Creation Of Working Group Research Articles

From SARS to COVID-19: the role of experience and experts in Hong Kong’s initial policy response to an emerging pandemic

As one of the most densely populated places in the world, Hong Kong fared relatively well in the first year of the COVID-19 pandemic, with a very low number of cases and fatalities per capita. This was mostly due to the Hong Kong government, healthcare workers, and the general public’s institutional and individual memory after they successfully overcame the deadly severe acute respiratory syndrome (SARS) epidemic in 2003. However, while Hong Kong was well accustomed to measures such as wearing masks and social distancing, the cooperation of the Hong Kong public to government restrictions was highly affected by its local political context, especially after widespread anti-government protests began mid-2019. This brought the public’s trust in government to an all-time low, creating a political ‘new normal’, which underpinned how COVID-19 policies would be proposed, accepted, and implemented, if at all. To understand how science advice was offered and how public health decisions were made, this research investigates the evolution of Hong Kong’s science advisory mechanisms for public health from before SARS, after SARS, and during COVID-19 in 2020, including the roles of key organisations and departments, the establishment of new centres and committees, and the creation of workgroups and expert advisory panels. This paper compares and analyses the reasons behind these differences in science advisory mechanisms between SARS and COVID-19. The findings from this research reinforce the unquestionable need for robust science advisory structures and knowledgeable scientific experts to solve health-related crises, though more research is required to understand the ways in which science advice influences both policy decisions and public acceptance of these policies.

FUZZY RECURSIVE RELATIONSHIPS IN RELATIONAL DATABASES

Recursive relationships are used for modelling problems coming from the real life, such as, for example, a relationship describing formal dependencies between employees of an enterprise, where creation of work groups and teams requires analysis of many elements. In conventional database systems, the precision of data is assumed. If our knowledge of the fragment of reality to be modelled is imperfect one should apply tools for describing uncertain or imprecise information. One of them is the fuzzy set theory. The paper deals with recursive relationships in fuzzy databases. The analysis is performed with the use of the theory of interval-valued fuzzy sets. A definition of a fuzzy interval recursive relationship has been presented. The paper defines different connections of entities which participate in such relationships. Op-erations of the extended relational algebra are also discussed.