Introduction: geospatial health research and GIS

While epidemiologists, medical geographers and public health practitioners have known for long that human health is not only about the individual body but should also be understood at the population level within particular geographic contexts, contemporary environmental and socioeconomic concerns (particularly global environmental change and globalization) have brought unprecedented attention to the connection between human health and factors at the landscape and even the global levels. As a result, in the past two decades, studies of human health from geographic perspectives and research on applying geospatial analyses to health problems have experienced tremendous development (in this essay, we use geospatial health research as a general term to refer to this kind of research) (e.g., Gatrell and Elliott 2009; Pearce and Witten 2010; Cromley and McLafferty 2011; Kwan 2013). Recent landmarks of this development include the position paper by Richardson et al. (2013) in Science, articulation of the uncertain geographic context problem (Kwan 2012a, 2012b) and the ongoing Spatial Uncertainty Program launched by the US National Institutes of Health (NIH) in 2011.

This special issue is a collection of papers contributed by some attendees of a high-level international workshop entitled ‘Fostering International Geospatial Health Research Collaborations: Challenges and Opportunities.’ The workshop was held at the Chinese University of Hong Kong (CUHK) during 16–18 June 2014. The organizers included the International Association of Chinese Professionals in Geographic Information Sciences (CPGIS), the Association of American Geographers (AAG), the CUHK, the University of Hong Kong and the Hong Kong Polytechnic University (HKPU).

The overarching goal of the workshop is to provide a review/overview of recent developments in geospatial health research and its future directions, as well as to foster international collaboration. During the period of 3 days, scholars from universities, research institutes, governmental agencies and nongovernmental organizations in North America, Europe and Asia gave about 20 invited presentations and participated in an intensive open discussion meeting. The nine papers included in this special issue are representative of some major discussions that took place in the workshops.

From an application perspective, geospatial health research can be generally classified into two broad areas: studies on disease and well-being of humans (including physical, mental, and behavioural aspects), which can be generally referred to as spatial epidemiology; and studies about healthcare services (e.g., quality and access to healthcare services). In spatial epidemiology, the focus can be on environmental health (where the environment can be physical and socioeconomic) and infectious diseases. However, the boundaries between these divisions are not clear-cut. Underlying these applications, there are also infrastructure issues and some are fairly unique to this area (e.g., data policy problem). The nine papers included in this special issue cover all these aspects.

The first three articles concern foundational challenges in geospatial health research. Michael Goodchild discusses the dichotomy of space and place and the importance of the latter in understanding human perceptions and behaviours in the context of health research. He argues that while GIS has been useful in health studies (e.g., in analysing patterns of disease, in tracking human exposures to the environment and in assessing spatial variations in health services and outcomes), its emphasis on space makes it difficult to understand human behaviours and perceptions. The paper emphasizes the need for a better understanding of place and the need for a technology that can represent, acquire, store and share the rich information about place that humans possess.

Accurate and precise location information is essential to geospatial analysis. But making personal health data available to researchers is a sensitive and challenging issue. It is often a significant bottleneck in geospatial health research, especially with regard to the replicability of research results and collaboration among researchers. Douglas Richardson, Mei-Po Kwan, George Alter and Jean McKendry review the obstacles to and potential methods for sharing georeferenced data within a growing and dynamic geospatial research community, particularly for data-intensive research across the social and environmental sciences. They then propose the development and implementation of a geospatial virtual data enclave (GVDE) methodology as an innovative and viable solution to share and archive georeferenced data while protecting the geoprivacy of research subjects.

Xun Shi and Shaowen Wang provide a helpful review of cyberGIS approaches and their application in geospatial health research. They emphasize that cyberGIS is a fruitful alternative approach when compared to traditional spatial analyses. The paper highlights several distinctive features of cyberGIS approaches in health–GIS: these approaches may greatly reduce the reliance on models or assumptions, and instead seek actual empirical evidence through data mining and computational methods; they tend to be non-parametric and tend to generate local solutions; they are scalable to high-resolution and less aggregate data; they tend to be stochastic rather than deterministic; and they are better at handling and evaluating uncertainties. The paper discussed several examples of cyberGIS approaches in health–GIS (e.g., a computational method for disaggregating areal location data).

The next three articles address specific challenges or advances in analytical methods in geospatial health research. Sara McLafferty reviews recent advances in methods for detecting spatial and spatiotemporal clusters of health and disease. Developments in four specific areas are discussed: spatial search processes, network-based methods, statistical analysis and modelling of local clusters and space–time cluster detection. The paper concludes that spatial cluster detection methods have advanced significantly in the past decade. It highlights the importance of integrating population, environmental and mobility data more fully with disease cluster detection in future research. It also emphasizes the need to incorporate process-based understandings of health behaviours and outcomes that impact spatial and social inequalities in health.

Fahui Wang and Tracy Onega propose and discuss a research framework for evaluating disparity in healthcare accessibility using the US cancer care system and its disparity as an example. The framework contains three interconnected themes: measuring disparities in access to the healthcare services or facilities; examining the pathway from accessibility to utilization of healthcare services and then to the health outcomes (e.g., cancer-specific mortality); and designing policy scenarios for minimal disparities in accessibility.

Jinfeng Wang proposes the so-called sandwich method as an alternative to the Kriging approach for interpolation when spatial autocorrelation is weak, especially due to small sample size. The sandwich mapping first stratifies the domain through minimizing variance within strata and maximizing variance between strata. It then estimates the expected value and its variance within each stratum. Finally, it transforms the values of the data strata into reporting units through areal interpolation. Sparse sampling and weak spatial autocorrelation are common problems in geospatial health research, especially in environmental health studies. The sandwich method is an innovative contribution to the methodology for dealing with this problem.

The last three articles included in the special issue address challenges and issues in research on particular health conditions. Research on the influence of the physical and social environments on human energy balance and associated health outcomes (e.g., lack of physical activity and obesity) has attracted much attention. David Berrigan and associates review this research with a focus on the United States as an example. The paper highlights four areas that call for more future research: the importance of valid and comparable data concerning behaviour across geographies; the ongoing need to identify and explore new environmental variables; the challenge of identifying the causally relevant context; and the need for stronger study designs and analytical methods. The paper emphasizes the need to strengthen international and interdisciplinary geospatial health research.

Bing Xu and Huaiyu Tian provide an update about the research on the connection between human infection with the novel avian influenza virus and live poultry markets. They argue that the sale of freshly slaughtered poultry, live poultry transportation and mixed trading of different domestic animals in the live poultry markets all provide environments conducive to genome segment reassortment, gene mutation and interspecies transmission of avian influenza virus. Modern transportation and trading systems as well as growing population and new lifestyles may all facilitate the spread of the virus. They point out that geospatial data and analysis should be able to play a major role in controlling such a spread.

Chinmoy Sarkar, Chris Webster and John Gallacher describe the UK Biobank Urban Morphometric Platform (UKBUMP), the first large database of urban morphological metrics (morphometrics) of the country that features very large sample size and high spatial resolution. The project has a half million participants spatially distributed across 22 UK cities. The database is the basis of a large-scale objective assessment of the built environment (BE), and will enable the development of BE–health modelling that has the potential to identify causal pathways from specific attributes of the BE to various complex chronic health outcomes as well as well-being, providing scientific support for decision-making in planning and intervention.

While these nine articles address different issues and challenges, they show how geographic perspectives and geospatial methods can contribute to advancing our understanding of the complex interactions between social and physical environments and health. We hope the special issue will promote further discussion and advances in geospatial health research.