Introduction

Methods

Results

Discussion

References

Introduction

Spatial mapping of infectious diseases, including malaria, tuberculosis, cholera, and HIV has shown considerable spatial heterogeneity in disease prevalence and incidence. From a public health perspective, a primary objective of mapping efforts is the identification of so-called hotspots—typically defined as spatial clusters of elevated disease burden or transmission efficiency—to target the highest risk populations, and maximise the public health effect of interventions. Geographically focused approaches to disease control are supported by modelling studies, which suggest that targeting a small proportion of the population with elevated contact rates and disease incidence (ie, a core group) relative to the overall population has the potential to avert most infections, otherwise known as the 80/20 rule. However, the overall projected impact of targeted interventions depends on the rate of transmission from core groups to the rest of the population.1 Targeting core groups has been used in the control of sexually transmitted infections for decades, for example gonorrhoea, in which geo-targeted approaches to high-burden areas have proved effective. With respect to HIV, the President’s Emergency Plan for AIDS Relief, the Global Fund, WHO, and UNAIDS among others have advocated geographical targeting of HIV control interventions to hotspots. These recommendations include calls for HIV elimination in the USA, based on targeting of geographical hotspots to “disrupt the kinetics of HIV spread”. Although targeting interventions to high-burden populations is ethically justified, and necessary for reducing HIV morbidity and mortality, it is unclear whether such focused approaches would also reduce transmission more broadly. In some cases, HIV hotspots and other high-prevalence groups have been directly or implicitly assumed to constitute core groups disproportionately disseminating infection to the wider transmission network. This assumption, while potentially stigmatising for residents living in hotspots, implies that geographically focused interventions would not only have a direct impact in the targeted geographies but also indirect benefits in the broader population. However, this theory of infection flow from high to low burden populations is rarely confirmed in practice, in part because it is difficult to empirically measure. In sub-Saharan Africa, where two-thirds of new HIV infections worldwide occur, hotspots include fishing communities bordering the Great Lakes of east and central Africa. These communities typically have a high HIV prevalence, ranging from 20% to 40%, and HIV incidence exceeding 3% annually. Historically, Lake Victoria fishing communities also have populations with high levels of mobility, HIV-related risk behaviours, and high sexual contact rates, as well as limited access to health services relative to inland east African populations. In 2013, the Ugandan Ministry of Health classified Lake Victoria fishing communities as priority populations for targeted combination HIV prevention services including antiretroviral therapy (ART) at time of HIV diagnosis irrespective of CD4 cell count, HIV counselling and testing, male circumcision, and risk reduction education. The rationale for targeting fishing communities was based on their high HIV burden, and because they were believed to be acting as core groups sustaining the generalised inland epidemic.