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Sheena G. Sullivan

Researcher at Royal Melbourne Hospital

Publications -  160
Citations -  6763

Sheena G. Sullivan is an academic researcher from Royal Melbourne Hospital. The author has contributed to research in topics: Population & Influenza vaccine. The author has an hindex of 37, co-authored 144 publications receiving 5280 citations. Previous affiliations of Sheena G. Sullivan include Chinese Center for Disease Control and Prevention & University of Western Australia.

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Decreased Influenza Activity During the COVID-19 Pandemic - United States, Australia, Chile, and South Africa, 2020.

TL;DR: The use of community mitigation measures for the COVID-19 pandemic, plus influenza vaccination, are likely to be effective in reducing the incidence and impact of influenza, and some of these mitigation measures could have a role in preventing influenza in future seasons.
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Evolution of China's response to HIV/AIDS

TL;DR: Four factors have driven China's response to the HIV/AIDS pandemic: existing government structures and networks of relationships, increasing scientific information, external influences that underscored the potential consequences of an HIV/ AIDS pandemic, accelerated strategic planning, and increasing political commitment at the highest levels.
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The Influence of Intellectual Disability on Life Expectancy

TL;DR: A study of trends in the survival profiles of people with intellectual disability in Western Australia indicates a major and expanding increase in the service requirements of this aging, intellectually disabled population during the past two generations.
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The changing survival profile of people with Down's syndrome: implications for genetic counselling.

TL;DR: The substantial increase in survival across the study period means that the life expectancy of people with Down's syndrome is approaching that of the general population, but accompanied by a range of significant mid‐life health problems.
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Theoretical Basis of the Test-Negative Study Design for Assessment of Influenza Vaccine Effectiveness.

TL;DR: Direct acyclic graphs are used to characterize potential biases in studies of influenza vaccine effectiveness using the test-negative design and show how studies using this design can avoid or minimize bias and where bias may be introduced with particular study design variations.