The public health importance of scabies in community domiciliary care settings: an exploratory cross-sectional survey of Health Protection Teams in England

A cross-sectional survey of knowledge and attitudes towards scabies control in Australian aged care facilities

Scabies outbreaks cause significant morbidity and disruption in aged care facilities and other institutional settings. Failure to manage scabies outbreaks may be attributable to low awareness amongst healthcare workers. A survey was distributed to healthcare workers across aged care facilities in South-East Queensland, Australia. The survey captured demographics, prior scabies experience, knowledge-based questions, and attitudes. Scabies was common in aged care facilities, with 41% of 128 respondents encountering the disease while working in aged care. Participants demonstrated sound theoretical knowledge regarding scabies (median knowledge score 82%). Scabies knowledge was not associated with years of experience in the sector or educational level but was associated with respondent age (p = 0.017). Knowledge gaps were evident regarding diagnosis, incubation periods, and treatment. Respondents demonstrated an inconsistent ability to identify atypical clinical presentations of scabies, showing discordance between theoretical knowledge and its practical application. The ability to identify crusted scabies was low, reflecting the high frequency of misdiagnosis of index cases in scabies outbreaks. Respondents considered scabies to be a problem and were supportive of improved management guidelines. These study outcomes will inform the design of accessible, targeted educational resources for scabies to help prevent and reduce the impact of outbreaks.

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 transmitted between clients and care workers in the UK domiciliary (home) 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 a susceptible-exposed-infected-recovered/dead (SEIR/D)-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 generic and can be adapted to any directly transmitted infectious disease, such as, more recently, corona virus disease 2019, provided accurate estimates of disease parameters can be obtained from real data.