Despite spending more than any other nation on medical care per person, the United States ranks behind other industrialized nations in key health performance measures. A main cause is the deep disparities in access to care and health outcomes. Federal programs such as the designations of Medically Underserved Areas/Populations and Health Professional Shortage Areas are designed to boost the number of health professionals serving these areas and to help alleviate the access problem. Their effectiveness relies first and foremost on an accurate measure of accessibility so that resources can be allocated to truly needy areas. Various measures of accessibility need to be integrated into one framework for comparison and evaluation. Optimization methods can be used to improve the distribution and supply of health care providers to maximize service coverage, minimize travel needs of patients, limit the number of facilities, and maximize health or access equality. Inequality in health care access comes at a personal and societal price, evidenced in disparities in health outcomes, including late-stage cancer diagnosis. This review surveys recent literature on the three named issues with emphasis on methodological advancements and implications for public policy.

The paper examines the geography of three street centrality indices and their correlations with various types of economic activities in Barcelona, Spain. The focus is on what type of street centrality (closeness, betweenness and straightness) is more closely associated with which type of economic activity (primary and secondary). Centralities are calculated purely on the street network by using a multiple centrality assessment model, and a kernel density estimation method is applied to both street centralities and economic activities to permit correlation analysis between them. Results indicate that street centralities are correlated with the location of economic activities and that the correlations are higher with secondary than primary activities. The research suggests that, in urban planning, central urban arterials should be conceived as the cores, not the borders, of neighbourhoods.

Many spatial analysis tasks call for the use of travel time between multiple origins and destinations, that is, O–D travel time matrix. Commercial geographical information systems (GIS) software requires the input of a well-defined road network dataset and significant efforts in implementing the task. However, road network data are often outdated, miss critical road condition details, or are expensive to acquire; and skillful usage of related software is a major obstacle for researchers without advanced training in GIS. This research develops a desktop tool for implementing the task by calling the Google Maps Application Programming Interface (API). By doing so, we are able to tap into the dynamically updated transportation network data and the routing rules maintained by Google and obtain a reliable estimate of O–D travel time matrix. The results are compared with those computed by the ArcGIS Network Analyst module to demonstrate its advantages. A case study in accessibility analysis is presented to illustrate the implications.

The short paper provides an overview on how geographic issues have become increasingly relevant to public health research and policy, particularly through the lens of geographic information systems (GIS). It covers six themes with an emphasis on methodological issues. (1) Our health-related behaviour varies across geographic settings, so should public health policy. (2) Facilities (supply) and patients (demand) in a health-care market interact with each other across geopolitical borders, and measures of health-care accessibility need to capture that. (3) Our health outcome is the result of joint effects of individual attributes and neighbourhood characteristics, and an adequate definition of neighbourhood is critical for assessing neighbourhood effect. (4) Disease rates in areas of small population are unreliable, and one effective way to mitigate the problem is to construct a larger, internally homogenous and comparable area unit. (5) Defining a scientific geographic unit for health-care market is critical for researchers, practitioners, and policy makers to evaluate health-care delivery, and GIS enables us to define the unit (e.g. primary care service areas, hospital service areas, and cancer service areas) automatically, efficiently and optimally. (6) Aside from various optimization objectives around ‘efficiency’, it is as important to plan the location and allocation of health-care resources towards maximum equality in health-care access. Case studies are cited to illustrate each theme.

In the literature various accessibility indices have been developed to assess the relative ease by which the locations of services (supply) can be reached from a residential (demand) location. In this paper we address the planning problem: how the resources can be redistributed to achieve the highest equality of accessibility to the service providers. In particular, a quadratic programming approach is used to minimize the variance of accessibility scores across demand locations by readjusting the amounts of service supplies. Two case studies—job access in Columbus, OH and primary healthcare access in Chicago, IL—are used to illustrate the method. The result suggests that in order to achieve better equality of accessibility, peripheral areas, in general, need additional supplies to compensate for their less-central locations, and some central city areas also need to add supplies to accommodate high demands by the high population density there.

Most existing point-based colocation methods are global measures (e.g., join count statistic, cross K function, and global colocation quotient). Most recently, a local indicator such as the local colocation quotient has been proposed to capture the variability of colocation across areas. Our research advances this line of work by developing a simulation-based statistical test for the local indicator of colocation quotient (LCLQ). The study applies the indicator to examine the association of land use facilities with crime patterns. Moreover, we use the street network distance in addition to the traditional Euclidean distance in defining neighbors because human activities (including facilities and crimes) usually occur along a street network. The method is applied to analyze the colocation of three types of crimes and three categories of facilities in a city in Jiangsu Province, China. The findings demonstrate the value of the proposed method in colocation analysis of crime and facilities and, in general, colocation analysis of point data.