Vaccination

Since hepatitis A vaccination became widely recommended in the US in the mid-1990's, rates of acute hepatitis A virus (HAV) infection have steadily declined, however, since 2011, incidence of new cases of HAV appears to be increasing1, often linked with foodborne outbreaks and socio-economic trends such as homelessness and substance abuse.2 In 2016, the CDC reported vaccination coverage among adults aged > 19 was 9.5%, 19-49 was 13.4%, and > 50 was 5.4%3. CDC issued a Health Alert Network Advisory in June 2018 with additional guidance on identification and prevention of HAV and updates on outbreaks in multiple states4 which prompted our program to conduct a more formal review of HAV infections in VHA. Herein we describe recent trends in HAV infection, vaccination and associated risk factors among Veterans.

Objective: To describe the epidemiology of hepatitis A virus (HAV) within the Veterans Health Administration (VHA).

After the 2009 H1N1 influenza pandemic, CDC initiated community-based surveillance of self-reported influenza-like illness (ILI)[1], defined as the presence of fever with cough or sore throat. Although ILI is frequently attributed to other pathogens, including rhinovirus, routine surveillance of ILI at the population level does aid in the detection of nascent influenza outbreaks. In the United States, approximately 90% of influenza-related deaths occur among adults aged 65 years and older[2]. We explored the association of influenza vaccination with ILI, among this vulnerable age group.

Objective

To explore the association of influenza vaccination with Influenza-like illness ( ILI) among adults aged 65 years and older

Historically, it has been the role of local health departments to administer, monitor, and report flu vaccinations of its residents to the state health department. In 2009, the looming threat of an influenza outbreak (H1N1) led to the extension of the Public Readiness and Emergency Preparedness Act (PREP) (1). On June 15, 2009, Kathleen Sebelius, Secretary of Health and Human Services, assigned all entities, including organizational and individual, tort liability immunity in the distribution and administration of H1N1 vaccines (1). This extension subsequently impaired local health departments ability to capture accurate estimates of flu immunizations being administered to their respective populations. Stark County Health Department, located in Ohio, in collaboration with Kent State University's College of Public Health, designed, developed, and deployed FITS based on the urgent need of accurate population data regarding influenza immunization at the county level.

Objective

To develop and implement a web-based, county-level flu immunization record keeping system that accurately tracks non-identifiable vaccine recipients and seamlessly uploads to the state record keeping system.

Work on vaccination timing and promotion largely precedes the 2009 pandemic. Post-pandemic studies examining the wide range of local vaccination efforts mostly have been limited to surveys assessing the role of administrative strategies, logistical challenges, and perceived deterrents of vaccination [1].

Objective

To assess the effectiveness of a Public Health automated phone campaign to increase vaccination uptake in targeted neighborhoods. To identify alternative predictors of variation in vaccination uptake, specifically to assess the association between vaccination uptake, and weather conditions and day-of-week.

Currently Scotland has a number of influenza surveillance schemes, including âflu-spotter’ practices, and enhanced surveillance general practices that submit clinical samples for virological testing (SERVIS practices). This information feeds annually into the European Influenza Surveillance Scheme1. Information from the systems is seasonal, and limited geographically covering 6% and 3% of the population respectively. The utilisation by Scottish community physicians (general practitioners, GP’s) of the same administration system in over 80% of settings - the General Practice Administration System for Scotland (GPASS) - offers an alternative approach to influenza surveillance with some additional benefits.

Objective

To develop and pilot an enhanced primary care surveillance system of influenza-like illness in Scotland, record influenza vaccine uptake and estimate vaccine effectiveness in season in real time.

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.

Aerial transmission and direct contact are important factors for flu. Consequently, close contact with large groups of people, such as during mass transit, present opportunities for transmission. One protective method that decreases the probabilities of becoming ill is vaccination. The potential health impact of  erminating subway service during a flu epidemic depends on both the potential for transmission and vaccination rates among riders. Mass transit, a major method of transit in NYC, exhibits a non-random distribution of riders based on demographics and socio-economic status. There is also a trend in vaccination rates by demography and socio-economic status. This analysis uses individual-based data on vaccination and ridership to separately predict vaccination and ridership for inclusion in agent-based models that can be used to assess impact of public health interventions.

Objective

Agent-based models (ABMs) have been developed to simulate epidemics including smallpox and pandemic flu. The ABM approach is an effective method to assess the potential impact of interventions on disease spread. Integrating the ABM approach with syndromic surveillance data provides potential benefits such  as permitting a realistic specification of some critical model contact parameters, and permitting synthetic outbreaks to be generated with extremely fine resolution (e.g., age, gender, and address). This would provide the ability to test various clustering detection algorithms – a key component of syndromic surveillance methods. RTI International (the Models of Infectious Disease Agent Study (MIDAS) informatics group) and NYC DOHMH (a premier syndromic surveillance research center) collaborated to create a NYC-ABM of flu transmission. This poster describes implementation of several features required for accurate model specification, including assigning immunization rates and subway ridership. Incorporating subway ridership is of great interest, because a large subway system, like the NYC system, has never been investigated as a contributor of disease spread.