1. Building Capacity for Geospatial Analysis and Data Demand and Use
to Improve Resource Allocation for HIV Programs: Experiences from Iringa, Tanzania
INTRODUCTION
In an increasingly resource-constrained
environment, effective programming
for public health is essential. To
appropriately target resources,
decision-makers need quality data in a
readily available format (tables, charts
and maps), as well as the capacity to
use these products for decision making.
Using geospatial analysis and data
demand and use (DDU) approaches,
we facilitated the use of maps in
the decision-making process for HIV
programs in Iringa Region of Tanzania.
We describe how we combined
Priorities for Local AIDS Control Efforts
(PLACE) - a methodology for identifying
local venues where sexual partnerships
form and where key populations,
especially female sex workers,
congregate - with geographical
information system (GIS) in mapping
of HIV prevention services, care and
treatment sites, population data and
semi-annual program performance
data to estimate the coverage of
HIV/AIDS services in Iringa Region
of Tanzania. We highlight how this
work contributed to improved decision
making and resource allocation in the
region through mentoring in use of
maps for data presentation and data
demand and use.
Figure 2: Hotspots and VCT coverage, Iringa Region
This research has been supported by the President’s Emergency Plan for AIDS Relief (PEPFAR) through the U.S. Agency for International
Development (USAID) under the terms of MEASURE Evaluation cooperative agreement GHA-A-00-08-00003-00, which is implemented by
the Carolina Population Center at the University of North Carolina at Chapel Hill, with Futures Group, ICF International, John Snow, Inc.,
Management Sciences for Health, and Tulane University. The views expressed in this publication do not necessarily reflect the views of
PEPFAR, USAID or the United States government.
PRESENTED BY
Y.W. Mapala
J. Patrick
M. Cunning
Z. Kibao
W.O. Odek
D. W alker
MEASURE Evaluation,
Futures Group
20th International
AIDS Conference
July 20–25, 2014
Melbourne, Australia
CONTACT US
MEASURE Evaluation
400 Meadowmont Village Circle, 3rd Floor
Chapel Hill, NC 27517 USA
www.measureevaluation.org
email: measure@unc.edu
Tel: +1.919.445.9350
Fax: +1.919.445.9353
DESCRIPTION
To determine the location of HIV
prevention services and HIV/AIDS
transmission hotspots, we conducted
key informant interviews at health
facilities and communities, respectively.
With the aid of maps, interviewers
asked the interviewees to identify
where the majority of their clients came
from. This information was used to
generate GIS datasets of the estimated
reach of the health facilities. The areas
reached by services were overlaid on
population data to estimate the total
population served within the catchment
of a health facility. Further, based on
HIV prevalence and district sex and
age distributions, the estimated target
population for different HIV prevention
programs were calculated. These
estimates were then compared to the
reported number of people receiving
prevention services through United
States government-supported programs
to determine level of coverage. The
level of coverage was determined
for three consecutive six-month time
periods: October 2009 to March
2010, April 2010 to September
2010 and October 2010 to March
2011. The service coverage maps
were overlaid with the PLACE survey
maps to show the relationship between
the hot-spots identified, the need for
HIV prevention services and where
HIV prevention services were being
provided. The catchment and coverage
for each service were compared with
each other, and with demographic and
geographic features.
Figure 1: Participants in a GIS training workshop
LESSONS
LEARNED
Maps showing catchment areas of
each HIV/AIDS prevention service and
transmission hotspots were produced
for the whole region and districts
within it. These maps were integrated
to show gaps in prevention services.
District-level staff were able to identify
gaps and prioritize interventions
using the integrated GIS maps. For
example, Mufindi district added four
new care and treatment sites for under-served
areas, while Iringa municipal,
Kilolo, and Njombe districts have
included integrated GIS maps in their
comprehensive district health plans.
Some of the districts are now able to
edit their maps and add new service
points, collect GPS coordinates and
import the coordinates into Quantum
GIS and customize maps according to
their needs.
District staff were mentored on how to
use the maps produced to advocate
for data-informed decision making and
resource allocation. The knowledge
and interest in GIS and data use have
expanded to non-HIV programs. For
example, upon their request, our team
conducted geographic mapping of
solid waste disposal points for Iringa
Municipal Council to improve their
waste disposal management.
CONCLUSIONS
Integrated GIS data have the potential
to provide strong evidence for
decision making. However, decision
makers need the skills and analytical
capacity to effectively use the data
and GIS map products for policy and
programmatic decision making on
a routine basis. We used an open
source software (QGIS) in order to
make this technology sustainable to the
district staff as they will incur no cost to
produce maps in the future. Also, we
have provided training materials for
GIS and DDU to the districts to enable
them sustain these efforts.
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