Application of geographic information systems and simulation modelling to dental public health: Where next?

Abstract

Public health research in dentistry has used geographic information systems since the 1960s. Since then, the methods used in the field have matured, moving beyond simple spatial associations to the use of complex spatial statistics and, on occasions, simulation modelling. Many analyses are often descriptive in nature; however, and the use of more advanced spatial simulation methods within dental public health remains rare, despite the potential they offer the field. This review introduces a new approach to geographical analysis of oral health outcomes in neighbourhoods and small area geographies through two novel simulation methods—spatial microsimulation and agent‐based modelling. Spatial microsimulation is a population synthesis technique, used to combine survey data with Census population totals to create representative individual‐level population datasets, allowing for the use of individual‐level data previously unavailable at small spatial scales. Agent‐based models are computer simulations capable of capturing interactions and feedback mechanisms, both of which are key to understanding health outcomes. Due to these dynamic and interactive processes, the method has an advantage over traditional statistical techniques such as regression analysis, which often isolate elements from each other when testing for statistical significance. This article discusses the current state of spatial analysis within the dental public health field, before reviewing each of the methods, their applications, as well as their advantages and limitations. Directions and topics for future research are also discussed, before addressing the potential to combine the two methods in order to further utilize their advantages. Overall, this review highlights the promise these methods offer, not just for making methodological advances, but also for adding to our ability to test and better understand theoretical concepts and pathways.

Neighborhood Contexts and Oral Health Outcomes in a Pediatric Population: An Exploratory Study

“…Geographic Information System (GIS) enables gathering, managing, visualizing, and analyzing neighborhood socioeconomic, demographic as well as health outcomes data in an integrated framework [10,18]. There are several methods of spatial analysis and GIS, which have been used with varying degrees of success in dentistry [19]. The major use of GIS techniques in dentistry has been in visualizing the spatial distribution of disease [20].…”

Estimating Health over Space and Time: A Review of Spatial Microsimulation Applied to Public Health

“…Other health behaviours or conditions identified in the review included problem gambling [18], mental health and alcohol consumption [19] and combinations of health outcomes [20][21][22][23]. Dental health [24], diabetes [25] and mortality [26] are more recent topics that were modelled. Spatial microsimulation for resource allocation, with the example of maternity services in England [27], or estimating the impacts of policies on health [28] were more unusual applications of this method for public health interests.…”

Geographic information systems in spatial epidemiology: Unveiling new horizons in dental public health

“…Health service utilization data is now available in the digital form as medical records or hospital discharge data sets, allowing to gauge the health service utilization patterns and access to health care. [ 32 33 34 ]…”