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

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

Snowbirds and infection--new phenomena in pneumonia and influenza hospitalizations from winter migration of older adults: A spatiotemporal analysis

Abstract Background Despite advances in surveillance and prevention, pneumonia and influenza (P&I) remain among the leading causes of mortality in the United States. Elderly adults experience the most severe morbidity from influenza-associated diseases, and have the highest rates of seasonal migration within the U.S. compared to other subpopulations. The objective of this study is to assess spatiotemporal patterns in influenza-associated hospitalizations in the elderly, by time, geography, and intensity of P&I. Given the high seasonal migration of individuals to Florida, this state was examined more closely using harmonic regression to assess spatial and temporal patterns of P&I hospitalizations by state of residence. Methods Data containing all Medicare-eligible hospitalizations in the United States for 1991-2006 with P&I (ICD-9-CM codes 480-487) were abstracted for the 65+ population. Hospitalizations were classified by state of residence, provider state, and date of admissions, specifically comparing those admitted between October and March to those admitted between April and September. We then compared the hospitalization profile data of Florida residents with that of out-of-state residents by state of primary residence and time of year (in-season or out-of-season). Results We observed distinct seasonal patterns of nonresident P&I hospitalizations, especially comparing typical winter destination states, such as California, Arizona, Texas, and Florida, to other states. Although most other states generally experienced a higher proportion of non-resident P&I during the summer months (April-September), these states had higher nonresident P&I during the traditional peak influenza season (October-March). Conclusions This study is among the first to quantify spatiotemporal P&I hospitalization patterns in the elderly, focusing on the change of patterns that are possibly due to seasonal population migration. Understanding migration and influenza-associated disease patterns in this vulnerable population is critical to prepare for and potentially prevent influenza outbreaks in this vulnerable population.</p

Switching to Versus Addition of Incretin-Based Drugs Among Patients With Type 2 Diabetes Taking Sodium-Glucose Cotransporter-2 Inhibitors.

Background Evidence is limited in comparing treatment modification by substitution or add-on of glucose-lowering medications in patients with type 2 diabetes. This observational study aims to compare switching versus add-on of incretin-based drugs among patients with type 2 diabetes on background sodium-glucose cotransporter-2 inhibitors (SGLT2i). Methods and Results This population-based, retrospective cohort study was conducted using the IQVIA Medical Research Data, including adults with type 2 diabetes on background SGLT2i from 2005 to 2020. New users of incretin-based drugs were allocated into the "Switch" group if they had discontinued SGLT2i treatment, or the "Add-on" group if their background SGLT2i was continued. Baseline characteristics of patients were balanced between groups. Study outcomes were all-cause mortality, cardiovascular diseases, kidney diseases, hypoglycemia, and ketoacidosis. Patients were observed from the index date of initiating incretin-based drugs until the earliest of an outcome event, death, or data cut-off date. Changes in anthropometric and metabolic parameters were also compared between groups from baseline to 12-month follow-up. A total of 2888 patients were included, classified into "Switch" (n=1461) or "Add-on" group (n=1427). Median follow-up was 18 months with 5183 person-years. Overall, no significant differences in the risks of study outcomes were observed between groups; however, patients in the "Add-on" group achieved significantly greater reductions in glycated hemoglobin, weight, percentage weight loss, and systolic blood pressure than their "Switch" counterparts. Conclusions Initiating incretin-based drugs as add-on among patients with type 2 diabetes on background SGLT2i was associated with risks of clinical end points comparable to switching treatments, in addition to better glycemic and weight control observed with the combination approach