Dataset Information

Seasonal synchronization of foodborne outbreaks in the United States, 1996-2017.

ABSTRACT: Modern food systems represent complex dynamic networks vulnerable to foodborne infectious outbreaks difficult to track and control. Seasonal co-occurrences (alignment of seasonal peaks) and synchronization (similarity of seasonal patterns) of infections are noted, yet rarely explored due to their complexity and methodological limitations. We proposed a systematic approach to evaluate the co-occurrence of seasonal peaks using a combination of L-moments, seasonality characteristics such as the timing (phase) and intensity (amplitude) of peaks, and three metrics of serial, phase-phase, and phase-amplitude synchronization. We used public records on counts of nine foodborne infections abstracted from CDC's FoodNet Fast online platform for the US and ten representative states from 1996 to 2017 (264 months). Based on annualized and trend-adjusted Negative Binomial Harmonic Regression (NBHR) models augmented with the ?-method, we determined that seasonal peaks of Campylobacter, Salmonella, and Shiga toxin-producing Escherichia Coli (STEC) were tightly clustered in late-July at the national and state levels. Phase-phase synchronization was observed between Cryptosporidium and Shigella, Listeria, and Salmonella (??=?0.51, 0.51, 0.46; p?

SUBMITTER: Simpson RB

PROVIDER: S-EPMC7562704 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Seasonal synchronization of foodborne outbreaks in the United States, 1996-2017.

Simpson Ryan B RB Zhou Bingjie B Naumova Elena N EN

Scientific reports 20201015 1

Modern food systems represent complex dynamic networks vulnerable to foodborne infectious outbreaks difficult to track and control. Seasonal co-occurrences (alignment of seasonal peaks) and synchronization (similarity of seasonal patterns) of infections are noted, yet rarely explored due to their complexity and methodological limitations. We proposed a systematic approach to evaluate the co-occurrence of seasonal peaks using a combination of L-moments, seasonality characteristics such as the tim ...[more]

PMID: 33060743

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Project description:BackgroundIn temperate regions, influenza epidemics occur annually with the highest activity occurring during the winter months. While seasonal dynamics of the influenza virus, such as time of onset and circulating strains, are well documented by the Centers for Disease Control and Prevention Influenza Surveillance System, an accurate prediction of timing, magnitude, and composition of circulating strains of seasonal influenza remains elusive. To facilitate public health preparedness for seasonal influenza and to obtain better insights into the spatiotemporal behavior of emerging strains, it is important to develop measurable characteristics of seasonal oscillation and to quantify the relationships between those parameters on a spatial scale. The objectives of our research were to examine the seasonality of influenza on a national and state level as well as the relationship between peak timing and intensity of influenza in the United States older adult population.Methodology/principal findingsA total of 248,889 hospitalization records were extracted from the Centers for Medicare and Medicaid Services for the influenza seasons 1991-2004. Harmonic regression models were used to quantify the peak timing and absolute intensity for each of the 48 contiguous states and Washington, DC. We found that individual influenza seasons showed spatial synchrony with consistent late or early timing occurring across all 48 states during each influenza season in comparison to the overall average. On a national level, seasons that had an earlier peak also had higher rates of influenza (r(s) = -0.5). We demonstrated a spatial trend in peak timing of influenza; western states such as Nevada, Utah, and California peaked earlier and New England States such as Rhode Island, Maine, and New Hampshire peaked later.Conclusions/significanceOur findings suggest that a systematic description of influenza seasonal patterns is a valuable tool for disease surveillance and can facilitate strategies for prevention of severe disease in the vulnerable, older adult population.

Project description:Each year foodborne diseases (FBD) affect approximately 1 in 6 Americans, resulting in 128 000 hospitalizations and 3000 deaths. Decreasing resources impact the ability of public health officials to identify, respond to, and control FBD outbreaks. Geographically dispersed outbreaks necessitate multijurisdictional coordination across all levels of the public health system. Rapid response depends on rapid detection.Targeted resources were provided to state and local health departments to improve completeness and timeliness of laboratory, epidemiology, and environmental health (EH) activities for FBD surveillance and outbreak response.Foodborne Disease Centers for Outbreak Response Enhancement (FoodCORE) centers, selected through competitive award, implemented work plans designed to make outbreak response more complete and faster in their jurisdiction. Performance metrics were developed and used to evaluate the impact and effectiveness of activities.Departments of Health in Connecticut, New York City, Ohio, South Carolina, Tennessee, Utah, and Wisconsin.From the first year (Y1) of the program in October 2010 to the end of the second year (Y2) in December 2012, the centers completed molecular subtyping for a higher proportion of Salmonella, Shiga toxin-producing Escherichia coli, and Listeria (SSL) isolates (86% vs 98%) and reduced the average time to complete testing from a median of 8 to 4 days. The centers attempted epidemiologic interviews with more SSL case-patients (93% vs 99%), and the average time to attempt interviews was reduced from a median of 4 to 2 days. During Y2, nearly 200 EH assessments were conducted. FoodCORE centers began documenting model practices such as streamlining and standardizing case-patient interviewing.Centers used targeted resources and process evaluation to implement and document practices that improve the completeness and timeliness of FBD surveillance and outbreak response activities in several public health settings. FoodCORE strategies and model practices could be replicated in other jurisdictions to improve FBD response.

Dataset Information

Seasonal synchronization of foodborne outbreaks in the United States, 1996-2017.

Publications

Seasonal synchronization of foodborne outbreaks in the United States, 1996-2017.

Similar Datasets

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