Public/Population Health

In response to the rise in obesity rates and obesity-related healthcare costs over the past several decades, numerous organizations have implemented obesity prevention programs. The current method for evaluating the success of these programs relies largely on annual surveys such as the Centers for Disease Control and Prevention’s Behavioral Risk Factor Surveillance System (BRFSS) which provides state-by-state obesity rates. As a result, public health policy makers lack the fine-grained evaluation data needed to make timely decisions about the success of their obesity prevention programs and to allocate resources more efficiently.

Objective

We developed Persistent Health Assessment Tools, PHAT, to equip public health policy makers with more precise tools and timely information for measuring the success of obesity prevention programs. PHAT monitors social media to supplement traditional surveillance by making real-time estimates based on observations of obesity-relevant behaviors.

 

Meat inspection data are routinely collected over several years providing the possibility to use historical data for constructing a baseline model defining the expected normal behaviour of the indicator monitored. In countries in which the reporting of data is compulsory (e.g. in the EU), coverage of the majority of the slaughtered population is ensured.

Objective

We evaluate the performance of the improved Farrington algorithm for the detection of simulated outbreaks in meat inspection data.

 

Bovine cysticercosis is a zoonotic foodborne disease caused by Taenia saginata involving cattle as the intermediate host and humans as the final host. Humans are infected by eating raw or undercooked meat of infected cattle. Cattle are infected after grazing on pasture infected by human feces. Disease detection in cattle is performed during post-mortem meat inspection at the slaughterhouse through the identification of cysts in muscle tissue. Cysts develop from a viable stage to a degenerated stage in one to nine months, both stages being visible and distinguishable in cattle muscle. Due to the slow development of cysts and the complexity of cattle movements (up to ten different herds from birth to slaughter in France), there is a strong bias to consider the last farm location before slaughter as the location of infection.

Objective

Spatial analysis of infectious diseases enables identification of areas at high risk for infection, a useful tool for implementation of risk-based surveillance. For chronic diseases, the period between infection and detection can be long and when animal movements are important, identifying the place of infection is difficult. The objective of this study is to propose an innovative approach for spatial analysis that takes into account uncertainty regarding the location where animals were infected. An animal-herd-level weighted analysis was used and applied to bovine cysticercosis in France.

 

The Affordable Care Act (ACA) was promoted with two goals: expanding health insurance coverage and reducing healthcare costs. Expanded coverage is expected to partially reduce costs. Emergency department (ED) visits are costlier than comparable primary care physician visits. If uninsured patients use the local ED more often than insured patients with comparable conditions, insuring them may change usage and lower costs. Some reports in the literature do not fit this model of ED usage. In one study, nonurgent ED visits were mainly the result of patient uncertainty about the severity of their condition. While trained medical personnel distinguished urgent and nonurgent cases after the fact, initial presentations were similar. In Oregon, an expansion of Medicaid increased health insurance coverage; ED usage increased rather than decreased. Thus, the motivating narrative about insurance coverage and ED usage informing the ACA may not be the complete story. Reduction of hospital readmissions is also expected to cut costs under the ACA. Hospital process improvements are expected to realize this reduction. Recently it was reported that up to 60% of hospital readmissions are predicted by patient demographics, raising questions about how much control a hospital has over its readmission rate. This research will examine whether data collected via syndromic surveillance can corroborate these findings.

Objective

To determine if data collected for syndromic surveillance can inform policy questions related to emergency department utilization and inpatient readmission.

 

Along with commensurate funding, an increased emphasis on syndromic surveillance systems occurred post September 11, 2001 and the subsequent anthrax attacks. Since then, many syndromic surveillance systems have evolved and have ever-increasing functionality and visualization tools. As outbreak detection using these systems has demonstrated an equivocal track record, epidemiologists have sought out other interesting and unique uses for these systems. Over the numerous years of the International Society for Disease Surveillance (ISDS) conference, many of these studies have been presented, however, there has been a dearth of discussion related to how these systems should be used on a routine basis. As the initial goal of these systems was to provide a near real-time disease surveillance tool, the question of how to most effectively conduct this type of routine surveillance is paramount.

Objective

To discuss how various emergency department based syndromic surveillance systems from across the country and world are being used and to develop best practices for moving forward.