Tara Cooper

A Multistate Outbreak of Salmonella enterica Serotype Newport Infection Linked to Mango Consumption: Impact of Water-Dip Disinfestation Technology

Fresh produce increasingly is recognized as an important source of salmonellosis in the United States. In December 1999, the Centers for Disease Control and Prevention detected a nationwide increase in Salmonella serotype Newport (SN) infections that had occurred during the previous month. SN isolates recovered from patients in this cluster had indistinguishable pulsed-field gel electrophoresis (PFGE) patterns (which identified the outbreak strain), suggesting a common source. Seventy-eight patients from 13 states were infected with the outbreak strain. Fifteen patients were hospitalized; 2 died. Among 28 patients enrolled in the matched case-control study, 14 (50%) reported they ate mangoes in the 5 days before illness onset, compared with 4 (10%) of the control subjects during the same period (matched odds ratio, 21.6; 95% confidence interval, 3.53- infinity; P=.0001). Traceback of the implicated mangoes led to a single Brazilian farm, where we identified hot water treatment as a possible point of contamination; this is a relatively new process to prevent importation of an agricultural pest, the Mediterranean fruit fly. This is the first reported outbreak of salmonellosis implicating mangoes. PFGE was critical to the timely recognition of this nationwide outbreak. This outbreak highlights the potential global health impact of foodborne diseases and newly implemented food processes.

Patients hospitalized with laboratory-confirmed influenza during the 2010-2011 influenza season: exploring disease severity by virus type and subtype

BACKGROUND  The 2010-2011 influenza season was dominated by influenza A(H3N2) virus, but influenza A(H1N1) pdm09 (pH1N1) and B viruses cocirculated. This provided an opportunity to explore within-season predictors of severity among hospitalized patients, avoiding biases associated with season-to-season differences in strain virulence, population immunity, and healthcare seeking. METHODS  Population-based, laboratory-confirmed influenza hospitalization surveillance data were used to examine the association between virus type/subtype and outcomes in children and adults. Multivariable analysis explored virus type/subtype, prompt antiviral treatment, medical conditions, and age as predictors for severity (intensive care unit admission or death). RESULTS  In children, pH1N1 (adjusted odds ratio [aOR], 2.19; 95% confidence interval [CI], 1.11-4.3), chronic metabolic disease (aOR, 5.23; 95% CI, 1.74-15.69), and neuromuscular disorder (aOR, 4.84; 95% CI, 2.02-11.58) were independently associated with severity. In adults, independent predictors were pH1N1 (aOR, 2.21; 95% CI, 1.66-2.94), chronic lung disease (aOR, 1.46, 95% CI, 1.12-1.89), and neuromuscular disorder (aOR, 1.68; 95% CI, 1.11-2.52).Antiviral treatment reduced the odds of severity among adults (aOR, 0.47; 95% CI, .33-.68). CONCLUSIONS  During the 2010-2011 season, pH1N1 caused more severe disease than H3N2 or B in hospitalized patients. Underlying medical conditions increased severity despite virus strain. Antiviral treatment reduced severity among adults. Our findings underscore the importance of influenza prevention.

A latent class model to identify city/town chronic disease patterns.

OBJECTIVE Most departments of health grapple with how to most effectively allocate resources to address chronic diseases. We adapted a model created by Massachusetts to create customized city/town profiles in order to identify the patterns of chronic disease among 39 cities/towns in Rhode Island. METHODS We used four data sources to identify 20 indicators of four domains: demographics and socioeconomic status; health behaviors and chronic diseases prevalence; no regular provider and non-emergent emergency department visits; and chronic disease-related hospitalizations. A latent class model was used to group cities/towns into distinct latent class memberships based on similar patterns of indicators. Data were analyzed in 2014. RESULTS The latent class model differentiated three distinct classes of city/town, reflecting three levels of economic and health indicators. CONCLUSIONS Our model was a simplified version of one constructed by Massachusetts that larger states can also use to understand chronic disease patterns among cities/towns. Chronic disease programs and policies can use the findings to direct resources toward targets not always identified by more traditional analyses.

Disparities in Health Risk Behaviors and Health Conditions Among Rhode Island Sexual Minority and Unsure High School Students

BACKGROUND Sexual minority students have higher risk for health-related behaviors. We examined 5 domains including 34 health risk behaviors and health conditions among sexual minorities and unsure students in Rhode Island. We also included sexual contact of heterosexually identified students to capture heterosexually identified students who may be considered sexual minorities by their behavior. METHODS We used the 2007-2015 Rhode Island Youth Risk Behavior Survey data (N = 14,264). We categorized students into 4 groups: students self-identified as heterosexual and reported no sexual contact with same sex only or both sexes (group 1); self-identified as heterosexual and reported sexual contact with same sex only or both sexes (group 2); self-identified as lesbian, gay, bisexual (group 3); and responded as unsure (group 4). We used multivariable adjusted logistic regression analyses to evaluate associations of sexual minority and unsure students with 34 health risk behaviors and health conditions accounting for complex sampling design. RESULTS Students in groups 2-4 were more likely to engage in health-risk behaviors including violent behaviors, attempted suicide, substance use, and no physical activity than their peers. CONCLUSIONS As sexual minority youth continue to report higher rates of health-related risk behaviors, targeted evidence-based prevention approaches must focus on reducing these risk behaviors among those youth.

State-Level Surveillance of Underinsurance and Health Care-Related Financial Burden

Background: The Affordable Care Act (ACA) has reduced uninsurance, but underinsurance, health care-related financial burden, and dental uninsurance may not follow suit. Underinsurance is associated with reduced access to care, household debt, and bankruptcy but has been difficult to track without economic data. Methods: We used readily available state-level survey data to build a model that states can adopt to implement surveillance over underinsurance and health care-related financial burden, as well as assess related disparities and health profiles. Results: The state prevalence of underinsurance and dental uninsurance did not change in the first year of the ACAs individual mandate. Underinsurance was associated with poorer health-related quality-of-life measures: compared with the fully insured, underinsured adults had an adjusted odds ratio of 2.40 (95% CI, 1.71-3.38) of fair or poor general health. Conclusion: Tracking underinsurance and medical debt can help public health and health care access stakeholders evaluate which mechanisms (deductibles, co-pays, uncovered services, or is proportionately priced health care services and products) are barriers to care and improved health outcomes.