Infectious Disease

The American Health Information Community Harmonized Use Case for the Biosurveillance minimum data set (MDS) was implemented to establish data exchange between regional health information organizations (RHIOs) and the New York State Department of Health (NYSDOH) for accelerating situational awareness through the Health Information Exchange (HIE) Project. However, the completeness, timeliness of the reporting and quality of data elements in the MDS through RHIOs are still unknown and need further validation before we can utilize them for NYSDOH public health surveillance.

Objective

Evaluate the availability, timeliness, and accuracy of MDS data elements received from one RHIO for emergency department (ED), in-patient, and outpatient visits. Compare the characteristics of patients meeting the HIE influenza-like illness definition who were admitted to the hospital or expired versus those discharged home.

Current influenza-like illness monitoring in Idaho is on the basis of syndromic surveillance using laboratory data, combined with periodic person-to-person reports collected by Idaho state workers. This system relies on voluntary reporting. Electronic medical records with relational databases offer a method of obtaining data in an automated fashion. Clinical data entered in CPRS includes real-time visit information, vital signs, ICD-9, pharmacy, and labs. ICD-9 and vital signs have been used to predict influenza-like illness in automated systems. We sought to combine these with lab and pharmacy data as part of an automated syndromic surveillance system.

Objective

The objective of this paper is to study whether syndromic surveillance using data from the Veterans Administration electronic medical record computerized patient record system (CPRS) correlates to officially reported influenza activity levels in the State of Idaho.

Surveillance of deaths due to influenza and pneumonia using death records has the potential to be a relatively inexpensive and quick approach to tracking and detecting influenza and respiratory illness outbreaks; however, presently such a system does not exist because of the time delays in processing death records: in Utah, as is similar elsewhere in the United States, coded death certificate data are typically not available for at least 1–3 months after the date of death, and coded national vital statistics data are not available until after 2–3 years.

Objective

This poster presents the rationale for designing a real-time surveillance system, based on mortality data, using grid and natural language processing tools that will address the current barrier that coded death certificate data not being available for several months. To develop a public health tool that delivers a timely surveillance system for influenza and pneumonia, we integrated death certificates from the Utah Department of Health, analytical grid services, and natural language processing tools to monitor levels of mortality. This example demonstrates how local, state, and national authorities can automate their influenza and pneumonia surveillance system, and expand the number of reporting cities.

The rise and associated risks of using the internet to find sexual partners among men who have sex with men (MSM) has been noted by many researchers.1,2 The anonymity and relative ease of finding partners on the internet has facilitated casual sexual encounters that can encompass a variety of unsafe sexual practices, from anonymous partners to ‘Party and Play’ activities (PNP), slang for illegal drug use, unprotected sex, group sex and so on. These anonymous sexual encounters make it more difficult for public health officials to notify exposed partners. In addition, detailed data regarding risk behaviors are generally obtained via conventional survey techniques, which are expensive to conduct. Thus, a general method of empirically deriving large scale, location-specific behavioral data could be immensely useful in understanding or anticipating STI outbreaks. Craigslist is a website specializing in online classified advertisements around the world. Our hypothesis is that Craigslist contains rich behavioral data regarding MSM communities and that such information can function as proxy for external prevalence rates for diseases (that is, HIV/AIDS).

Objective

This paper describes a novel method of obtaining large scale, geographically diverse behavioral data about Men who use the Internet to seek Sex with Men (MSM) by examining anonymous Craigslist message posts to predict HIV/AIDS.

The HEDSS system was implemented in 2004 to monitor disease activity.1 In all, 18 of 32 emergency departments (ED) and urgent care clinic provide data. Chief complaints are routinely categorized into eight syndromes. The fever/flu syndrome is used for early detection and monitoring of influenza in the community. Area-based measures, such as zip code, enable linkage to area-based socioeconomic census data. Neighborhood poverty, defined as the percentage of persons living below the federal poverty level in a geographic area, predicts a wide range of disease outcomes.

Objective

To describe the relationship between neighborhood poverty and emergency department visits for fever/flu syndrome illnesses reported through the Connecticut Hospital Emergency Department Syndromic Surveillance (HEDSS) system.

Unfortunately, confirmation and notification of all A/H1N1 (2009) patients in Japan was ceased on 24 July when the cumulative number of patients was about 5000. After that, as all suspected patients are not necessarily confirmed or reported, the only official surveillance was the sentinel surveillance for influenza-like-illness (ILI) patients from 5000 clinics accounting for almost 10% of all clinics and hospitals in Japan. However, because the surveillance results are reported weekly, it tends to lack timeliness. To collect and analyze the information in more timely manner, we, Infectious Disease Surveillance Center, National Institute of Infectious Diseases, developed a full automatic daily reporting system of ILI patients. Using this information, we had estimated Rv and predict its course in every week.

Objective

This paper summarized our effort for real-time estimation of pandemic influenza A/H1N1pdm in Japan.

Many studies evaluate the timeliness and accuracy of outbreak detection algorithms used in syndromic surveillance. Of greater interest, however, is defining the outcome associated with improved detection. In case of a waterborne cryptosporidiosis outbreak, public health interventions are aimed exclusively at preventing new infections, and not at medical treatment of infected individuals. The effectiveness of these interventions in reducing morbidity and mortality will depend on their timeliness, the level of compliance, and the duration of exposure to pathogen. In this work, we use simulation modeling to examine several scenarios of issuing a boil-water advisory (BWA) as a response to outbreak detection through syndromic surveillance, and quantify the possible benefits of earlier interventions.

Objective

To quantitatively assess the benefit of issuing a boil-water advisory for preventing morbidity and mortality from a waterborne outbreak of cryptosporidiosis.

Real-time emergency department (ED) data from the BioSense surveillance program for ILI visits and ILI admissions provide valuable insight into disease severity that bridges gaps in traditional influenza surveillance systems that monitor ILI in outpatient settings and laboratory-confirmed hospitalization, but do not quantify the relationship between ILI visits and hospital admissions.

Objective

The purpose of this analysis is to gain understanding of the burden of influenza in recent years through analysis of clinically rich hospital data. Patterns of visits and severity measures such as the ratio of admissions related to influenzalike illness (ILI) by age group from 2007 to 2010 are described.

Cryptosporidiosis is a gastrointestinal illness due to a protozoan parasite that is highly contagious, and resistant to multiple disinfectants. Utah experienced a large, community-wide outbreak of cryptosporidiosis between June and December of 2007. During this time period, the Utah Department of Health received reports of 1,902 laboratory confirmed cryptosporidiosis cases across the state.2 Nearly 40% of these cases occurred in Salt Lake County (SL County), Utah. In past years, SL County averaged fewer than five cases annually; however, the incidence rate in the county for this entire outbreak was 125.9 per 100,000 person–years.

Objective

The objective of this study was to investigate if prospectively applied space-time surveillance could have detected significant, emerging clusters as cryptosporidiosis, cases were reported to the Salt Lake Valley Health Department during the 2007 outbreak.

Epidemiological information realized by modern disease surveillance systems offers great potential for supporting clinical decision-making. Providing health practitioners with population-based, pathogen-specific information about regional communicable infectious disease epidemiology can engender enhanced knowledge about specific pathogens, which may, in turn, lead to improved clinical performance. To enhance the pathogen-specificity of Utah’s surveillance system, which includes tracking syndromes and notifiable diseases, we developed a system that tracks microbiologic testing in Utah’s largest health care delivery system.

Objective

The objective of this study is to describe a system 'Germ Watch' that provides information about the regional activity of common communicable infectious diseases.