COVID-19 management in social care in England: a systematic review of changing policies and newspaper reported staff perspectives.

Adult social care has been a major focus of public attention and infection control guidance during the COVID-19 pandemic, with a high mortality both for carers and those receiving care. To protect themselves and others from infection, staff in residential and domiciliary care settings had to quickly adapt to infection control measures that heavily impacted on their working and every-day life, whilst navigating new responsibilities, uncertainties and anxieties. We sought to explore the production and reception of guidance and look at ways these can be adapted to improve the working life of care staff in domiciliary and residential care whilst reducing the risk of SARS-CoV-2 transmission amid this pandemic and of future emerging infections. We conducted two complementary and integrated systematic reviews of published documents in the pre-vaccination era: (1) National guidance for social care (conducted between 29 July to 28 October 2020), and (2) Newspaper coverage of infection control issues in social care (conducted between 27th July to 10th September 2020). Three higher order common themes emerged in the integrated systematic review of guidance documents and newspaper articles: a) Testing, b) Personal Protective Equipment, c) Employment. The reviews revealed a sharp disjunction between the content of infection control guidance and its usability and applicability in social care settings. We suggest that infection control guidance needs to be better adapted to social care settings and informed by the sector. The practicalities of care work and care settings need to be at the core of the process for guidance to be relevant and effective. Modes and timings of communications also need to be optimised.

How can risk of COVID-19 transmission be minimised in domiciliary care for older people: development, parameterisation and initial results of a simple mathematical model

This paper proposes and analyses a stochastic model for the spread of an infectious disease that is transmitted between clients and care workers in the UK domiciliary care setting. Interactions between clients and care workers are modelled using specially generated networks, with network parameters reflecting realistic patterns of care needs and visit allocation. These networks are then used to simulate and SEIR-type epidemic dynamics with different numbers of infectious and recovery stages. The results indicate that with the same overall capacity provided by care workers, the minimum peak proportion of infection, and the smallest overall size of infection are achieved for the highest proportion of overlap between visit allocation, i.e. when care workers have the highest chances of being allocated a visit to the same client they have visited before. An intuitive explanation of this is that while providing the required care coverage, maximising overlap in visit allocation reduces the possibility of an infectious care worker inadvertently spreading the infection to other clients. The model is quite generic and can be adapted to any particular directly transmitted infectious disease, such as, more recently, COVID-19, provided accurate estimates of disease parameters can be obtained from real data.