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Influenza

Given the periodic nature of influenza activity, it is important to develop visualization tools that enable enhanced decision-making. User-Centered Design is a set of software development methodologies that primarily employ user needs to develop applications. Similarly, Usability Heuristics provide a set of rules that increase the performance of user interfaces, and ease of use. We combined some of these techniques to develop FluView Interactive, a prototype that will enable users to better understand influenza information.

 

Objective

The objective of this study is to report on the use of User-Centered Design and Usability Heuristics to improve visualization of influenza-related information at the national level. The intention of the prototype is to make data more accessible to different stakeholders including the general public, public health officials at the local and state level, and other experts.

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Submitted by hparton on

Syndromic surveillance has been widely adopted as a real-time monitoring tool in early response to disease outbreaks. In order to provide real-time information on the impact of 2009 H1N1 during the Fall 2009 semester, Georgetown University (GU) and George Washington University (GWU) employed syndromic surveillance systems incorporating a variety of data sources. 

 

Objective

To describe the 2009 H1N1 outbreak at GU and GWU in Fall 2009. Identify the datasets that most accurately depict 2009 H1N1 disease in real time.

Referenced File
Submitted by hparton on

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.

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Submitted by uysz on

The use of syndromic surveillance systems to detect illness and outbreaks in the mid 1990s in New York City resulted in recommendations for increased use of these systems for detection of bioterrorist agents, and tracking influenza throughout the region. Discussions on approaches to best respond to surveillance system signals led to initial efforts to organize a coordinating group of various public health agencies throughout the New York City region. These efforts were strengthened after the events of September 11, 2001, and resulted in the development of a regional workgroup consisting of epidemiologists and other staff from all state, county, and municipal health departments who operate, respond to, or oversee public health preparedness surveillance systems throughout the greater New York City metropolitan area.

 

Objective

The rapid and effective coordination of the multi-jurisdictional communications and response to a surveillance system signal are an important goal of public health preparedness planning. This goal is particularly challenging if the signal indicates a possible risk that could adversely affect populations in multiple states and municipalities. This paper examines the value of a regional workgroup in the activation, integration, and coordination of multiple surveillance systems along with efforts to coordinate risk communication messaging. Recommendations for the development of similar groups in other regions are discussed.

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Submitted by hparton on

The novel strain of H1N1 Influenza A virus, which first caused localized outbreaks in parts of Mexico, was declared a pandemic in June 2009. The Centers for Disease Control and Prevention’s (CDC) Countermeasure and Response Administration System (CRA) was used to track the H1N1 vaccine uptake across population age groups during the first eight weeks of the event (3 October to 21 November 2009). The CRA application was utilized to track vaccine doses administered in the initial period of H1N1 vaccine campaign, as there was no other method available to inform how well the vaccine was reaching target age groups.

 

Objective

The objective of this paper is to report the use of the CDC CRA to track and monitor H1N1 doses administered during the initial weeks of the 2009–2010 H1N1 Vaccine Program when supplies of the vaccines were limited, and before population-based surveys like Behavioral Risk Factor Surveillance Systems, and National H1N1 Flu Survey could effectively monitor vaccine coverage.

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Submitted by hparton on

Quantifying the spatial-temporal diffusion of diseases such as seasonal influenza is difficult at the urban scale for a variety of reasons including the low specificity of the extant data, the heterogenous nature of healthcare seeking behavior and the speed with which diseases spread throughout the city. Nevertheless, the New York City Department of Health and Mental Hygiene’s syndromic surveillance system attempts to detect spatial clusters resulting from outbreaks of influenza. The success of such systems is dependent on there being a discernible spatial-temporal pattern of disease at the neighborhood (sub-urban) scale.

We explore ways to extend global methods such as serfling regression that estimate excess burdens during outbreak periods to characterize these patterns. Traditionally, these methods are aggregated at the national or regional scale and are used only to estimate the total burden of a disease outbreak period. Our extension characterizes the spatial-temporal pattern at the neighborhood scale by day. We then compare our characterizations to prospective spatial cluster detection efforts of our syndromic surveillance system and to demographic covariates.

 

Objective

To develop a novel method to characterize the spatial-temporal pattern of seasonal influenza and then use this characterization to: (1) inform the spatial cluster detection efforts of syndromic surveillance, (2) explore the relationship of spatial-temporal patterns and covariates and (3) inform conclusions made about the burden of seasonal and pandemic influenza. 

Referenced File
Submitted by hparton on

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.

Submitted by elamb on

Surveillance of severe influenza infections is lacking in the Netherlands. Ambulance dispatch (AD) data may provide information about severity of the influenza epidemic and its burden on emergency services. The current gold standard, primary care-based surveillance of influenza-like-illness (ILI), mainly captures mild to moderate influenza cases, and does not provide adequate information on severe disease. Monitoring the severity of the annual epidemic, particularly among groups most at risk of complications, is of importance for the planning of health services and the public health response.

Objective: We aim to assess whether influenza circulation, as measured through influenza-like-illness (ILI) in primary care, is reflected in ambulance dispatch (AD) calls.

Submitted by elamb on

Social media as Twitter are used today by people to disseminate health information but also to share or exchange on their health. Based on this observation, recent studies showed that Twitter data can be used to monitor trends of infectious diseases such as influenza. These studies were mainly carried out in United States where Twitter is very popular1-4. In our knowledge, no research has been implemented in France to know whether Twitter data can be a complementary data source to monitor seasonal influenza epidemic.

Objective: To investigate whether Twitter data can be used as a proxy for the surveillance of the seasonal influenza epidemic in France and at the regional level.

Submitted by elamb on

Although residents of LTCFs have high morbidity and mortality associated with ARIs, there is very limited information on the virology of ARI in LTCFs.[1,2] Moreover, most virological testing of LCTF residents is reactive and is triggered by a resident meeting selected surveillance criteria. We report on incidental findings from a prospective trial of introducing rapid influenza diagnostic testing (RIDT) in ten Wisconsin LTCFs over a two-year period with an approach of testing any resident with ARI.

Objective: To assess the feasibility of conducting respiratory virus surveillance for residents of long term care facilities (LTCF) using simple nasal swab specimens and to describe the virology of acute respiratory infections (ARI) in LCTFs.

Submitted by elamb on
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