gh-2020_2 DEF.qxp_Hrev_master 15/01/21 12:47 Pagina 210 Geospatial Health 2020; volume 15:863 Spatial and temporal analysis of the human immunodeficiency virus in an area of social vulnerability in Northeast Brazil Géssyca Cavalcante de Melo,1,2 Emilia Carolle Azevedo de Oliveira,3 Iane Brito Leal,2 Carolina Piedade Morais de Freitas Soares Silva,3 Roberta Andrade Beltrão,3 Allan Dantas dos Santos,4 Renata Karina Reis,5 Marco Antônio Prado Nunes,2 Karina Conceição Gomes Machado de Araújo2 1State University of Health Sciences of Alagoas, Alagoas; 2Postgraduate Program in Health Science, Federal University of Sergipe; 3Instituto Aggeu Magalhães, Fundação Oswaldo Cruz, Pernambuco; 4Postgraduate in Nursing, Federal University of Sergipe, Sergipe; 5University of São Paulo, Brazil Spatial regression explained 46% of the dependent variable. The Abstract HIV incidence rate was positively influenced by rate of primary Human Immunodeficiency Virus (HIV) infection still repre- health care units (P=0.00), and negatively by Gini index (P=0.00) sents an important public health problem, because it involves clin- and proportion of heads of household without or low education ical, epidemiological, social, economic and political issues. We (P=0.02). We conclude that the relationship found between indica- analyzed the temporal and spatial pattern of the HIV incidence in tors of better socioeconomiconly conditions and HIV infection sug- an area of social inequality in northeast Brazil and its association gests unequal access to the diagnosis of infection. Prevention and with socioeconomic indicators. An ecological study was carried control strategies can be established according to each epidemio- out with a focus on all HIV cases reported in Alagoas State, logical reality. Northeast Brazil from 2007 to 2016 using its 102 municipalities as use the units of our analysis. Data from the Brazilian information sys- tems were used. Georeferenced data were analyzed using TerraView 4.2.2 software, QGis 2.18.2 and GeoDa 1.14.0. Time Introduction trend analyses were performed by the Joinpoint Regression soft- Human Immunodeficiency Virus (HIV) infection still repre- ware and the spatial analyses included the empirical Bayesian sents an important public health problem, because it involves clin- model and Moran autocorrelation. Spatial regression was used to ical, epidemiological, social, economic and political issues. determine the influence of space on HIV incidence rate and Currently, the number of people living with HIV worldwide is socioeconomic inequalities. There was an increasing trend of HIV estimated at 37.9 million, with Latin America considered the third rates, especially in the municipalities of the interior. Significant most affected region (UNAIDS, 2019). here, Brazil has the high- spatial correlations were observed with the formation of clusters est number of HIV cases (UNAIDS, 2019), despite being one of with emphasis on the coast of the state and in tourist regions. the countries that stand out in the infection treatment scenario due to the local production of drugs, free antiretroviral treatment pro- tocols and universal access (Galvão, 2002a; Galvão, 2002b). From 2007 to June 2019, 300,496 cases of HIV were registered in the Correspondence: Karina Conceição Gomes Machado de Araújo, country by the Ministry of Health (MoH), and the current inci- Marechal Rondon Avenue, São Cristóvão-SE, Zip code 49100-000, dence rate of the Acquired Immunodeficiency Syndrome (AIDS) Brazil. Non-commercial is 18.3 cases per 100,000 inhabitants (MoH, 2018). E-mail: [email protected] There is a tendency towards a reduction in the rate of HIV Key words: HIV; social vulnerability; spatiotemporal analysis; epi- detection observed in general in the country in the last 10 years. demiology, Brazil. However, it is still discreet and some places, especially the Northeast, have shown a substantial increase of cases detected in Conflict of interests: The authors declare no potential conflict of interests. the same period, which suggests the existence of concentrated epi- demics (Grangeiro et al., 2015; Sousa et al., 2016; MoH, 2018). Received for publication: 7 February 2020. This heterogeneity can lead to the hypothesis of a relationship Accepted for publication: 30 September 2020. between the social determination of the epidemic and geographi- cal context. Studies from different parts of the world have reported ©Copyright: the Author(s), 2020 Licensee PAGEPress, Italy the existence of regional sub-epidemics and have shown associa- Geospatial Health 2020; 15:863 tions between the spatial grouping of HIV incidence and mortality doi:10.4081/gh.2020.863 cases in areas with diverse individual, socioeconomic population and migration specificities (Zulu et al., 2014; Xing et al., 2014; This article is distributed under the terms of the Creative Commons Wand et al., 2015; Barankanira et al., 2016; Qian et al., 2014; Attribution Noncommercial License (CC BY-NC 4.0) which permits any Wabiri et al., 2016; Bose, 2017; Zhang et al., 2015; Momenyan et noncommercial use, distribution, and reproduction in any medium, pro- al., 2018). vided the original author(s) and source are credited. The investigation of relationships between illness and geo- [page 210] [Geospatial Health 2020; 15:863] gh-2020_2 DEF.qxp_Hrev_master 15/01/21 12:47 Pagina 211 Article graphic space over time is important to elucidate the extent and mary health care units calculated for 18,000 inhabitants, as recom- severity of the infection and its impact on public health. This mended by the Brazilian health system. makes it possible to identify specific demands, priority locations and more effective and equitable control interventions. More Data analysis specifically, this analysis can result in planning with the objective Trends in the number of new HIV cases per year were analyzed of early diagnosis in individuals with unknown serology enabling using a model based on the assumption of a minimum number of access to treatment, contributing to the non-development of the points (Joinpoint) to describe whether they were stable, increasing syndrome and consequently breaking the cycle of transmissibility. or decreasing over the period of time studied and the moment when These plans are important, especially given the Fast-Track strategy the trend had changed. The Annual Percentage Change (APC) was (90-90-90) proposed by the Joint United Nations Programme on calculated and a 95% confidence interval was adopted. The analy- HIV/AIDS (UNAIDS, 2019) to end the HIV epidemic by 2030. sis was performed using Joinpoint Regression software (Statistical This strategy proposes that, by 2020, 90% of all people living with Methodology and Applications Branch, Surveillance Research HIV must be diagnosed and know they carry the virus; that 90% of Program of the National Cancer Institute, USA, version 4.7.0.0, those diagnosed receive treatment continuously; and that, of those National Cancer Institute, USA). who receive treatment, at least 90% reach an undetectable viral For the construction of spatial analysis maps, we used the car- load. In this study, we analysed the temporal and spatial patterns of tographic base of the State of Alagoas, which is available in an the HIV incidence rates in an area of social inequality in north- electronic database of the IBGE. The georeferenced data were eastern Brazil and its association with socioeconomic indicators analysed using TerraView (National Institute for Space Research, from 2007 to 2016. (Instituto Nacional de Pesquisas Espaciais, INPE), SP, BR 4.2.2), Open Source Geospatial Foundation (QGIS) of OSGeo, CHI, USA, Version 2.18.2) and GeoDa (Spatial Analysis Laboratory, University of Illinois, Urbanaonly Champaign, USA, version 1.14.0). Materials and methods The maps were compiled from the average incidence rates of HIV infection recorded in two periods by municipality (2007–2011 Design and study and 2012–2016). Incidence rates were smoothed by the local This was an ecological study with temporal and spatial compo- empirical Bayesianuse method to correct random fluctuations in pop- nents. The spatial units of analysis were the 102 municipalities in ulations or small occurrence numbers by means of a re-estimate the state of Alagoas, located in north-eastern Brazil. According to that considers autocorrelation between rates in neighbouring areas. the Brazilian Institute of Geography and Statistics (Instituto For this, a weighted average was obtained between the measured Brasileiro de Geografia e Estatística, IBGE), Alagoas has a popu- value and the average neighbourhood rate, with weights inversely lation of 3,375,823 inhabitants in an area of 278,185 km² and has proportional to the population of each area (Almeida, 2012). the lowest Human Development Index (HDI) in the country To estimate the variability of the space in the data analysis, a (IBGE, 2010). In addition, the state has the highest income proximity matrix was built, in which the adjacent municipalities inequality in the country, with a Gini index of 0.711 (IBGE, 2019). received the value 1 and those that did not have adjacent border geometries were categorized with the value 0. The univariate Sample, data sources and measures Global Moran’s statistic was used to identify spatial autocorrela- The study included all cases of HIV in individuals aged 13 tions using values ranging from -1 to 1, which indicate clusters of years or older diagnosed during the period from 1 January 2007 to areas with similar risks for the