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

<p>Abstract</p> <p>Background</p> <p>Epidemiologic 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.</p> <p>Methods</p> <p>The spatio-temporal dynamics of <it>Salmonella </it>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.</p> <p>Results</p> <p>The dynamic maps revealed that the <it>Salmonella </it>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.</p> <p>Conclusions</p> <p>Dynamic 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.</p

Visual Analytics for Epidemiologists: Understanding the Interactions Between Age, Time, and Disease with Multi-Panel Graphs

Visual analytics, a technique aiding data analysis and decision making, is a novel tool that allows for a better understanding of the context of complex systems. Public health professionals can greatly benefit from this technique since context is integral in disease monitoring and biosurveillance. We propose a graphical tool that can reveal the distribution of an outcome by time and age simultaneously.We introduce and demonstrate multi-panel (MP) graphs applied in four different settings: U.S. national influenza-associated and salmonellosis-associated hospitalizations among the older adult population (≥65 years old), 1991-2004; confirmed salmonellosis cases reported to the Massachusetts Department of Public Health for the general population, 2004-2005; and asthma-associated hospital visits for children aged 0-18 at Milwaukee Children's Hospital of Wisconsin, 1997-2006. We illustrate trends and anomalies that otherwise would be obscured by traditional visualization techniques such as case pyramids and time-series plots.MP graphs can weave together two vital dynamics--temporality and demographics--that play important roles in the distribution and spread of diseases, making these graphs a powerful tool for public health and disease biosurveillance efforts

Geographic variations and temporal trends of Salmonella-associated hospitalization in the U.S. elderly, 1991-2004: A time series analysis of the impact of HACCP regulation

<p>Abstract</p> <p>Background</p> <p>About 1.4 million <it>Salmonella </it>infections, a common food-borne illness, occur in the U.S. annually; the elderly (aged 65 or above) are most susceptible. In 1997, the USDA introduced the Pathogen Reduction and Hazard Analysis and Critical Control Points Systems (PR/HACCP) which demands regular <it>Salmonella </it>testing in various establishments processing meat products, such as broiler chickens. Impact evaluations of PR/HACCP on hospitalizations related to <it>Salmonella </it>are lacking.</p> <p>Methods</p> <p>Hospitalization records of the U.S. elderly in 1991-2004 were obtained from the Centers of Medicare and Medicaid Services. Harmonic regression analyses were performed to evaluate the long-term trends of <it>Salmonella</it>-related hospitalizations in pre- and post-HACCP periods. Seasonal characteristics of the outcome in the nine Census divisions of the contiguous U.S. were also derived and contrasted.</p> <p>Results</p> <p>Predicted rates decreased in most divisions after 1997, except South Atlantic, East South Central, and West South Central. These three divisions also demonstrated higher overall hospitalization rates, pronounced seasonal patterns, and consistent times to peak at about 32^ndto 34^thweek of the year.</p> <p>Conclusion</p> <p>The impact of HACCP was geographically different. South Atlantic, East South Central, and West South Central divisions should be targeted in further <it>Salmonella </it>preventive programs. Further research is needed to identify the best program type and timing of implementation.</p

Analysis of human immune responses in quasi-experimental settings: tutorial in biostatistics

<p>Abstract</p> <p>Background</p> <p>Human immunology is a growing field of research in which experimental, clinical, and analytical methods of many life science disciplines are utilized. Classic epidemiological study designs, including observational longitudinal birth cohort studies, offer strong potential for gaining new knowledge and insights into immune response to pathogens in humans. However, rigorous discussion of methodological issues related to designs and statistical analysis that are appropriate for longitudinal studies is lacking.</p> <p>Methods</p> <p>In this communication we address key questions of quality and validity of traditional and recently developed statistical tools applied to measures of immune responses. For this purpose we use data on humoral immune response (IR) associated with the first cryptosporidial diarrhea in a birth cohort of children residing in an urban slum in south India. The main objective is to detect the difference and derive inferences for a change in IR measured at two time points, before (pre) and after (post) an event of interest. We illustrate the use and interpretation of analytical and data visualization techniques including generalized linear and additive models, data-driven smoothing, and combinations of box-, scatter-, and needle-plots.</p> <p>Results</p> <p>We provide step-by-step instructions for conducting a thorough and relatively simple analytical investigation, describe the challenges and pitfalls, and offer practical solutions for comprehensive examination of data. We illustrate how the assumption of time irrelevance can be handled in a study with a pre-post design. We demonstrate how one can study the dynamics of IR in humans by considering the timing of response following an event of interest and seasonal fluctuation of exposure by proper alignment of time of measurements. This alignment of calendar time of measurements and a child's age at the event of interest allows us to explore interactions between IR, seasonal exposures and age at first infection.</p> <p>Conclusions</p> <p>The use of traditional statistical techniques to analyze immunological data derived from observational human studies can result in loss of important information. Detailed analysis using well-tailored techniques allows the depiction of new features of immune response to a pathogen in longitudinal studies in humans. The proposed staged approach has prominent implications for future study designs and analyses.</p

Seasonality in Human Zoonotic Enteric Diseases: A Systematic Review

BACKGROUND: Although seasonality is a defining characteristic of many infectious diseases, few studies have described and compared seasonal patterns across diseases globally, impeding our understanding of putative mechanisms. Here, we review seasonal patterns across five enteric zoonotic diseases: campylobacteriosis, salmonellosis, vero-cytotoxigenic Escherichia coli (VTEC), cryptosporidiosis and giardiasis in the context of two primary drivers of seasonality: (i) environmental effects on pathogen occurrence and pathogen-host associations and (ii) population characteristics/behaviour. METHODOLOGY/PRINCIPAL FINDINGS: We systematically reviewed published literature from 1960-2010, resulting in the review of 86 studies across the five diseases. The Gini coefficient compared temporal variations in incidence across diseases and the monthly seasonality index characterised timing of seasonal peaks. Consistent seasonal patterns across transnational boundaries, albeit with regional variations was observed. The bacterial diseases all had a distinct summer peak, with identical Gini values for campylobacteriosis and salmonellosis (0.22) and a higher index for VTEC (Gini  0.36). Cryptosporidiosis displayed a bi-modal peak with spring and summer highs and the most marked temporal variation (Gini = 0.39). Giardiasis showed a relatively small summer increase and was the least variable (Gini = 0.18). CONCLUSIONS/SIGNIFICANCE: Seasonal variation in enteric zoonotic diseases is ubiquitous, with regional variations highlighting complex environment-pathogen-host interactions. Results suggest that proximal environmental influences and host population dynamics, together with distal, longer-term climatic variability could have important direct and indirect consequences for future enteric disease risk. Additional understanding of the concerted influence of these factors on disease patterns may improve assessment and prediction of enteric disease burden in temperate, developed countries

Impact on diarrhoeal illness of a community educational intervention to improve drinking water quality in rural communities in Puerto Rico

<p>Abstract</p> <p>Background</p> <p>Waterborne disease is a major risk for small water supplies in rural settings. This study was done to assess the impact of an educational intervention designed to improve water quality and estimate the contribution of water to the incidence of diarrhoeal disease in poor rural communities in Puerto Rico a two-part study was undertaken.</p> <p>Methods</p> <p>An educational intervention was delivered to communities relying on community water supplies. This intervention consisted of student operators and administrators supervising and assisting community members who voluntarily "operate" these systems. These voluntary operators had no previous training and were principally concerned with seeing that some water was delivered. The quality of that water was not something they either understood or addressed. The impact of this intervention was measured through water sampling for standard bacteriological indicators and a frank pathogen. In addition, face-to-face epidemiological studies designed to determine the base-line occurrence of diarrhoeal disease in the communities were conducted. Some 15 months after the intervention a further epidemiological study was conducted in both the intervention communities and in control communities that had not received any intervention.</p> <p>Results</p> <p>Diarrhoeal illness rates over a four week period prior to the intervention were 3.5%. <it>Salmonella </it>was isolated from all of 5 distributed samples prior to intervention and from only 2 of 12 samples after the intervention. In the 15 months follow-up study, illness rates were lower in the intervention compared to control communities (2.5% <it>vs </it>3.6%%) (RR = 0.70, 95%CI 0.43, 1.15), though this was not statistically significant. However, in the final Poisson regression model living in an intervention system (RR = 0.318; 95%CI 0.137 - 0.739) and owning a dog (RR = 0.597, 95%CI 0.145 - 0.962) was negatively associated with illness. Whilst size of system (RR = 1.006, 95%CI 1.001 - 1.010) and reporting problems with sewage system (RR = 2.973, 95%CI 1.539 - 5.744) were positively associated with illness.</p> <p>Conclusions</p> <p>Educational interventions directed both at identified individuals and the community in general in small communities with poor water quality is a way of giving communities the skills and knowledge to manage their own drinking water quality. This may also have important and sustainable health benefits, though further research preferably using a randomised control trial design is needed.</p

The effectiveness of public health interventions to reduce the health impact of climate change:a systematic review of systematic reviews

Climate change is likely to be one of the most important threats to public health in the coming years. Yet despite the large number of papers considering the health impact of climate change, few have considered what public health interventions may be of most value in reducing the disease burden. We aimed to evaluate the effectiveness of public health interventions to reduce the disease burden of high priority climate sensitive diseases