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BackgroundHIV-, HCV- and HIV/HCV co-infections among drug users have become a rapidly emerging global public health problem. In order to constrain the dual epidemics of HIV/AIDS and drug use, China has adopted a methadone maintenance treatment program (MMTP) since 2004. Studies of the geographic heterogeneity of HIV and HCV infections at a local scale are sparse, which has critical implications for future MMTP implementation and health policies covering both HIV and HCV prevention among drug users in China. This study aimed to characterize geographic patterns of HIV and HCV prevalence at the township level among drug users in a Yi Autonomous Prefecture, Southwest of China.MethodsData on demographic and clinical characteristics of all clients in the 11 MMTP clinics of the Yi Autonomous Prefecture from March 2004 to December 2012 were collected. A GIS-based geographic analysis involving geographic autocorrelation analysis and geographic scan statistics were employed to identify the geographic distribution pattern of HIV-, HCV- and co-infections among drug users.ResultsA total of 6690 MMTP clients was analyzed. The prevalence of HIV-, HCV- and co-infections were 25.2%, 30.8%, and 10.9% respectively. There were significant global and local geographic autocorrelations for HIV-, HCV-, and co-infection. The Moran’s I was 0.3015, 0.3449, and 0.3155, respectively (P < 0.0001). Both the geographic autocorrelation analysis and the geographic scan statistical analysis showed that HIV-, HCV-, and co-infections in the prefecture exhibited significant geographic clustering at the township level. The geographic distribution pattern of each infection group was different.ConclusionHIV-, HCV-, and co-infections among drug users in the Yi Autonomous Prefecture all exhibited substantial geographic heterogeneity at the township level. The geographic distribution patterns of the three groups were different. These findings imply that it may be necessary to inform or invent site-specific intervention strategies to better devote currently limited resource to combat these two viruses.

BackgroundPrevious studies have shown inconsistent or even contradictory results for some risk factors associated with HIV infection among drug users, and these may be partially explained by geographical variations.MethodsData were collected from 11 methadone clinics in the Liangshan Yi Autonomous Prefecture from 2004 to 2012. A non-spatial logistical regression model and a geographically weighted logistic regression model were fitted to analyze the association between HIV infection and specific factors at the individual level.ResultsThis study enrolled 6,458 patients. The prevalence of HIV infection was 25.1 %. The non-spatial model indicated that being divorced was positively associated with HIV infection. The spatial model also showed that being divorced was positively associated with HIV infection, but only for 49.4 % of individuals residing in some northern counties. The non-spatial model suggested that service sector work was negatively associated with HIV infection. However, the spatial model indicated that service work was associated with HIV infection, but only for 23.0 % of patients living in some western counties. The non-spatial model did not show that being married was associated with HIV infection in our study field, but the spatial model indicated that being married was negatively associated with HIV infection for 12.0 % of individuals living in some western counties. For other factors, the non-spatial and spatial models showed similar results.ConclusionThe spatial model may be useful for improving understanding of geographical heterogeneity in the relationship between HIV infection and individual factors. Spatial heterogeneity may be useful for tailoring intervention strategies for local regions, which can consequently result in a more efficient allocation of limited resources toward the control of HIV transmission.Electronic supplementary materialThe online version of this article (doi:10.1186/s40249-015-0073-x) contains supplementary material, which is available to authorized users.

BackgroundYi people make up about 50% of the population in Liangshan Prefecture, Sichuan Province, China, but accounted for 88.07% of new HIV cases in the prefecture from 2011 to 2013. This study evaluated HIV prevalence in pregnant women of Liangshan Prefecture using HIV sentinel surveillance (HSS) data over the period of 2009 to 2015.MethodsXichang, Zhaojue County, and Butuo County were selected as HSS sites. We investigated the temporal trends in HIV prevalence in these areas, and the association between demographic and behavioral characteristics and risk of HIV infection.ResultsData on a total of 2797 pregnant women in Xichang and 3983 pregnant women in Zhaojue and Butuo was collected for the period 2009 to 2015. There was a fluctuating HIV prevalence among pregnant women of Xichang, with a rate of 0.75% in 2015 (χ2trend = 2.27, P = 0.13). HIV prevalence among pregnant women of Zhaojue and Butuo was consistently high, varying between 3.4% (9/267, 2011) and 10.3% (82/796, 2012) over the period of 2010 to 2015 (χ2trend = 0.12, P = 0.73). In Xichang, we found that Yi ethnicity (OR = 11.37, 95% CI = 2.92–44.25) and a husband who used drugs (OR = 32.13, 95% CI = 5.33–193.67) were significantly associated with HIV risk in pregnant women. For Zhaojue and Butuo, we observed that pregnant women had a higher risk of HIV infection when they were over 30 years old (OR = 1.72, 95% CI = 1.17–2.52), when they had a higher number of previous births, when their husbands had a history of migrating for work (OR = 1.56, 95% CI = 1.16–2.08), and when they had a history of other sexually transmitted infections (OR = 2.19, 95% CI = 1.16–2.08). Compared to those with a primary school education or below, pregnant women with a secondary or high school education level had a lower risk of HIV infection (OR = 0.28, 95% CI = 0.09–0.89).ConclusionOur results indicate that there is a serious HIV epidemic among pregnant Yi women, especially for those with less education, more past births, or a husband with a history of out-migrating for work or STD infection.