Infectious Disease

Sequence-informed surveillance is now recognized as an important extension to the monitoring of rapidly evolving pathogens [2]. This includes phylogeography, a field that studies the geographical lineages of species including viruses [3] by using sequence data (and relevant metadata such as sampling location). This work relies on bioinformatics knowledge. For example, the user first needs to find a relevant sequence database, navigate through it, and use proper search parameters to obtain the desired data. They also must ensure that there is sufficient metadata such as collection date and sampling location. They then need to align the sequences and integrate everything into specific software for phylogeography. For example, BEAST [4] is a popular tool for discrete phylogeography. For proper use, the software requires knowledge of phylogenetics and utilization of BEAUti, its XML processing software. The user then needs to use other software, like TreeAnnotator [4], to produce a single (representative) maximum clade credibility (MCC) tree. Even then, the evolutionary spread of the virus can be difficult to interpret via a simple tree viewer. There is software (such as SpreaD3 [5]) for visualizing a tree within a geographic context, yet for novice users, it might not be easy to use. Currently, there are only a few systems designed to automate these types of tasks for virus surveillance and phylogeography.

Objective: We will describe the ZooPhy system for virus phylogeography and public health surveillance [1]. ZooPhy is designed for public health personnel that do not have expertise in bioinformatics or phylogeography. We will show its functionality by performing case studies of different viruses of public health concern including influenza and rabies virus. We will also provide its URL for user feedback by ISDS delegates.

Syndromic surveillance data is typically used for the monitoring of symptom combinations in patient chief complaints (i.e. syndromes) or health indicators within a population to inform public health actions. The Tennessee Department of Health collects emergency department (ED) data from more than 80 hospitals across Tennessee to support statewide situational awareness. Most hospitals in Tennessee provide data within 48 hours of the patient being seen in the emergency department. The timeliness of syndromic surveillance data allow for rapid estimates of impact in emergency department populations. Tennessee has successfully used these data to monitor influenza, heat related illnesses, and emergency department impacts from disaster evacuations. In addition to assessing impact and trends, syndromic surveillance can also provide early warnings for conditions of public health concern and increase the lead time public health has to initiate a response. In Tennessee, routine syndromic surveillance for mumps, hepatitis A, and other conditions has been successfully conducted statewide. Three successes from these surveillance efforts include detecting a clinically diagnosed but unreported case of mumps, early identification of hepatitis A cases during Tennessee's ongoing 2018 hepatitis A outbreak, and the detection of an epidemiologically unlikely clinical diagnosis of mumps associated with an exposure at a recreational center.

Objective: To demonstrate the utility of syndromic surveillance data in aiding public health actions and response across multiple investigations in Tennessee.

Monitoring of long-term infectious disease mortality trends is of great value to national public health systems both in estimation of the efficacy of preventive programs, and in development of the new strategies of preventive measures. In the developed countries, there are a number of studies with long-term time series of infectious disease mortality analysis in epidemiological and historical aspects. Our research was based on the work by Armstrong GL, Conn LA and Pinner RW, 1999. Literature review revealed that such analysis has been never carried out in Ukraine up to now.

Objective: The aim of our work is to determine the main trends and structure in infectious disease mortality in Ukraine over the last 50 years.

Infectious disease was the second most common cause of death in 1949, and the epidemic situation of infectious diseases was so severe that the Chinese government made major investments to the control and prevention of infectious diseases. During the past 60 years the development of the notifiable disease surveillance system in China has experienced 3 phases, including germination stage, development stage, improvement and consolidation stage (1). As the quality of infectious diseases surveillance has been improved stepwisely, the national morbidity of class A and B notifiable disease decreased from 7157.5 per 100,000 in 1970 to 225.8 per 100,000 in 2013, and the mortality decreased from 56.0 per 100,000 in 1959 to 1.2 per 100,000 in 2013(2).

Objective: We aimed to review the development and changes of National Notifiable Disease Surveillance System (NNDSS) from 1950 to 2013, and to analyze and summarize the changes in regulations and public health surveillance practices in China.

Military service members and their families work and live around the world where both endemic and emerging infectious diseases are common. Timely infectious disease surveillance helps to inform medical and policy decisions which ensure mission readiness and beneficiary health. The EpiData Center (EDC) at the Navy and Marine Corps Public Health Center has performed public health surveillance, including routine infectious disease monitoring among service members, their families, and others eligible for military medical benefits for the Department of the Navy (DON) and Department of Defense (DOD) since 2005. The EDC stores and maintains 15 databases totaling over 20 terabytes of health and administrative data. These include administrative data from outpatient encounters and inpatient admissions, Health Level-7 (HL7) formatted ancillary services data, and medical event reports. These data provide the potential for robust surveillance methodologies to monitor diseases of interest and identify trends and outbreaks. The primary intent and design of these data sources is not for disease surveillance, but rather for administrative and billing purposes. However, due to the availability of this data, it is routinely used by academic organizations, private industry, health systems, and government organizations to conduct health surveillance and research. Ancillary services data in particular can be very powerful for near-real time infectious disease surveillance in the DOD as the aggregated data is available within 1 to 2 days after processing. The EDC has demonstrated the value of using laboratory data for surveillance through outbreak detection and longitudinal health trends for specific diseases among select populations. The fact that this data is not designed for surveillance does present several pitfalls in regards to analysis, from issues ranging from free text interpretation to changing testing practices. These pitfalls can be mitigated through standardized processes and detailed quality assurance testing. The EDC has harnessed the power of available administrative health data to improve health outcomes and influence policy among military beneficiaries.

Objective: Discuss the power of utilizing DOD clinical ancillary services data for infectious disease surveillance, the steps used to mitigate pitfalls which may occur during the surveillance process, and the potential of adapting this data for surveillance of emerging infectious diseases.

There are a wide variety of available web-based apps, such as CDC'™s Epidemic Information Exchange, that provide infectious disease information and disease distribution [1]. Publicly available, online data can be used to inform a user of general risks based on disease distribution maps and case count data. Unfortunately, each app contains different aspects of the data, which is often represented in different ways and incompatible formats. This heterogeneity can overwhelm a user with confusing information making it difficult to interpret or gain valuable insight into their own situational risk in a specified location. In addition, online resources do not filter information based on the user's current location or situational needs and, therefore, reduces the value of information a user may be interpreting. However, information formatted and represented appropriately in a single app could be used to better understand an individual's situational infectious disease risk. In addition, this information may further educate a user based on a situation or incident to prevent disease spread, especially in higher risk populations. To accomplish these goals, PNNL has developed an offline, Android app that provides the user with simple, easy to understand filterable global infectious disease information integrated with their location to provide personalized situational health risk and decision support in the field.

Objective: The Pocket Atlas of Infectious Diseases (PocketAID) mobile application developed at Pacific Northwest National Laboratory (PNNL) provides infectious disease education and decision support offline for an enhanced personal situational risk assessment anywhere in the world. The app integrates a user's location, demographic information, and infectious disease data to present the user with important information including personalized, calculated risk level. PocketAID features a global disease distribution map and epidemiological curve of country-based case counts by year. Filter options allow users to customize disease lists available to aid in situational awareness. PocketAID, first of its kind, is being developed for offline decision support use by Department of Defense's Defense Threat Reduction Agency (DTRA).

Hepatitis C virus (HCV) infection is a leading cause of liver disease-related morbidity and mortality in the United States. Approximately 75% of people infected with chronic HCV were born between 1945 and 1965. Since 2012, the CDC has recommended one-time screening for chronic HCV infection for all persons in this birth cohort (baby boomers). The United States Preventive Services Task Force (USPSTF) subsequently made the same recommendation in June 2013. We estimated the rate of HCV testing between 2011 and 2017 among persons with commercial health insurance coverage and compared rates by birth cohort.

Objective: Using the two largest commercial laboratory data sources nationally, we estimated the annual rates of hepatitis C testing among individuals who were recommended to be tested (i.e., baby boomer cohort born between 1945 and 1965) by the CDC and United States Preventive Services Task Force. This panel will discuss strengths and weaknesses for monitoring hepatitis C testing using alternative data sources including self-reported data, insurance claims data, and laboratory testing data.

The Tennessee Department of Health (TDH) Foodborne Disease Program conducts routine surveillance for foodborne illnesses and enteric disease outbreaks and participates in statewide enhanced surveillance as part of the Foodborne Disease Center for Outbreak Response Enhancement (FoodCORE) and the Foodborne Diseases Active Surveillance Network (FoodNet) supported by the Centers for Disease Control and Prevention (CDC). TDH uses the CDC NEDSS Base System (NBS) application for routine disease surveillance. However, NBS serves multiple disease programs within TDH and modifications to the system for the rapidly changing data demands, grant requirements, and outbreak needs of the foodborne program, may not be a priority for the system as a whole. In 2014, the TDH Foodborne Disease Program began using the Research Electronic Data Capture (REDCap) application as a solution to changing surveillance needs. FoodCORE, FoodNet, and routine surveillance data elements are entered into REDCap to supplement NBS, depending on program specific needs and system capability.

Objective: The objective of this study is to evaluate the use of a supplementary data management application to meet surveillance demands for foodborne disease in Tennessee and to highlight successes, challenges, and opportunities identified through this process.