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The COVID-19 pandemic has dramatically impacted cancer care worldwide. Disruptions have been seen across all facets of care. While the long-term impact of COVID-19 remains unclear, the immediate impacts on patients, their carers and the healthcare workforce are increasingly evident. This study describes disruptions and reorganisation of cancer services in Australia since the onset of COVID-19, from the perspectives of people affected by cancer and healthcare workers. Two separate online cross-sectional surveys were completed by: a) cancer patients, survivors, carers, family members or friends (n = 852) and b) healthcare workers (n = 150). Descriptive analyses of quantitative survey data were conducted, followed by inductive thematic content analyses of qualitative survey responses relating to cancer care disruption and perceptions of telehealth. Overall, 42% of cancer patients and survivors reported experiencing some level of care disruption. A further 43% of healthcare workers reported atypical delays in delivering cancer care, and 50% agreed that patient access to research and clinical trials had been reduced. Almost three quarters (73%) of patients and carers reported using telehealth following the onset of COVID-19, with high overall satisfaction. However, gaps were identified in provision of psychological support and 20% of participants reported that they were unlikely to use telehealth again. The reorganisation of cancer care increased the psychological and practical burden on carers, with hospital visitation restrictions and appointment changes reducing their ability to provide essential support. COVID-19 has exacerbated a stressful and uncertain time for people affected by cancer and healthcare workers. Service reconfiguration and the adoption of telehealth have been essential adaptations for the pandemic response, offering long-term value. However, our findings highlight the need to better integrate psychosocial support and the important role of carers into evolving pandemic response measures. Learnings from this study could inform service improvements that would benefit patients and carers longer-term.

Introduction The Chief Medical Officer for England recommends that healthcare workers have a seasonal influenza vaccination in an attempt to protect both patients and NHS staff. Despite this, many healthcare workers do not have a seasonal influenza vaccination. Social network analysis is a well-established research approach that looks at individuals in the context of their social connections. We examine the effects of social networks on influenza vaccination decision and disease dynamics. Methods We used a social network analysis approach to look at vaccination distribution within the network of the Lancaster Medical School students and combined these data with the students’ beliefs about vaccination behaviours. We then developed a model which simulated influenza outbreaks to study the effects of preferentially vaccinating individuals within this network. Results Of the 253 eligible students, 217 (86%) provided relational data, and 65% of responders had received a seasonal influenza vaccination. Students who were vaccinated were more likely to think other medical students were vaccinated. However, there was no clustering of vaccinated individuals within the medical student social network. The influenza simulation model demonstrated that vaccination of well-connected individuals may have a disproportional effect on disease dynamics. Conclusions This medical student population exhibited vaccination coverage levels similar to those seen in other healthcare groups but below recommendations. However, in this population, a lack of vaccination clustering might provide natural protection from influenza outbreaks. An individual student’s perception of the vaccination coverage amongst their peers appears to correlate with their own decision to vaccinate, but the directionality of this relationship is not clear. When looking at the spread of disease within a population it is important to include social structures alongside vaccination data. Social networks influence disease epidemiology and vaccination campaigns designed with information from social networks could be a future target for policy makers.