gis in health

No description available.

Geographic Informatics in Health: Geographic Informatics in Health Maged N Kamel Boulos PhD, MSc, MBBCh School for Health, University of Bath Bath BA2 7AY, UK E-mail: M.N.K.Boulos@bath.ac.uk

Introduction: Location Matters: Introduction: Location Matters The concept that location can influence health is a very old one in medicine. As far back as the time of Hippocrates (c. 3rd century BC), physicians observed that certain diseases tend to occur in some places and not others. In fact, different locations on Earth are usually associated with different profiles: physical, biological, environmental, economic, social, cultural and sometimes even spiritual profiles, that do affect and are affected by health, disease and healthcare. These profiles and associated health and disease conditions may also change with time (the longitudinal or temporal dimension).

Introduction: The Origins of Spatial Analysis: Introduction: The Origins of Spatial Analysis In 1854, a major cholera outbreak in London had already taken nearly six hundred lives when Dr. John Snow, using a hand-drawn map, showed that the source of the disease was a contaminated water pump. By plotting each known cholera case on a street map of Soho district (where the outbreak took place), Snow could see that the cases occurred almost entirely among those who lived near the Broad Street water pump. This pump belonged to the Southwark and Vauxhall Water Company, which drew water polluted with London sewage from the lower Thames River. The Lambeth Water Company, which had relocated its water source to the upper Thames, escaped the contamination.

Introduction: The Origins of Spatial Analysis: Introduction: The Origins of Spatial Analysis Snow recommended that the handle of this pump be removed, and this simple action stopped the outbreak and proved his theory that cholera is transmitted through contaminated drinking water. People could also see on this map that cholera deaths were not confined to the area around a cemetery of plague victims and were thus convinced that the infection was not due to vapours coming from it as they first thought.

Introduction: The Origins of Spatial Analysis: Introduction: The Origins of Spatial Analysis This map is a digital recreation of Dr. Snow’s hand-drawn map. The 1854 cholera deaths are displayed as small black circles. The grey polygon represents the former burial plot of plague victims. The Broad Street pump (shown in the centre of the map) proved to be the source of contaminated water, just as Snow had hypothesised. (Generated using CDC Epi Map 2000 for Windows, a public domain package that can be downloaded from: http://www.cdc.gov/epiinfo/)

Introduction: The Origins of Spatial Analysis: Introduction: The Origins of Spatial Analysis By using a map to examine the geographical (spatial) locations of cholera cases in relation to other features on the map (water pumps and cemetery of plague victims), Snow was actually performing what is now known as spatial analysis. < Dr. John Snow (1813-1858), a legendary figure in the history of public health, epidemiology and anesthesiology

Health Geography: Health Geography It is very useful and customary to divide the geography of health into two interrelated areas: The geography of disease, which covers the exploration, description and modelling of the spatio-temporal (space-time) incidence of disease and related environmental phenomena, the detection and analysis of disease clusters and patterns, causality analysis and the generation of new disease hypotheses; The geography of healthcare systems, which deals with the planning, management and delivery of suitable health services (ensuring among other things adequate patient access) after determining healthcare needs of the target community and service catchment zones.

Health Geography: Health Geography Health geography plays a vital role in public health surveillance, including the design and monitoring of the implementation of health interventions and disease prevention strategies. Geographical research into healthcare services can also help identifying inequities in health service delivery between classes and regions, and in the efficient allocation and monitoring of scarce healthcare resources. Examples include allocating healthcare staff by region based on actual needs, and assisting in determining the best location and specifications for new healthcare facilities and in planning extensions to existing ones.

Videohttp://vega.soi.city.ac.uk/~dk708/res/esri_promo.rmESRI promotional video introducing geographic information systems (Format: RealVideo; Running Time: 4:52 min. - Source: ESRI, US): Video http://vega.soi.city.ac.uk/~dk708/res/esri_promo.rm ESRI promotional video introducing geographic information systems (Format: RealVideo; Running Time: 4:52 min. - Source: ESRI, US)

Essentials of Geographic Informatics: Essentials of Geographic Informatics Geographic Informatics, also known as geoinformatics or geomatics, is the science and technology of gathering, storing, analysing, interpreting, modelling, distributing and using spatially referenced (georeferenced) information. Geographic Informatics is multidisciplinary by nature. It comprises a broad range of disciplines, including surveying and mapping, remote sensing, geographical information systems (GIS), and the Global Positioning System (GPS). These, in turn, draw from a wide variety of other fields and technologies, including computational geometry, computer graphics, digital image processing, multimedia and virtual reality, computer-aided design (CAD), database management systems (DBMS), spatio-temporal statistics, artificial intelligence, communications and Internet technologies amongst others.

Essentials of Geographic Informatics: Essentials of Geographic Informatics GIS also favours an interdisciplinary approach to the solution of problems. Going beyond conventional spreadsheet and database tables, it helps us discover and visualise new data patterns and relationships that would have otherwise remained invisible. It achieves this through its unique way of classifying multifaceted, real-world data coming from disparate sources into map layers (coverages or themes), each covering a single aspect of reality, then linking these layers by spatially matching them, and querying and analysing them together to produce new information and hypotheses. This can be considered one form of data-mining, and is especially useful in the context of aggregated patient records.

Essentials of Geographic Informatics: Essentials of Geographic Informatics

Essentials of Geographic Informatics: Essentials of Geographic Informatics It is possible, for example, to overlay and integrate the following data to perform different types of health-related analyses: population data, e.g., census and socio-economic data; environmental and ecological data, e.g., monitored data on pollution and vegetation (satellite pictures); topography, hydrology and climate data; land-use and public infrastructure data, e.g., schools and main drinking water supply; transportation networks (access routes) data, e.g., roads and railways; health infrastructure and epidemiological data, e.g., data on mortality, morbidity, disease distribution and healthcare facilities; and other data as needed to perform different types of health-related analyses.

Essentials of Geographic Informatics: Essentials of Geographic Informatics As a modelling and decision support tool, GIS can help determining the geographical distribution and variation of diseases (e.g., prevalence, incidence) and associated factors, analysing spatial and longitudinal trends, mapping populations at risk and stratifying risk factors. GIS can also assist in assessing resource allocation and accessibility (health services, schools, water points), planning and targeting interventions, including simulating (predicting) many “what-if” scenarios before implementing them, forecasting epidemics, and monitoring diseases and interventions over time. GIS provides a range of extrapolation techniques, for example, to extrapolate sentinel site surveillance to unsampled regions. Other important GIS applications include routing functions and emergency dispatch systems.

GIS-related Technologies: Remote Sensing: GIS-related Technologies: Remote Sensing In 1970, in an article titled “New eyes for epidemiologists: aerial photography and other remote sensing techniques”, Cline predicted that remote sensing (RS) will be used in detecting and monitoring disease outbreaks; this proved correct in the following years. Remote sensing is gathering geographical data from above, usually by aircraft or satellite sensors. It is a major source of GIS data and can rapidly cover large areas of the Earth with relatively low cost per ground unit.

GIS-related Technologies: Remote Sensing: GIS-related Technologies: Remote Sensing Moreover, additional data from parts of the electromagnetic energy spectrum that are not visible to the human eye can provide very useful information that would have otherwise remained unknown. For example, thermal infrared sensors pick up subtle temperature differences and display them on film or electronic devices. This is useful in thermal pollution monitoring, allowing industrial effluence to be analysed in terms of heat characteristics.

GIS-related Technologies:The Global Positioning System : GIS-related Technologies: The Global Positioning System The Global Positioning System (GPS) consists of 24 Earth-orbiting satellites that transmit signals to special receivers on the ground, either hand-held units or more sophisticated vehicle-mounted and stationary equipment, for accurate determination of positional co-ordinates. Some receivers can also display digital maps, and plot the positional co-ordinates on them. GPS can also provide data on elevation, velocity (while moving) and time of measurement. Ground crew workers use GPS in collecting accurately positioned (georeferenced) field data to create and update GIS coverages.

GIS-related Technologies:The Global Positioning System : GIS-related Technologies: The Global Positioning System

GIS-related Technologies:The Global Positioning System : GIS-related Technologies: The Global Positioning System GPS technology is also used to dispatch police cars, ambulances and fire fighters in emergency situations. Ground emergency units receive signals from GPS receivers mounted in moving emergency vehicles to determine, track and guide the vehicle nearest to an emergency. GPS can be also combined with real-time GIS to ensure efficient routing of ambulance trips by finding the shortest and quickest routes, and avoiding routes with traffic congestion (based on live traffic maps). This can dramatically reduce the response time in emergency situations and help saving more lives. Furthermore, new FCC rules (Federal Communications Commission - http://www.fcc.gov/911/enhanced/) mean that GPS receivers will be very soon incorporated into mobile phones, thus helping ambulance or rescue teams to precisely and quickly locate and track people who are in a medical emergency, injured or lost but cannot give their precise location.

Examples of Health and Healthcare Applications of Geographic Informatics: Examples of Health and Healthcare Applications of Geographic Informatics

Applications Using Remote Sensing for Data Acquisition: Applications Using Remote Sensing for Data Acquisition Since 1985, CHAART (Centre for Health Applications of Aerospace Related Technologies, US - http://geo.arc.nasa.gov/esdstaff/health/chaart.html) has been involved in a number of projects on the application of RS and GIS technology to human health problems. Among these projects was a study of the spatial patterns of filariasis in the Nile Delta, Egypt, and prediction of villages at risk for filariasis transmission in the Nile Delta. Landsat Thematic Mapper data coinciding with epidemiological field data were converted into vegetation and moisture indices and classified into land-cover types. Statistical analyses were used to correlate these land-cover variables with the spatial distribution of microfilaria in 201 villages.

Applications Using Remote Sensing for Data Acquisition: Applications Using Remote Sensing for Data Acquisition Another study investigated Lyme disease in Westchester County, New York, US to develop a satellite remote sensing/GIS model for prediction of Lyme disease risk, which can help public health workers in their efforts to reduce disease incidence. Similarly, a third study of schistosomiasis in China aimed at developing a hydrological model that could be used to identify risk factors for disease transmission. CHAART has also been involved in two malaria surveillance projects carried in California, US and Chiapas, Mexico as part of NASA’s Global Monitoring and Human Health programme. The field research focused on the relationship of Anopheles mosquito to environmental variables associated with regional landscape elements, including larval habitats (flooded pastures and transitional wetlands), blood-meal sources (cattle in pastures) and resting sites (trees). The remote sensing research involved identifying and mapping these and other landscape elements using multi-temporal Landsat Thematic Mapper data.

Applications Using Remote Sensing for Data Acquisition: Applications Using Remote Sensing for Data Acquisition Left: Landsat TM images of Mexico Coastal Plain from July 1991 showing the wet season, and the landscape is mostly green. Right: Landsat TM images of the same Mexico Coastal Plain from March 1992. In the spring season, much of this area is dry and is purple in this image (right)

Applications Using Remote Sensing for Data Acquisition: Applications Using Remote Sensing for Data Acquisition The MALSAT (Environmental Information Systems for Malaria - http://www.liv.ac.uk/lstm/malsat.html) team is another group of researchers, based at the Liverpool School of Tropical Medicine, UK, who are investigating the eco-epidemiology of vector-borne diseases, including malaria in sub-Saharan Africa, using GIS and RS. Studies in The Gambia have demonstrated how satellite-derived data can be used to explain variation in malaria transmission, while the value of such data in predicting malaria epidemics is being examined in other parts of Africa. The group is now involved in another project titled “Forecasting meningitis epidemics in Africa” to develop a climate-driven model for predicting outbreaks of meningococcal meningitis in Africa.

Applications Using GPS for Data Acquisition: Applications Using GPS for Data Acquisition In Kenya, researchers from the Division of Parasitic Diseases of the Centres for Disease Control and Prevention (CDC, Atlanta, Georgia, US) work with the Kenya Medical Research Institute to study malaria and means of preventing it. These researchers use GPS to collect positions and data in the field, and then edit and analyse this data in GIS. One study region had its last map made in the late 1960s, and researchers needed an updated map for their study. GPS helped them update the old map features to reflect the current status of the land.

Applications Using GPS for Data Acquisition: Applications Using GPS for Data Acquisition The GPS mapping team hired local fishermen to row them in small fishing boats to map the shore of the lake. Roads were mapped by driving cars along them while a team member captured location data with GPS. Once they had an updated map of the region, they could begin using their GIS and create maps to help them in their malaria studies.

Examples of Health/Public Health Applications: Examples of Health/Public Health Applications

WHO (World Health Organisation) GIS Programmes: WHO (World Health Organisation) GIS Programmes HealthMap (http://www.who.int/csr/mapping/en/) is a joint WHO/UNICEF GIS Programme that was initially created in 1993 to provide GIS support for the management and monitoring of the Guinea Worm Eradication Programme. But since 1995, the scope of the work has been expanded to cover other disease control and public health programmes. The HealthMap project has successfully contributed to the surveillance, control, prevention and eradication of many communicable diseases, including Guinea worm, onchocerciasis, lymphatic filariasis, malaria, schistosomiasis, intestinal parasites, blinding trachoma and HIV. The programme has developed its own HealthMapper application and is providing it at no cost to developing countries. This is a database management and mapping system that simplifies the collection, storage, retrieval, management, spatial and statistical analyses, and visualisation of public health data through its user-friendly interface.

WHO (World Health Organisation) GIS Programmes: WHO (World Health Organisation) GIS Programmes

WHO (World Health Organisation) GIS Programmes: WHO (World Health Organisation) GIS Programmes The WHO is also using GIS technology in its Leprosy Elimination Programme (LEP - http://www.who.int/lep/Monitoring_and_Evaluation/gis.htm). The WHO Regional Office for the Americas (PAHO - Pan American Health Organisation - http://www.paho.org/english/sha/SHASIG.htm) has developed its own GIS in Health project for the Americas (SIG-EPI).

GIS in Malaria: The MARA/ARMA Initiative : GIS in Malaria: The MARA/ARMA Initiative The MARA/ARMA collaboration (Mapping Malaria Risk in Africa / Atlas du Risque de la Malaria en Afrique) is funded by the International Development Research Centre of Canada (IDRC), the South African Medical Research Council (SAMRC), the UK Wellcome Trust, the Swiss Tropical Institute and the UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR). MARA/ARMA aims at providing a GIS atlas of malaria risk for Africa, by integrating spatial environmental and malaria datasets to produce maps of the type and severity of malaria transmission in different regions of the continent. The project attempts to define malaria risk categories (environmental strata) in terms of non-malaria data, e.g., environmental and climatic data, and to develop a mask layer of factors that exclude malaria (a no-risk category), e.g., absence of population, high altitude, deserts, etc. Areas of no data are highlighted during the course of the project with the possibility of using geographical modelling to extrapolate to such no-data areas, based on the defined environmental stratification rules.

Slide33: http://www.mara.org.za By spatially defining the African continent into regions of similar type and severity of malaria transmission, appropriate control measures can be tailored to each region according to its needs, thus maximising the potential and outcomes of available control resources (human, financial and technical). The MARA/ARMA maps should be of great value to research on malaria transmission dynamics. MARA/ARMA can also serve as a model for the study and control of other diseases, and all non-malaria-specific information gathered during the course of the project can be reused in a similar manner.

HealthQuery: An Example of a Healthcare Services/Access Application: HealthQuery: An Example of a Healthcare Services/Access Application HealthQuery (http://www.healthquery.org/chs.html) is a collection of Web-based public domain tools designed to assist California residents and health organisations in making more informed health decisions. It is a collaborative project of many US organisations and end-users including the Good Hope Medical Foundation, California Department of Health Services — Centre for Health Statistics, the National Health Foundation (NHF), a Los Angeles-based, public benefit organisation, and three companies: ESRI, Oracle and Sun Microsystems. The included Health Facility Finder tool allows users to locate the hospitals, clinics and emergency rooms that are nearest to them (within a user-defined radius) and provides them with detailed driving directions from their current locations to matching facilities. HealthQuery also has plans to develop other tools to model and simulate the supply and demand for healthcare services into the future and allow users to compare the current supply and demand for these services.

HealthQuery: An Example of a Healthcare Services/Access Application: HealthQuery: An Example of a Healthcare Services/Access Application In this screenshot, we searched for the nearest hospitals within a 5-mile radius around 92373 (Zip code, CA, US). HealthQuery found 4 locations.

HealthQuery: An Example of a Healthcare Services/Access Application: HealthQuery: An Example of a Healthcare Services/Access Application In this screenshot, we asked HealthQuery to give us detailed driving directions from near 92373 (Zip code, CA, US) to one of the facilities located in the previous figure (Redlands Community Hospital).

Conclusions: Conclusions Understanding the relationship between location and health can greatly assist us in understanding, controlling and preventing disease, and in better healthcare planning, with more efficient and effective resource utilisation. This should ultimately lead to better healthcare outcomes and improved health for everyone. However, for geographic informatics to become one day a mainstream technology in the health sector like today’s spreadsheet and database packages, we still need to combat many data availability/quality barriers, as well as cultural and organisational barriers, including “spatial illiteracy” among healthcare workers, while making the tools cheaper and much easier to learn and use. Professional education and hands-on training courses in geographic informatics are extremely important in achieving this goal.

Resources: Resources Web site: http://soi.city.ac.uk/~dk708/ Kamel Boulos MN, Roudsari AV, Carson ER. Health Geomatics: An Enabling Suite of Technologies in Health and Healthcare (Methodolical Review). Journal of Biomedical Informatics 2001 Jun;34(3):195-219 ESRI Virtual Campus (http://campus.esri.com) courses on Health GIS Applications. Make sure you have all the required software and ArcView extensions before ordering any of these courses!