Dynamic maps: a visual-analytic methodology for exploring spatio-temporal disease patterns

Abstract

BackgroundEpidemiologic studies are often confounded by the human and environmental interactions that are complex and dynamic spatio-temporal processes. Hence, it is difficult to discover nuances in the data and generate pertinent hypotheses. Dynamic mapping, a method to simultaneously visualize temporal and spatial information, was introduced to elucidate such complexities. A conceptual framework for dynamic mapping regarding principles and implementation methods was proposed.MethodsThe spatio-temporal dynamics of Salmonella infections for 2002 in the U.S. elderly were depicted via dynamic mapping. Hospitalization records were obtained from the Centers of Medicare and Medicaid Services. To visualize the spatial relationship, hospitalization rates were computed and superimposed onto maps of environmental exposure factors including livestock densities and ambient temperatures. To visualize the temporal relationship, the resultant maps were composed into a movie.ResultsThe dynamic maps revealed that the Salmonella infections peaked at specific spatio-temporal loci: more clusters were observed in the summer months and higher density of such clusters in the South. The peaks were reached when the average temperatures were greater than 83.4°F (28.6°C). Although the relationship of salmonellosis rates and occurrence of temperature anomalies was non-uniform, a strong synchronization was found between high broiler chicken sales and dense clusters of cases in the summer.ConclusionsDynamic mapping is a practical visual-analytic technique for public health practitioners and has an outstanding potential in providing insights into spatio-temporal processes such as revealing outbreak origins, percolation and travelling waves of the diseases, peak timing of seasonal outbreaks, and persistence of disease clusters.

Exploring Risk Factors of Recall-Associated Foodborne Disease Outbreaks in the United States, 2009–2019

“…Investigations of seasonality can also improve emergency and incident response coordination and enhance early warnings of foodborne outbreaks. In our prior work, we demonstrated stable seasonal patterns of foodborne illnesses in the United States and how these patterns can be examined and understood visually [8,27,46,47]. Across all studies, outbreak peak timing ranged from early July to late August for most enteric infections.…”

Dynamic mapping of cholera outbreak during the Yemeni Civil War, 2016–2019

“…Movie 2 provides a dynamic map of governorate-level rates over the 208-week study period. With this dynamic map, we provided the desired data visualization experience using an optimized frame speed of 1 second per frame to give enough time for the viewer to identify clusters of infections, store this pattern into short-term memory, and compare older clusters to newer clusters when examining the following frame [ 25 ]. We also provided an interactive user interface to enable viewers to replay frames at their discretion using a sliding calendar bar that traced the national time series of cholera rates.…”

“…We standardized mapping properties to ease the examination of spatiotemporal disease dynamics including when outbreaks occurred, how long they persisted, and differences by governorate [ 25 ]. For example, we converted daily and monthly records into weekly estimates to reduce ‘noise’ and sporadic fluctuations typical for daily records while preventing the over-smoothing typical for monthly records.…”

Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review

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“…Disease mapping, hypotheses generation, clinical decision making, and knowledge discovery [ 66 , 77 , 78 ].…”