Geographical mobility and heterogeneity of the HIV epidemic

Comment Geographical mobility and heterogeneity of the HIV epidemic Improved HIV surveillance, novel and creative data sources and data collection technologies, and long-term cohort studies help to identify ﬁ ne-scale geographical heterogeneities in HIV prevalence and incidence. In The Lancet HIV, Larry Chang and colleagues 1 document substantial heterogeneities using a population-based cohort study to assess HIV disease burden, sexual behaviours, and treatment and prevention service coverage in Rakai, Uganda. They mapped HIV prevalence and assessed diﬀ erences in HIV risk factors and uptake of antiretroviral therapy and male circumcision among people in agrarian (n=9931), trading (n=3318), and ﬁ shing (n=3870) communities. HIV prevalence ranged from 9% to 43%, with the highest prevalence in Lake Victoria ﬁ shing communities. This persistence of heterogeneity in HIV prevalence four decades since HIV/AIDS emerged in Uganda across communities even within a small geographical area is remarkable. The message is clear: geography aﬀ ects risk. How and why HIV risk can change so quickly over space and time is less clear, but is probably a result of patterns of human geographical mobility and contextual factors in addition to individual behaviours. To understand and respond to ﬁ ne-scale heterogeneities, we must consider the social and cultural contexts in which HIV continues to circulate. Rigorous social science theory and research need to be integrated into all stages of the scientiﬁ c process, from descriptive epidemiological studies to planning, targeting, and implementing HIV prevention eﬀ orts in transmission hotspots and most-at-risk populations. 2,3 In the case of African inland ﬁ shing communities, and indeed in most other settings where HIV prevalence is high, we must understand sex-speciﬁ c patterns of mobility and HIV risk to respond to the epidemic. The focus of mobility as a factor in risk, spatial diﬀ usion, and transmission dynamics of HIV has changed markedly since the early days of research on male truck drivers. 4,5 Increasingly, a thorough understanding of how and why mobility patterns are intertwined with HIV risk and transmission patterns over time and space is emerging because of attention paid to sex-speciﬁ c patterns of mobility and the gendered contexts in which they are embedded. 6,7 The concentrated HIV epidemic in ﬁ shing communities in the Lake Victoria basin provides a rich context for these advances in research and understanding (ﬁ gure). 8–12 The mobility of men who work in the ﬁ shing industry is well known, but mobility of women ﬁ sh traders who circulate between beaches and markets has received less attention. 8,12 Many people who work in the ﬁ sh industry also engage in a transactional, so called, ﬁ sh-for-sex economy in which traders exchange sex with ﬁ shermen to gain preferential ﬁ sh access (termed Jaboya in Kenya). Despite stigma surrounding these practices, 8 declines in the ﬁ sh population in Lake Victoria continue to foster ﬁ sh-for-sex relationships, reducing relationship durations and women’s bargaining power. 13 31°E 32°E 33°E Lancet HIV 2016 Published Online July 8, 2016 http://dx.doi.org/10.1016/ S2352-3018(16)30048-0 See Online/Articles http://dx.doi.org/10.1016/ S2352-3018(16)30034-0 See Online for appendix 34°E 35°E 1°N 1°N Uganda Opio et al, 2013 Kiwanuka et al, 2013 Kwena et al, 2010 Kenya Hoshi et al, 2016 1°S 1°S Asiki et al, 2011 2°S 2°S Komugola et al, 2010 N 3°S 3°S Tanzania 4°S 4°S Lake Victoria Lake Victoria Basin Country borders km 31°E 32°E 33°E 34°E 35°E Figure: HIV prevalence in Lake Victoria ﬁ shing communities, estimated in several research studies Map produced by Kevin Mwenda. References are provided in the appendix. www.thelancet.com/hiv Published online July 8, 2016 http://dx.doi.org/10.1016/S2352-3018(16)30048-0