ABSTRACT
Summary In this chapter, we describe the main molecular features of SARS-CoV-2 that cause COVID-19 disease, as well as a high-efficiency computational prediction called Polarity Index Method?. We also introduce a molecular classification of the RNA virus and DNA virus families and two main classifications: supervised and non-supervised algorithms of the predictions of the predominant function of proteins. Finally, some results obtained by the proposed non-supervised method are given, as well as some particularities found about the linear representation of proteins. Background Due to the global pandemic, governments have enforced household isolation and social distancing to reduce infection and mortality rate. However, the impact of prolonged enforced isolation for older people who are prone to social isolation and loneliness has yet to be understood. Objectives A longitudinal study to understand the lived experience of people aged 70 and older, living in England during COVID-19 restrictions. Methods All participants completed five qualitative telephone interviews from 20 April to 7 July 2020. The majority completed individual interviews (n = 13), whilst two participants completed these interviews as a couple. Interviews were audio-recorded, transcribed verbatim and thematic analysis completed from the perspective of hermeneutic phenomenology. Results Three themes included (1) engagement and confusion with government restrictions;(2) socialisation through virtual platforms and opportunistic physical social contact;and (3) accessing health care during COVID-19 restrictions. Conclusion Older people are committed to following government restrictions, and government campaigns need to consider the potential impact of placing an emphasis on avoiding healthcare services. Virtual platforms are supportive but not sufficient to reduce social isolation and loneliness of older people. Thus, nurses supporting older people living in the community need to understand these concepts to provide holistic care and support older people's mental and physical health. Implications for practice Nurses are ideally placed to support older people to understand the current government restrictions, when to attend acute healthcare services or to engage virtually with healthcare appointments, and to discuss the risks of physically socialising with others.
ABSTRACT
Summary In this chapter, we describe the main molecular features of SARS-CoV-2 that cause COVID-19 disease, as well as a high-efficiency computational prediction called Polarity Index Method?. We also introduce a molecular classification of the RNA virus and DNA virus families and two main classifications: supervised and non-supervised algorithms of the predictions of the predominant function of proteins. Finally, some results obtained by the proposed non-supervised method are given, as well as some particularities found about the linear representation of proteins.