Influenza

Influenza poses a global health threat. The disease affects all ages, often with variable clinical features.

Abidjan, where this study took place, has a long rainy season April-July with a shorter less intense rainy season October-November. Temperatures vary very little during the year. In temperate areas, children and adults aged >=65 years are risk groups. In these countries the seasonality of influenza is clearly defined, with seasonal epidemics in cold weather periods. But in the tropics, the risk groups of influenza are not as well defined. Also, the dynamics of influenza transmission and climatological parameters that influence it are specific to the tropical region and not as thoroughly studied.

Objective

This study aims to determine the epidemiological and clinical profiles of influenza infections related to different strains and the effect of climatological parameters on the temporal distribution of the disease for the prediction.

GFT is a surveillance tool that gathers data on local internet searches to estimate the emergence of influenza-like illness in a given geographic location in real time.3 Previously, GFT has been proven to strongly correlate with influenza incidence at the national and regional level.2,3 GFT has shown promise as an easily accessed tool to enhance influenza surveillance and forecasting; however, further geographic validation of city-level data is needed. 1,2,6

Objective

To test if Google Flu Trends (GFT) is predictive of the volume of influenza and pneumonia emergency department (ED) visits across multiple United States cities.

 

In Mozambique about 10% of deaths in children are due to ARI. Although influenza (Flu) virus may be implicated in these infections, little is known about the circulation of this virus in the country. Thus, Mozambique implemented the influenza surveillance based on sentinel sites, facing a great challenge due to several factors. One of them is the proper influenza case definition along with others challenges since its international standardization is difficult. In order to get insights to the epidemiology of flu we reviewed the first year of surveillance implementation monitoring data to improve procedures.

Objective

Analyse challenges of the first year of surveillance implementation in Mozambique, according to samples income, hospital staff performance and available tools.

Compare two influenza surveillance approaches

Standardized electronic pre-diagnostic information is routinely collected in Alberta, Canada. ARTSSN is an automated real-time surveillance data repository able to rapidly refresh data that include school absenteeism information, calls about health concerns from Health Link Alberta; a provincial telephone service for health advice and information, and emergency department visits categorized by standardized chief complaint. Until recently, real-time ARTSSN data for public health surveillance and decision making has been underutilized.

Objective

We developed early warning algorithms using data from ARTSSN and used them to detect signatures of potential pandemics and provide regular weekly forecasts on influenza trends in Alberta during 2012-2014.

The influenza A(H7N9) virus emerged in early 2013 in China, with more than 130 laboratory-confirmed cases identified within a short period of about three months. Evidence-based public health response is essential for effective control of the disease, which relies on epidemiological and clinical data with good quality and timeliness. Publicly available information from sources such as official health website, online news, blogs or social media has the potential of rapid sharing of data to a wide community of experts for more comprehensive analyses. In our study we described the strength and limitation of these data for various types of epidemiological inferences.

Objective

This study described the strength and limitation of using line lists that built on publicly available data in various types of epidemiological inferences during the H7N9 epidemic in China, 2013.

VA began using ESSENCE as a public health surveillance tool in 2005. The system offered alerting capability for pre-defined syndromes and querying capability for outpatient ICD-9 diagnosis codes. Herein, we highlight examples of how we have invested in upgrades to analytic capabilities and expanded data sources available to ESSENCE in order to augment the overall utility of this system within VA.

Objective

To describe VA’s experience developing innovative and alternative uses of a surveillance system and improve the overall value proposition of this tool for the agency.