded by a set of concentric, seg- than one municipality and there was a discrepancy, the mented rings. Each ring displays an additional data di- municipality of superior rank was prioritized. The five mension that represents an attribute of a particular categories were urban Barcelona (ABS in Barcelona city), location. We built maps with a base map of Catalonia in urban metropolitan (ABS in municipalities included in the the center showing the rates of new HIV diagnoses for metropolitan area of Barcelona), urban county (ABS in each ABS surrounded by a set of histograms with the municipalities of more than 20,000 inhabitants and out- distribution of the mode of transmission of HIV, sex, side the metropolitan area of Barcelona), semi-urban and country of birth for ABSs with new HIV diagnoses (ABS in municipalities with a population of 10,000 and rates > 10 per 100,000 population. The ring maps were 20,000 inhabitants and a density of more than 150 in- developed using QGIS and Inkscape, both are and free habitants/km2, and, rural (ABS in municipalities with open source. fewer than 10,000 inhabitants or a density of less than 150 inhabitants/km2. Statistical analysis The percentage of men aged 15–44 years among the The univariate distribution of the new diagnoses of HIV assigned ABS population (year 2016) and the percentage infection, as well as its association with the predictor of men from Western Europe and Latin America (year variables, was examined from both the statistical and 2014) at the ABS level were calculated to account for geographical perspective using bivariate statistics. differences in the proportion of men in the most com- A negative binomial regression model with the popula- mon age range of new HIV diagnoses and the influence tion at risk as an offset was adjusted to account for the of the migrant population, respectively. The percentage overdispersion of new diagnoses of HIV infection. The for GBMSM as the transmission mode among new HIV exponentiated coefficients of the model is the incidence diagnoses was calculated by ABS. Given the very small rate ratio (IRR) relative to the reference category. counts in many ABSs, the Agresti-Coull binomial pro- Quantitative variables were scaled to make the IRRs portion estimation was used to obtain less extreme comparable. values; this approach also has the advantage of imputing The Moran I test was used to check for spatial auto- a value for ABS with zero incidence counts [21]. Relative correlation of the residuals, and a second model includ- socioeconomic disadvantage across Catalonia was evalu- ing an autocovariate based on the residuals of the first ated using a socioeconomic deprivation index built for one was fitted. The AIC, BIC, and McFadden’s pseudo the assignation of budgets to the primary healthcare R2 were calculated to test the quality of the model. All teams in Catalonia [22]. This index is a composite meas- calculations were performed using R. ure based on five indicators extracted from the national The study was approved by the Ethics Committee of health registry of 2015, as follows: percentage of manual Hospital Germans Trias i Pujol. workers, percentage of people with a low educational level, rate of premature mortality, rate of avoidable Results hospitalization, percentage of population exempt from The characteristics of the new HIV diagnoses reported pharmaceutical copayment, and percentage of popula- in Catalonia during the study period (2012–2016) are tion with an annual income lower than €18,000. All presented in Table 1. these predictor variables were acquired from the set of The choropleths in the base map of Fig. 1 show the basic health and health care indicators at the ABS level rates of new HIV diagnoses. New HIV diagnoses are far Agustí et al. BMC Public Health (2020) 20:1533 Page 4 of 10 Table 1 Characteristics of the new HIV diagnoses reported in Catalonia (Spain), 2012–2016. N: 3220 n % Rate of New HIV Diagnosesa 95%CI Sex Male 2810 87.28 6.93 (5.75–8.11) Female 410 12.73 1.04 (0.90–1.18) Country of birth Spain 1890 58.69 4.76 (4.23–5.29) Other 1330 41.30 3.2 (2.42–3.98) Transmission mode Heterosexual men 470 14.60 1.18 (1.04–1.32) Heterosexual women 313 9.72 0.8 (0.68–0.92) GBMSM 2009 62.39 4.88 (3.78–5.98) PWID 122 3.79 3.69 (2.77–4.61) Other 306 9.50 0.8 (0.68–0.92) Total 3220 100 7.97 (6.72–9.22) a per 100,000 persons GBMSM: Gay, bisexual and other men who have sex with men PWID: People who inject drugs Other: Parenteral transmission other than PWID, mother to child transmission and unknown Fig. 1 Rate of new HIV diagnoses per basic health area (ABS) in Catalonia (Spain), 2012–2016. N: 355 Agustí et al. BMC Public Health (2020) 20:1533 Page 5 of 10 from being homogenously distributed across Catalonia, area is shown in Fig. 2. Both maps reveal a spatial associ- with a gradient ranging from rural low-incidence areas ation between the rate of new HIV diagnoses and the to urban high-incidence areas and the highest rates in number of gay locations in the ABS. Gay locations were the ABSs of Barcelona city and its metropolitan area. A concentrated in downtown Barcelona city and in the vil- total of 22 ABSs out of 355 had no HIV diagnoses dur- lage of Sitges. The ABS “Universitat” (Barcelona), which ing the study period, while 31 had only one case. presented the highest rate, with 154.23 cases per 100,000 A marked gender difference was observed in the diag- persons, was the ABS with most gay venues (N = 82) in nosis rate (Fig. 1), with men being the most affected by Catalonia. The second ABS in number of gay references the HIV epidemic in Catalonia. The main mode of trans- was Sitges (N = 40), with a new HIV diagnosis rate of mission of HIV was GBMSM in the vast majority of 17.18 cases per 100,000 persons. ABSs, with a diagnosis rate > 10 cases per 100,000 popu- Mean new HIV diagnosis rates tended to increase in lation. The percentage of new HIV diagnoses among the all cases, with the exception of the deprivation index, migrant population varied widely across Catalonia where the highest HIV diagnosis rate (11.6 cases per (Fig. 1). 100,000 persons) was found in the first quartile of less The circles in the map of Figs. 1 and 2 show the gay deprived ABS. The Pearson correlation with the diagno- locations. A zoom of Barcelona city and its metropolitan sis rate was positive and significant (p < 0.001) for all the Fig. 2 Rate of new HIV diagnoses per basic health area (ABS) in Barcelona and its metropolitan area, Catalonia (Spain), 2012–2016 Agustí et al. BMC Public Health (2020) 20:1533 Page 6 of 10 Table 2 Mean rate of new HIV diagnoses in Catalonia basic diagnoses of HIV infection in Catalonia (Spain) and their health areas (ABS) for each quartile (2a) / category (2b) of the spatial distribution. We performed an ecological study at risk factor, 2012–2016. N: 355 the small area level based on surveillance data from the 2a) Quartile Corr.b national registry of new diagnoses of HIV and publicly 1st 2nd 3rd 4th accessible data from the Agency of Health Quality and Men, 15–44 years (%) 4.60 5.78 7.13 14.36 0.473*** Evaluation of Catalonia and the Information System for Men, Western Europe (%) 5.01 5.49 5.71 15.64 0.491*** the Development of Research in Primary Care. We also Men, Latin America (%) 3.90 4.74 6.70 16.52 0.318*** assessed the effect of the number of gay locations in the Gay references (count)a 6.22 30.50 50.14 67.44 0.725*** neighborhood. Infection from GBMSM (%) 5.31 4.77 5.93 17.68 0.410*** Geographical information systems can help to better understand the spatial distribution of HIV and high-risk Deprivation index 11.60 6.56 5.29 8.40 −0.129* areas for disease transmission and acquisition [24, 25]. 2b) Our study showed the heterogeneous distribution of the Type of municipality (n) Corr.c rate of new diagnoses across Catalonia. Our data re- Rural 125 21.15 0.289*** vealed differences for sex, transmission mode, and coun- Semi-urban 89 7.97 try of birth between small areas in Catalonia. The Urban (county) 26 3.66 highest rates of new HIV diagnoses were in ABSs lo- Urban (metropolitan) 48 5.31 cated in urban areas, especially the city of Barcelona. Urban (Barcelona) 67 7.03 While differences between urban and rural areas have Total 355 6.21 been reported [2], the fact that people living with HIV in a Quantiles calculated at 95, 97.5 and 99.15% for this variable rural areas are more likely to be diagnosed later than b Pearson their urban counterparts [26, 27] should be taken into c Eta-squared * Significant at p < 0.05; **Significant at p < 0.01; ***Significant at p < 0.001 account. Rural residents at risk for or living with HIV GBMSM: Gay, bisexual and other men who have sex with men experience barriers that include greater local stigma about HIV infection, a socially conservative climate, and factors considered except for the deprivation index scarcity of funding for widespread testing and treatment (Table 2a). The mean new diagnosis rate was clearly programs [3]. higher for the city of Barcelona than for the rest of Cata- Our results indicate that a higher percentage of trans- lonia (21.16 cases per 100,000 population), and type of mission via GBMSM in ABSs is associated with a higher municipality was significantly associated with HIV diag- incidence of HIV. This observation is consistent with the nosis rate (eta-squared = 0.289, p < 0.001) (Table 2b). finding that GBMSM was the most common transmis- The statistical modeling of new HIV diagnoses in sion mode in Catalonia during the study period, ranging Model (1) showed significant spatial autocorrelation from 53.7% of the new diagnoses of HIV infection re- (Moran I, 0.163, p < 0.001, see Table 3), suggesting the ported among GBMSM in 2012 to 57.3% in 2016 [19]. need for correction; therefore, only Model (2) results (in- We found that the HIV diagnosis rate was higher in cluding the autocovariate) are commented on. The Mc- ABSs with a higher number of gay locations. In Cata- Fadden R2 value was 0.236, indicating adequate lonia gay neighborhoods concentrate higher propor- goodness of fit of the model. The ABSs that proved to tions of GBMSM than other areas of settings. be significantly associated with a higher rate of new HIV Consequently, as GBMSM is the group most affected diagnoses were those located in the city of Barcelona by the HIV epidemic in Catalonia, we can expect to (IRR, 2.520; P < 0.001), those with a higher proportion of find higher rates of new diagnoses in these neighbor- men aged 15–44 years (IRR, 1.193; P = 0.003), those with hoods. The probability of acquiring the infection by higher proportion of MSM as the transmission mode having HIV-positive people among one’s own sexual (IRR, 1.230; P = 0.030), those with a higher proportion of contacts is higher for people living in areas with a men from Western Europe (IRR, 1.281; P = 0.003) and high prevalence of HIV. On the other hand, GBMSM men from Latin America (IRR: 1.260 P = 0.003), and living in gay neighborhoods often engage in the gay fast- those with a higher number of gay locations (IRR, 2.665; lane subculture (defined as a way of life that is full of ex- P < 0.001). On the contrary, no association was observed citement, activity, and often risk), where drug use is fre- between HIV diagnosis rate and economic deprivation quently perceived to be normative [28]. Previous studies (Table 3). associated living in a gay neighborhood with the use of drugs to enhance sexual experiences and recent unpro- Discussion tected anal intercourse [11, 13]. Thus, the neighborhood The main aim of this study was to identify socioeco- itself could shape riskier sexual behavior through social nomic risk factors associated with the rate of new networks and social norms. Agustí et al. BMC Public Health (2020) 20:1533 Page 7 of 10 Table 3 Factors associated with the rate of new HIV diagnoses in basic health areas (ABS) of Catalonia (Spain), 2012–2016. N: 355 MODEL (1) MODEL (2) Negative Binomial Model (1) + Autocovariate Coef. (95%CI) Pr(>|z|) Coef. (95%CI) Pr(>|z|) Variable (ABS level) Constant 0 (0–0) 0 < 0.001 0 (0–0) < 0,001 Type of municipality Rural Ref. Ref. Semi-urban 1.147 (0.962–1.369) 0,126 1.118 (0.941–1.329) 0,204 Urban (county) 1.586 (1.231–2.043) < 0.001 *** 1.44 (1.122–1.849) 0,004 ** Urban (metropolitan) 1.331 (1.063–1.669) 0,012 * 1.307 (1.048–1.630) 0,016 * Urban (Barcelona) 2.52 (2.020–3.149) < 0.001 *** 2.483 (2.004–3.080) < 0.001 *** Men, 15–44 years (%) 1.193 (1.113–1.280) < 0.001 *** 1.189 (1.112–1.272) < 0.001 *** a Men, Western Europe (%) [0.02–2.13] Ref. [2.13–13.2] 1.281 (1.085–1.513) 0,003 ** 1.29 (1.098–1.516) 0,002 ** Men, Latin America (%)a [0.45–5.35] Ref. [5.35–22.2] 1.26 (1.077–1.473) 0,003 ** 1.246 (1.071–1.449) 0,004 ** Gay references (count) [0–2] Ref. [3–6] 1.342 (0.995–1.824) 0,056 1.343 (1.009–1.799) 0,044 [7–82] 2.665 (1.924–3.742) < 0.001 *** 2.529 (1.853–3.491) < 0.001 *** b Infection from MSM (%) [0.72–45.4] Ref. Ref. (45.4–55.6] 0.878 (0.733–1.052) 0,158 0.887 (0.744–1.057) 0,181 [55.6–67.1] 1.024 (0.865–1.212) 0,779 1.027 (0.871–1.210) 0,751 [67.1–95.2] 1.23 (1.016–1.488) 0,03 * 1.226 (1.019–1.475) 0,028 * Deprivation indexb [0.00–37.4] Ref. Ref. [37.4–46.4] 1.031 (0.859–1.237) 0,745 1.004 (0.842–1.198) 0,965 [46.4–54.5] 1.045 (0.865–1.264) 0,647 1.009 (0.838–1.214) 0,926 [54.5–100.0] 1.131 (0.923–1.387) 0,237 1.092 (0.896–1.332) 0,382 Autocovariate – – – 1.156 (1.09–1.227) < 0.001 *** Model adjustment McFadden’s R2 0.226 0.236 -2LL − 1789.8 − 1767.4 AIC 1823.8 1803.4 BIC 1889.6 1873.1 n 355 355 g.l. 339 338 Moran I test 0.163 0,033 < 0.001 −0.038 0,033 0,841 *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001 a 1st-3rd vs. 4th quartile; bquartiles Agustí et al. BMC Public Health (2020) 20:1533 Page 8 of 10 The rate of new diagnoses of HIV infection is higher Nevertheless, it is important to remember that we in ABS with a higher proportion of migrants from West- used population-based sources of data on new HIV diag- ern Europe and Latin America. Transmission of HIV has noses and publicly available socioeconomic data. We been severely affected by mobility. Migrants are consid- complemented the results of the multivariate analysis to ered a key group at risk for HIV infection [6], and the describe the distribution of new HIV diagnoses with European Centre for Disease Prevention and Control geovisual representations using ring maps. Another (ECDC) and the European Commission consider them a strength of the study is the use of the ABS—the smallest priority group in HIV prevention and care [29]. In Cata- administrative territorial health unit in Catalonia—as a lonia, sex between men is the most frequent route of geographical study unit. This approach could potentially transmission among migrants from Western Europe facilitate future management of the HIV epidemic. (65%) and from Latin America (60.4%), who account for 19.8 and 70.5%, respectively, of all cases of HIV infection Conclusions reported among migrant GBMSM [30] in Catalonia. The Our results confirm the epidemiological pattern of the mode of transmission of HIV infection among migrants HIV epidemic observed in Catalonia. Nevertheless, the in Western Europe mimics epidemics in their countries spatial analysis we performed provided us with a very ac- of origin, that is, mainly through GBMSM. Conversely, curate picture of the heterogeneous distribution of new transmission of HIV infection between men is less com- diagnoses in Catalonia. We also determined factors re- mon in Latin America, and the high rates of HIV infec- lated to ABS with a higher rate of new diagnoses. Our tion among GBMSM from Latin America may reflect findings have important implications for the implemen- selective migration of GBMSM from this region to Eur- tation of a scientific and public health response to HIV/ ope owing to the more permissive attitudes toward same AIDS. We showed that socioeconomic deprivation is not sex relationships [7]. related to the incidence of HIV infection, thus indicating No association was observed between the socioeco- that the high rate of newly diagnosed HIV infection in nomic deprivation index and the new HIV diagnosis certain small areas suggests that the socioeconomic level rate. Other factors shown to be associated with the inci- should not be the only criterion for budgetary allocation dence of HIV infection among heterosexual men and in the ABS. Furthermore, HIV prevention programs in women and people who inject drugs include high in- Catalonia should continue to focus on GBMSM, mainly come inequality, low income, high unemployment, and in urban areas. Our study identified geographical hot- high poverty, although these are not significantly associ- spots for HIV and could help guide the locations where ated with incidence among GBMSM [18]. Economic HIV testing should be enhanced in primary care and deprivation is not thought to be a significant factor, where to implement specific HIV prevention campaigns. since the HIV epidemic in Catalonia is associated mainly with GBMSM. Previous studies have reported higher in- Abbreviations comes among GBMSM residing in gay neighborhoods ABS: Basic health area; AIDS: Acquired immune deficiency syndrome; than in those who do not [31]. Generally, urban areas GBMSM: Gay, bisexual and other men who have sex with men; HIV: Human immunodeficiency virus; IRR: Incidence rate ratios; PWID: People who inject with a high significance for the gay community confirm drugs the paradox of the post-Fordist city, i.e., ghettos develop in the city, although not all are marginal and some, for Acknowledgements example, gay neighborhoods, show signs of urban The authors thank the Heath Department of the Catalan Government (Spain) elitization [32]. and Thomas O’Boyle for reviewing the English. Joan Benach gratefully acknowledges the financial support by ICREA under the ICREA Acadèmia Our study has several limitations. Given that we report programme. the results of an ecological study at the ABS level, the inferences drawn are only valid at this level and do not Authors’ contributions demonstrate any causal relationship. Furthermore, our CA conceived of the original idea, lead the research and wrote the manuscript with input from all of the authors. NF participated in the study results are based on the place of residence of newly diag- design and made the ring maps. FB performed the statistical analysis and nosed persons. However, place of residence and place of contributed to the writing of the manuscript. MJ and JP contributed to the exposure may not necessarily be the same. Data on the study design and the interpretation of the results. NV and AM extracted and managed the data from the Catalan HIV Surveillance Registry and rate of new diagnoses were obtained from the Catalan participated in the study design. JB and JC supervised the study, participated HIV Surveillance Registry, where 10–20% of cases are in the study design and contributed to the interpretation of the results. All thought to be undiagnosed, as reported in similar regis- authors discussed the results and commented on the manuscript. The authors read and approved the final manuscript. tries [33]. The percentage of transmission among GBMSM is estimated from very small samples in many Funding ABSs. In addition, no information was available on the The study was funded by the Heath Department of the Catalan Government mode of transmission in 9% of all diagnoses. (Spain). Agustí et al. BMC Public Health (2020) 20:1533 Page 9 of 10 Availability of data and materials Syndr. 2015;70(2):204–11 Available from: http://www.ncbi.nlm.nih.gov/ Data is publically available on demand by contacting the correspondence pubmed/26068723. [cited 2019 Jul 1]. author: Cristina Agustí, cagusti@iconcologia.net. 8. Roux AVD. Investigating neighborhood and Area effects on health. Am J Public Health. 2001;91(11):1783–9. Ethics approval and consent to participate 9. Tieu HV, Koblin BA, Latkin C, Curriero FC, Greene ER, Rundle A, et al. The authors declare that the study was approved by the Ethics Committee Neighborhood and network characteristics and the HIV Care continuum of the Hospital Germans Trias i Pujol (Badalona, Spain). among gay, bisexual, and other men who have sex with men. J Urban Heal. 2018:1–17. https://doi.org/10.1007/s11524-018-0266-2. Consent for publication 10. Baral S, Logie CH, Grosso A, Wirtz AL, Beyrer C. Modified social ecological Not applicable. model: a tool to guide the assessment of the risks and risk contexts of HIV epidemics. BMC Public Health. 2013;13(1):1 Available from: BMC Public Competing interests Health. CA and JC had received Financial support for research and travel 11. Buttram ME, Kurtz SP. Risk and protective factors associated with gay reimbursements from Gilead Sciences and ViiV Healthcare. The other authors neighborhood Residence. Am J Mens Health. 2013;7(2):110–8. declare that they not have competing interests. 12. Bauermeister JA, Connochie D, Eaton L, Demers M, Stephenson R. Geospatial indicators of space and place: a review of multilevel studies of Author details HIV prevention and Care outcomes among young men who have sex with 1 Centre d’Estudis Epidemiològics sobre les Infeccions de Transmissió Sexual i men in the United States. J Sex Res. 2017;54(4–5):446–64. Sida de Catalunya (CEEISCAT), Agència de Salut Pública de Catalunya (ASPC), 13. Kelly BC, Carpiano RM, Easterbrook A, Parsons JT. Sex and the community: Generalitat de Catalunya, Edifici Muntanya, Ctra Can Ruti, Cami de les Escoles the implications of neighbourhoods and social networks for sexual risk s/n, 08916 Badalona, Barcelona, Spain. 2Centro de Investigación Biomédica behaviours among urban gay men. Sociol Heal Illn. 2012;34(7):1085–102. en Red de Epidemiologia y Salud Pública CIBERESP, Madrid, Spain. 3Fundació 14. Harling G, Subramanian SV, Bärnighausen T, Kawachi I. Income inequality Institut d’Investigació Germans Trias i Pujol IGTP, Badalona, Barcelona, Spain. and sexually transmitted in the United States: Who bears the burden? Soc 4 Department of Geography, Universitat de Barcelona, Barcelona, Spain. Sci Med. 2014;102:174–82. https://doi.org/10.1016/j.socscimed.2013.11.025. 5 Department of Political and Social Sciences, Health Inequalities Research 15. Lòpez-De Fede A, Stewart JE, Hardin JW, Mayfield-Smith K, Sudduth D. Group, Employment Conditions Knowledge Network (GREDS-EMCONET), Spatial visualization of multivariate datasets: an analysis of STD and HIV/ Universitat Pompeu Fabra, Barcelona, Spain. 6Johns Hopkins AIDS diagnosis rates and socioeconomic context using ring maps. Public University-Universitat Pompeu Fabra Public Policy Center, Barcelona, Spain. Health Rep. 126 Suppl 3:115–26 Available from: http://www.ncbi.nlm.nih. 7 Unit of Infections and Cancer - Information and Interventions (UNIC - I&I), gov/pubmed/21836744. [cited 2019 Apr 17]. Cancer Epidemiology Research Program (CERP), Hospitalet de Llobregat, 16. Krieger N, Waterman PD, Chen JT, Soobader M-J, Subramanian S. Barcelona, Spain. 8Cancer Screening Unit, Catalan Institute of Oncology, Monitoring socioeconomic inequalities in sexually transmitted infections, Hospitalet de Llobregat, Barcelona, Spain. 9Vall d’Hebron Institute for tuberculosis, and violence: geocoding and choice of Area-based Research (VHIR), Barcelona, Spain. 10Infectious Disease Department, Hospital socioeconomic measures—the public health disparities geocoding project Clínic de Barcelona, Barcelona, Spain. 11Departament de Pediatria, (US). Public Health Rep. 2003;118(3):240–60. d’Obstetrícia i Ginecologia i de Medicina Preventiva i de Salut Pública, 17. Hughes GJ, Gorton R. Inequalities in the incidence of infectious disease in Universidad Autónoma de Barcelona, Bellaterra, Cerdanyola del Vallès, the north east of England: a population-based study. Epidemiol Infect. 2015; Barcelona, Spain. 12Grupo de Investigación Transdisciplinar sobre Transiciones 143(1):189–201. Socioecológicas (GinTRANS2), Universidad Autónoma de Madrid, Madrid, 18. Buot MLG, Docena JP, Ratemo BK, Bittner MJ, Burlew JT, Nuritdinov AR, et al. Spain. Beyond race and place: distal sociological determinants of HIV disparities. PLoS One. 2014;9(4):e91711. Received: 29 May 2020 Accepted: 23 September 2020 19. Centre d’Estudis Epidemiològics sobre les Infeccions de Transmissió Sexual i Sida de Catalunya (CEEISCAT). Vigilància epidemiològica de la infecció pel VIH i la SIDA a Catalunya. Informe anual 2017. Badalona; 2018. References 20. European Centre for Disease Prevention and Control/WHO Regional Office 1. World Health Organization. MONITORING An essential step for achieving for Europe. HIV/AIDS surveillance in Europe 2017 – 2016 data. Stockholm: health equity [Internet]. Geneva; Available from: http://www.who.int/gho/ ECDC; 2017. health_equity/en/. Accessed 6 Oct 2020. 21. Agresti A, Coull BA. Approximate is better than “exact” for interval 2. Patel D, Taylor-Aidoo N, Marandet A, Heitgerd J, Maciak B. Assessing estimation of binomial proportions. Am Stat. 1998;52(2):119–26. Differences in CDC-Funded HIV Testing by Urbanicity, United States, 2016. J 22. García-Altés A, Ruiz-Muñoz D, Colls C, Mias M, Martín Bassols N. Community Health. 2019;44(1):95–102 Available from: http://www.ncbi.nlm. Socioeconomic inequalities in health and the use of healthcare services in nih.gov/pubmed/30069826. [cited 2019 Jul 1]. Catalonia: analysis of the individual data of 7.5 million residents. J Epidemiol 3. Schafer KR, Albrecht H, Dillingham R, Hogg RS, Jaworsky D, Kasper K, et al. Community Health. 2018;72(10):871–9. https://doi.org/10.1136/jech-2018- The Continuum of HIV Care in Rural Communities in the United States and 210817. Canada. JAIDS J Acquir Immune Defic Syndr. 2017;75(1):35–44 Available 23. Huang G, Govoni S, Choi J, Hartley D, Wilson J. Geovisualizing data with from: http://insights.ovid.com/crossref?an=00126334-201705010-00006. ring maps. ArcUser, Winter. 2008:54-55. http://www.esri.com/news/arcuser/ [cited 2019 Jul 1]. 0408/files/ringmaps.pdf.. 4. Ohl ME, Perencevich E. Frequency of human immunodeficiency virus (HIV) 24. Stopka TJ, Brinkley-Rubinstein L, Johnson K, Chan PA, Hutcheson M, Crosby R, et al. testing in urban vs. rural areas of the United States: Results from a HIV clustering in Mississippi: spatial epidemiological study to inform implementation nationally-representative sample. BMC Public Health. 2011;11(1):681 science in the deep south. JMIR Public Health Surveill. 2018;4(2):e35. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21884599. [cited 2019 25. Stopka TJ, Lutnick A, Wenger LD, DeRiemer K, Geraghty EM, Kral AH. Jul 1]. Demographic, risk, and spatial factors associated with over-the-counter 5. Deane KD, Parkhurst JO, Johnston D. Linking migration, mobility and HIV. syringe purchase among injection drug users. Am J Epidemiol. 2012;176(1): Trop Med Int Health. 2010;15(12):1458–63 Available from: http://doi.wiley. 14–23. com/10.1111/j.1365-3156.2010.02647.x. [cited 2019 Jul 1]. 26. Trepka MJ, Fennie KP, Sheehan DM, Lutfi K, Maddox L, Lieb S. Late HIV 6. Camlin CS, Charlebois ED. Mobility and its Effects on HIV Acquisition and Diagnosis: Differences by Rural/Urban Residence, Florida, 2007–2011. AIDS Treatment Engagement: Recent Theoretical and Empirical Advances. Curr Patient Care STDS. 2014;28(4):188–97 Available from: http://www.ncbi.nlm. HIV/AIDS Rep. 2019; Available from: http://www.ncbi.nlm.nih.gov/ nih.gov/pubmed/24660767. [cited 2019 Jul 11]. pubmed/31256348. [cited 2019 Jul 1]. 27. Hall HI, Tang T, Espinoza L. Late Diagnosis of HIV Infection in Metropolitan 7. Hernando V, Alvárez-del Arco D, Alejos B, Monge S, Amato-Gauci AJ, Noori Areas of the United States and Puerto Rico. AIDS Behav. 2016;20(5):967–72 T, et al. HIV Infection in Migrant Populations in the European Union and Available from: http://www.ncbi.nlm.nih.gov/pubmed/26542730. [cited 2019 European Economic Area in 2007–2012. JAIDS J Acquir Immune Defic Jul 11]. Agustí et al. BMC Public Health (2020) 20:1533 Page 10 of 10 28. Kurtz SP. In: Cohler B, editor. The story of sexual identy: Narrative perspectives on the gay and lesbian life course. New York: Oxford Uni. Hammack, PL; 2009. p. 157–75. 29. European Centre for Disease Prevention and Control (ECDC). Assessing the burden of key infectious diseases affecting migrant populations in the EU/ EEA. Stockholm: European Centre for Disease Prevention and Control; 2014. https://doi.org/10.2900/28792.2014. 30. Reyes-Urueña J, Campbell C, Hernando C, Vives N, Folch C, Ferrer L, et al. Differences between migrants and Spanish-born population through the HIV care cascade, Catalonia: an analysis using multiple data sources. Epidemiol Infect. 2017;145(8):1670–81 Available from: https://www. cambridge.org/core/product/identifier/S0950268817000437/type/journal_ article. [cited 2019 Jul 1]. 31. Mills TC, Stall R, Pollack L, Paul JP, Binson D, Canchola J, et al. Health-related characteristics of men who have sex with men: a comparison of those living in “gay ghettos” with those living elsewhere. Am J Public Health. 2001;91(6):980–3. 32. Salinas VF. Visibilidad y escena gay masculina en la ciudad española. Doc d’Analisi Geogr. 2007;49:139–60. 33. Mammone A, Pezzotti P, Regine V, Camoni L, Puro V, Ippolito G, et al. How many people are living with undiagnosed HIV infection? An estimate for Italy, based on surveillance data. AIDS. 2016;30(7):1131–6 Available from: http://www.ncbi.nlm.nih.gov/pubmed/26807973. [cited 2019 Jul 5]. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.