Skip to main content

Poster

Description

In 2015, suicide was the 8th leading cause of death in Salt Lake County, Utah, and has recently been identified as a priority public health issue. For suicide, suicide ideation and suicide attempts surveillance, Salt Lake County Health Department staff use National Violent Death Reporting System (NVDRS) mortality data to monitor historical trends and vital records mortality data and ESSENCE ED encounter morbidity data to monitor trends and populations in real time. To improve surveillance and better identify populations at higher risk of suicide, we tested whether we could retrospectively identify residents who died from suicide and visited an ED in the year before death.

Objective:

To explore the use of ED syndromic surveillance data to retrospectively identify individuals who died from suicide and visited an ED before death in order to improve suicide surveillance and inform planning and prevention efforts in Salt Lake County, Utah.

Submitted by elamb on
Description

Indiana utilizes the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) to collect and analyze data from participating hospital emergency departments. This real-time collection of health related data is used to identify disease clusters and unusual disease occurrences. By Administrative Code, the Indiana State Department of Health (ISDH) requires electronic submission of chief complaints from patient visits to EDs. Submission of discharge diagnosis is not required by Indiana Administrative Code, leaving coverage gaps. Our goal was to identify which areas in the state may see under reporting or incomplete surveillance due to the lack of the discharge diagnosis field.

Objective:

To identify surveillance coverage gaps in emergency department (ED) and urgent care facility data due to missing discharge diagnoses.

Submitted by elamb on
Description

Over the past decade Swaziland has experienced recurring drought episodes. In 2016 the country experienced challenges regarding water supplies in both urban and rural areas due to the drought impact. A rapid health and Nutrition Assessment was conducted in 2016 revealed an increase in number of cases of acute watery diarrhea of all age groups. While there is a high demand for epidemiological data in the country a passive system through Health Management Information System (HMIS) and Immediate Disease Notification System (IDNS) has been used to monitor acute watery diarrhea and a set of priority notifiable diseases in the country.

Objective:

To evaluate the difference in sensitivity between passive and active diarrheal and malnutrition disease surveillance system post-drought period in Swaziland

Submitted by elamb on
Description

Malaria remains a major public health problem in Madagascar. Indoor Residual Spraying (IRS) is the adopted strategy for malaria control in the CHs and Fringe regions of Madagascar. Remotely sensed data analysis combined with Multi-Criteria Evaluation become crucial to target priority areas for intervention.

Objective:

Madagascar is one of the low-income countries with limited resources. In order to minimize the cost of the fight against malaria, the main objective of this study is to identify the priority zone for Indoor Residual Spraying (IRS).

Submitted by elamb on
Description

Influenza infection is caused by the influenza virus, a single-stranded RNA virus belonging to the Orthomyxoviridae family. Influenza viruses are classified as types A, B and C. Influenza A and B viruses can cause epidemic disease in humans and type C viruses usually cause a mild, cold-like illness. The influenza virus spreads rapidly around the world in seasonal epidemics, resulting in significant morbidity and mortality. On the 10th of July 2017, a case of confirmed Influenza A/H1N1 was reported through the immediate disease notification system from a private hospital in the Hhohho region. A 49 year old female was diagnosed of Influenza A/H1N1 after presenting with flu-like symptoms. Contacts of the index case were followed and further positive cases were identified.

Objective:

To establish morbidity patterns of influenza A/H1N1 in Swaziland from 10th July to 15th August 2017.

Submitted by elamb on
Description

NBIC integrates, analyzes, and distributes key information about health and disease events to help ensure the nation’s responses are well-informed, save lives, and minimize economic impact. To meet its mission objectives, NBIC utilizes a variety of data sets, including open source information, to provide comprehensive coverage of biological events occurring across the globe. NBIC Biofeeds is a digital tool designed to improve the efficiency of analyzing large volumes of open source reporting and increase the number of relevant insights gleaned from this dataset. Moreover, the tool provides a mechanism to disseminate tailored, electronic message notifications in near-real time so that NBIC can share specific information of interest to its interagency partners in a timely manner. NBIC is deploying the tool for operational use by the Center and eventual use by federal partners with biosurveillance mission objectives. Core functionality for data collection, curation, and dissemination useful to other federal agencies was implemented, and NBIC is incorporating custom taxonomies for capturing metadata specific to the unique missions of NBIC partners.

Objective:

The National Biosurveillance Integration Center (NBIC) is deploying a scalable, flexible open source data collection, analysis, and dissemination tool to support biosurveillance operations by the U.S. Department of Homeland Security (DHS) and its federal interagency partners.

Submitted by elamb on
Description

There have been a number of non-infectious intoxication outbreaks reported in North American companion animal populations over the last decade. The most devastating outbreak to date was the 2007 melamine pet food contamination incident which affected thousands of pet dogs and cats across North America. Despite these events, there have been limited efforts to conduct real-time surveillance of toxicological exposures in companion animals nationally, and there is no central registry for the reporting of toxicological events in companion animals in the United States. However, there are a number of poison control centers in the US that collect extensive data on toxicological exposures in companion animals, one of which is the Animal Poison Control Center (APCC) operated by the American Society for the Prevention of Cruelty to Animals (ASPCA). Each year the APCC receives thousands of reports of suspected animal poisonings and collects extensive information from each case, including location of caller, exposure history, diagnostic findings, and outcome. The records from each case are subsequently entered and stored in the AnTox database, an electronic medical record database maintained by the APCC. Therefore, the AnTox database represents a novel source of data for real-time surveillance of toxicological events in companion animals, and may be used for surveillance of pet food and environmental contamination events that may negatively impact both veterinary and human health.

Objective:

Our objective was to assess the suitability of the data collected by the Animal Poison Control Center, run by the American Society for the Prevention of Cruelty to Animals, for the surveillance of toxicological exposures in companion animals in the United States.

Submitted by elamb on
Description

The Global Public Health Intelligence Network is a non-traditional all-hazards multilingual surveillance system introduced in 1997 by the Government of Canada in collaboration with the World Health Organization.1 GPHIN software collects news articles, media releases, and incident reports and analyzes them for information about communicable diseases, natural disasters, product recalls, radiological events and other public health crises. Since 2016, the Public Health Agency of Canada (PHAC) and National Research Council Canada (NRC) have collaborated to replace GPHIN with a modular platform that incorporates modern natural language processing techniques to support more ambitious situational awareness goals.

Objective:

To rebuild the software that underpins the Global Public Health Intelligence Network using modern natural language processing techniques to support recent and future improvements in situational awareness capability.

Submitted by elamb on
Description

As a part of the Zika Birth Defects Surveillance, a national effort coordinated by the Centers for Disease Control and Prevention (CDC), NYC is conducting enhanced surveillance of all births with defects included in the congenital Zika syndrome (CZS) phenotype among infants born in NYC beginning in 2016. The intent of the project is to provide background on the prevalence of these conditions, regardless of cause. The surveillance project builds on the New York State (NYS) Congenital Malformations Registry, a passive, mandatory reporting system that relies on reporting from hospitals and providers. For the Surveillance project, potential cases of Zika-related birth defects (ZBD) are identified by hospital and administrative data of birth records with one or more of the International Classification of Diseases, 10th Revision (ICD-10) diagnostic codes associated with CZS.1 The list of included diagnostic codes was specified by the NYS registry following guidance established by CDC. Full medical record chart abstraction of the birth hospital visit of potential cases is then conducted applying further inclusion guidelines to identify ZBD cases. Recent reports of late presentation of birth defects consistent with CZS suggest that some cases are being missed due to identification and diagnosis of the condition after birth.2 As one component of a broader strategy to obtain a more accurate surveillance count, we seek to identify potential ZBD cases first diagnosed in the 6-month postpartum period using Medicaid claims data.

Objective:

To assess the use of Medicaid claims data to conduct surveillance for cases of Zika-related birth defects identified after birth among infants born in New York City (NYC).

Submitted by elamb on
Description

The Epi Evident application was designed for clear and comprehensive visualization for monitoring, comparing, and forecasting notifiable diseases simultaneously across chosen countries. Epi Evident addresses the taxing analytical evaluation of how diseases behave differently across countries. This application provides a user-friendly platform with easily interpretable analytics which allows analysts to conduct biosurveillance with minimal user tasks. Developed at the Pacific Northwest National Laboratory (PNNL), Epi Evident utilizes time-series disease case count data from the Biosurveillance Ecosystem (BSVE) application Epi Archive. This diverse data source is filtered through the flexible Epi Evident workflow for forecast model building designed to integrate any entering combination of country and disease. The application aims to quickly inform analysts of anomalies in disease & location specific behavior and aid in evidence based decision making to help control or prevent disease outbreaks.

Objective:

Epi Evident is a web based application built to empower public health analysts by providing a platform that improves monitoring, comparing, and forecasting case counts and period prevalence of notifiable diseases for any scale jurisdiction at regional, country, or global-level. This proof of concept application development addresses improving visualization, access, situational awareness, and prediction of disease behavior.

Submitted by elamb on