Spatial epidemiology: current approaches and future challenges

Air pollution impact assessment on agroecosystem and human health characterisation in the area surrounding the industrial settlement of Milazzo (Italy): a multidisciplinary approach

In order to evaluate the impact of atmospheric pollutants emitted by the industrial settlement of Milazzo (Italy) on agriculture, sulphur dioxide and ozone levels in air were monitored and the data were used to estimate yield losses of the most widespread cultures. Trace element concentrations in crops and soils were also detected and metabolic profiles of soil microbial communities were considered. Vibrio fischeri test was used to appraise airborne pollutant ecotoxicity and epidemiological studies on causes of death distribution were carried out to characterize health state of people living in the area. All the sampling points were selected in farms on the basis of a theoretical meteo-diffusive model of industrial air pollutants. Experimental SO2 and O3 values mainly exceeded the threshold established by Italian and EU regulations to protect vegetation and they correspond to estimated significant crop losses. Conversely toxic element residues in soils and in agroalimentary products were generally lower than the fixed values. SO2 and O3 concentrations, toxic element contents and ecotoxicity levels of airborne pollutants were not related only to industrial site emissions, while the fluctuations on metabolic profiles of soil microbial communities seem to agree with the predicted deposition of xenobiotic compounds from the industrial plants. The epidemiological study evidenced a better health state of populations living in the investigated area than in the Messina province and the Sicily region but, inside the area, males living in the municipalities closest to the industrial settlement exhibited a worst health state than those in the very far ones.

A test of association between spatially defined exposure patterns and health outcome risk contours

Advances in the availability of geographically referenced health and environmental quality data of high spatial resolution have created new opportunities in environmental epidemiology. Novel statistical methods for linking health, exposure, and hazards are required to underpin the development of public health tracking. A test for the association between spatial contours of health risk and exposure is outlined. This test is examined using, as an example, the spatial contours of congenital malformation risk obtained from a routine dataset in the vicinity of a landfill site and an exposure model based on exponential reduction with distance from the site. Spatial contours of risk of congenital malformation were simulated using the exposure model stated and a given population pattern. These were compared with the corresponding expected risk derived from routine birth data to yield relative risk contours. For each simulation three test statistics were devised: the slope of the regression line of standardized relative risk on exposure level, the proportion of standardized relative risks above zero, and the mean standardized relative risk of individuals not subject to exposure. The distributions of these test statistics (under the null no exposure from site and alternative hypotheses) were determined from a simulation exercise. A comparison of receiver operator characteristic (ROC) curves between those relating to the proposed test and those relating to a widely used method proposed by Stone (1988) demonstrated our test to be more efficient. Formal statistical testing of the concordance between spatial contours of risk and environmental exposure enables optimal use of spatial data.

Geographic distribution of human immunodeficiency virus in South Africa

In common with most countries, little is know about the geographic distribution of human immunodeficiency virus (HIV) in South Africa. Variations in HIV infection of persons 15-24 years of age were modeled and mapped using generalized linear spatial models and Bayesian prediction based on data from a national HIV household survey conducted in 2003 and comprising 11,904 youth from approximately 700 enumeration areas that were randomly selected from the national census. The maps show considerable variation in HIV prevalence within provinces. The lowest levels were found in inland rural areas of the Western Cape, and the highest in northwestern parts of KwaZulu Natal, southern Mpumalanga, and eastern Free State. Prevalence of HIV was associated with ethnicity, urban status, and unemployment. Detailed maps of HIV prevalence can be effectively used in guiding and focusing intervention programs to areas of particular need.

Evaluating the effect of neighbourhood weight matrices on smoothing properties of Conditional Autoregressive (CAR) models

BACKGROUND

The Conditional Autoregressive (CAR) model is widely used in many small-area ecological studies to analyse outcomes measured at an areal level. There has been little evaluation of the influence of different neighbourhood weight matrix structures on the amount of smoothing performed by the CAR model. We examined this issue in detail.

METHODS

We created several neighbourhood weight matrices and applied them to a large dataset of births and birth defects in New South Wales (NSW), Australia within 198 Statistical Local Areas. Between the years 1995-2003, there were 17,595 geocoded birth defects and 770,638 geocoded birth records with available data. Spatio-temporal models were developed with data from 1995-2000 and their fit evaluated within the following time period: 2001-2003.

RESULTS

We were able to create four adjacency-based weight matrices, seven distance-based weight matrices and one matrix based on similarity in terms of a key covariate (i.e. maternal age). In terms of agreement between observed and predicted relative risks, categorised in epidemiologically relevant groups, generally the distance-based matrices performed better than the adjacency-based neighbourhoods. In terms of recovering the underlying risk structure, the weight-7 model (smoothing by maternal-age 'Covariate model') was able to correctly classify 35/47 high-risk areas (sensitivity 74%) with a specificity of 47%, and the 'Gravity' model had sensitivity and specificity values of 74% and 39% respectively.

CONCLUSION

We found considerable differences in the smoothing properties of the CAR model, depending on the type of neighbours specified. This in turn had an effect on the models' ability to recover the observed risk in an area. Prior to risk mapping or ecological modelling, an exploratory analysis of the neighbourhood weight matrix to guide the choice of a suitable weight matrix is recommended. Alternatively, the weight matrix can be chosen a priori based on decision-theoretic considerations including loss, cost and inferential aims.

[Spatial cluster detection without point source specification: the use of five methods and comparison of their results]

BACKGROUND

Various statistical methods have been developed to describe spatial heterogeneity, in terms of high risk zones. If no source can be determined, this heterogeneity can be globally or locally described. Global methods test a statistic estimated over the whole studied geographical area, whereas local methods estimate a statistic on each spatial unit (or regrouping unit). This paper aimed to present, and to compare results of an epidemiological application, of five methods of spatial cluster detection.

METHODS

The two global detection methods were: 1) Moran's coefficient, a classically used autocorrelation coefficient; 2) Tango's statistic, a spatial generalization of the Chi(2) statistic. The three local methods were: 1) the local application of Moran's coefficient, proposed by Anselin; 2) the scan statistic, which searches for grouping of spatial units; 3) the oblique regression tree, which splits the studied zone into sub-zones of different risks. These five methods were applied to the description of the spatial heterogeneity of the malaria risk over a hyperendemic village, in Mali.

RESULTS

All the methods highlighted a significant spatial heterogeneity. Both global methods (Moran's coefficient and Tango's statistic) showed weak spatial correlations. Local Moran's coefficient (with Bonferronis' adjustment) highlighted five spatial units. The scan statistic identified a single high risk cluster. The regression oblique tree split the study area into six sub-zones; the sub-zone with the higher risk was consistent with the cluster identified by the scan statistic.

CONCLUSION

These presented methods do not require any previous knowledge of a source. They allow evaluating spatial risk heterogeneity over the entire geographical area under study. It is noteworthy that shape, size, and spatial heterogeneity characteristics (either global or local) of the study area, as well as the definition of the proximity, significantly influence the spatial risk analysis' outcome. Although their results should be cautiously interpreted, these methods are useful for preliminary field studies or epidemiological surveys.

Neighbourhood mortality inequalities in New York City, 1989-1991 and 1999-2001

OBJECTIVES

To examine whether inequalities in mortality across socioeconomically diverse neighbourhoods changed alongside the decline in mortality observed in New York City between 1990 and 2000.

DESIGN

Cross-sectional analysis of neighbourhood-level vital statistics.

SETTING

New York City, 1989-1991 and 1999-2001.

MAIN RESULTS

In both poor and wealthy neighbourhoods, age-adjusted mortality for most causes declined between the time periods, although mortality from diabetes increased. Relative inequalities decreased slightly-largely in the under 65 years population-although all-cause rates in 1999-2001 were still 50% higher, and rates of years of potential life lost before age 65 years were 150% higher, in the poorest communities than in the wealthiest ones (relative index of inequality 1.7 and 3.3, respectively). The relative index of inequality for mortality from AIDS increased from 4.7 to 13.9. Over 50% of the excess mortality in the poorest neighbourhoods in 1999-2001 was due to cardiovascular disease, AIDS and cancer.

CONCLUSIONS

In New York City, despite substantial declines in absolute mortality and rate differences between poor and wealthy neighbourhoods, great relative socioeconomic inequalities in mortality persist.

Error and bias in determining exposure potential of children at school locations using proximity-based GIS techniques

BACKGROUND

The widespread availability of powerful tools in commercial geographic information system (GIS) software has made address geocoding a widely employed technique in spatial epidemiologic studies.

OBJECTIVE

The objective of this study was to determine the effect of the positional error in geocoding on the analysis of exposure to traffic-related air pollution of children at school locations.

METHODS

For a case study of Orange County, Florida, we determined the positional error of geocoding of school locations through comparisons with a parcel database and digital orthophotography. We used four different geocoding techniques for comparison to establish the repeatability of geocoding, and an analysis of proximity to major roads to determine bias and error in environmental exposure assessment.

RESULTS

RESULTS INDICATE THAT THE POSITIONAL ERROR IN GEOCODING OF SCHOOLS IS VERY SUBSTANTIAL: We found that the 95% root mean square error was 196 m using street centerlines, 306 m using TIGER roads, and 210 and 235 m for two commercial geocoding firms. We found bias and error in proximity analysis to major roads to be unacceptably large at distances of < 500 m. Bias and error are introduced by lack of positional accuracy and lack of repeatability of geocoding of school locations.

CONCLUSIONS

These results suggest that typical geocoding is insufficient for fine-scale analysis of school locations and more accurate alternatives need to be considered.

[Spatial analysis of air pollution and lung cancer incidence and mortality in 7 metropolitan cities in Korea]

OBJECTIVES

We aimed to assess the relationship between long-term exposure to air pollution and lung cancer in the Republic of Korea.

METHODS

Using the Annual Report of Ambient Air Quality in Korea, Annual Report of National Cancer Registration, and Annual Report on the Cause of Death Statistics, we calculated the standardized mortality ratio (SMR) and standardized incidence ratio (SIR) of lung cancer for both sexes in 74 areas from 7 Korean metropolitan cities. We performed random intercept,Poisson regression using empirical Bayes method.

RESULTS

Both SMRs and SIRs in the 7 metropolitan cities were higher in women than in men. Mean SIRs were 99.0 for males and 107.0 for females. The association between PM10 and lung cancer risk differed according to gender. PM10 was not associated with the risk of lung cancer in males, but both incidence and mortality of lung cancer were positively associated with PM10 in females. The estimated percentage increases in the rate of female lung cancer mortality and incidence were 27% and 65% at the highest PM10 category (>or=70 microgram/m3), compared to the referent category (<50 microgram/m3).

CONCLUSIONS

Long-term exposure to PM10 was significantly associated with female lung cancer incidence in 7 Korean metropolitan cities. Further study is undergoing to estimate the relative risk of PM10 using multi-level analysis for controlling individual and regional confounders such as smoking and socioeconomic position.

Investigating the spatial risk distribution of West Nile virus disease in birds and humans in southern Ontario from 2002 to 2005

BACKGROUND

The West Nile virus (WNv) became a veterinary public health concern in southern Ontario in 2001 and has continued to threaten public health. Wild bird mortality has been shown to be an indicator for tracking the geographic distribution of the WNv. The purpose of this study was to investigate the latent risk distribution of WNv disease among dead birds and humans in southern Ontario and to compare the spatial risk patterns for the period 2002-2005. The relationship between the mortality fraction in birds and incidence rate in humans was also investigated.

METHODS

Choropleth maps were created to investigate the spatial variation in bird and human WNv risk for the public health units of southern Ontario. The data were smoothed by empirical Bayesian estimation before being mapped. Isopleth risk maps for both the bird and human data were created to identify high risk areas and to investigate the potential relationship between the WNv mortality fraction in birds and incidence rates in humans. This was carried out by the geostatistical prediction method of kriging. A Poisson regression analysis was used to model regional human WNv case counts as a function of the spatial coordinates in the east and north direction and the regional bird mortality fractions. The presence of disease clustering and the location of disease clusters were investigated by the spatial scan test.

RESULTS

The isopleth risk maps exhibited high risk areas that were relatively constant from year to year. There was an overlap in the bird and human high risk areas, which occurred in the central-west and south-west areas of southern Ontario. The annual WNv cause-specific mortality fractions in birds for 2002 to 2005 were 31.9, 22.0, 19.2 and 25.2 positive birds per 100 birds tested, respectively. The annual human WNv incidence rates for 2002 to 2005 were 2.21, 0.76, 0.13 and 2.10 human cases per 100,000 population, respectively. The relative risk of human WNv disease was 0.72 times lower for a public health unit that was 100 km north of another public health unit. The relative risk of human WNv disease increased by the factor 1.44 with every 10 positive birds per 100 tested. The scan statistic detected disease cluster in the bird and human data. The human clusters were not significant, when the analysis was conditioned on the bird data.

CONCLUSION

The study indicates a significant relationship between the spatial pattern of WNv risk in humans and birds.

Adequacy of state capacity to address noncommunicable disease clusters in the era of environmental public health tracking

OBJECTIVES

We sought to assess the capacity of state public health agencies to address noncommunicable disease clusters (NCCs) and to develop recommendations to enhance agencies' NCC response capacity.

METHODS

We conducted an inventory of state public health agency Web sites and administered a Web-based survey of state health agency personnel to examine NCC capacity with respect to responsibility and authority, scope, protocols, trends in NCC investigations, and desired assistance.

RESULTS

Twenty-six of the state agency Web sites listed an NCC contact, and 12 mentioned a cluster response team. Thirty-seven states completed the Web-based survey, all addressed cancer clusters, and 30 also responded to other NCCs, such as multiple sclerosis, amyotrophic lateral sclerosis, and autism.

CONCLUSIONS

NCCs are of key concern to communities, and all of the survey respondents indicated that citizen reports were an impetus for investigations; yet, state-level capacity to address NCCs was inconsistent and disjointed. State agency personnel were committed to responding to NCC inquiries but were hampered by lack of personnel, resources, and prescribed protocols, as well as inadequate interagency communication. We offer recommendations to address these challenges.

Influence of geocoding quality on environmental exposure assessment of children living near high traffic roads

Background

The widespread availability of powerful geocoding tools in commercial GIS software and the interest in spatial analysis at the individual level have made address geocoding a widely employed technique in epidemiological studies. This study determined the effect of the positional error in street geocoding on the analysis of traffic-related air pollution on children.

Methods

For a case-study of a large sample of school children in Orange County, Florida (n = 104,865) the positional error of street geocoding was determined through comparison with a parcel database. The effect of this error was evaluated by analyzing the proximity of street and parcel geocoded locations to road segments with high traffic volume and determining the accuracy of the classification using the results of street geocoding. Of the original sample of 163,886 addresses 36% were not used in the final analysis because they could not be reliably geocoded using either street or parcel geocoding. The estimates of positional error can therefore be considered conservative underestimates.

Results

Street geocoding was found to have a median error of 41 meters, a 90^th percentile of 100 meters, a 95^th percentile of 137 meters and a 99^th percentile of 273 meters. These positional errors were found to be non-random in nature and introduced substantial bias and error in the estimates of potential exposure to traffic-related air pollution. Street geocoding was found to consistently over-estimate the number of potentially exposed children at small distances up to 250 meters. False positives and negatives were also found to be very common at these small distances.

Conclusion

Results of the case-study presented here strongly suggest that typical street geocoding is insufficient for fine-scale analysis and more accurate alternatives need to be considered.

Geographical epidemiology, spatial analysis and geographical information systems: a multidisciplinary glossary

We provide a relatively non-technical glossary of terms and a description of the tools used in spatial or geographical epidemiology and associated geographical information systems. Statistical topics included cover adjustment and standardisation to allow for demographic and other background differences, data structures, data smoothing, spatial autocorrelation and spatial regression. We also discuss the rationale for geographical epidemiology and specific techniques such as disease clustering, disease mapping, ecological analyses, geographical information systems and global positioning systems.

Oesophageal cancer mortality in Spain: a spatial analysis

Background

Oesophageal carcinoma is one of the most common cancers worldwide. Its incidence and mortality rates show a wide geographical variation at a world and regional level. Geographic mapping of age-standardized, cause-specific death rates at a municipal level could be a helpful and powerful tool for providing clues leading to a better understanding of its aetiology.

Methods

This study sought to describe the geographic distribution of oesophageal cancer mortality for Spain's 8077 towns, using the autoregressive spatial model proposed by Besag, York and Mollié. Maps were plotted, depicting standardised mortality ratios, smoothed relative risk (RR) estimates, and the spatial pattern of the posterior probability of RR being greater than 1.

Results

Important differences associated with area of residence were observed in risk of dying from oesophageal cancer in Spain during the study period (1989–1998). Among men, excess risk appeared across the north of the country, along a band spanning the length of the Cantabrian coastline, Navarre, the north of Castile & León and the north-west of La Rioja. Excess risk was likewise observed in the provinces of Cadiz and part of Seville in Andalusia, the islands of Tenerife and Gran Canaria, and some towns in the Barcelona and Gerona areas. Among women, there was a noteworthy absence of risk along the mid-section of the Cantabrian seaboard, and increases in mortality, not observed for men, in the west of Extremadura and south-east of Andalusia.

Conclusion

These major gender- and area-related geographical differences in risk would seem to reflect differences in the prevalence of some well-established and modifiable risk factors, including smoking, alcohol consumption, obesity and diet. In addition, excess risks were in evidence for both sexes in some areas, possibly suggesting the implication of certain local environmental or socio-cultural factors. From a public health standpoint, small-area studies could be very useful for identifying locations where epidemiological research and intervention measures ought to receive priority, given the potential for reducing risk in certain places.

An update on cancer cluster activities at the Centers for Disease Control and Prevention

The Centers for Disease Control and Prevention (CDC) continues to be aware of the need for response to public concern as well as to state and local agency concern about cancer clusters. In 1990 the CDC published the "Guidelines for Investigating Clusters of Health Events," in which a four-stage process was presented. This document has provided a framework that most state health departments have adopted, with modifications pertaining to their specific situations, available resources, and philosophy concerning disease clusters. The purpose of this present article is not to revise the CDC guidelines; they retain their original usefulness and validity. However, in the past 15 years, multiple cluster studies as well as scientific and technologic developments have affected duster science and response (improvements in cancer registries, a federal initiative in environmental public health tracking, refinement of biomarker technology, cluster identification using geographic information systems software, and the emergence of the Internet). Thus, we offer an addendum for use with the original document. Currently, to address both the needs of state health departments as well as public concern, the CDC now a) provides a centralized, coordinated response system for cancer cluster inquiries, b) supports an electronic cancer cluster listserver, c) maintains an informative web page, and d) provides support to states, ranging from laboratory analysis to epidemiologic assistance and expertise. Response to cancer clusters is appropriate public health action, and the CDC will continue to provide assistance, facilitate communication among states, and foster the development of new approaches in duster science.

On ecological fallacy, assessment errors stemming from misguided variable selection, and the effect of aggregation on the outcome of epidemiological study

In social and environmental sciences, ecological fallacy is an incorrect assumption about an individual based on aggregate data for a group. In the present study, the validity of this assumption was tested using both individual estimates of exposure to air pollution and aggregate data for 1,492 schoolchildren living in the in vicinity of a major coal-fired power station in the Hadera region of Israel. In 1996 and 1999, the children underwent subsequent pulmonary function tests (PFT), and their parents completed a detailed questionnaire on their health status and housing conditions. The association between children's PFT results and their exposure to air pollution was investigated in two phases. During the first phase, PFT averages were compared with average levels of air pollution detected in townships, and small census areas in which the children reside. During the second phase, individual pollution estimates were compared with individual PFT results, and pattern detection techniques (Getis-Ord statistic) were used to investigate the spatial data structure. While different levels of areal data aggregation changed the results only marginally, the choice of indices measuring the children's PFT performance had a significant influence on the outcome of the analysis. As argued, differences between individual-level and group-level effects of exposure (i.e., ecological or cross-level bias) are not necessary outcomes of data aggregation, and that seemingly unexpected results may often stem from a misguided selection of variables chosen to measure health effects. The implications of the results of the analysis for epidemiological studies are discussed, and recommendations for public health policy are formulated.

Perspectives on applied spatial analysis to animal health: a case of rodents in Thailand

Geographic information systems (GIS) and remote sensing have been increasingly used in ecology and epidemiology, providing a spatial approach for animal health issues. Recent development of earth environmental satellites--i.e., their growing number, improving sensor resolutions and capabilities--has offered new opportunities to delineate possible habitats and understand animals and associated parasites in their environment, by identifying the nature and structure of land use, hydrological network, soil hydromorphy, and human settlements. Integrated into GIS, remotely sensed and other geo-referenced data allow both spatial and temporal analyses of animal ecology and health. However, a review of their applications has showed the poor quality of data sources and processing used, revealing limitations between theory and practical implementations. As an example, the assessment of the expected distribution of Bandicoot rats, main agricultural pest and vector of zoonoses in Phrae province (North Thailand), illustrates a rational use of spatial analysis, with the choice of relevant data, scales, and processing. Vegetation indices are computed on a TERRA ASTER image and further classified using elevation data. The biotopes of Bandicota indica and Bandicota savilei are delimited, providing a major source of knowledge for rodent and human health analyses.

Towards a multidisciplinary and integrated strategy in the assessment of adverse health effects related to air pollution: the case study of Cracow (Poland) and asthma

Complex interaction between anthropogenic activities, air quality and human health in urban areas, such as in Cracow sustains the need for the development of an interdisciplinary and integrated risk-assessment methodology. In such purpose, we propose a pilot study performed on asthmatics and based on a combined use of a biomarker, such as metallothionein 2A (MT-2A) in the characterization of human exposure to one or a mixture of pollutants and of Geographical Information Systems (G.I.S.) which integrates climatic and urban anthropogenic parameters in the assessment of spatio-temporal dispersion of air pollutants. Considering global incidence of air pollution on asthma and on peripheral blood lymphocytes MT-2A expression should provide a complementary information on biological risks linked to urban anthropogenic activities. Such study would help for the establishment of a sustainable development in urban areas that can maintain the integrity of air quality and preserve human health.

Childhood leukemia incidence and exposure to indoor radon, terrestrial and cosmic gamma radiation

This study was undertaken to evaluate the ecological association between terrestrial and cosmic gamma radiation, indoor radon, and acute leukemia incidence among children under 15 y of age. From 1990 to 2001, 5,330 cases of acute leukemia were registered by the French National Registry of Childhood Leukemia and Lymphoma. Exposure to terrestrial gamma radiation was based on measurements, using thermoluminescent dosimeters, at about 1,000 sites covering all the "Départements." In addition, 8,737 indoor terrestrial gamma dose rate measurements covering 62% of the "Départements" and 13,240 indoor radon concentration measurements covering all the "Départements" were made during a national campaign. Cosmic ray doses were estimated in each of the 36,363 "Communes" of France. There was no evidence of an ecological association between terrestrial gamma dose (range: 0.22-0.90 mSv y) or total gamma dose (range: 0.49-1.28 mSv y) and childhood acute leukemia incidence, for acute myeloid leukemia (AML) or for acute lymphoblastic leukemia (ALL), in univariate or multivariate regression analyses including indoor radon. A significant positive association between indoor radon (range: 22-262 Bq m) and AML incidence among children was observed and remained significant in multivariate regression analyses including either terrestrial gamma dose [SIR per 100 Bq m = 1.29 (1.09-1.53)] or total gamma dose [SIR per 100 Bq m = 1.29 (1.09-1.53)]. The study showed no ecological association between terrestrial gamma radiation and childhood leukemia for the range of variation in gamma dose rates observed in France. The moderate ecological association between childhood AML incidence and indoor radon does not appear to be confounded by terrestrial gamma dose.

Policy and programmatic importance of spatial alignment of data sources

Geographic information systems have proven instrumental in assessing environmental impacts on individual and community health, but numerous methodological challenges are associated with analyses of highly localized phenomena in which spatially misaligned data are used. In a case study based on child care facility and traffic data for the Los Angeles metropolitan area, we assessed the extent of facility misclassification with spatially unreconciled data from 3 different governmental agencies in an attempt to identify child care centers in which young children are at risk from high concentrations of toxic vehicle-exhaust pollutants. Relative to geographically corrected data, unreconciled information produced a modest bias in terms of aggregated number of facilities at risk and a substantial number of false positives and negatives.

Análise de dados espaciais em saúde pública: métodos, problemas, perspectivas

Estudos mostram que a localização espacial dos eventos em saúde e os Sistemas de Informações Geográficas (SIG), têm papel destacado e vêm se tornando mais freqüentes na literatura da área de saúde pública. Entretanto, os métodos e software necessários ao aprofundamento desta abordagem ainda apresentam limitações devido à dificuldade de uso e desconhecimento dos pesquisadores e profissionais da área. O objetivo deste trabalho é apresentar algumas aplicações exemplares de métodos voltados para a análise de padrões espaciais de eventos em saúde, discutindo vantagens, desvantagens e aplicabilidade dos modelos propostos, particularmente no campo dos estudos ecológicos e na análise do uso de serviços de saúde, além de sistematizar o estado da arte da utilização de metodologias de análise espacial na saúde pública.

Health and environment information systems for exposure and disease mapping, and risk assessment

A large number of chemicals are used on a regular basis in modern society. Thousands of new chemicals are added each year, many of which may have toxic properties constituting potential health hazards. Rapid assessment of the risk associated with the use of these chemicals is therefore essential to protect people from exposure to potentially harmful substances. Exposures to chemicals (and physical agents) are typically unevenly distributed geographically as well as temporally. Disease occurrence also shows geographically varying patterns. Geographic information systems (GIS) may be used to produce maps of exposure and/or disease to reveal spatial patterns. Exposure mapping using advanced GIS modeling may enhance exposure assessment in environmental epidemiology studies. Disease maps can be valuable tools in risk assessment to explore changes in disease patterns potentially associated with changes in environmental exposures. Spatial variations in risk and trends related to distance from pollution sources may be studied using software tools such as the Rapid Inquiry Facility, developed by the U.K. Small Area Health Statistics Unit and enhanced in the European Health and Environment Information System project, for an initial quick evaluation of any potential health hazards associated with an environmental pollutant.