Surveillance

The outbreak of infectious diseases with a propensity to spread across international boundaries is on an upward rise. Such outbreaks can be devastating with significant associated morbidity and mortality. The recent Ebola Virus Disease outbreak in West Africa which spread to Nigeria is an example. Nigeria like several other African countries implements the Integrated Disease Surveillance and Response (IDSR) system as its method for achieving the International Health Regulations (IHR). Yet, compliance to the IDSR is questioned. This study seeks to investigate the legal instruments in place and the factors affecting performance of the disease surveillance in the country.

Objective:

Assess the legal framework establishing disease surveillance in Nigeria and identify major factors affecting the performance of the surveillance system.

In mid-2017, the Kentucky Injury Prevention and Research Center (a bonafide agent of Kentucky Department for Public Health-KDPH) was alerted by members of KDPH to anecdotal evidence of a possible increase of SynCan (primarily Serenity) overdoses. The situation presented an opportunity to demonstrate the capabilities of syndromic surveillance and emergency medical services (EMS) data systems to provide rapid situational awareness about SynCan overdoses.

Objective:

The aim of this project was to investigate anecdotal reports of an increase in synthetic cannabinoid (SynCan) overdoses in Lexington-Fayette County area of Kentucky, using rapid surveillance systems including emergency department (ED) syndromic surveillance (SyS) and emergency medical services (EMS) data.

The Kansas Syndromic Surveillance Program (KSSP) utilizes the ESSENCE v.1.20 program provided by the National Syndromic Surveillance Program to view and analyze Kansas Emergency Department (ED) data. Methods that allow an ESSENCE user to query both the Discharge Diagnosis (DD) and Chief Complaint (CC) fields simultaneously allow for more specific and accurate syndromic surveillance definitions. As ESSENCE use increases, two common methodologies have been developed for querying the data in this way. The first is a query of the field named “CC and DD.” The CC and DD field contains a concatenation of the parsed patient chief complaint and the discharge diagnosis. The discharge diagnosis consists of the last non-null value for that patient visit ID and the chief complaint parsed is the first non-null chief complaint value for that patient visit ID that is parsed by the ESSENCE platform. For this comparison, this method shall be called the CCDD method. The second method involves a query of the fields named, Chief Complaint History and œDischarge Diagnosis History. While the first requires only one field be queried, this method queries the CC History and DD History fields, combines the resulting data and de-duplicates this final data set by the C_BioSense_ID. Chief Complaint History is a list of all chief complaint values related to a singular ED visit, and Discharge Diagnosis History is the same concept, except involving all Discharge Diagnosis values. For this comparison, this method shall be called the CCDDHX method. While both methods are based on the same query concept, each method can yield different results.

Objective:

To compare and contrast two ESSENCE syndrome definition query methods and establish best practices for syndrome definition creation.

In 2016, twelve states received Center for Disease Control and Prevention (CDC) Enhanced State Opioid Overdose Surveillance grants. The purpose of the grant is to explore enhanced data sources to track nonfatal opioid overdoses. One data source is ambulance runs. Wisconsin collects ambulance run information within the Wisconsin Ambulance Runs Data System (WARDS). Around 84% of all Wisconsin administrative services report into this electronic system. This is a timely, robust data system that has not been used previously to examine drug overdoses and presents an analytical challenge as it contains many free text fields.

Objective:

1. Develop an understanding of the benefits and challenges of analyzing free text fields on a population level.

2. Observe how a complex surveillance definition can be created from free text fields.

3. Observe how an ambulance data system can be used to describe the opioid epidemic.

In 2016, the Centers for Disease Control and Prevention funded 12 states, under the Enhanced State Opioid Overdose Surveillance (ESOOS) program, to utilize state Emergency Medical Services (EMS) and emergency department (ED) syndromic surveillance (SyS) data systems to increase timeliness of state data on drug overdoses. A key aspect of the ESOOS program is the development and validation of case definitions for drug overdoses for EMS and ED SyS data systems. Kentucky's ESOOS team conducted a pilot validation study of a candidate EMS case definition for HOD, using data from the Kentucky State Ambulance Reporting System (KStARS). We examined internal, face validity of the EMS HOD case definition by reviewing pertinent information captured in KStARS data elements; and we examined external agreement with HOD cases identified Kentucky’s statewide hospital billing database.

Objective:

The aims of this project were 1) to assess the validity of a surveillance case definition for identifying heroin overdoses (HOD) in a NEMSIS 3 compliant, state ambulance reporting system; and 2) to develop an approach that can be applied to assess the validity of case definitions for other types of drug overdose events in similar data state data systems.

Hepatitis A virus (HAV) infections have persisted in the United States despite the availability of an effective vaccine. Recent outbreaks of HAV infections among unvaccinated adults attributed to consumption of HAV-contaminated food, or person-to-person contact in certain populations (e.g., men who have sex with men) or settings (e.g., homeless shelters) have emphasized the importance of targeted vaccination of at-risk adults.

Objective:

To evaluate the use of commercial laboratory data for monitoring trends in HAV infections over time and identifying geographic and demographic characteristics of HAV case clusters for the purpose of targeting interventions.

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

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).

Public health agencies worldwide all enjoy the same mission—providing healthcare warnings, guidance, and support to the public and healthcare professionals they represent. A critical element in achieving this mission is accessing timely and comprehensive surveillance information about disease in their regions of responsibility. Advances in diagnostic technologies for infectious disease and in the wireless conveyance of information hold great promise for advancing the quality of surveillance information and in facilitating the delivery of timely, accurate, and impactful public health information. Quidel Corporation has developed a cloud–based, wireless communications system that is fully integrated with its Sofia fluorescence immunoassay (FIA) platform for rapid, point-of-care diagnosis of infectious disease. The system, called the Virena Global Wireless Surveillance System (hereinafter, Virena) provides test results to public health organizations and other appropriate entities in near-real time. Currently, more than 4,000 Sofia instruments are transmitting results automatically by Virena. This presentation describes the use of Virena in surveilling influenza in the U.S. in the 2016-2017 influenza season, when over 700,000 influenza-like-illness (ILI) patient results were transmitted. The methods employed, results, and the promise of this innovative system will be discussed.

Objective:

Demonstrate performance of the Virena Global Wireless Surveillance System, an automated platform utilized in conjunction with the Sofia FIA Analyzer, for near real-time transmission of infectious disease test results to public health and other healthcare organizations.

National initiatives, such as Meaningful Use, are automating the detection and reporting of reportable disease events to public health, which has led to more complete, timely, and accurate public health surveillance data. However, electronic reporting has also lead to significant increases in the number of cases reported to public health. In order for this data to be useful to public health, it must be processed and made available to epidemiologists and investigators in a timely fashion for intervention and monitoring. To meet this challenge, the Utah Department of Health (UDOH)’s Disease Control and Prevention Informatics Program (DCPIP) has developed the Electronic Message Staging Area (EMSA). EMSA is a system capable of automatically filtering, processing, and evaluating incoming electronic laboratory reporting (ELR) messages for relevance to public health, and entering those laboratory results into Utah’s integrated disease surveillance system (UT-NEDSS) without impacting the overall efficiency of UT-NEDSS or increasing the workload of epidemiologists.

Objective:

The objective of this abstract is to illustrate how the Utah Department of Health processes a high volume of electronic data in an automated way. We do this by a series of rules engines that does not require human intervention.