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The uptake and acceptance of Geographic Information Systems (GIS) technology has increased since the early 1990s and public health applications are rapidly expanding. In this paper, we summarize the common uses of GIS technology in the public health sector, emphasizing applications related to mapping and understanding of parasitic diseases. We also present some of the success stories, and discuss the challenges that still prevent a full scope application of GIS technology in the public health context. Geographical analysis has allowed researchers to interlink health, population and environmental data, thus enabling them to evaluate and quantify relationships between health-related variables and environmental risk factors at different geographical scales. The ability to access, share and utilize satellite and remote-sensing data has made possible even wider understanding of disease processes and of their links to the environment, an important consideration in the study of parasitic diseases. For example, disease prevention and control strategies resulting from investigations conducted in a GIS environment have been applied in many areas, particularly in Africa. However, there remain several challenges to a more widespread use of GIS technology, such as: limited access to GIS infrastructure, inadequate technical and analytical skills, and uneven data availability. Opportunities exist for international collaboration to address these limitations through knowledge sharing and governance. Full text
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Application of GIS technology in public health: successes
and challenges
South Western Sydney Local Health District, Public Health Unit, PO Box 38, Liverpool, NSW 1871, Australia
Division of IT, Engineering and the Environment, University of South Australia, GPO Box 2471, Adelaide, SA 5001,
(Received 1 July 2015; revised 29 November 2015; accepted 14 December 2015)
The uptake and acceptance of Geographic Information Systems (GIS) technology has increased since the early 1990s and
public health applications are rapidly expanding. In this paper, we summarize the common uses of GIS technology in the
public health sector, emphasizing applications related to mapping and understanding of parasitic diseases. We also present
some of the success stories, and discuss the challenges that still prevent a full scope application of GIS technology in the
public health context. Geographical analysis has allowed researchers to interlink health, population and environmental
data, thus enabling them to evaluate and quantify relationships between health-related variables and environmental risk
factors at dierent geographical scales. The ability to access, share and utilize satellite and remote-sensing data has
made possible even wider understanding of disease processes and of their links to the environment, an important consid-
eration in the study of parasitic diseases. For example, disease prevention and control strategies resulting from investiga-
tions conducted in a GIS environment have been applied in many areas, particularly in Africa. However, there remain
several challenges to a more widespread use of GIS technology, such as: limited access to GIS infrastructure, inadequate
technical and analytical skills, and uneven data availability. Opportunities exist for international collaboration to address
these limitations through knowledge sharing and governance.
Key words: Geographic information systems, infectious diseases, public health, parasitology, spatial analysis.
Geographic Information Systems (GIS) play a
major role in health care, surveillance of infectious
diseases, and mapping and monitoring of the
spatial and temporal distributions of vectors of infec-
tion (Shaw, 2012). GIS combine sophisticated
algorithms, spatial analysis, geo-statistics and mod-
elling, making GIS technology a powerful tool for
the prediction of disease patterns and parasite
ecology associations (Higgs, 2004;Guoet al. 2005;
García-Rangel and Pettorelli, 2013). Given the
variety of tools, concepts and applications of GIS
in public health, a brief synthesis of the state of the
eld is due. In this paper, we review examples of
successful applications of GIS in public health,
with emphasis on parasitic diseases. Some us eful
denitions and concepts of GIS discussed in this
paper are briey introduced here, but we refer
the readers to Caprarelli and Fletcher (2014 and
references therein) for a comprehensive review of
GIS architecture, availability, analytical tools,
and for a synthesis of relevant principles of spatial
analysis and modelling (Caprarelli and Fletcher,
Every GIS is structured around ve fundamental
components (Fig. 1): (i) spatially referenced data,
collected and stored in a relational geodatabase, i.e.
an information system from which data can be
retrieved by formulation of sequences of logical
queries; (ii) the hardware physically storing data
and processing tools; (iii) the software assembling
the user-interface algorithms by which users access
the database, query and analyse the data; (iv) the
algorithms and data management procedures; and
(v) the people, both producers and consumers of
spatial data. Each of these components incorporates
varying levels of complexity, depending on the
scope and scale for which GIS is used. Regardless
of the dierences, all systems provide basic
mapping and spatial analysis tools, which can be
mastered in relatively short time even by users
with no programming skills. The most basic opera-
tions involve creating maps by overlaying data
stored as tables comprising details of geographic fea-
tures symbolized by points, lines or polygons, or
raster datasets (e.g., photographs), and their geo-
graphic coordinates (an example is shown in
Fig. 2). Once the features are mapped, geo-statistical
analysis, such as cluster analysis and network ana-
lysis, important for disease monitoring and invest i-
gation (Bergquist and Rinaldi, 2010), can be
carried out using the analysis tools included in the
GIS software package. This basic approach may be
followed by more complex modelling to understand
* Corresponding author. South Western Sydney Local
Health District, Public Health Unit, PO Box 38,
Liverpool, NSW 1871, Australia. E-mail: stephanie.
Parasitology, Page 1 of 15. © Cambridge University Press 2016
the mechanisms of disease spreading, by linking
disease processes and explanatory spatial variables
(Graham et al. 2004). GIS has increased the accessi-
bility and reliability of integration between health
data and mapping processes (Brooker et al. 2009b),
allowing researchers to study the relationships
between spatial and temporal trends and risk
(Clements et al. 2006a; Brooker and Clements,
2009; Brooker et al. 2009b), and between environ-
mental factors and health, to all scales (McGeehin
et al. 2004; Beale et al. 2010). Examples include
the epidemiological application of data obtained
from climate-based forecast systems that include ob-
servation of oceans, land, elevat ions, land cover, land
use, surface temperatures and rainfall, for disease
surveillance and early-warning systems (Bergquist
and Rinaldi, 2010).
While GIS is broadly used in many countries as
part of routine public health management and ser-
vices, its diusion is not uniform across developing
countries, where some of the most lethal and crip-
pling parasitic diseases are endemic. We will
discuss some of the challenges faced by many coun-
tries in adopting GIS for routine monitoring and
spatial analysis of infectious diseases and of the en-
vironmental factors contributing to their spreading.
We also suggest possible simple and low-cost initia-
tives that might assist embracing this technology
more widely where it is most needed.
Personal experience, particularly of one of the
authors (SF-L), has been the principal source of in-
spiration for this paper. Working in the eld in
several developing regions in Central America and
the Western Pacic, has brought about the realiza-
tion that the management of some of the most
debilitating infectious diseases require eective
approaches, informed by geospatial analyses at the
local level. While regulations and ethical con sidera-
tions do not allow dissemination of specic informa-
tion collected in the eld, the authors believe that
addressing some of the more general aspects can
provide insight to public health practitioners glo-
bally. The authors observations and experiences
derived from eld notes [a concept frequently used
in qualitative studies (Baxter and Jack, 2008)],
have informed the challenges and solutions section.
These observations indicate that, in spite of the
obvious willingness of local public health workers
and some local communities to educate and train
themselves to combat and prevent the spread of
diseases, the uneven distribution of infrastructural
resources and expertise, otherwise taken for
granted in the developed world, stands in the way
of a systematic approach that would produce real
long-term benets.
Peer-reviewed reports describing how GIS has
been successfully applied to the monitoring and pre-
diction of parasitic diseases, focusing mainly on
examples from developing countries, were also
reviewed. This provided a clear indication that the
information collected and managed within a GIS is
linked to real and measurable public health benets
for communities in those regions. We then consid-
ered individually each of the ve principal elements
composing a GIS (Fig 1), to identify possible bar-
riers to their eective deployment in developing
countries, and referred to examples in the peer-
reviewed literature that could highlight specic chal-
lenges. Following this step we then looked at
Fig. 1. The ve components of GIS represented as the edges of a pentagon (left polygon in the gure): data, hardware,
software, procedures, people. Public health data are perfectly suited to be treated and analysed as information layers in a
GIS, provided location specic information (e.g., geographic coordinates, addresses, street names, etc.) is also included in
the database. Additional information layers, for example census or environmental data, can be added in the database and
can be queried together with the health data in order to map, analyse, interpret and model the incidence and spread of
diseases. Where one or more of the GIS components are lacking or inadequately resourced, however, the geodatabase loses
its analytical and predictive power. Challenges (graphically represented by the right-hand pentagon in the gure) ensue
when data are collected unevenly or unrepresentatively, when the layers of information are handled by an unskilled
workforce, in the absence of proper data handling and storage procedures, and if adequate hardware and software cannot be
obtained. In dealing with zoonotic diseases, aecting mostly developing countries, these challenges represent obstacles in
building ecient and eective GIS architectures.
2S. M. Fletcher-Lartey and G. Caprarelli
possible solutions that could alleviate the challenges.
Where no examples of solutions were found in
the literature, we proposed some recommended
actions, informed by personal experiences. Our
literature search repositories were PubMed and
Google Scholar. Based on the study aim, we
adopted a discursive writing approach and a narra-
tive literature review approach rather than present-
ing a systematic review of the literat ure.
Understanding the socio-cultural determinants of
Investments into disease prevention and control ac-
tivities should take into consideration the broad
socioeconomic, cultural, and educational determi-
nants, which are often modiable predictors of
health outcomes (Njau et al. 2014). Epidemiological
studies have generally described the association
between various health determinants and the risk
for transmission and spread of infectious diseases.
Whilst it is generally accepted that some people are
more at risk of infection than others, some of the
underlying determinants of disease spread are not
clearly understood, and even within the same popu-
lation group, heterogeneity in disease distribution
exists, and has been identied through spatial ana-
lysis (Clements et al. 2013; Kasasa et al. 2013).
The application of GIS in disease studies has furth-
ered the understanding of the intersection between
person, place and time in infectious disease out-
breaks and underlying social and cultural factors.
These factors are often unevenly distributed but
the extent and intensity of a particular disease may
be inuenced by their spatial distribution (Moore
and Carpenter, 1999). Epidemiological mapping
has helped to advance understanding of the social
and cultural perspectives of the spread of certain
Fig. 2. Draft map showing information layers in GIS. Example of draft of map prepared with information layers in GIS.
The location is the administrative province of Kasai Occidental, in the Democratic Republic of Congo. The map is
prepared by overlaying geo-referenced vector layers stacked on top of each other (as in the map legend) on a basemap
obtained from NASA satellite imagery through the free Bing Maps web mapping service (
The vector layers were digitized by editing GIS shapeles at a scale 1:3 322 505, using a WGS 84/Pseudo Mercator
projection, and taking the basemap as a reference map. Yellow circles (Cities): point shapele; shaded red area
(Administrative unit): polygon shapele; blue lines (Main rivers): polyline shapele. The shapeles and the map were
prepared using the open-source software QGIS v. 2·8·1 Wien. No topological rules, validation procedure or error
corrections were applied, so the shapes and geographic coordinates of all vector layers in this gure must be considered
only approximations and the resulting map in the gure should not be used as a detailed geographical reference.
3Application of GIS in public health
infectious diseases. Social and cultural variables (such
as access to water, sanitation, health care, population
density, over-crowding, farming and nutritional
practices, to name a few) can be mapped in a
similar way to relevant environmental covariates
such as temperature and rainfall. Predictive model-
ling utilizes current estimates of disease burden to
predict future burden based on expected changes
in population demographics and relevant social
determinants (Lau et al. 2014). By understanding
the distribution of social determinants of health,
hotspots can be identied and targeted i nterven-
tions developed to address them (Schneider et al.
Poverty remains a signicant social determinant in
the propagation of neg lected tropical diseases, and
forms part of a vicious cycle of reduced economic
productivity due to long-term disability and mor-
bidity, maternal and child health issues and other
health-related challenges. These limit productivity,
resulting in individuals and their communities
being caught in a health-related poverty trap
(Brooker et al. 2010; Conteh et al. 2010; Hotez and
Pecoul, 2010). The development of poverty maps
for many countries by the United Nations
Development Programme (UNDP), the World
Bank and similar agencies, has provided the means
by which health services can identify priority
Variability in human activities that may impact
inadvertently upon the life cycle of parasites and
their vectors and the degree to which humans are
exposed have improved understanding of emerging
and re-emerging diseases. This is possible when
local human activities (e.g., migration, outdoor
leisure activities and forest use) impact the nature
and level of contact between people, parasites
and/or their vectors (Semenza et al. 2010). The
value of geospatial databases has been demonstrated
through the incorporation of multiple sources of in-
formation on human health and demographics to de-
termine hotspots for disease transm ission, and the
use of predictive risk charts and maps to inform
public health interventions (Lau et al. 2014).
Mapping socio-economic and cultural deter-
minants has been successfully used to predict the
occurrence of parasite co-infections and multi-
parasitism (Raso et al. 2006). There is evidence
that the distribution of trachoma shows heterogen-
eity between districts and regions and while its oc-
currence has been linked to environmental
sanitation and behavioural factors, patterns at large
scales reect disparities in socioeconomic status
and indicators such as water, sanitation and
hygiene (WASH) (Clements et al. 2010; Smith
et al. 2013). The spatial variation in the incidence
of WASH is associated with the geographical vari-
ation in soil-transmitted helminths (Smith et al.
2013). By understanding the spatial aspects of
WASH indicators, Magalhães et al.(2011) were
able to determine the contribution of water and sani-
tation to the overall burden of helminthic infections
in school-aged children. Geo-referenced househ old-
level data for three WASH indicators obtained from
demographic health surveys (DHS) conducted in
participating countries (Burkina Faso, 2003;
Ghana, 2003; Mali, 2006) were used to generate pre-
dictive maps of areas without piped water, toilet fa-
cilities and improved household oor types. This
facilitated the identication of areas in West Africa
that were lagging behind the Millennium
Development Goals for water and sanitation
(Magalhães et al. 2011). The authors were then
able to quantify the role of WASH in the risk of
Schistosoma hematobium, Schistosoma mansoni and
hookworm infection in school-aged children. Lack
of access to clean water and sanitation is a possible
determinant of polyparasitism (Brooker and
Clements, 2009). The ability to identify this associ-
ation between WASH and the occurrence of parasit-
ic diseases facilitates identication of communities
in West Africa where interventions to prevent
disease spread and improvement of WASH can
produce greater health benets (Magalhães et al.
2011). Similarly for Western Côte dIvoire, demo-
graphic, environmental, and socioeconomic data
were incorporated into GIS in order to conduct
risk proling and spatial prediction of co-infection
with Schistosoma mansoni and hookworm. The evi-
dence suggests that the socioeconomic status was
useful in predicting co-infections between S.
mansoni and hookworm at small geographical scales
(Raso et al. 2006). Maternal education mapped at
small scale was found to be a signicant variable
associated with the availability of water supply and
sanitation facilities in households in West Africa.
Higher levels of maternal education were correlated
with childhood protection from helminth infection
(Magalhães et al. 2011).
Household and community practices have been
mapped to understand disease risk in the Pacic
Island Countries. In Papua New Guinea, spatial
stratication of district-specic risks associated with
high-risk areas of malnutrition was used to describe
the spatial features associated with the prevalence of
stunting and wasting outcomes at the province and
district-levels (Wand et al. 2012). By conducting a
spatial analysis study, high geographical variability
of stunting and wasting over the targeted region
was identied. This was useful to highlight dis-
trict-level dierences in health outcomes, which are
often masked because of data aggregation, resulting
in misleading conclusions (Wand et al. 2012). The
advancement in understanding of the distribution
of social determinants of health will continue to
inform ongoing targeted surveillance and the devel-
opment of interventions to prevent and control
infectious diseases (Schneider et al. 2011).
4S. M. Fletcher-Lartey and G. Caprarelli
Disease surveillance and early warning systems
Public health surveillance is dened as the continu-
ous, systematic collection, analysis and interpretation
of health-related data needed for the plann ing, imple-
mentation, and evaluation of public health practice
(World Health Organization, 2015). Eective sur-
veillance systems provide early warning systems for
public health emergencies, assess the impact of inter-
ventions or evaluate progress towards specied
goals, and monitor trends in the development and
proliferation of health threats, informing the priori-
tization of issues, allocation of resources, public
health policy and strategies. Mapping with GIS
tools is increasingly being used globally as part of
disease surveillance and monitoring programmes.
Maps provide a symbolic representation of under-
lying geographical distribution of disease incidence,
improving the understanding of disease rates over
time, and enabling the detection of outbreaks or pos-
sible epidemics (Bailey, 2001; Norstrom, 2001;
Boulos, 2004; Blanton et al. 2006; Duncombe et al.
2012; Kelly et al. 2013). Spatial observations of en-
vironmental factors such as rainfall, land use,
surface temperatures, oceans and land cover have a
direct epidemiological impact on the transmission
of diseases. Consequently, the ability to apply GIS
techniques to disease surveillance has opened up a
world of possibilities in creating early-warning
systems for emerging and re-emerging diseases
(Bergquist and Rinaldi, 2010).
Geospatial tools improve understanding of the
spatiotemporal distribution of parasitic diseases
and thus enhance our ability to design appropriate
cost-eective integrated disease control programmes
(Brooker and Utzinger, 2007; Fletcher et al. 2014).
For example, geospatial tools assisted Jamaica to
rapidly control and eliminate malaria after its re-
introduction to the country in 2006. Mapping
revealed the foci of infection and enabled targeted
intervention and rapid containment of the outbreak.
Public health ocials were able to divide the aected
area into 23 geographic grids, eight of which corre-
sponded to the aected communities. This enabled
surveillance teams to systematically examine com-
munities for anopheles breeding sites that were sub-
jected to larvicidal treatment or implementation of
environmental controls, and concentration of adulti-
cidal treatment in the aected grids (Webster-Kerr
et al. 2011).
The incorporation of GIS technology into routine
disease surveillance has been achieved in some re-
source limited settings based on increased recogni-
tion of the value of GIS technology in the
understanding and control of infectious diseases,
which has led to increased political, nancial and
technical support for such programmes (Malone
et al. 2001; Zhou et al. 2009; Brooker et al. 2009b).
The incorporation of a GIS-based spatial decision
support system (SDSS) into the surveillance-
response system in the South Pacic is a major
achievement for Vanuatu and Solomon Islands.
The SDSS is designed to automatically locate and
map conrmed malaria cases, to classify active foci
of infection, and to guide targeted interventions.
With technical assistance provided by the Pacic
Malaria Initiative Support Centre (PacMISC) and
WHO, local authori ties were able to build custom
applications into the existing provincial SDSS
used in previously identied elimination provinces,
to support general topographic mapping, geographic
reconnaissance and vector control intervention
management. This enabled teams to automatically
classify and map transmission foci based on the
spatiotemporal distribution of cases, and to identify
priority areas of interest for the implementation of
foci-specic targeted response (Kelly et al. 2013).
Several developing countries now have to access
GIS technology as a result of their participation in
the Global Fund for Tuberculosis, Malaria and
AIDS programmes (Chang et al. 2009). The
Global Fund for Tuberculosis, Malaria and AIDS
programmes is a partnership between governments,
civil society, the private sector and people aected by
these diseases to accelerate the end of AIDS, TB and
malaria as epidemics (http://www.theglobalfund.
Other examples demonstrate that the incorpor-
ation of GIS technology into disease surveillance
systems has facilitated the control of infectious
diseases such as: cutaneous leishmaniasis (Ali-
Akbarpour et al. 2012), human African trypano-
somiasis (Cecchi et al. 2009; Simarro et al. 2010),
schistosomiasis (Bergquist, 2002; Raso et al. 2005;
Clements et al. 2006a; Brooker, 2007; Ekpo et al.
2008), loiasis (Diggle et al. 2007), various animal dis-
eases (Norstrom, 2001; Clements et al. 2007), tick-
borne diseases (Randolph and Rogers, 2006;
Estrada-Peña, 2007), rabies (Blanton et al. 2006)
and malaria (Keating et al. 2003; Snow et al. 2005;
Gosoniu et al. 2006; Mabaso
et al. 2006;Hayet al.
2009; Grillet et al. 2010; Mboera et al. 2011; Noor
et al. 2012).
A vector-borne disease surveillance system was
established in American Samoa to monitor the elim-
ination progress of lymphatic lariasis after mass
drug administration (MDA) from 2000 to 2006.
Spatial epidemiology was incorporated into the
system and applied to geo-referenced serum bank
data to look for hot spots of transmission of lymph-
atic lariasis based on spatial dependence, and
household level clustering based on the assessment
of the seroprevalence of lymphatic lariasis antigens
and antibodies (2010) in American Samoan adults.
Geographic analysis identied the possible location
and estimated size of residual foci of potentially in-
fectious adults. The study demonstrated the value
of spatial analysis in post-MDA surveillance and
5Application of GIS in public health
conrmed the risk of re-introduction of the disease
by new migrants, while identifying strategies to de-
termine whether ongoing targeted surveillance of
high risk groups was warranted (Lau et al. 2014).
The rapid epidemiological mapping of onchocer-
ciasis (REMO) in over 20 African countries
(Brooker et al. 2010) led by the African
Programme for Onchocerciasis Control (APOC),
quickly and cheaply identied priority areas and
the number of individuals requiring treatment by
community-directed treatment with ivermectin
(CDTI) (Noma et al. 2002; Brooker et al. 2010).
This was achieved due to the ability to conduct
rapid assessments that enabled the stratication of
countries into areas that are suitable and unsuitable
for transmission (Brooker et al. 2010).
Increased availability and access to geospatial tools
facilitates the acquisition of advantageous geograph-
ical and environmental perspectives on the diseases
(Beale et al. 2010). Increased availability of free or
inexpensive tools (such as WHOs HealthMapper
or CDCs EpiMap) for mapping disease distribution
and community treatment information has enabled
public health workers to be more eective and
reach wider population. Recognizing the burden
from neglected parasitic diseases upon aected coun-
tries, the World Health Assembly resolved that the
elimination of lymphatic lariasis and onchocerciasis
was a public health priority for the WHO and its
member-states (World Health Assembly, 1997).
Remarkable progress has been made towards the
elimination of targets due to the ability to map the
distribution of disease, and conduct spatial analysis
to evaluate transmission levels in populations
under MDA (Molyneux, 2003). Geographical ana-
lysis was cond ucted to determine the level of risk
of infection amongst populations residing in
Implementation Units (or health districts) in pro-
gramme countries (Hooper et al. 2014). Mapping
of the geographical distribution of infected persons
and spatial modelling to determine the magnitude
of the population needing intervention were critical
to the progress of elimination eorts (Ottesen,
2000; Hooper et al. 2014).
Luan and Law (2014) provided an in-depth
review of web GIS-based Public Health
Surveillance Systems (WGPHSSs). One note-
worthy example of how GIS has been applied to
other infect ious diseases is the World Health
Organization (WHO)s DengueNet, a centralized
data management system that includes a database
and GIS for the global epidemiological and viro-
logical surveillance of dengue fever (DF) and
dengue haemorrhagic fever (DHF). This web-
based system makes available to users a standard
platform where current surveillance data on the inci-
dence and trends of dengue and DHF are shared.
Data are standardized and reported at the country
level resulting in greater comparability of the reported
cases of dengue fever across di
erent geographical
areas. This translates into useful early warning infor-
mation for public health professionals who can then
be better prepared for the management of individual
cases and epidemics, thus reducing fatality rates.
The data can also be used to relate health and eco-
nomic conditions to the cost eectiveness of preven-
tion and control interventions (World Health
Organization, 2014), thus building useful blueprints
for prediction and prevention of future outbreaks.
Growth in the user-base of GIS technology
applied to dengue fever has improved our under-
standing of the geographical prevalence of the
disease, of its distribution over time, hence its
spreading potential, and has enabled the evaluation
of the spatial relationships between incidence and
disease risk factors to inform eective control pro-
grammes (Duncombe et al. 2012;Hsuet al. 2012;
Luan and Law, 2014). There are several other exam-
ples where the successful application of inexpensive
geodatabase tools have resulted in long-term benets
for communities: the utilization of epidemiological
data, rapid assessment surveys and climate-based
risk prediction models to map the distribution of
urinary and intestinal schistosomiasis across Africa
(Brooker et al. 2009a); the development of empirical
databases and predictive maps which describe the
global distribution of helminths (Brooker et al.
2000; Brooker, 2010; Brooker et al. 2010) and
malaria (Snow et al. 2005; Hay and Snow, 2006);
the use and analysis of raster datasets obtained
from orbit using remote sensing techniques, in
order to map the distribution of sch istosomiasis
and a variety of other parasites, and to study the as-
sociation between infection and environmental vari-
ables (Cross and Bailey, 1984; Cross et al. 1984;
Malone et al. 2001; Brooker et al. 2002; Clements
et al. 2006a, b).
International collaboration on zoonotic parasite
There is growing political and nancial commitment
in both developed and developing countries to estab-
lish measures aimed at providing ecient and cost-
eective control of neglected tropical diseases.
These include infections mostly endemic to low-
income populations in Africa and the Middle East,
South America and Asia, (Zhou et al. 2009;
Simarro et al. 2010; Scholte
et al. 2012). In recogni-
tion of the need to improve understanding of the
social, economic and environmental burden caused
by these diseases, global experts have come together
to support the establishment of spatial databases
aimed at proling multiple species of parasitic dis-
eases (Malone et al. 2001; Zhou et al. 2009 ). One
example of a spatial database of parasitic diseases is
the Global Network for Geospatial Health (GNGH),
established in 2000, initially set up to develop
6S. M. Fletcher-Lartey and G. Caprarelli
computer-based models to improve control pro-
grammes for schistosomiasis and other snail-borne
diseases of medical and veterinary importance
(Malone et al. 2001; Zhou et al. 2009). The scope
of the GNGH has since expanded to include other
widespread infectious diseases, such as soil-trans-
mitted and waterborne helminth infections, as well
as arthropod-borne diseases such as leishmaniasis,
malaria and lymphatic lariasis (Zhou et al. 2009).
In the Latin American and Caribbean Region,
The Pan American Health Organization developed
a Regional Strategic Framework to address
neglected diseases (NDs) in neglected populations.
The aim of the plan is to strengthen surveillance,
prevention, and control system s for neglected dis-
eases, and by extension strengthen other disease sur-
veillance and control programmes. The plan outlines
that epidemiological surveillance and mapping are
integrated into the achievement of three strategic
priorities: (1) diseases that can be eliminated by
mass preventive or targeted chemotherapy alone;
(2) diseases that can be controlled by mass prevent-
ive or targeted chemotherapy coupled with inten-
sied, improved, early case detection and
management; and (3) diseases which require
improved transmission control through better
health promotion, behaviour change, emergency
preparedness, and environmental sanitation and
management strategies (Ault, 2007). The expected
outcome of the strategic framework is to improve
public health by developing multi-disease based sur-
veillance systems and incorporating GIS into the
planning, monitoring, risk and impact assessment
processes to inform decision-making for NDs in
the participating countries and communities (Ault,
WHO and the Partners for Parasite Control are
coordinating a global programme to control hel-
minths and schistosomiasis. The partnership,
formed in 2001, includes governments of WHO
Member States where helminthic infections are
endemic, governments of Member States committed
to reduce poverty in low-income countries, various
United Nations (UN) agencies, universities, philan-
thropic foundations and pharmaceutical companies
(Ault, 2007). The aim of the partnership is to
deliver permanent relief from helminthic diseases
for millions of aected people by utilizing risk
mapping, regular chemotherapy, and education in
the control of at least 75% of all school-age children
at risk of morbidity from schistosomiasis and soil-
transmitted helminthiasis (World Health
Organization, 2005; Ault, 2007).
The First International Symposium on Geospatial
Health was organized by the GNGH in Lijiang,
Yunnan province, Peoples Republic of China in
September 2007. The aim of the symposium was
to review advances made in the control of zoonotic
parasitic diseases through the use of geospatial tools.
The symposium brought together local and inter-
national scientists to encourage sharing of data and
geospatial health applications in formats that can
be used across health disciplines in dierent contexts
(Zhou et al. 2009 ).
Since then, other collaborative approaches have
emerged targeting parasitic disease control. The
Roll Back Malaria (RBM) Partnership has developed
the Global Malaria Action Plan (GMAP) (http://
html). The GMAP is based on input from experts
from 30 malaria endemic countries and regions, 65
international institutions and 250 experts globally,
consolidated into a vision for a substantial and sus-
tained reduction in the burden of malaria and the
eventual global eradication of malaria. The GMAP
provides a global framework for action to assist part-
ners to coordinate their eorts through an evidence-
based approach for the delivery of e
ective preven-
tion and treatment to all people at risk, and estimates
the annual funding needed to achieve its goals (Roll
Back Malaria Partnership, 2008).
Several other international projects involve the
use of datasets on a global scale. The Malaria
Atlas Project (MAP;
managed by the University of Oxford, in the
United Kingdom (UK), brings together researchers
interested in developing techniques to map and
understand the distribution and spread of malaria.
The project seeks to support eective planning of
malaria control (Hay and Snow, 2006). The online
portal provides access to maps and data processing
tools that are updated regularly to ensure the infor-
mation provided stays current. Users with advanced
mathematical and geospatial skills may also down-
load programs and instructions for data modelling
and apply the spatial analysis concepts to new
datasets. Publications by scientists contributing to
the project are also accessible from the website.
The London School of Hygiene and Tropical
Medicine in the UK manages the Glob al Atlas of
Helminth Infections (GAHI; http://www.this The GAHI uses data from thou-
sands of eld surveys to provide reliable and updated
maps of helminth infection distribution to facilitate
and prioritize targeted treatment. A variety of
maps including survey data maps, predictive risk
maps and control and planning maps can be accessed
through the GAHI and new datasets can be for-
warded to the project team members directly by
email. The project team provides capacity building
in mapping and the use of epidemiological tools.
GAHI also provides access to updated publications
(Brooker et al. 2010).
An example of how regional organizations have
attempted to build local mapping and analytic
capacity through technical cooperation is with
SIGEpi: Application and development of GIS in
Epidemiology and Public Health. The purpose of
7Application of GIS in public health
this project is to strengthen the analytical capacities
of the Ministries of Heal th and other institutions
of the Pan American Health Organization (PAHO)
WHO member countries in the Region of the
Americas and other regions. The SIGEpis license
is available to local ministries and institutions upon
request through the PAHO/WHO Representative
Oces in the respective countries, and to other pro-
fessionals, academics, researchers and the private
sector directly from the Management of the Area
of Analysis of Health and Information Systems
(AIS) of PAHO (Martínez Piedra et al. 2001).
There are opportunities to learn from the many
examples of successful studies combining GIS, sat-
ellite data and spatial epidemiology concepts, to
enable application to other infectious vector-borne
diseases (Yang et al. 2005; Brooker, 2007; Ekpo
et al. 2008; Simoonga et al. 2009; Bergquist and
Rinaldi, 2010; Brooker et al. 2010; Zeng et al.
2011). The query and analysis tools developed in a
GIS framework would assist with decisions regard-
ing the most eective deployment of defence mea-
sures against all vector-bo rne diseases. There is
much scope for wider application of GIS in Latin
America, the Caribbean and the Asia Pacic
region, where internet access is constantly improv-
ing. These regions share similarities in geographical
and ecological risk factors for infectious diseases and
as such there is scope to translate some of the experi-
ence acquired in Africa to these regions.
The scale at which mapping and geostatistical ana-
lyses are carried out is extremely important if GIS
is to be adopted as an eective tool in the hand of
communities and public health ocials to control
the spread of parasitic diseases. Data collected from
the Global Infectious Diseases and Epidemiology
Network (GIDEON), complemented by those
mined from indexed PubMed publications, were
analysed by Hay et al.(2013) to obtain a global per-
spective regarding the extent by which infectious
diseases are mapped. These authors found that
only 7, out of 174 clinically signicant mappable in-
fectious diseases, had actually been documented for
their spatial distribution. Their list however
missed some of the most diused, chronic and de-
bilitating tropical parasitic diseases, such as trach-
oma and soil-transmitted helminths, because
distribution of these parasitic diseases and of the
relevant agents and vectors of infection did not
meet the rst inclusion criterion of being spatially
variable at the global scale at which the statistical
analysis was conducted, and was thus considered a
low priority for mapping (Hay et al. 2013). Some
important infectious diseases show no spatial vari-
ability at global planetary scale, but prove to be
space dependent when their prevalence is analysed
at ner statistical scale and interpreted against envir-
onmental and ecological data.
In commending the massive statistical work
undertaken by these authors, Smith et al.(2013)
pointed out however that, while Hay et al. s (2013)
analysis provided a valuable framework for global-
scale interpretations, mining data only from the
GIDEON database and from topical publications
indexed in PubMed, did not capture important
local data collection and open-source mapping
initiatives feeding into the regional scale modelling
on which surveillance, prevention and eective
intervention initiatives must ultimately be based
(Smith et al. 2013). Additionally, local and regional
mapping eorts (where available), supported by
open-access projects (such as those listed in the pre-
vious sections of this review) demonstrate granular-
ity at the local and regional scale (Clements et al.
2010; Magalhães et al. 2011). Furthermore, local en-
vironmental conditions, and the ecological dimen-
sion of parasitic spread, must be considered an
integral par t of the spatial analysis of infectious
disease transmission, requiring complex high-
resolution modelling of several types of data layers
(e.g., Caprarelli and Fletcher, 2014) over a range of
scales. Reliable spatial information gathered locally
by public health ocers, health carers, environmen-
tal assessors and the general community must there-
fore be included in all spatial analyses and models of
infectious diseases. However, this information is
often lacking.
Some deadly diseases, such as dengue fever, to
date have received very little attention (Eisen and
Lozano-Fuentes, 2009). This may be in part
because of the uneven distribution of resources in
aected countries and the lack of uniformity in
data collection processes (Brooker et al. 2009a;
et al. 2010). For example, while popula-
tion-level datasets on the incidence of human infec-
tion are generally available for Burundi, Rwanda and
Uganda, data from Kenya and Tanzania are sparse
and statistically non-representative (Brooker et al.
2009b; Brooker et al. 2010). This has limited the ap-
plication and impact of geospatial mapping eorts.
There is consistent evidence that the application of
GIS technology to public health and parasitology
has far reaching benets, particularly to study the
distribution of parasites and their vectors. Most of
the focus has been on the African continent, which
suers signicant burden from infectious and
neglected parasitic diseases. The limited application
of GIS in other regions suggests there may be some
challenges to its widespread uptake and application.
In the following sections we list and examine some
of these challenges and suggest cost-eective solu-
tions. Content is based on the available literature,
complemented and supplemented by the personal
experiences of one of the authors (SF-L) gained
over many years working in various capacities in
8S. M. Fletcher-Lartey and G. Caprarelli
Public Health in dierent geographical settings.
Table 1 summarizes some of the major challenges
and proposed cost-eective solutions, particularly
geared at low- and middle-income settings.
Limited access to GIS infrastructure
Lack of infrastructure has historically been a barrier
to the utilization of GIS technology. This is partly
related to the need for sophisticated (and usually ex-
pensive) licensed GIS software, which may be a
signicant hurdle for resource limited settings
(Bergquist and Rinaldi, 2010). Signicant costs are
associated with the development of SDSSs, which
often require specialized equipment. One study
found that geographical reconnaissance accounted
for the majority of the costs and, had household
geo-reference data been previously collected, the
costs would have been signicantly reduced
(Marston et al. 2014).
There is increasing use of GIS in the mapping of
households in countries where the technology is
readily available (Clements et al. 2013;Kellyet al.
2013). Open source GIS software is becoming in-
creasingly user friendly, by incorporating graphic
user interfaces (GUI) in addition to traditional
command line operations, and a variety of algorithms
and structured query language (SQL) packages analo-
gous to those of the commercial options (Table 1 in
Caprarelli and Fletcher, 2014). The use of low-cost
internet and free GIS infrastructure is documented
by Fisher and Myers (2011). Their experience
demonstrates how free software can be eectively
applied to mapping and preliminary geospatial ana-
lysis, without the need for any centralized database
or internet access (Fisher and Myers, 2011).
Chang et al. (2009) have successfully developed a
low-cost mapping and geo-referencing system
which does not rely on continuous access to
Internet, and is particularly useful for vector-borne
disease surveillance and control. The system,
created in Nicaragua as part of a nation-wide initia-
tive, was successfully built around satellite images
from Google Earth 4·3 (Google Inc. Mountain
View, CA, USA) and constructed with ArcGIS 9
ArcMap software (ESRI, Redlands, CA, USA)
made available through the Global Fund Program.
The authors were able to easily manipulate base
maps using ArcGIS and Erdas Imagine software,
enabling future users to work with the complete sat-
ellite map without need of an Internet connection.
The system is exible and scalable, and could
easily be replicated in other developing contexts
with limited internet access (Chang et al. 2009),
using open source GIS software.
Limited technical capacity and experience
There are several analytical techniques employed in
the application of GIS technology which require
from basic to more advanced skills (see Caprarelli
and Fletcher, 2014 ). However, many organizations
still do not have access to even the basic technical ex-
pertise, properly trained or devoted sta, to focus on
GIS-related activities and to follow standardized
procedures (Boulos, 2004). Many humanitarian
and development focused agencies are increasingly
utilizing GIS as par t of their work in developing
countries but lack of local technical capacity has
resulted in external technical experts having to be
brought in to build capacity for GIS-related
activities (Kaiser
et al. 2003 ; Eisen and Lozano-
Fuentes, 2009). This increases the cost of the tech-
nology to the local organizations. Building local
capacity is necessary for sustained use and mainten-
ance of the resources, and requires a concerted eort
to empower individuals and group s, sucient time
for training, and motivation and strategic planning.
All these factors must exist to ensure that knowledge
transfer, up-skilling and building of local technical
capacity actually occurs (Ramasubramanian, 1999).
International aid or donor-driven programmes in
aid-dependent economies often nd limited local
capacity on which to build, due to limited or
already stretched human resources, lack of institu-
tional will and numerous competing priorities, un-
sustainable practices, heavy reliance upo n technical
assistance, with little or no transfer of technical
skills, thus undermining post-project sustainability
(Kimaro and Nhampossa, 2007; Chapman, 2010).
Hence, the vicious cycle of dependence on external
technical assistance in developing capacity continues
(Godfrey et al. 2002; Eade, 2007).
One solution to this problem could be for local au-
thorities to ensure that a capacity-building compo-
nent that facilitates technical up-skilling of local
personnel is included in all technical agreements.
Strategic planning for workforce needs should also
include identication of training capacity, both in
terms of those to be trained and the source of train-
ing, and where this is not available locally, a suitable
sustainable alternative ought to be identied. This
may require strong links and collaboration with aca-
demic institutions and industry partners. Many
high-income countries now oer scholarships/fel-
lowships to developing counterparts for technical
up-skilling, and GIS should be an area included in
this development agenda. Local scientists could be
regarded as assets in this area, by being involved in
developing local GIS capability using their under-
standing of the local context, politics and needs, to
ensure sustainability through continued knowledge
transfer and skill development of local public
health ocers (Dunn et al. 1997; Sieber, 2000;
Saikia, 2010), perhaps in the form of targeted high-
intensity short training courses.
The experience with SIGEpi demonstrates how
development partners have collaborated to build
local capacity through technical cooperation.
9Application of GIS in public health
Table 1: Summary of challenges and possible solutions to the application of GIS in public health settings.
Themes Challenges and solutions
1. Access to GIS infrastructure: 1.1. Lack of infrastructure and of sophisticated costly GIS software (Bergquist and
Rinaldi, 2010)
Solutions: Open source GIS software with user-friendly GUI, algorithms, and structured query
language (SQL) packages analogous to those of the commercial options (Table 1,
Caprarelli and Fletcher, 2014)
1.2. Costs associated with the development of spatial decision support systems re-
quiring specialized equipment, and cost of geographical reconnaissance
(Marston et al. 2014)
Solutions: Free software including functionality not requiring centralised databases or internet
access (Chang et al. 2009). Examples include: Cybertracker for eld data collection
on GPS-enabled PDAs (personal digital assistant); Open Jump , a Java-based, open source GIS for data visualisation and simple ana-
lysis; and AccessMod
©, a free
extension from the World Health Organisation (WHO), used for service availability
mapping (Fisher and Myers, 2011)
1.3. Convoluted structured procedures and hidden costs associated with dierent
levels of licensing and usage access of free software and data resources from
mapping system providers (for e.g. SIGEpi)
Establishment of scaled down process for emergency situations to enable mapping
resources to reach a broader pool of lower level users, thus facilitating fast and
topical analyses and response strategies
2. Technical capacity and
2.1. Limited or no access to properly trained sta capable of focusing on GIS related
activities and to follow standardised procedures (Boulos, 2004)
Solutions: Building local capacity aimed at sustained use and maintenance of GIS resources,
including sucient time for training, and motivation and strategic planning
(Ramasubramanian, 1999)
2.2. Limited local capacity due to limited or already stretched human resources, lack of
institutional will and numerous competing priorities, unsustainable mapping
practices (Clarke et al. 1996;Kaiseret al. 2003;McLaerty, 2003;Kimaroand
Nhampossa, 2007; Eisen and Lozano-Fuentes, 2009; Chapman, 2010)
Solutions: (a) Strategic planning for workforce to include identication of training capacity
(personnel to be trained and the source of training) and, where this is not locally
available, identication of a suitable sustainable alternative
(b) Establishment of long term links and collaboration with academic institutions
and industry partners
2.3. Heavy reliance on technical assistance, with little or no transfer of technical skills,
undermining post-project sustainability (Godfrey et al. 2002; Eade, 2007)
Solutions: (a) Capacity building component aimed at technical up-skilling of local personnel
to be included in donor funded technical agreements
(b) Local experts (scientists, engineers, academics) to be engaged in framing long
term sustainable solutions for development and scalability of local GIS cap-
ability by knowledge transfer and up-skilling of local sta (Dunn et al. 1997;
Sieber, 2000; Saikia, 2010)
3. Data availability and
analysis capacity
3.1. Limited availability of good quality spatial data; privacy and condentiality
issues; restrictions to access and use of individual health incidence and outcomes
data; data ownership; ability to link or cross-reference publicly available data
due to inconsistencies in data collection parameters and systems (McLaerty,
2003; McGeehin et al. 2004; Beale et al. 2010)
Solutions: (a) Regular updating of data, allowing the addition of environmental and geographical
variables to historical datasets that previously lacked them (Brooker et al. 2009b;
Brooker et al. 2010)
(b) Inclusion of data sharing protocols to existing or new international collaborative
3.2. Lack of uniformity in the way disease-related metrics (rates, incidence, preva-
lence) are recorded and reported within and between countries, and inconsist-
encies in the use of a wide array of covariates, complicating the development of
national, regional and globally comparative maps of the same diseases (Hay
et al. 2013). Imprecise exposure measurements based on proxy variables which
can result in underestimating true eects, or lead to regression dilution bias
(Frost and Thompson, 2000; Magalhães et al. 2011)
(a) Encourage sharing of data collection tools and establish standardised format for
data collection and storage in global repositories
(b) Facilitate sharing of data through existing international collaborative approaches
to make data available and accessible ensuring global public health is protected.
For example, sharing disease surveillance data for The Outbreaks Global Incident
Maps, that display outbreaks, cases and deaths globally, caused by viral and
bacterial diseases, has potential to indicate biological terrorism threats (Global
Incident Map, 2012)
10S. M. Fletcher-Lartey and G. Caprarelli
However, the process of requesting resources,
support and engagement from the consortium
members i s highly structured, requiring a detailed
proposal and high level institutional i nvolvement.
This may limit the eectiveness of this system to
completely full its stated objective to be a GIS
tool for dierent analytical procedures and pro-
cesses related to monitoring of health events,
health situation analysis, and support for the deci-
sion-making in health (Pan American Health
Organization, 2008) in the broader Central and
South American region. This is ultimately a
problem, considering that the spread of infectious
diseases does not recognize human-made political
barriers between countries. Hence, aordability
by the largest possible number of local and regional
institutions should be one of the priorities to imple-
ment, and economic studies should provide ancil-
lary data to envisage sustainable strategies to make
this possible.
Limited data availability and analysis capacity
While the use and recognition of geographical infor-
mation systems in health care and research institu-
tions is increasing, some authors have lamented the
fact that health and population datasets are imported
on an ad-hoc basis and as such are not routinely
stored or available for analysis (McGeehin et al.
2004; Beale et al. 2010). This generates problems,
both in relation to the statistical uncertainties that
are introduced as a consequence of uneven distribu-
tion of data in the spatial analysis, and in relation to
the eectiveness of intervention, considering that the
most data-poor areas are generally those that would
require the most intensive monitoring (e.g., low-
and middle-income countries, or less wealthy area
codes in developed countries). Thus, in the public
health context, an essential consideration for the
use of GIS applications is the availability of good
quality data, with access and utilization guided by
appropriate polic ies and standard operating proce-
dures, to ensure that public health policy and prac-
tice are informed by the best available evidence
(Boulos, 2004).
Problems often arise with the use of population-
based surveys that were not collected for mapping.
This can lead to the use of clustering of data
resulting in uneven geographical coverage (Clements
et al. 2010), and the use of proxy variables which are
imprecise exposure measurements, resulting in
underestimation of the true eects or in a regression di-
lution bias (Frost and Thompson, 2000;Magalhães
et al. 2011). Lack of uniformity in the way disease-
related metrics (rates, incidence and prevalence) are
recorded and reported within and between countries,
and an inconsistency in the use of a wide array of
covariates, complicates the development of national,
regional and globally comparative maps of the same
diseases (Hay et al. 2013).
Good quality data are needed to determine the
eectiveness of dierent spatial models such as
Table 1: (Cont.)
Themes Challenges and solutions
3.3. Lack of appropriate policies informed by the best available evidence and
standard operating procedures to guide access and utilisation of public health
Solutions: (a) Development of data governance procedures and ethical processes ensuring
streamlined de-identication, storage and access to data
(b) Development and establishment of policies and standard operating procedures
to guide data access and utilisation based on the best available evidence (Boulos,
3.4. Restricted access to data obtained via sponsors, donors or grants
Solutions: (a) Agreements between granting donors, sponsors and users must be set in place to
govern future ownership of the data collected. Such agreements must also
include instructions for managing the infrastructure, and provisions for post-
grant integration and management of infrastructure into local systems
(b) Donors and local partners need to establish clear standard operating procedures
about the data entry (who, what, and when) and the sharing of information
between stakeholders at the local level (Dunn et al. 1997; Sieber, 2000; Saikia,
2010). Some international organisations have already produced open access
declarations in support of publicly funded research been made publicly avail-
able as a global public good (Chan et al. 2005)
3.5. Lack of uniform approach in quantifying the level of heterogeneity required for
intervention eectiveness (Clements et al. 2013; Kasasa et al. 2013)
Solutions: (a) Setting-up a formal framework to assess the eect of spatial decision support
systems on disease elimination, and support of research aimed to identify
measureable indicators for assessing appropriateness and eectiveness of geo-
spatial methods (Clements et al. 2013)
(b) Operational research and randomised controlled trials to be carried out in order
to determine the eectiveness of geospatial methods in real world settings
11Application of GIS in public health
spatially targeted vs. ad hoc or spatially uniform re-
source allocation strategies for disease elimination
(Clements et al. 2013). Geospatial methods can be
applied to the identication of malaria hotspots by
investigation of spatial heterogeneity at dierent
scales (Clements et al. 2013; Kasasa et al. 2013).
Limited emphasis has been placed on the conduct
of operational research and randomized controlled
trials that can determine the eectiv eness of geospa-
tial methods in real-world settings. Clements et al.
(2013) suggested that these types of studies are
needed to demonstrate the eectiveness of geospatial
science on improving decision-making and resource
allocation in real-world elimination programmes.
They postulated that a formal framework is needed
to assess the eect of SDSSs on malaria elimination
and that research is needed to identify measureable
indicators to assess geospatial methods (Clements
et al. 2013).
With the availability of cheaper and more user-
friendly GIS technology, some of the problems of
uneven data capture are being resolved: regular up-
dating of data, allowing the addition of environmen-
tal and geographical variables to historical datasets
that previously lacked them, has now become
broad practice (Brooker et al. 2009b; Brooker et al.
2010). Limited availability of spatial data, privacy
and condentiality issues, restrictions to the access
and use of individual health incident and outcomes
data are some of the challenges that can be encoun-
tered particularly in working with human diseases.
Challenges with data ownership, the ability to link
publicly available data due to inconsi stencies in
data collection parameters and systems and limited
knowledge of the application and interpretation of
GIS in decision-making processes have also been
reported (McLaerty, 2003). Data ownership is
particularly problematic when it comes to access,
and laws vary widely in dierent countries.
Accessibility to data obtained via sponsors, donors
or grants may be restricted.
Donors should ensure that clear agreements are in
place to govern future ownership of the data col-
lected in their sponsored projects, and how the infra-
structure will be managed or integrated into local
systems once donor funding ceases. Donors and
local partners should ensure that clear guidelines
and standard operating procedures are established
around data entry (who, what, when and where)
and for the sharing of information between stake-
holders at the local level (Dunn et al. 1997; Sieber,
2000; Saikia, 2010). Some international organiza-
tions have already produced open access declarations
in support of publicly funded research been made
publicly available as a global public good (Chan
et al. 2005). This approach could be adopted by
other countries with the use of publicly funded
data. In the public health context, ethical issues
associated with rare conditions, condentiality and
de-identication of data woul d need to be considered
and governed. In those cases, an ethics review
process would need to be developed to streamline
data access and use, and ensure that data are properly
The overarching rationale to make data available
and accessible is to ensure global public health is
protected. Geospatial tools are paramount to preven-
tion and containment of global threats. The inter-
national public health community therefore has
interest in ensuring that adequate regulations are in
place to govern the sharing of geospatial data for
public health purposes. This could be achieved
through existing international collaborative
approaches such as those discussed in the previous
The application of GIS technology in public
health and epidemiology is expanding, thanks to in-
creasing availability of the technology. The incorp-
oration of GIS technology into disease surveillance
systems and for the study of the distribution of
parasites and of their vectors has furthered our
understanding of the spatial components of disease
risk and distribution patterns. The application of
GIS technology to the study of parasitic diseases
has contributed signicantly to the understanding
of parasite ecology and their associations with
disease distribut ion, enabling the development of
eective control and prevention interventions,
mainly in developing regions. However, it is
evident that GIS has been underutilized in some
areas of public health and in some regions. While
systemic limitations (lack of infrastructure, training,
long-term maintenance of database, uniform and
complete data collection, sharing of databases) may
have contributed to its underutilization, there are
several opportunities to improve free or low-cost
access to GIS infrastructure, develop local technical
capacity, and improve data availability and analysis
capacity. This can be achieved through well-
designed operational research and randomized
control trials that can provide adequate evidence
on the eectiveness of the GIS technology and
SDSSs particularly in areas where implementation
has so far been limited. Numerous lessons have
been learned from the application of GIS technology
in the developing world that can be translated to
other regions sharing similar public health chal-
lenges and risks, as well as for the understanding of
exotic diseases and risk factors among remote popu-
lations in industrialized regions. A good starting
point is to build local technical capacity in under-
resourced areas and to ensure that clear guidelines
are in place to facilitate the use of GIS infrastruc-
ture, and sharing and application of data to manage
public health problems. International collaborations
12S. M. Fletcher-Lartey and G. Caprarelli
that facilitate the sharing of knowledge and best
practice should be encouraged.
Two anonymous reviewers provided valuable comments
that led to an improved version of the manuscript.
This research received no specic grant from any funding
agency, commercial or not-for-prot sectors.
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15Application of GIS in public health
... GIS has many successes as well as challenges ( Figure 3). [24] GIS can be successfully applied to monitor and predict many diseases mainly from developing countries. Some of the advantages and successes of using GISs are: Understanding the socio-cultural determinants of health: Modifiable predictors of health like socioeconomic, cultural, and educational determinants outcomes can be investigated using GIS. ...
... ▪ Engaging local experts (scientists, engineers, academics) in framing long term sustainable solutions for development and knowledge transfer and up-skilling of local staff. [24] ▪ Effectiveness and appropriateness of geospatial methods should be identified with the help of rigorous research. In addition, the effect of spatial decision support systems on disease control and disease elimination should be analysed and assessed by setting-up a formal framework . ...
GIS (Geographic Information System) are computer-based tools used to visualize, analyze, accumulate and explicate geographic data. The determinants of health status are often correlated and analogous. Establishing GIS-based approaches and programmes can predict and analyze the complexity of web of causation of many health issues. GIS can be used to efficaciously investigate health along with its physical, social and cultural environments. Mapping functions of GIS can be used to plot health attributes for better visualization, exploration, and modeling of health patterns. GIS based healthcare helps in explaining and describing health outcomes, health disparities, healthcare access and how health care delivery can be improved. GIS can also be used to bring all spatial data under one umbrella of “Geo Data Bank” that could provide easy accessibility and help in better utility of healthcare services. In India, the adoption and use of digital spatial methods like GIS in the field of healthcare has lagged. However, the “Computer Aided Utility Mapping Project for six cities” in India is a significant benefit for the GIS users in the country which can be used by healthcare sector in the near future for the upliftment of healthcare facility. The primary focus of the paper is to provide details about benefits of using GIS-based analytical approaches in healthcare planning, the successes, challenges, remedies and future perspective of GIS in healthcare delivery. Keywords: GIS, healthcare planning, location allocation modeling, public health, spatial analysis, spatial epidemiology.
... However, it is often the case that expert knowledge and spatial analysis expertise is required to work with and manipulate GIS datasets. This can severely limit the accessibility and use of available data to those with the GIS skills to undertake such analyses, creating a significant barrier to information and use of best-available science in practice [5][6][7][8]. Similarly, the increasing complexity of GIS environments and tools, and the speed at which they evolve, can hinder the usability of spatial analysis if the tools and processes are not easily understood by the end-user [9, 10]. ...
... The industry needs to make much better use of such resources, but in an efficient and user-friendly way [10]. Here we provide a methodology to enable non-technical GIS users directly involved in river management, to interrogate datasets such as the NSW River Styles database (and others like it in various parts of the world) to produce outputs and results that can inform consistent and transparent decision making and prioritisation for resource allocation [5,31,32]. ...
Full-text available
The provision of a simplified GIS workflow to analyse the Open Access NSW River Styles database provides non-technical GIS users in river management with the ability to quickly and efficiently obtain information to assist them in catchment-scale rehabilitation prioritisation. Publicly available proprietary GIS software, standard GIS tools, and a packaged digital elevation model are used to demonstrate the ease of analysis for those with some GIS skills, to establish where corridors of geomorphic river recovery occur or could be built at-scale. Rather than a ‘single use’ report, this novel application of GIS methods is designed to be used by those responsible for river management, replicated across landscapes and adjusted according to preferences. Decision making becomes more cost effective, and adaptive to local circumstances and changing river management priorities. The method could also be adjusted and applied to other river monitoring and condition datasets where polyline data layers are available.
... In public health research, GIS are used for disease surveillance, mapping, and modeling (Fletcher-Lartey & Caprarelli, 2016;Parrott et al., 2010;Swienton et al., 2021); recognizing healthcare access and disparities within communities and larger scale regions (Hawthorne & Kwan, 2012) and public participatory, collaborative efforts that facilitate community understandings of health (Cromley & McLafferty, 2011;Keddem et al., 2015). Many other disciplines, including anthropology (Padilla, 2013), policy planning (Greene, 2000), engineering (Haklay & Zafiri, 2008), sociology (Downey, 2006), and the digital humanities (Bodenhamer, 2008), have also used GIS in research. ...
Full-text available
We propose geographic information systems (GIS) as a framework in organization studies, particularly for scholars who consider the nuances of space and geography in various organizational contexts. GIS are computer-based systems that manage, store, analyze, and distribute spatial data. While more and more scholars recognize the theoretical significance of organizational space, suggestions for conducting empirical research around organizational space using alternative frameworks-such as GIS-are seldom made. We present an introduction to GIS and various spatial analyses through a case study of organizations in the reproductive healthcare field and offer future directions related to the geographic implications of understanding organizations and organizing through GIS.
... Leveraging this capability, we used 11 criteria in three major groups to analyze and develop human vulnerability and health risk maps. The selection of the relevant criteria was based on the data availability and research literature 23,[58][59][60][61][62] . Table 3 shows the list of selected criteria for vulnerability and health risk mapping. ...
Full-text available
Climate change and its respective environmental impacts, such as dying lakes, is widely acknowledged. Studies on the impact of shrinking hyper-saline lakes suggest severe negative consequences for the health of the affected population. The primary aim was to investigate the relationship between changes in the water level of the hyper-saline Lake Urmia, along with the associated salt release, and the prevalence of hypertension and the general state of health of the local population in Shabestar County north of the lake. Moreover, we sought to map the vulnerability of the local population to the health risks associated with salt-dust scatter using multiple environmental and demographic characteristics. We applied a spatiotemporal analysis of the environmental parameters of Lake Urmia and the health of the local population. We analyzed health survey data from local health care centers and a national STEPS study in Shabestar County, Iran. We used a time-series of remote sensing images to monitor the trend of occurrence and extent of salt-dust storms between 2012 and 2020. To evaluate the impacts of lake drought on the health of the residences, we investigated the spatiotemporal correlation of the lake drought and the state of health of local residents. We applied a GIScience multiple decision analysis to identify areas affected by salt-dust particles and related these to the health status of the residents. According to our results, the lake drought has significantly contributed to the increasing cases of hypertension in local patients. The number of hypertensive patients has increased from 2.09% in 2012 to 19.5% in 2019 before decreasing slightly to 16.05% in 2020. Detailed results showed that adults, and particularly females, were affected most by the effects of the salt-dust scatter in the residential areas close to the lake. The results of this study provide critical insights into the environmental impacts of the Lake Urmia drought on the human health of the residents. Based on the results we suggest that detailed socioeconomic studies might be required for a comprehensive analysis of the human health issues in this area. Nonetheless, the proposed methods can be applied to monitor the environmental impacts of climate change on human health.
... Today, geospatial information plays a wide ranging and crucial role in society across many sectors, including government, research and development, the military, and civilian companies (Avand & Moradi, 2021;Fletcher-Lartey & Caprarelli, 2016;Landres, 2001). In the distant past, a small number of geographic information system (GIS) products was accessible to selected expert users. ...
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We conducted a study to find out whether and why South African users accepted QGIS. In the quantitative part of the study, we found that QGIS acceptance is primarily influenced by habit, followed by facilitating conditions, price value, and social influence. To better understand and explain these results, we conducted a qualitative study in which semi‐structured interviews were conducted with 12 geospatial practitioners. While a geographic information system (GIS) product was often prescribed by their workplace, interviewees had clear preferences for a specific GIS product for certain kinds of tasks, supporting the finding that habit is the main reason for using a GIS product. Interviewees used QGIS because it opens most data formats and there is one license for all functionality (facilitating conditions), is free (price value), and/or had been advised by someone important (social influence). The interviews revealed why software support (commercial or free) was not significant in the quantitative results: users think GIS support is not necessary or else available online. Identical to the quantitative study, interviews confirmed that customizability, no vendor lock‐in, improved reliability, quality, and security do not play a role when deciding to use QGIS. These qualitative results provide a deeper understanding of the quantitative results and can be used by promotors of open‐source geospatial software to increase uptake. In general, they can also help managers embed new products into any organization's workflows. In our study, interviewees and questionnaire respondents were selected to be users. Repeating the study for GIS developers and/or managers will provide further insight into QGIS acceptance.
... Geographic information systems (GISs) are identified as a powerful tool to visualise data by spatial referencing, visually disseminate information, as a training tool, and link the activities with measurable public health benefits in communities and districts. 25 In addition, GIS can be considered an 'enabling technology' that can answer pertinent questions related to evaluating community-based health promotion interventions (such as healthy settings) conducted at the field level. For example, a visual map can be produced using GIS with community profiling (with identified health issues) in the districts, which helps plan and monitor interventions more efficiently. ...
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The health promotion settings approach has been recognised as an effective method of health promotion in the recent era, and mobile health (mHealth) is a highly evolving field in the health sector. The health promotion settings are shifting the focus away from the individuals and moving towards a more holistic model of health promotion. We identified five settings in Sri Lanka to promote a mHealth model, including villages, schools, preschools, workplaces, and hospitals. The specified model using mHealth helps monitor the activities at various levels of healthcare, including regional, district and national levels. The model also maps the location of the healthy settings, which provide a visual picture to the policymakers, helpful in planning and decision-making.
... GIS technology has been acknowledged as one of six innovations on the frontier of social science research for its contribution to quantifying the built environment (Butz and Torrey, 2006). GIS data are especially important in health sciences that study the contextual attributes of neighborhoods in relation to physical and mental health (Pearce et al., 2006;Thornton et al., 2011;D'Angelo et al., 2014;Fletcher-Lartey and Caprarelli, 2016). ...
Collecting information about the built environment is a challenging process and often leads to measures of environmental exposures that are error-prone and thus result in biased inference. While the use of GIS (Geographic Information System) databases is growing exponentially in health research, there is little guidance on strategies to handle erroneous exposure measures specific to built environment data. Our motivating examples focus on the environmental exposure that is expressed as the number of food outlets (e.g., fast food restaurants) within a circular buffer around the subjects' locations. Measurement error in the exposure can mislead inferences about the impact of the availability of environmental features on health, which is the key factor in place-based strategies or policies to improve public health. This dissertation focuses on developing methods to address measurement challenges in studies of built environment health effects, namely measurement error and data integration. In Chapter II, we propose a split-combine simulation extrapolation (SC-SIMEX) method that accommodates non-classical measurement error due to incorrect geocodes without requiring external data. The standard SIMEX citep{cook1994simulation} is widely used to correct the effect of measurement error on regression problems under distributional assumptions on errors. However, the exposure measurement errors that arise due to geocode coarsening have a novel distribution compared to the commonly used distributions in existing measurement error literature. The proposed SC-SIMEX relaxes the measurement error assumptions required for the standard SIMEX. The utility of SC-SIMEX is demonstrated in a study of children’s obesity in California in relation to the junk food environment. In Chapter III, we develop a multi-source measurement error model to effectively integrate different data sources using external knowledge of source credibility. Secondary commercial lists often provide conflicting claims about the presence and location of businesses. Consequently, disagreement among exposures collected from different sources gives different inferences. Our work shows that bias in the naïve regression model is dependent upon the dispersion of true exposure and the source credibility. Knowing the reliability of databases from field validation studies, the proposed measurement error model can derive complete information about latent true exposures using incomplete data tables with partially known margins. Our method uses a Bayesian nonparametric model that makes few distributional assumptions about the counts of businesses in a region and handles the overdispersion in exposure counts. The application assesses the association between children’s BMI in urban schools and exposure to nearby convenience and grocery stores. Chapter IV extends the data integration methodology in Chapter III to the time-varying setting. For example, commercial business lists often provide annual business listings, which enables us to compute time-varying exposures. We extend the method described in Chapter III to flexibly model the latent time-dependences in true exposures using integer-valued autoregressive process. We aim to estimate the dynamic latent exposures and reduce bias in longitudinal analyses of the exposure health effect. The dissertation concludes with a discussion of future work and the wider implications of the proposed methods. Our methods help future built-environment studies where measurement errors are inevitable and their impacts are little known. This dissertation contributes to improved understanding of measurement error properties that need to be addressed when using built-environment databases and provides novel methods to overcome the bias in epidemiologic analyses.
... The incorporation of Geographical Information Systems (GIS) provides the means to perform such surveillance functions by geocoding cases for rate calculations and modelling space-time patterns (20). Furthermore, opensource GIS software offers the opportunity to develop a low-cost, sustainable surveillance system, ensuring that developing countries with restrained resources can also implement a sustainable surveillance model (21,22). To date, there is no available scientific literature to suggest the implementation of GIS in real-time suicide surveillance, demonstrating innovation in such an approach. ...
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Introduction/Aim Data visualisation is key to informing data-driven decision-making, yet this is an underexplored area of suicide surveillance. By way of enhancing a real-time suicide surveillance system model, an interactive dashboard prototype has been developed to facilitate emerging cluster detection, risk profiling and trend observation, as well as to establish a formal data sharing connection with key stakeholders via an intuitive interface. Materials and Methods Individual-level demographic and circumstantial data on cases of confirmed suicide and open verdicts meeting the criteria for suicide in County Cork 2008–2017 were analysed to validate the model. The retrospective and prospective space-time scan statistics based on a discrete Poisson model were employed via the R software environment using the “ rsatscan ” and “ shiny” packages to conduct the space-time cluster analysis and deliver the mapping and graphic components encompassing the dashboard interface. Results Using the best-fit parameters, the retrospective scan statistic returned several emerging non-significant clusters detected during the 10-year period, while the prospective approach demonstrated the predictive ability of the model. The outputs of the investigations are visually displayed using a geographical map of the identified clusters and a timeline of cluster occurrence. Discussion The challenges of designing and implementing visualizations for suspected suicide data are presented through a discussion of the development of the dashboard prototype and the potential it holds for supporting real-time decision-making. Conclusions The results demonstrate that integration of a cluster detection approach involving geo-visualisation techniques, space-time scan statistics and predictive modelling would facilitate prospective early detection of emerging clusters, at-risk populations, and locations of concern. The prototype demonstrates real-world applicability as a proactive monitoring tool for timely action in suicide prevention by facilitating informed planning and preparedness to respond to emerging suicide clusters and other concerning trends.
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Health outcomes of mothers and their (unborn) children in the perinatal period, i.e., during pregnancy and shortly after birth, can vary by geographical location. This is often due to differences in exposure to medical and social risk factors. Policies aimed at reducing inequalities in perinatal health can provide significant long-term health benefits, especially for (unborn) children. However, a lack of insight into regional perinatal health inequalities means that perinatal health is not always a priority in policy formulation. Novel methods should be used to draw attention to these inequalities, spark interdisciplinary debate and encourage collaborative initiatives. In this commentary, we propose that the development of heat maps that visualize perinatal health outcomes, and risk factors for those outcomes, could be a valuable tool in doing this. Heat maps are a data visualization technique that uses color variations to emphasize value differences between areas. Visualizing health inequalities could potentially create a sense of urgency among (local) stakeholders to initiate polices aimed at improving perinatal health. We illustrate the targeted use of heat maps with an example from the city of Rotterdam, the Netherlands. Large perinatal health inequalities between neighborhoods were visualized in heat maps by a team from the Erasmus Medical Center to bring these inequalities to the attention of the municipality of Rotterdam. Local collaborative initiatives were set up to reduce perinatal health inequalities. These local initiatives formed the foundation for later national policies, including proposals to online implement heat maps regarding perinatal health topics, that are still ongoing today.
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This paper describes a geographic sampling strategy for ecologic studies and describes the relationship between human activities and anopheline larval ecology in urban areas. Kisumu and Malindi, Kenya were mapped using global positioning systems, and a geographic information system was used to overlay a measured grid, which served as a sampling frame. Grid cells were stratified and randomly selected according to levels of planning and drainage. A cross-sectional survey was conducted in April and May 2001 to collect entomologic and human ecologic data. Multivariate regression analysis was used to test the relationship between the abundance of potential larval habitats, and house density, socioeconomic status, and planning and drainage. In Kisumu, 98 aquatic habitats were identified, 65% of which were human made and 39% were positive for anopheline larvae. In Malindi, 91 aquatic habitats were identified, of which, 93% were human made and 65% were harboring anopheline larvae. The regression model explains 82% of the variance associated with the abundance of potential larval habitats in Kisumu. In Malindi, 59% of the variance was explained. As the number of households increased, the number of larval habitats increased correspondingly to a point. Beyond a critical threshold, the density of households appeared to suppress the development of aquatic habitats. The proportion of high-income households and the planning and drainage variables tested insignificant in both locations. The integration of social and biologic sciences will allow local mosquito and malaria control groups an opportunity to assess the risk of encountering potentially infectious mosquitoes in a given area, and concentrate resources accordingly.
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Web Geographic Information System (Web GIS) has been extensively and successfully exploited in various arenas. However, to date, the application of this technology in public health surveillance has yet to be systematically explored in the Web 2.0 era. We reviewed existing Web GIS-based Public Health Surveillance Systems (WGPHSSs) and assessed them based on 20 indicators adapted from previous studies. The indicators comprehensively cover various aspects of WGPHSS development, including metadata, data, cartography, data analysis, and technical aspects. Our literature search identified 58 relevant journal articles and 27 eligible WGPHSSs. Analyses of results revealed that WGPHSSs were frequently used for infectious-disease surveillance, and that geographical and performance inequalities existed in their development. The latest Web and Web GIS technologies have been used in developing WGPHSSs; however, significant deficiencies in data analysis, system compatibility, maintenance, and accessibility exist. A balance between public health surveillance and privacy concerns has yet to be struck. Use of news and social media as well as Web-user searching records as data sources, participatory public health surveillance, collaborations among health sectors at different spatial levels and among various disciplines, adaption or reuse of existing WGPHSSs, and adoption of geomashup and open-source development models were identified as the directions for advancing WGPHSSs.