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Infectious Disease

Particular family of tandem repeats, such as Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) found in a wide range of prokaryotic genomes. CRISPRs consist of highly conserved repeats interspaced with non-repetitive elements or "spacers" usually of viral origin. In the Yersinia pestis genome, three CRISPR elements YPa, YPb and YPc are found. The distribution of spacers and their arrays in Y. pestis strains is region and focus specific and can provide important information for genotyping and evolutionary research of bacteria.

Objective: The purpose of our study was CRISPR-based analysis of Y. pestis isolates from Georgia and neighboring countries.

Submitted by elamb on

Although cases of acute HAV have declined in recent years, elevated numbers of HAV infections began to be reported by California and Michigan in the fall of 2016.1,2 Since this time, associated outbreaks have been reported in 9 additional states (Arizona, Utah, Kentucky, Missouri, Tennessee, Indiana, Ohio, Arkansas, and West Virginia).3 No common source of food, beverages or drugs have been identified and transmission appears to be primarily person-to-person with high-risk individuals including people experiencing homelessness, those who use illicit drugs and their close direct contacts. In June 2018, CDC issued a Health Alert Network Advisory providing additional guidance on identification and prevention of HAV and updates on the outbreaks.4 This prompted our office to more closely review our HAV surveillance, to identify Veterans who may be part of these outbreaks, and assess risk factors and outcomes of HAV infection.

Objective: To conduct surveillance for acute Hepatitis A virus (HAV) infections in Veterans from states reporting outbreaks among high-risk individuals beginning in fiscal year (FY) 2017.

Submitted by elamb on

Since hepatitis A vaccination became widely recommended in the US in the mid-1990's, rates of acute hepatitis A virus (HAV) infection have steadily declined, however, since 2011, incidence of new cases of HAV appears to be increasing1, often linked with foodborne outbreaks and socio-economic trends such as homelessness and substance abuse.2 In 2016, the CDC reported vaccination coverage among adults aged > 19 was 9.5%, 19-49 was 13.4%, and > 50 was 5.4%3. CDC issued a Health Alert Network Advisory in June 2018 with additional guidance on identification and prevention of HAV and updates on outbreaks in multiple states4 which prompted our program to conduct a more formal review of HAV infections in VHA. Herein we describe recent trends in HAV infection, vaccination and associated risk factors among Veterans.

Objective: To describe the epidemiology of hepatitis A virus (HAV) within the Veterans Health Administration (VHA).

Submitted by elamb on

Administrative data refers to data generated during the processes of health care. These data are a rich source of patient health information, including diagnoses and problem lists, laboratory and diagnostic tests, and medications. Established standards are used to code each data into the appropriate coding systems. The International Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification (ICD-9-CM and ICD-10-CM) codes are the coding standard for diagnoses and have been frequently used to identify cases for the creation of cohorts in examining care delivery, screening, prevalence, and risk factors. However, while some studies have assessed the validity and reliability of ICD-CM codes to identify various conditions such as cerebral palsy and rheumatoid arthritis3,4, the evidence for using ICD codes to accurately identify sexually transmitted infection (STI) cases is largely unexamined. The purpose of this study is to review the extant literature for evidence on the validity of ICD codes for identifying cases of chlamydia, gonorrhea, and syphilis. Our findings will inform efforts to improve the use of administrative data for STI-related health service and surveillance researches.

Objective: The purpose of this study is to review the extant literature for evidence on the validity of ICD-9-CM and -10-CM codes for the purpose of identifying cases of chlamydia, gonorrhea, and syphilis.

Submitted by elamb on

Management policies for influenza outbreaks balance the expected morbidity and mortality costs versus the cost of intervention policies under outbreak parameter uncertainty. Previous approaches have not updated parameter estimates as data arrives or have had a limited set of possible intervention policies. We present a methodology for dynamic determination of optimal policies in a stochastic compartmental model with sequentially updated parameter uncertainty that searches the full set of sequential control strategies.

Objective

This abstract highlights a methodology to build optimal management policy maps for use in influenza outbreaks in small populations.

Referenced File
Submitted by uysz on

Traditional public health practice has relied on public health surveillance of disease to detect outbreaks in an effort to mitigate their effects. Often the earlier an outbreak is detected, the greater the mitigation of its effects. The logical extension of this relationship is to predict outbreaks before they occur. A predictive model for an emerging infectious disease would forecast, when and where an outbreak of a given disease will occur, well before its emergence. This is a challenging task and truly predictive models for emerging infectious diseases and is still in their infancy.

Objective

This paper addresses the problem of predicting outbreaks of diseases of military importance in a chosen region of the world, one to several months in advance.

Referenced File
Submitted by uysz on

The United States outpatient Influenza-like Illness Surveillance Network (ILINet) is one of the five systems used for influenza surveillance in the United States. In Pennsylvania, ILINet providers are asked to report, every Monday, the total number of patients seen for any cause, and the number of patients with influenza-like illness (ILI) by age group. In order to encourage timely reporting, weekly reminders along with a data summary were sent to all sentinel providers postoutbreak recognition. Through the study period, recruitment of new sentinel sites was done through local health departments, health alerts, and training sessions. Sentinel providers were not restricted from submitting specimens to the state lab before and after the outbreak, whereas non sentinel providers had strict restrictions.

Objective

The objective of this study is to describe changes in influenza-like illness (ILI) surveillance, eight weeks before and after the 2009 A/H1N1 pandemic influenza outbreak. We examined changes in provider recruitment, composition, reporting of ILI, and we characterize ILI data in terms of timeliness, and ILI baselines by type of sentinel provider.

Referenced File
Submitted by teresa.hamby@d… on

GI disease outbreaks can be focal (for example, restaurant associated), generalized (for example, seasonal rotavirus increases) or intermediate (for example, widely disseminated contaminated commercial products). Health departments (HDs) are commonly notified of focal outbreaks by passive reporting, whereas generalized outbreaks in non-institutional settings are seldom reported as clusters. Intermediate outbreaks are often detected via laboratory testing, which may be subjected to backlogs and delays. Healthcare systems routinely collect in EMRs clinical data related to GI disease, such as ambulatory care diagnoses, that could be exploited for surveillance. Multiple syndromic and laboratory data sources could potentially be used to prospectively detect generalized and intermediate GI disease outbreaks for situational awareness and possible epidemiological investigation.

Objective

To identify which syndromic and laboratory-based data streams from electronic medical records (EMRs) may be used to detect gastrointestinal (GI) disease outbreaks in a timely manner.

Referenced File
Submitted by teresa.hamby@d… on

Reliable detection and accurate scoping of outbreaks of foodborne illness are the keys to effective mitigation of their impacts. However, relatively small number of persons affected and underreporting, challenge the reliability of surveillance models. In this work, we correlate a record of identified outbreaks and sporadic cases of Salmonellosis in humans retained in PulseNet1, and diagnosis codes in hospital claims collected in California from 2006 to 2010. We hypothesize that the data support and reliability of detection could be improved by including cases in which Salmonella infection may be confused2.

Objective

To investigate utility of using inpatient and emergency room diagnoses to detect outbreaks of Salmonellosis in humans. To quantify the impact of including in the analysis cases diagnosed with conditions that may have physiological appearance similar to Salmonellosis.

Submitted by elamb on

In light of recent communicable disease outbreaks, the ability of Florida Department of HealthÕs (FDOH) syndromic surveillance system, ESSENCE-FL, to identify emergent disease outbreaks using reportable disease data and algorithms originally designed for emergency department chief complaint data was examined. Preliminary work on this analysis presented last year was recently updated and expanded to include additional diseases, further levels of locale, and detector algorithm comparisons. Cases are entered into Merlin, the Bureau of EpidemiologyÕs secure web-based reporting and epidemiologic analysis system, by all 67 county health departments and the de-identified case data are sent hourly to ESSENCE-FL. These data are then available for ad hoc queries, allowing users to observe unusual changes in disease activity and assist in timely identification of infectious disease outbreaks. Based on system algorithms, weekly case tallies are assigned an increasing intensity awareness status from normal to alert and are monitored by county and state epidemiologists to guide timely disease control efforts, but may not by themselves be definitive actionable information.

Objective

To determine if there is an association between known outbreak activity and ESSENCE generated alerts. 

Submitted by elamb on
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