The Diplom thesis will deal with the economic-mangerial evaluation of the incidence of swine flu in 2009 - 2010, with emphasis on epidemic data, a vector of its spreading and the consequences of the disease. The work will also deal with the effect of vaccination. The main objective of the presented diplom thesis is the evaluation of the economic consequences related to its outbreak.

Thesis (Ph. D.)--Ohio State University, 2002. / Title from first page of PDF file. Document formatted into pages; contains xii, 97 p.; also contains graphics (some col.). Includes abstract and vita. Advisor: Ming-Daw Tsai, Dept. of Chemistry. Includes bibliographical references (p. 92-97).

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Introduction: H1N1 flu (swine flu) first emerged in mid-April 2009, and the Centers for Disease Control and Prevention (CDC) was a lead U.S. federal agency responding to the disease, the first pandemic in more than 40 years. Aim: The purpose of this program evaluation is to assess CDC’s Web-based outreach for the first part of the H1N1 flu pandemic (April to July 2009). Evaluation focuses on the seven CDC Web sites used for H1N1 flu outreach: H1N1 Flu (English and Spanish), CDC.gov, CDC en Español, CDC Partners, CDC Seasonal Flu, and MMWR. Methods: The evaluation assessed Web use and users through data collected by the American Consumer Satisfaction Index (ACSI) and specific Web statistics gathered through Omniture SiteCatalyst. Discussion: People have been using the internet to collect health information since the early days of popular usage. During the early H1N1 flu emergency, CDC used seven different Web sites to reach out to its users, who are primarily public health professionals, healthcare providers and consumers. Most users cite one of four reasons for visiting CDC’s Web sites: health information for my work, health information for myself, health information for patient or client, and health information for someone else. Between April and July, a clear majority of users visited the Web site for H1N1 flu information (from a high of 58% in May to a low of 35% in July). CDC.gov has received ACSI satisfaction scores of 80 (considered a top performer) or higher since the first quarter of 2007; the overall site satisfaction score of 82 during the first quarter of 2009 was bested by the H1N1-specific satisfaction score of 84 from mid-April to the end of June. Traffic to the site increased enormously during the early H1N1 flu emergency, from approximately 45 million page views per month in February and March 2009 to more than 98.2 million page views in April 2009. Recommendations: Those working on CDC.gov H1N1 flu-related content should continue trying to anticipate and meet user needs by expanding Web content, partnering with external organizations to share key information through syndication and information placement, and enhancing translation capabilities.

This paper examines the correlates of seasonal flu vaccination in Canada between 2000 and 2011. In terms of the socio-economic characteristics of the population that relate to higher take-up, my findings are consistent with the previous literature. Specifically, the most important predictors of vaccination are the risk factors: age and chronic conditions. My results also suggest that both novel respiratory disease outbreaks and provincial immunization program design are important determinants of the seasonal flu vaccine take-up. The absence of a separate vaccine intended to protect from a novel virus during its epidemic could increase the seasonal flu vaccine take-up. In cases when a separate vaccine is offered, the seasonal flu vaccine take-up depends on the timing of vaccines’ delivery and the extent of prior influenza immunization coverage for a specific population subgroup in a province.

abstract: ABSTRACT The cold and the flu are two of the most prevalent diseases in the world. Many over the counter (OTC) medications have been created to combat the symptoms of these illnesses. Some medications take a holistic approach by claiming to alleviate a wide range of symptoms, while others target a specific symptom. As these medications become more ubiquitous within the United State of America (USA), consumers form associations and mental models about the cold/flu field. The goal of Study 1 was to build a Pathfinder network based on the associations consumers make between cold/flu symptoms and medications. 100 participants, 18 years or older, fluent in English, and residing in the USA, completed a survey about the relatedness of cold/flu symptoms to OTC medications. They rated the relatedness on a scale of 1 (highly unrelated) to 7 (highly related) and those rankings were used to build a Pathfinder network that represented the average of those associations. Study 2 was conducted to validate the Pathfinder network. A different set of 90 participants with the same restrictions as those in Study 1 completed a matching associations test. They were prompted to match symptoms and medications they associated closely with each other. Results showered a significant negative correlation between the geodetic distance (the number of links between objects in the Pathfinder network) separating symptoms and medications and frequency of pairing symptoms with medication. This provides evidence of the validity of the Pathfinder network. It was also seen that, higher the relatedness rating between symptoms and medications in Study 1, higher the frequency of pairing symptom to medication in Study 2, and the more directly linked those symptoms and medications were in the Pathfinder network. This network can inform pharmaceutical companies about which symptoms they most closely associate with, who their competitors are, what symptoms they can dominate, and how to market their medications more effectively. / Dissertation/Thesis / Masters Thesis Engineering 2020

The seasonal influenza (flu) vaccine has been shown to prevent flu outbreaks that can cause debilitating effects on the body and even death. Underserved members of Black communities are more likely to refuse the flu vaccine than are persons of other ethnicities. The purpose of the project was to determine from a needs assessment the reasons for flu vaccine refusal in the Black population of an inner city clinic in order to develop tailored communication and nursing actions that promote awareness of the flu vaccine's importance and safety. The health belief model constructs (perceived susceptibility, perceived severity, perceived benefits, and perceived barriers) were used to guide the project. A survey based on the constructs of the health belief model was administered to a convenience sample of 40 adult patients in an inner city clinic who completed the anonymous survey while they waited for the physician. Descriptive statistics showed that adults ages 18 to 36, who were the largest group of respondents (n = 33), agreed to be vaccinated and believed the flu to be a serious disease for their age group. Reported barriers to vaccination included finding time to get vaccinated and the belief that the vaccine causes the flu. The findings supported development of an annual seasonal flu vaccine campaign that included verbal and written education, informational posters, social media messages, and a standing order to offer and administer the injection to all adults served by the practice. Social change implications are expected to include decreased morbidity and mortality from flu among the Black inner city patients and closer alignment of the clinic with the Healthy People 2020 vaccination goals.

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published_or_final_version / Microbiology / Doctoral / Doctor of Philosophy

Seasonal influenza epidemics are a major public health concern, causing three to five million cases of severe illness and about 250,000 to 500,000 deaths worldwide. Given the unpredictability of these epidemics, hospitals and health authorities are often left unprepared to handle the sudden surge in demand. Hence early detection of disease activity is fundamental to reduce the burden on the healthcare system, to provide the most effective care for infected patients and to optimize the timing of control efforts. Early detection requires reliable forecasting methods that make efficient use of surveillance data. We developed a dynamic Bayesian estimator to predict weekly hospitalizations due to influenza related illnesses in the state of Texas. The prediction of peak hospitalizations using our model is accurate both in terms of number of hospitalizations and the time at which the peak occurs. For 1-to 8 week predictions, the predicted number of hospitalizations was within 8% of actual value and the predicted time of occurrence was within a week of actual peak. / text