Infectious Disease

On Monday, August 29, 2005, Hurricane Katrina struck the Gulf Coast. Outside of the affected areas of TX, LA, MS, and AL, GA received the largest number of these evacuees, approximately 125,000. By August 30, 2005, GA began receiving a total of approximately 1,300 NDMS patients from flights arriving at Dobbins Air Force Base. Within days, Georgia established 13 shelters for evacuees. Crowded shelters can increase the risk for communicable diseases. In addition, many evacuees left behind needed medications, thus increasing the risk for chronic disease exacerbations.

Objective

To assess public health needs among sheltered evacuees, the GA Department of Human Resources, Division of Public Health recommended daily surveillance.

Surveillance strategies following major natural disasters have varied widely with respect to methods used to collect and analyze data. Following Hurricane Katrina, public health concerns included infectious disease outbreaks, injuries, mental health and exacerbation of preexisting chronic conditions resulting from unprecedented population displacement and disruption of public health services and health-care infrastructure.

Objective

This paper describes the public health surveillance response to hurricane Katrina in New Orleans and surrounding Parishes; particularly illustrating the methods, results, and lessons learned for implementing passive, active and electronic syndromic surveillance systems during a major disaster.

Electronic laboratory-based surveillance can significantly improve the diagnostic specificity and response time of traditional infectious disease surveillance. Under the project “Models of Infectious Disease Agent Study”, we wished to evaluate the application of space-time outbreak detection algorithms utilizing SaTScan to a national database of routinely collected microbiology laboratory data.

Objective

This paper describes the application of the WHONET software integrated with SaTScan to the detection of Shigella outbreaks in a national database using a space-time cluster detection algorithm in simulated real-time and comparison of findings to outbreaks reported to the Ministry of Health.

To determine the feasibility of using BioSense laboratory data to do surveillance on Clostridium difficile infection (CDI) and calculate overall and facility rates of disease.

The revised International Health Regulations (IHR) have expanded traditional infectious disease notification to include surveillance diseases of international importance, including emerging infectious diseases.  However, there are no clearly established guidelines for how countries should conduct this surveillance, which types of syndromes should be reported, nor any means for enforcement.  The commonly established concept of syndromic surveillance in developed regions encompasses the use of pre-diagnostic information in a near real time fashion for further investigation for public health action.  Syndromic surveillance is widely used in North America and Europe, and is typically thought of as a highly complex, technology driven automated tool for early detection of outbreaks.  Nonetheless, applications of syndromic surveillance using technology appropriate for the setting are being used worldwide to augment traditional surveillance, and may enhance compliance with the revised IHR.

Objective:

To review applications of syndromic surveillance in developing countries

Historical data are essential for development of detection algorithms. Spatio-temporal data, however, are difficult to come by due to variety of issues concerning patient confidentiality. Several approaches have been used to generate benchmark data using statistical methods. Here, we demonstrate how to generate benchmark data using a discrete event model simulating inter- and intra-contact network transmission dynamics of infectious diseases in space and time using publicly available population data.

OBJECTIVE

The objective of this study is to generate benchmark data from a discrete event model simulating the transmission dynamics of an infectious disease within and between contact networks in urban settings using real population data. Such data can be used to test the performance of various temporal and spatio-temporal detection algorithms when real data are scarce or cannot be shared.

The paper outlined the major findings and statistical results of syndromic surveillance system in Taiwan since year 2000.

We developed, implemented and evaluated Meningitis and Encephalitis (M/E) syndrome case definitions based on electronic Emergency Department (ED) chief complaint data; and assessed their ability to detect aberrations that correspond with M/E outbreaks.

Multiple surveillance activities have been conducted in Great Britain (GB) with the objective of estimating the occurrence of scrapie, a fatal neurological infectious disease of small ruminants: statutory reporting of clinical cases, annual surveys on sections of the population and occasional anonymous postal surveys. None of the surveillance sources is either unbiased or comprehensive and if the progress of control schemes is to be closely monitored, better estimates of disease occurrence are required. With this objective, the Department for Food, Environment and Rural Affairs (Defra) funded a project to: i)provide estimates of the frequency of scrapie that integrate currently available surveillance data; and ii)inform the most effective surveillance strategies that will result in sensitive systems for the detection of changes in disease prevalence in time. To make this review as comprehensive as possible it should also: i)consider clinical disease and infection at both individual animal and holding level; ii) subject to data availability, extend all analyses to the recently detected atypical form of scrapie and iii) in a context of scarce and competitive resources, approach the problem efficiently. The approaches used within this project, outlined below, describe the efficient use and integration of all existing sources to evaluate the surveillance effort. Three surveillance attributes were of particular interest in the evaluation process: sensitivity, representativeness and cost.

This paper describes a comparison between two statistics ñ SaTScan and FleXScan, applying to a data of absentees in primary school in Japan.