Pneumonia

Influenza peaks around June and December in Singapore every year. Facing an ageing population, hospitals in Singapore have been constantly reaching maximum bed occupancy. The ability to be able to make early decisions during peak periods is important. Tan Tock Seng Hospital is the second largest adult acute care general hospital in Singapore. Pneumonia-related emergency department (ED) admissions are a huge burden to the hospital's resources. The number of cases vary year on year as it depends on seasonal vaccine effectiveness and the population's immunity to the circulating strain. While many pneumonia cases are of unknown origin, they tend to mirror the influenza seasons very closely.

Objective: Using the information that we have available, our primary objective is to explore if there was any cross-correlation between pneumonia admissions and hospital influenza positivity. We then aim to develop a data driven approach to forecast pneumonia admissions using data from our hospital's weekly surveillance. We also attempted using external sources of information such as national infectious diseases notifications and climate data to see if they were useful for our model.

Influenza is a serious disease that seasonality causes substantial but varying morbidity and mortality. In Taiwan, estimates of the influenza mortality burden were based on post-hoc analyses of national mortality statistics and not available until at least six months after the corresponding epidemic. Timely monitoring and early detection of influenza-associated excess mortality can guide antiviral or vaccine interventions and help healthcare capacity planning. Beginning April 2009, Taiwan Centers for Disease Control has been collaborating with the Department of Health Office of Statistics to develop an automated system for real-time pneumonia and influenza (P&I) mortality surveillance.

Objective 

To develop and evaluate a nationwide automated system for early detection of aberrations and real-time monitoring of P&I mortality in Taiwan.

Influenza is a major cause of mortality. In developed countries, mortality is at its highest during winter months, not only as a result of deaths from influenza and pneumonia but also as a result of deaths attributed to other diseases (e.g. cardiovascular disease). Understandably, much of the surveillance of influenza follows predefined geographic regions (e.g. census regions or state boundaries). However, the spread of influenza and its resulting mortality does not respect such boundaries.

Objective

To cluster cities in the United States based on their levels of mortality from influenza and pneumonia.

Routine primary care data provide the means to systematically monitor a variety of syndromes which could give early warning of health protection issues (microbiological and chemical). It is possible to track milder illnesses which may not present to hospitals (e.g. chicken pox, conjunctivitis) or illnesses for which laboratory specimens are not routinely taken (e.g. influenza). Real-time data are also needed to respond to major health protection incidents.

Objective

To describe the arrangements for Primary Care Surveillance in the UK and provide examples of the benefits of this work for Public Health.

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.

During influenza season, the Boston Public Health Commission uses syndromic surveillance to monitor Emergency Department visits for chief complaints indicative of influenza-like illness (ILI). We created three syndrome definitions for ILI to capture variable presentations of disease, and compared the trends with Boston pneumonia and influenza mortality data, and onset dates for reported cases of influenza.

Objective

To evaluate the impact of different syndrome definitions for ILI by comparing weekly trends with other data sources during the 2005-2006 influenza season in Boston.

BioSense currently receives demographic and chief complaint data from more than 360 hospitals and text radiology reports from 36 hospitals. Detection of pneumonia is an important as several Category A bioterrorism diseases as well as avian influenza can manifest as pneumonia. Radiology text reports are often received within 1-2 days and may provide a faster way to identify pneumonia than coded diagnoses. Objective To study the performance of a simple keyword search of radiology reports for identifying pneumonia.

In response to increasing reports of avian influenza being identified throughout the eastern hemisphere, the World Health Organization and the U.S. Department of Health and Human Services have published pandemic influenza preparedness plans. These plans include detailed recommendations for routine influenza surveillance during ongoing interpandemic periods as well as recommendations for enhanced influenza surveillance during episodes of international, national, and local pandemic alerts. Like many states, the Connecticut Department of Public Health (DPH), prepared its own Pandemic Influenza Response Plan. The DPH has also been expanding its arsenal of surveillance systems. These systems include a syndromic surveillance system, known as the Hospital Admissions Surveillance System (HASS), developed in September 2001 to monitor for possible bioterrorism events and emerging infections. HASS data has been utilized to supplement information received from laboratoryconfirmed influenza test, influenza-like-illness reporting, and pneumonia influenza mortality to track seasonal influenza.

Objective

This paper examines the results of a review of state pandemic influenza preparedness plans and compares various approaches for routine influenza surveillance during interpandemic periods with approaches for enhanced surveillance during pandemic alerts. The results of this review are compared with the experience of using a hospital-based syndromic surveillance system as a supplement to laboratory and clinical influenza surveillance systems.

Methicillin resistant staphylococcus aureus (MRSA) is a leading cause of skin and soft tissue infections (SSTI). Until recently, S. aureus pneumonia has been considered primarily a nosocomial infection, and was reported infrequently as a cause of severe community-acquired pneumonia. In recent years, there have been several reports of MRSA community-acquired pneumonia cases associated with influenza among healthy individuals resulting in hospitalization or death. During the 2007-08 influenza season, the WA DOH received reports of necrotizing staphylococcus pneumonia associated with flu-like illness and confirmed flu; these included severe cases of pneumonia caused by MRSA. We examined data from our biosurveillance system to describe trends in staphylococcus infection among ED patients and patients hospitalized with pneumonia or influenza in King County, WA.

Objective

We used our biosurveillance system to describe trends in emergency department visits for SSTI as well as staphylococcus pneumonia hospitalization trends.

We sought to evaluate the validity of pneumonia and influenza hospitalizations (PI) data gathered by our biosurveillance system.