Recent health threats, such as the SARS, H1N1, and ebola pandemics, have stimulated great interest in network models to study the transmission of communicable diseases through human interaction and mobility. Most current network models have focused on an individual-centric perspective where individuals are represented as nodes and the interactions among them as edges. Few of these models are concerned with the discovery of the spatial patterns and dynamics of epidemics. We propose a location-centric, transmission network approach, in which nodes denote locations and edges denote possible disease transmissions between locations. We then identify the dynamics of transmission flows, the dynamics of critical locations, and the spatial–temporal extent of transmission pathways to assess the impact of these spatial dynamics on the evolution of an epidemic. Results show that transmission flows shift from elementary schools to middle schools and finally universities and professional schools at different phases of an epidemic. Critical locations, identified using network analysis, are responsible for the upsurge in transmission flows during the peaks of the epidemic. The length of transmission pathways shows a power law distribution and their spatial extent is rather small. Insights gained from this study will help devise spatially sensitive strategies to control communicable diseases.

Family doctors serve as the initial contact for individuals seeking regular medical service like routine physical exam, diagnosis, and treatment of illness. Nonetheless, immigrant population who do not speak the official language usually prefers receiving healthcare in their own mother tongues. Past studies have focused on exploring accessibility to family doctors speaking Mandarin Chinese, which is not mutually intelligible with another major Chinese language called Cantonese. Despite the significant number of Cantonese‐speaking population in the Greater Toronto Area (GTA) and a recent wave of immigration from Hong Kong, China (hereafter “Hong Kong”) to Canada, little knowledge has been obtained regarding the geographic accessibility to Cantonese‐speaking family doctors. This study seeks to fill the knowledge gap of spatial accessibility to Cantonese‐speaking family doctors in the GTA by using the two‐step floating catchment area (2SFCA) method. By considering the vulnerability in terms of spatial accessibility and attractiveness to the new immigrants from Hong Kong, we have unveiled that more than 90% of neighbourhoods, with below‐median accessibility scores across all five thresholds yet high likelihood of attracting new Hong Kong immigrants, are clustered within four lower‐tier municipalities of Markham, Toronto, Richmond Hill, and Vaughan. This study not only sheds lights on the knowledge gap but also provides timely guidance in formulating public health policies in light of the incoming Cantonese‐speaking immigrants from Hong Kong.

Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of transmission-driving factors have been considered in these models. Because of the lack of individual-scaled validations, the effectiveness of factors at their intended scale is not substantiated. These gaps significantly undermine the efficacy of the models in assessing the vulnerability of individuals, communities, and urban society. The objectives of this study are twofold. First, we aim to model and, most importantly, validate influenza-like illness (ILI) symptoms at the individual scale based on four sets of transmission-driving factors pertinent to home–work space, service space, ambient environment, and demographics. The effort is supported by an ensemble approach. For the second objective, we investigate the effectiveness of the factor sets through an impact analysis. The validation accuracy reaches 73.2–95.1%. The validation substantiates the effectiveness of factors pertinent to urban spaces and unveils the underlying mechanism that connects urban spaces and population health. With more fine-scaled health data becoming available, the findings of this study may see increasing value in informing policies that improve population health and urban livability.