Geospatial Analysis

Seasonality has a major effect on the spatial and temporal (i.e. spatiotemporal) dynamics of natural systems and their populations (1). Although the seasonality of influenza in temperate countries is widely recognized, inter-regional spread of influenza in the United States has not been well characterized.

Objective

To study the seasonality of influenza in the United States between 1972 and 2007 through the evaluation of the timing, velocity, and spatial spread of annual epidemic cycles.

The global health threat of highly pathogenic avian influenza H5N1 has been increasing rapidly in the world since the crosscountry outbreaks during 2003-04. In South and East Asia, the human influenza A (H3N2) was proved to be seeded there with occurring annual cases. Intensive surveillance of influenza is the most urgent strategy to avoid large-scale epidemics and high case fatality rates. Sentinel physicians’ surveillance is the most sensitive mechanism to reflect the health status of community people. In France and Japan, comprehensive sentinel-physician surveillance systems were set up and geographic information system was applied to display the diffusion patterns of influenza-like illness. Kriging method, which was used to display the diffusion, was hard to monitor the multiple temporal and spatial dimensions in one map. Therefore, Ring maps were proposed to overcome this difficulty.

Objective

This study describes a visualizing ring maps to monitor the alert levels of Influenza-like illness, and provide possible insights of temporal and spatial diffusion patterns in epidemic and nonepidemic seasons.

Geographic visualization methods allow analysts to visually discover clusters in multivariate, spatially-referenced data. Computational and statistical cluster detection techniques can automatically detect spatial clusters of high values of a variable of interest. The authors propose that the two approaches can be complementary; and present an integration of the GeoViz Toolkit and Proclude software suites as proof-of-concept.

To inform health professionals and the public directly about real-time utilization of local Emergency Departments for respiratory and gastrointestinal illness to enable enhanced communication and collaboration between Public Health and health care workers.

The inception of syndromic surveillance has spawned a great deal of research into emergency department chief complaint data. In addition to its use as an early warning system of a bioterror or outbreak event, many health departments are attempting to maximize the utility of the information to augment chronic and communicable disease surveillance. Hence, it can be used to enhance the traditional methods of surveillance. Using syndromic data to describe what could be the normal for a geographic area may be useful in monitoring a population for disease trends. Prevention efforts could be concentrated during a particular time of year. In addition, geospatial shifts in directional trends may indicate an unusual occurrence related to the utilization of emergency department services.

Objective

To describe the geographical mean as well as the directional trends of syndromes for the District of Columbia using temporal and geospatial analyses.

We present the EpiEarly, EpiGrid, and EpiCast tools for mechanistically-based biological decision support. The range of tools covers coarse-, medium-, and fine-grained models. The coarse-grained, aggregated time-series only data tool (EpiEarly) provides a statistic quantifying epidemic growth potential and associated uncertainties. The medium grained, geographically-resolved model (EpiGrid) is based on differential equation type simulations of disease and epidemic progression in the presence of various human interventions geared toward understanding the role of infection control, early vs. late diagnosis, vaccination, etc. in outbreak control. A fine-grained hybrid-agent epidemic model (EpiCast) with diurnal agent travel and contagion allows the analysis of the importance of contact-networks, travel, and detailed intervention strategies for the control of outbreaks and epidemics.

Objective:

We will demonstrate tools that allow mechanistic contraints on disease progression and epidemic spread to play off against interventions, mitigation, and control measures. The fundamental mechanisms of disease progression and epidemic spread provide important constraints on interpreting changing epidemic cases counts with time and geography in the context of on-going interventions, mitigations, and controls. Models such as these that account for the effects of human actions can also allow evaluation of the importance of categories of epidemic and disease controls.

There have been a number of non-infectious intoxication outbreaks reported in North American companion animal populations over the last decade. The most devastating outbreak to date was the 2007 melamine pet food contamination incident which affected thousands of pet dogs and cats across North America. Despite these events, there have been limited efforts to conduct real-time surveillance of toxicological exposures in companion animals nationally, and there is no central registry for the reporting of toxicological events in companion animals in the United States. However, there are a number of poison control centers in the US that collect extensive data on toxicological exposures in companion animals, one of which is the Animal Poison Control Center (APCC) operated by the American Society for the Prevention of Cruelty to Animals (ASPCA). Each year the APCC receives thousands of reports of suspected animal poisonings and collects extensive information from each case, including location of caller, exposure history, diagnostic findings, and outcome. The records from each case are subsequently entered and stored in the AnTox database, an electronic medical record database maintained by the APCC. Therefore, the AnTox database represents a novel source of data for real-time surveillance of toxicological events in companion animals, and may be used for surveillance of pet food and environmental contamination events that may negatively impact both veterinary and human health.

Objective:

Our objective was to assess the suitability of the data collected by the Animal Poison Control Center, run by the American Society for the Prevention of Cruelty to Animals, for the surveillance of toxicological exposures in companion animals in the United States.