Geographical Information Systems and Health: Current State and Future Directions

Shaw, Nicola

doi:10.4258/hir.2012.18.2.88

Cited by 38 publications

(39 citation statements)

References 75 publications

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“…It was the concept of developing an understanding of his own risks for a heart attack based on the environmental and risk factors associated with the geographical locations at which he had lived all his life that caused Davenhall to conclude that place history can be just as important as a person’s lifestyle and genetics when determining current and possible health issues 34 , 35. For example, if someone spends most of their life in communities with large amounts of air pollution, their risk of developing lung cancer can be significantly higher than someone who has spent their life in a farming community.…”

Section: Providing Personalized Health Care Through Gismentioning

confidence: 99%

“…For example, if someone spends most of their life in communities with large amounts of air pollution, their risk of developing lung cancer can be significantly higher than someone who has spent their life in a farming community. This justifies the implementation of GIS in population health 34. With all of the eclectic forms of research that continue to occur over the last century, one may ask why it has taken so long to determine this?…”

Section: Providing Personalized Health Care Through Gismentioning

confidence: 99%

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Understanding the use of geographical information systems (GIS) in health informatics research: A review

Shaw

McGuire

2017

jhi

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Section: Providing Personalized Health Care Through Gismentioning

confidence: 99%

Section: Providing Personalized Health Care Through Gismentioning

confidence: 99%

Understanding the use of geographical information systems (GIS) in health informatics research: A review

Shaw

McGuire

2017

jhi

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“…GIS-based cancer mortality maps produced by the National Cancer Institute and Centers for Disease Control and Prevention (CDC) are widely used by public health officials to guide disease surveillance and control activities throughout the United States (34). Beyond traditional GIS mapping capabilities, more sophisticated spatial statistical analyses have been utilized to identify spatial disease clusters (i.e., nonrandom spatial distributions of disease cases, incidence, or prevalence), map and monitor disease patterns and trends over time and space, and assess the impact of ecological and SES on the spatial distribution of diseases.…”

Section: Introductionmentioning

confidence: 99%

Geospatial and Temporal Analysis of Thyroid Cancer Incidence in a Rural Population

Hanley

Jackson

Morrissey

et al. 2015

Thyroid

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Background: The increasing incidence of thyroid cancer has resulted in the rate tripling over the past 30 years. Reasons for this increase have not been established. Geostatistics and geographic information system (GIS) tools have emerged as powerful geospatial technologies to identify disease clusters, map patterns and trends, and assess the impact of ecological and socioeconomic factors (SES) on the spatial distribution of diseases. In this study, these tools were used to analyze thyroid cancer incidence in a rural population. Methods: Thyroid cancer incidence and socio-demographic factors in Vermont (VT), United States, between 1994 and 2007 were analyzed by logistic regression and geospatial and temporal analyses. Results: The thyroid cancer age-adjusted incidence in Vermont (8.0 per 100,000) was comparable to the national level (8.4 per 100,000), as were the ratio of the incidence of females to males (3.1:1) and the mortality rate (0.5 per 100,000). However, the estimated annual percentage change was higher (8.3 VT; 5.7 U.S.). Incidence among females peaked at 30-59 years of age, reflecting a significant rise from 1994 to 2007, while incidence trends for males did not vary significantly by age. For both females and males, the distribution of tumors by size did not vary over time; £1.0 cm, 1.1-2.0 cm, and >2.0 cm represented 38%, 22%, and 40%, respectively. In females, papillary thyroid cancer (PTC) accounted for 89% of cases, follicular (FTC) 8%, medullary (MTC) 2%, and anaplastic (ATC) 0.6%, while in males PTC accounted for 77% of cases, FTC 15%, MTC 1%, and ATC 3%. Geospatial analysis revealed locations and spatial patterns that, when combined with multivariate incidence analyses, indicated that factors other than increased surveillance and access to healthcare (physician density or insurance) contributed to the increased thyroid cancer incidence. Nine thyroid cancer incidence hot spots, areas with very high normalized incidence, were identified based on zip code data. Those locations did not correlate with urban areas or healthcare centers. Conclusions: These data provide evidence of increased thyroid cancer incidence in a rural population likely due to environmental drivers and SES. Geospatial modeling can provide an important framework for evaluation of additional associative risk factors.

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“…Such systems should be developed in order to extend EO capacity into operational disease surveillance, control and early warning with a generic focus on resource-poor environments and architectures. Kelly et al (2012) and Shaw (2012) have requested further development, validation and sustainable implementation of SDSS tools in operational disease control. The operationalization of the service generation within a SDSS will be a key for providing up-to-date information on disease risk.…”

Section: Discussionmentioning

confidence: 99%

Earth observation in support of malaria control and epidemiology: MALAREO monitoring approaches

Franke

Gebreslasie

Bauwens³

et al. 2015

Geospat Health

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Malaria affects about half of the world's population, with the vast majority of cases occuring in Africa. National malaria control programmes aim to reduce the burden of malaria and its negative, socioeconomic effects by using various control strategies (e.g. vector control, environmental management and case tracking). Vector control is the most effective transmission prevention strategy, while environmental factors are the key parameters affecting transmission. Geographic information systems (GIS), earth observation (EO) and spatial modelling are increasingly being recognised as valuable tools for effective management and malaria vector control. Issues previously inhibiting the use of EO in epidemiology and malaria control such as poor satellite sensor performance, high costs and long turnaround times, have since been resolved through modern technology. The core goal of this study was to develop and implement the capabilities of EO data for national malaria control programmes in South Africa, Swaziland and Mozambique. High-and very high resolution (HR and VHR) land cover and wetland maps were generated for the identification of potential vector habitats and human activities, as well as geoinformation on distance to wetlands for malaria risk modelling, population density maps, habitat foci maps and VHR household maps. These products were further used for modelling malaria incidence and the analysis of environmental factors that favour vector breeding. Geoproducts were also transferred to the staff of national malaria control programmes in seven African countries to demonstrate how EO data and GIS can support vector control strategy planning and monitoring. The transferred EO products support better epidemiological understanding of environmental factors related to malaria transmission, and allow for spatio-temporal targeting of malaria control interventions, thereby improving the cost-effectiveness of interventions. IntroductionThere is a vital need for new strategies and innovative health-related monitoring approaches that support the reduction of the burden of environmentally related diseases such as malaria and related negative, socio-economic effects. According to the World Health Organization (WHO), malaria is currently endemic in more than 100 countries worldwide, affects about half of the world's population, and sees the largest number of cases reported in Africa (WHO, 2013b). Each year, approximately 220 million cases and 650 thousands deaths are reported (WHO, 2012b). In Africa, the highly efficient Anopheles gambiae mosquito is the dominant vector of Plasmodium falciparum, the most dangerous of the four human malaria parasites. Besides the serious situation it poses for the infected individual, malaria has far-reaching impacts on both the private and the public healthcare sector, which ultimately impede the economic development of countries or regions. In addition, increased travel and migration have caused many imported cases outside of endemic areas. For instance, over 100,000 imported malaria...

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Geographical Information Systems and Health: Current State and Future Directions

Cited by 38 publications

References 75 publications

Understanding the use of geographical information systems (GIS) in health informatics research: A review

Understanding the use of geographical information systems (GIS) in health informatics research: A review

Geospatial and Temporal Analysis of Thyroid Cancer Incidence in a Rural Population

Earth observation in support of malaria control and epidemiology: MALAREO monitoring approaches

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