Influenza

The first prototype syndromic surveillance in Japan was used during the G8 summit meeting in 2000 with two local prefectures involved. The second trial syndromic surveillance and the first internet-based surveillance used in 2002 for the Japan-Korea 2002 World Cup soccer games. Since 2002, surveillances on over-the-counter medications, ambulance call, and outpatient visits were explored as syndromic approach candidates for early detection. Internet-based events and case reporting frame work has been reviewed for outpatient visits daily reporting concurrently. Limited spread of electrical patient record and vast range of commercialized medical record formats posed obstacles to nationwide syndromic surveillance implementation.

Recent threats from bioterrorism and influenza pandemic empowered Japanese government introducing surveillance of rapid detection mechanism. In line with the revision of the Infection Control Law took place in 2007 April, national syndromic surveillance system was implemented.

Objective

This paper describes recent establishment of national surveillance system for early detection of infectious diseases in Japan. With diagnostic data fed from existed routine surveillance, newly introduced system is expected to provide timely information for control response. We aim to facilitate cross-informative regional surveillance by sharing our experience and system frame work.

Objective

To enable the early detection of pandemic influenza, we have designed a system to differentiate between severe and mild influenza outbreaks. Historic information about previous pandemics suggested the evaluation of two specific discriminants: (1) the rapid development of disease to pneumonia within 1-2 days and (2) patient age distribution, as the virus usually targets specific age groups. The system is based on the hypothesis that an increased number of diagnosed pneumonia cases offers an early indication of severe influenza outbreaks. This approach is based on the fact that pneumonia cases will appear promptly in a severe influenza outbreak and can be diagnosed immediately in a physician office visit, while a confirmed influenza diagnosis requires a laboratory test. Furthermore, laboratory tests are unlikely to be ordered outside of the expected influenza season.

A pandemic caused by influenza A/H5N1 or another novel strain could kill millions of people and devastate economies worldwide. Recent computer simulations suggest that an emerging influenza pandemic might be contained in Southeast Asia through rapid detection, antiviral distribution, and other interventions [1]. To facilitate containment, the World Health Organization (WHO) has established large, global antiviral stockpiles and called on countries to develop rapid pandemic detection and response protocols [2]. However, developing countries in Southeast Asia would face significant challenges in containing an emerging pandemic. Limited surveillance coverage and diagnostic capabilities; poor communication and transportation infrastructure; and lack of resources to investigate outbreaks could cause critical delays in pandemic recognition. Wealthy countries have committed substantial funds to improve pandemic detection and response in developing countries, but tools to guide system planning, evaluation, and enhancement in such places are lacking.

Objective

We propose a framework for evaluating the ability of syndromic, laboratory-based, and other public health surveillance systems to contain an emerging influenza pandemic influenza in developing countries, and apply the framework to systems in Laos.

Many syndromic surveillance systems have been developed and are operational, yet lack concise guidelines for investigating and conducting followups on daily alarms. Daily emergency department visits from six reporting hospitals in the Duval County area are assessed and classified into a BioDefend (BD) system entry by triage personnel. Alarms are categorized into alerts, 3 SD above a 30 day rolling mean, or warnings, 2-3 SD above the mean. Signals are monitored and in response, public health investigations and recommended interventions are initiated.

Objective

To evaluate the protocol that the Duval County Health Department (DCHD) epidemiology staff uses to respond to BD syndromic surveillance system alarms. The response protocol utilizes all signals detected by BD and its secondary resources, within the DCHD jurisdiction.

This project was established through the Border Infectious Disease Surveillance (BIDS) program in Arizona (AZ) to monitor infecting respiratory pathogens among hospitalized patients with Severe Acute Respiratory Infections (SARI) in the AZ border region from September 2010 to the present.

Objective

To present the epidemiology, clinical aspects, and laboratory results of AZ SARI case patients and to describe respiratory viruses in the AZ border region.

Surveillance systems utilizing early indicator of disease activity would be useful for monitoring community disease pattern and facilitating timely decision making on public health interventions in an evidence-based manner. School absenteeism has been previously considered as a possible syndromic approach for monitoring influenza activity. We explored the feasibility and practicability of establishing an electronic school absenteeism surveillance system in Hong Kong for monitoring influenza-like illness (ILI) and other diseases using automatically captured data employing smart card technology.

Objective

We examined the utility of an electronic school absenteeism system for monitoring multiple types of diseases.

Coordinated proactive school closures can help to reduce disease transmission in communities during an influenza pandemic; however, limited information is available about effects of school closures during influenza-like illness (ILI) outbreaks. A rural school district (District A) in Kentucky was closed during January 29-February 1, 2013, in response to an increase in ILI-related student absenteeism.

Objective

We investigated effects of this closure by comparing self-reported illness among household members of students enrolled in District A with 2 adjacent districts (Districts B and C) that remained open during that period.

Researchers have developed varied methods for forecasting influenza activity using surveillance data with predictive models, but real-world applications in public health programs are rare. To inform consideration of whether and how public health practice should incorporate influenza forecasting, we conducted a systematic review of these methods.

Objective

To assess studies of epidemiological forecasting models for human influenza activity.

Influenza is a significant public health problems in the US leading to over one million hospitalizations in the elderly population (age 65 and over) annually. While influenza preparedness is an important public health issue, previous research has not provided comprehensive analysis of season-by-season timing and geographic shift of influenza in the elderly population. These findings fail to document the intricacies of each unique influenza season, which would benefit influenza preparedness and intervention. The annual harmonic regression model fits each season of disease incidence characterized by its own unique curve. Using this model, characteristics of the seasonal curve for each state and each season can be compared. We hypothesize that travelling waves of influenza in the 48 contiguous states differ dramatically in each influenza season.

Objective

In surveillance it is imperative that we know when and where a disease first begins. The objective of this study was to examine trends in traveling waves of influenza in the US elderly population. Preparedness for influenza is an important yet difficult public health goal due to variability in annual strains, timing, and shift of the influenza virus. In order to better prepare for influenza epidemics, it is important to assess seasonal variation across individual influenza seasons on a state-by-state basis. This approach will lead to effective interventions especially for susceptible populations such as the elderly.