Role of geographic information systems in birth defects surveillance and research

Internet search data with spatiotemporal analysis in infectious disease surveillance: Challenges and perspectives

With the rapid development of the internet, the application of internet search data has been seen as a novel data source to offer timely infectious disease surveillance intelligence. Moreover, the advancements in internet search data, which include rich information at both space and time scales, enable investigators to sufficiently consider the spatiotemporal uncertainty, which can benefit researchers to better monitor infectious diseases and epidemics. In the present study, we present the necessary groundwork and critical appraisal of the use of internet search data and spatiotemporal analysis approaches in infectious disease surveillance by updating the current stage of knowledge on them. The study also provides future directions for researchers to investigate the combination of internet search data with the spatiotemporal analysis in infectious disease surveillance. Internet search data demonstrate a promising potential to offer timely epidemic intelligence, which can be seen as the prerequisite for improving infectious disease surveillance.

Uncertainty in geospatial health: challenges and opportunities ahead

PURPOSE

Uncertainty is not always well captured, understood, or modeled properly, and can bias the robustness of complex relationships, such as the association between the environment and public health through exposure, estimates of geographic accessibility and cluster detection, to name a few.

METHODS

We review current challenges and future opportunities as geospatial data and analyses are applied to the field of public health. We are particularly interested in the sources of uncertainty in geospatial data and how this uncertainty may propagate in spatial analysis.

RESULTS

We present opportunities to reduce the magnitude and impact of uncertainty. Specifically, we focus on (1) the use of multiple reference data sources to reduce geocoding errors, (2) the validity of online geocoders and how confidentiality (e.g., HIPAA) may be breached, (3) use of multiple reference data sources to reduce geocoding errors, (4) the impact of geoimputation techniques on travel estimates, (5) residential mobility and how it affects accessibility metrics and clustering, and (6) modeling errors in the American Community Survey. Our paper discusses how to communicate spatial and spatiotemporal uncertainty, and high-performance computing to conduct large amounts of simulations to ultimately increase statistical robustness for studies in public health.

CONCLUSIONS

Our paper contributes to recent efforts to fill in knowledge gaps at the intersection of spatial uncertainty and public health.

A spatial analysis of birth defects in Texas, 1999-2011

BACKGROUND

The etiologies of major birth defects are still unclear and few spatial analyses have been conducted in the United States. Spatial analyses of individual-level data can help elucidate environmental and social risk factors.

METHODS

We used generalized additive models to analyze 52,955 cases of neural tube defects, congenital heart defects (CHDs), gastroschisis, and orofacial cleft defects, and sampled from 642,399 controls born between 1999 and 2011 in Texas. The effect of geographic location was measured using a bivariable smooth term of geocoded birth address within a logistic regression framework. We calculated and mapped odds ratios (ORs) and 95% confidence intervals (CIs) for birth defects subtypes across Texas, and adjusted for maternal characteristics, environmental indicators, and community-level covariates. We also performed time-stratified spatiotemporal analyses for more prevalent birth defects.

RESULTS

Location was significantly associated with crude odds of all birth defects except hypoplastic left heart syndrome. After adjusting for maternal characteristics, environmental indicators, and community-level factors, ORs in many geographic areas were no longer statistically significant for most defects, especially CHDs. However, areas of significant and insignificant elevated risk remained for defects in all groups in North and South Texas, with ORs for ventricular septal defects increasing over time. Low risk of birth defects was often present in the northern part of East Texas.

CONCLUSION

Significant spatial patterns of birth defects were identified and varied depending on adjustment of different categories of covariates. Further investigation of areas with increased risks may aid in our understanding of birth defects.

Evidence for a cluster of rare birth defects in the Ain department (France)

BACKGROUND

REMERA (REgistre des Malformations En Rhône-Alpes) is a registry of congenital malformations that covers 58,000 births annually in Central-East France. In 2010, the registry raised an alarm to the health authorities (Santé publique France, SpF) about three cases of a unilateral isolated transverse upper limb reduction defect (UITULRD) in a small subarea; the general prevalence of this defect is one case in 10,000 births. In the following years, more infants were born with the same malformation in the same territory of the Ain department. Public health authorities, supported by an expert committee, rejected the existence of a cluster, but we aim here at providing evidence for this cluster.

METHODS

Geocoded data for all UITULRD cases (ICD-10 codes Q71.2 and Q71.3) were extracted from the REMERA database. We conducted a Kulldorff cluster analysis of these data, using the spatial SaTScanTM algorithm.

RESULTS

The analysis found a cluster of eight cases of UITULRD among the 8,204 births occurring between 2009 and 2014 within a circle of 16.24 km radius centered on a village of the Ain department, whereas 0.82 cases were expected under a uniform probability of such a birth throughout the registry territory. This represents an almost 10fold excess over the expected number of cases (p = .0057).

CONCLUSIONS

The arguments used to deny the cluster are disputed and we present the evidence supporting its reality. The controversy that has followed the alarm has compromised the search for the cause(s) of this excess of rare malformations.

Spatial Analytics Based on Confidential Data for Strategic Planning in Urban Health Departments

Spatial data analytics can detect patterns of clustering of events in small geographies across an urban region. This study presents and demonstrates a robust research design to study the longitudinal stability of spatial clustering with small case numbers per census tract and assess the clustering changes over time across the urban environment to better inform public health policy making at the community level. We argue this analysis enables the greater efficiency of public health departments, while leveraging existing data and preserving citizen personal privacy. Analysis at the census tract level is conducted in Mecklenburg County, North Carolina, on hypertension during pregnancy compiled from 2011–2014 birth certificates. Data were derived from per year and per multi-year moving counts by aggregating spatially to census tracts and then assessed for clustering using global Moran’s I. With evidence of clustering, local indicators of spatial association are calculated to pinpoint hot spots, while time series data identified hot spot changes. Knowledge regarding the geographical distribution of diseases is essential in public health to define strategies that improve the health of populations and quality of life. Our findings support that spatial aggregation at the census tract level contributes to identifying the location of at-risk “hot spot” communities to refine health programs, while temporal windowing reduces random noise effects on spatial clustering patterns. With tight state budgets limiting health departments’ funds, using geographic analytics provides for a targeted and efficient approach to health resource planning.

Factors Associated with Travel Time and Distance to Access Hospital Care Among Infants with Spina Bifida

OBJECTIVES

Using geographic information systems (GIS), we examined travel time and distance to access hospital care for infants with spina bifida (SB).

METHODS

This study was a statewide, population-based analysis of Florida-born children with SB, 1998-2007, identified by the Florida Birth Defects Registry and linked to hospitalizations. We geocoded maternal residence at delivery and identified hospital locations for infants (<1 year). Using 2007 Florida Department of Transportation road data, we calculated one-way mean travel time and distance to access hospital care. We used Poisson regression to examine selected factors associated with travel time and distance [≤30 vs. >30 min/miles (reference)], including presence of hydrocephalus and SB type [isolated (no other major birth defect) versus non-isolated SB].

RESULTS

For 612 infants, one-way mean (median) travel time was 45.1 (25.9) min. Infants with both non-isolated SB and hydrocephalus traveled longest to access hospitals (mean 60.8 min/48.5 miles; median 34.2 min/26.9 miles). In adjusted results, infants with non-isolated SB and whose mothers had a rural residence were less likely to travel ≤30 min to hospitals. Infants born to mothers in minority racial/ethnic groups were more likely to travel ≤30 min.

CONCLUSIONS

Birth defects registry data and GIS-based methods can be used to evaluate geographic accessibility to hospital care for infants with birth defects. Results can help to identify geographic barriers to accessing hospital care, such as travel time and distance, and inform opportunities to improve access to care for infants with SB or other special needs.

Modeling travel impedance to medical care for children with birth defects using Geographic Information Systems

BACKGROUND

Children with birth defects may face significant geographic barriers accessing medical care and specialized services. Using a Geographic Information Systems-based approach, one-way travel time and distance to access medical care for children born with spina bifida was estimated.

METHODS

Using 2007 road information from the Florida Department of Transportation, we built a topological network of Florida roads. Live-born Florida infants with spina bifida during 1998 to 2007 were identified by the Florida Birth Defects Registry and linked to hospital discharge records. Maternal residence at delivery and hospitalization locations were identified during the first year of life.

RESULTS

Of 668 infants with spina bifida, 8.1% (n = 54) could not be linked to inpatient data, resulting in 614 infants. Of those 614 infants, 99.7% (n = 612) of the maternal residential addresses at delivery were successfully geocoded. Infants with spina bifida living in rural areas in Florida experienced travel times almost twice as high compared with those living in urban areas. When aggregated at county levels, one-way network travel times exhibited statistically significant spatial autocorrelation, indicating that families living in some clusters of counties experienced substantially greater travel times compared with families living in other areas of Florida.

CONCLUSION

This analysis demonstrates the usefulness of linking birth defects registry and hospital discharge data to examine geographic differences in access to medical care. Geographic Information Systems methods are important in evaluating accessibility and geographic barriers to care and could be used among children with special health care needs, including children with birth defects.

Leveraging geospatial data, technology, and methods for improving the health of communities: priorities and strategies from an expert panel convened by the CDC

In 2008, CDC convened an expert panel to gather input on the use of geospatial science in surveillance, research and program activities focused on CDC's Healthy Communities Goal. The panel suggested six priorities: spatially enable and strengthen public health surveillance infrastructure; develop metrics for geospatial categorization of community health and health inequity; evaluate the feasibility and validity of standard metrics of community health and health inequities; support and develop GIScience and geospatial analysis; provide geospatial capacity building, training and education; and, engage non-traditional partners. Following the meeting, the strategies and action items suggested by the expert panel were reviewed by a CDC subcommittee to determine priorities relative to ongoing CDC geospatial activities, recognizing that many activities may need to occur either in parallel, or occur multiple times across phases. Phase A of the action items centers on developing leadership support. Phase B focuses on developing internal and external capacity in both physical (e.g., software and hardware) and intellectual infrastructure. Phase C of the action items plan concerns the development and integration of geospatial methods. In summary, the panel members provided critical input to the development of CDC's strategic thinking on integrating geospatial methods and research issues across program efforts in support of its Healthy Communities Goal.

Methods for retrospective geocoding in population studies: the Jackson Heart Study

The increasing use of geographic information systems (GIS) in epidemiological population studies requires careful attention to the methods employed in accomplishing geocoding and creating a GIS. Studies have provided limited details,hampering the ability to assess validity of spatial data. The purpose of this paper is to describe the multiphase geocoding methods used to retrospectively create a GIS in the Jackson Heart Study (JHS). We used baseline data from 5,302 participants enrolled in the JHS between 2000 and 2004 in a multiphase process to accomplish geocoding2 years after participant enrollment. After initial deletion of ungeocodable addresses(n=52), 96% were geocoded using ArcGIS. An interactive method using data abstraction from participant records, use of additional maps and street reference files,and verification of existence of address, yielded successful geocoding of all but 13 addresses. Overall, nearly 99% (n=5,237) of the JHS cohort was geocoded retrospectively using the multiple strategies for improving and locating geocodable addresses. Geocoding validation procedures revealed highly accurate and reliable geographic data. Using the methods and protocol developed provided a reliable spatial database that can be used for further investigation of spatial epidemiology. Baseline results were used to describe participants by select geographic indicators, including residence in urban or rural areas, as well as to validate the effectiveness of the study's sampling plan. Further, our results indicate that retrospectively developing a reliable GIS for a large, epidemiological study is feasible. This paper describes some of the challenges in retrospectively creating a GIS and provides practical tips that enhanced the success.

Musings on privacy issues in health research involving disaggregate geographic data about individuals

This paper offers a state-of-the-art overview of the intertwined privacy, confidentiality, and security issues that are commonly encountered in health research involving disaggregate geographic data about individuals. Key definitions are provided, along with some examples of actual and potential security and confidentiality breaches and related incidents that captured mainstream media and public interest in recent months and years. The paper then goes on to present a brief survey of the research literature on location privacy/confidentiality concerns and on privacy-preserving solutions in conventional health research and beyond, touching on the emerging privacy issues associated with online consumer geoinformatics and location-based services. The 'missing ring' (in many treatments of the topic) of data security is also discussed. Personal information and privacy legislations in two countries, Canada and the UK, are covered, as well as some examples of recent research projects and events about the subject. Select highlights from a June 2009 URISA (Urban and Regional Information Systems Association) workshop entitled 'Protecting Privacy and Confidentiality of Geographic Data in Health Research' are then presented. The paper concludes by briefly charting the complexity of the domain and the many challenges associated with it, and proposing a novel, 'one stop shop' case-based reasoning framework to streamline the provision of clear and individualised guidance for the design and approval of new research projects (involving geographical identifiers about individuals), including crisp recommendations on which specific privacy-preserving solutions and approaches would be suitable in each case.

Residential mobility during pregnancy: patterns and correlates

Information on patterns and correlates of residential mobility can be important in studies of environmental factors and birth outcomes. The objective of this study was to describe residential mobility patterns and possible sociodemographic correlates of residential mobility among pregnant women. We obtained information on 656 mothers of infants with birth defects (cases) and 335 mothers of infants without birth defects (controls) from the geocoded dataset of the Birth Defects Risk Factor Surveillance Study, a case-control study conducted in Atlanta, Georgia, from 1993 through 1997. Using geographic information techniques, we measured distances mothers moved between residential addresses, and evaluated the proportion of moves and movement patterns by trimester. We used multivariate logistic regression to evaluate possible correlates of residential mobility for case and control mothers, including race, age, education, occupation, socioeconomic status, smoking, parity, and pregnancy planning. About 22% of women moved during pregnancy and most of them moved during the second trimester (11.9%), with no variation by case-control status. Among mothers who moved 51% moved within the same county. Pregnant women were more likely to move if they were younger (20-24 years, adjusted odds ratio (aOR) 3.39, 95% confidence interval (CI) 2.12-5.42; > or = 30 years: reference), did not plan their pregnancy (aOR 1.66, 95% CI 1.18-2.34), and smoked (aOR 1.46, 95% CI 1.01-2.12). For these associations with mother's residential mobility, there were no appreciable confounding or effect modification effects by case-control status. In studies of pregnancy outcomes and potential environmental exposures based on residence at the time of delivery, residential mobility during pregnancy may not vary by case-control status, but it still needs to be considered as a possible source of exposure misclassification. Accounting for potential case-control differences in correlates of residential mobility could be useful in minimizing potential non-differential misclassification.

Residential Anonymous Linking Fields (RALFs): a novel information infrastructure to study the interaction between the environment and individuals' health

BACKGROUND

The necessity of aggregating health data over areas can impede our understanding of health determinants.

METHODS

We demonstrate the possibility of creating anonymous links between individual residences and the local environment using digital map data and a data linkage system.

RESULTS

Digital map data were used successfully to anonymously link 1.3 million addresses to the local environment. The data linkage system allows detailed environment data surrounding each residence to be linked both to each resident therein and to their medical records.

CONCLUSIONS

Local environment data specific to each house can be effectively and anonymously linked to the population registered with the National Health Service. Our integrated approach potentially enables flexible fine-scale, large-area observational studies of communities and health.

Application of the automated spatial surveillance program to birth defects surveillance data

BACKGROUND

Although many birth defects surveillance programs incorporate georeferenced records into their databases, practical methods for routine spatial surveillance are lacking. We present a macroprogram written for the software package R designed for routine exploratory spatial analysis of birth defects data, the Automated Spatial Surveillance Program (ASSP), and present an application of this program using spina bifida prevalence data for metropolitan Atlanta.

METHODS

Birth defects surveillance data were collected by the Metropolitan Atlanta Congenital Defects Program. We generated ASSP maps for two groups of years that correspond roughly to the periods before (1994-1998) and after (1999-2002) folic acid fortification of flour. ASSP maps display census tract-specific spina bifida prevalence, smoothed prevalence contours, and locations of statistically elevated prevalence. We used these maps to identify areas of elevated prevalence for spina bifida.

RESULTS

We identified a large area of potential concern in the years following fortification of grains and cereals with folic acid. This area overlapped census tracts containing large numbers of Hispanic residents.

CONCLUSIONS

The potential utility of ASSP for spatial disease monitoring was demonstrated by the identification of areas of high prevalence of spina bifida and may warrant further study and monitoring. We intend to further develop ASSP so that it becomes practical for routine spatial monitoring of birth defects.