Maximising the effect of combination HIV prevention through prioritisation of the people and places in greatest need: a modelling study

BACKGROUND

Epidemiological data show substantial variation in the risk of HIV infection between communities within African countries. We hypothesised that focusing appropriate interventions on geographies and key populations at high risk of HIV infection could improve the effect of investments in the HIV response.

METHODS

With use of Kenya as a case study, we developed a mathematical model that described the spatiotemporal evolution of the HIV epidemic and that incorporated the demographic, behavioural, and programmatic differences across subnational units. Modelled interventions (male circumcision, behaviour change communication, early antiretoviral therapy, and pre-exposure prophylaxis) could be provided to different population groups according to their risk behaviours or their location. For a given national budget, we compared the effect of a uniform intervention strategy, in which the same complement of interventions is provided across the country, with a focused strategy that tailors the set of interventions and amount of resources allocated to the local epidemiological conditions.

FINDINGS

A uniformly distributed combination of HIV prevention interventions could reduce the total number of new HIV infections by 40% during a 15-year period. With no additional spending, this effect could be increased by 14% during the 15 years-almost 100,000 extra infections, and result in 33% fewer new HIV infections occurring every year by the end of the period if the focused approach is used to tailor resource allocation to reflect patterns in local epidemiology. The cumulative difference in new infections during the 15-year projection period depends on total budget and costs of interventions, and could be as great as 150,000 (a cumulative difference as great as 22%) under different assumptions about the unit costs of intervention.

INTERPRETATION

The focused approach achieves greater effect than the uniform approach despite exactly the same investment. Through prioritisation of the people and locations at greatest risk of infection, and adaption of the interventions to reflect the local epidemiological context, the focused approach could substantially increase the efficiency and effectiveness of investments in HIV prevention.

FUNDING

The Bill & Melinda Gates Foundation and UNAIDS.

Estimating the size of the female sex worker population in Kenya to inform HIV prevention programming

Background

The high burden of HIV infections among female sex workers (FSW) in sub-Saharan Africa has been long recognised, but effective preventive interventions have largely not been taken to scale. We undertook a national geographical mapping exercise in 2011/2012 to assess the locations and population size of FSW in Kenya, to facilitate targeted HIV prevention services for this population.

Methods and Findings

We used a geographical mapping approach, consisting of interviews with secondary key informants to identify “hot” spots frequented by FSW, their operational dynamics and the estimated numbers of FSW in those spots. This was followed by validation of the estimates through interviews with FSW at each spot identified. The mapping covered Nairobi, the capital city of Kenya, and 50 other major urban centres. In total, 11,609 secondary key informant interviews were conducted to identify FSW spots. Further, a total of 6,360 FSW were interviewed for spot validation purposes. A total of 10,670 spots where FSW congregate were identified. The estimated FSW population in all the towns mapped was 103,298 (range 77,878 to 128, 717). Size estimates in the towns mapped were extended to smaller towns that were not mapped, using a statistical model. The national urban FSW population estimate was 138,420 (range 107, 552 to 169, 288), covering all towns of over 5,000 population. We estimated that approximately 5% of the urban female population of reproductive age in Kenya could be sex workers, which is consistent with previous estimates from other sub-Saharan African countries.

Conclusions

This study provides the first national level data on the size of the FSW population in Kenya. These data can be used to enhance HIV prevention programme planning and implementation for FSW, to form the basis for impact evaluations, and to improve programme coverage by directing efforts to locations with the greatest need.

Road traffic injuries in Kenya: the health burden and risk factors in two districts

BACKGROUND

Road traffic injuries (RTIs) contribute to a significant proportion of the burden of disease in Kenya. They also have a significant impact on the social and economic well-being of individuals, their families, and society. However, though estimates quantifying the burden of RTIs in Kenya do exist, most of these studies date back to the early 2000s-more than one decade ago.

OBJECTIVE

This article aims to present the current status of road safety in Kenya. Using data from the police and vital registration systems in Kenya, we present the current epidemiology of RTIs in the nation. We also sought to assess the status of 3 well-known risk factors for RTIs-speeding and the use of helmets and reflective clothing.

METHODS

Data for this study were collected in 2 steps. The first step involved the collection of secondary data from the Kenya traffic police as well as the National Vital Registration System to assess the current trends of RTIs in Kenya. Following this, observational studies were conducted in the Thika and Naivasha districts in Kenya to assess the current status of speeding among all vehicles and the use of helmets and reflective clothing among motorcyclists.

RESULTS

The overall RTI rate in Kenya was 59.96 per 100,000 population in 2009, with vehicle passengers being the most affected. Notably, injuries to motorcyclists increased at an annual rate of approximately 29 percent (95% confidence interval [CI]: 27-32; P < .001). The mean age of death due to road traffic crashes was 35 years. Fatalities due to RTIs increased at an annual rate of 7 percent (95% CI: 6-8; P < .001) for the period 2004 to 2009. Observational studies revealed that 69.45 percent of vehicles in Thika and 34.32 percent of vehicles in Naivasha were speeding. Helmets were used by less than one third of motorcycle drivers in both study districts, with prevalence rates ranging between 3 and 4 percent among passengers.

CONCLUSIONS

This study highlights the significant burden of RTIs in Kenya. A renewed focus on addressing this burden is necessary. Focusing on increasing helmet and reflective clothing use and enforcement of speed limits has the potential to prevent a large number of road traffic crashes, injuries, and fatalities. However, it is difficult to demonstrate the magnitude of the injury problem to policymakers with minimal or inaccurate data, and this study illustrates the need for national continuous, systematic, and sustainable data collection efforts, echoing similar calls for action throughout the injury literature.