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Mapping local HIV epidemics can help target resources to areas with the greatest need
Roger Pebody, 2016-07-26 15:30:00
Global health agencies have recently put a new emphasis on geography.
UNAIDS have called for programmes to focus on “location and population”. PEPFAR
says there is a “need to do the right things in the right places at the right
time”. The Global Fund believes there is a need to “target resources to areas
with the greatest need”.
But how can these principles be applied in practice?
Speakers at the 21st International AIDS Conference (AIDS 2016) in
Durban, South Africa, last week outlined examples in which maps and geographic
analyses have helped improve HIV services. Their examples came from the United
States and South Africa.
Travis Sanchez of Emory University introduced AIDSVu, a set
of interactive, online maps that allows users to visually explore the HIV
epidemic in the United States. By making it readily accessible to policy makers,
it has been used to better target limited healthcare and HIV prevention
For example, Sanchez showed maps of Chicago, showing rates
of diagnosed HIV in different parts of the city, broken down by ethnic group. As
expected, rates in black people are higher than among whites and this is the
case throughout the city. But the map highlighted some unexpected clusters of
cases – high rates in white people in some predominantly black zip codes in the
city’s south-central area, as well as high rates in black people in some
predominantly white zip codes in the north-east of the city.
In Philadelphia, health officials used HIV prevalence data
at the census-tract level (the most detailed unit available, covering a
neighbourhood with a few thousand residents) in order to target door-to-door testing
campaigns. “This is really about targeting local resources in the local
communities that need them most,” Sanchez said.
Mapping rural Alabama it became clear that a number of counties
with high rates of HIV were also designated as ‘Health Professional Shortage
Areas’. With HIV concentrated in deprived populations who have limited access to transport
to medical facilities further afield, there is a potential for people to drop
out of care and have uncontrolled viral load. In response, health
officials set up a telemedicine service so that primary care clinics in the
under-served areas could be linked with medical providers elsewhere in Alabama.
A web-based video link (a bit like a Skype call) allows patients to receive
medical care and counselling at distance.
In Atlanta, the mapping demonstrated how HIV and poverty
overlapped. Looking into the data in more detail, ‘hot spots’ of poor linkage
to care and low rates of viral suppression were identified. While some areas of high HIV prevalence were served by HIV
treatment facilities, several other
hot spots were far from medical facilities, with low rates of car ownership and
poor public transport links.
Sanchez said that mapping these relationships had been “transformational”
in helping local officials identify the structural barriers to care and prepare
the local Strategy
to End AIDS. The plans place emphasis on creating patient-friendly systems
that facilitate entry into care, including transport support.
Frank Tanser of the Africa Centre for Population Heath has been intensively studying a
rural, poor area of KwaZulu Natal. His mapping shows that HIV incidence,
HIV prevalence and deaths are far from evenly distributed, with all three highly
concentrated in informal settlements and peri-urban areas bordering a major
“I think these maps speak to the tyranny of averages,”
Tanser said. Rather than spreading healthcare resources evenly across all
areas, there’s an opportunity to use this “incredible spatial heterogeneity” to
focus investment on the most vulnerable populations and so bring epidemics
under control, he said.
The maps have identified ‘hot spots’ in which a significant
proportion of people have uncontrolled HIV – in some specific locations, more
than one-in-four adults in the general population have a detectable viral load.
Such communities may not only have a high burden of HIV themselves, but may
also be driving onward transmission in the wider geographical area.
Phylogenetic analysis (examining the genetic links between
HIV in different individuals) suggests that a high proportion of new infections
in other communities can be linked back to individuals living in the ‘hot spot’
communities beside the highway. Transport and migration is likely to play
an important part in this.
Targeting resources so as to improve the treatment cascade
in these specific locations could have a disproportionate impact on the larger
epidemic, he suggested.
The examples presented to the conference depend on rich
sources of data. AIDSVu links extensive data collected by American public
health agencies with socio-economic information from the American census. The
Africa Centre conducts intensive HIV surveillance activities within a 20km by
20km area. How then can the approach be applied in settings where such
resources are not available?
Frank Tanser said that insights derived from studies, such
as the relationship between distance to health facility and HIV prevalence,
would likely be applicable elsewhere. Other urban and peri-urban informal
settlements in African countries are likely to be ‘hot spots’. Those located
near major transport routes are especially likely to contribute to new infections, but can also be easily reached by health providers.
One important gap in routinely collected data is that it
rarely records details that would identify individuals as members of key
populations (such as sex workers or people who inject drugs). As a result, key populations tend to be invisible in many spatial analyses although they may
cluster in specific areas. Frank Tanser said that there was potential to apply geographical
analyses to key populations (using respondent-driven sampling) but that there
could be sensitivities when mapping stigmatised and criminalised groups.
Closing the session, Gesine Meyer-Rath said that funders
were often very interested in mapping as targeting could mean that financial
resources could be used more efficiently. This could be a way of justifying spending
less. But she said that the same data could also be used by activists and
members of affected communities, to demand services where they really are needed.