OBJECTIVES: Reporting of COVID-19 cases, deaths and testing has often lacked context for appropriate assessment of disease burden within risk groups . The research considers how routine surveillance data might provide initial insights and identify risk factors, setting COVID-19 deaths early in the pandemic into context . This will facilitate the understanding of wider consequences of a pandemic from the earliest stage, reducing fear, aiding in accurately assessing disease burden and ensuring appropriate disease mitigation .
SETTING: UK , 2020 .
PARTICIPANTS: The study is a secondary analysis of routine, public domain, surveillance data and information from Office for National Statistics (ONS), National Health Service (NHS) 111 and Public Health England (PHE) on deaths and disease . PRIMARY AND SECONDARY OUTCOME MEASURES: Our principal focus is ONS data on deaths mentioning COVID-19 on the death certificate . We also consider information provided in NHS 111 and PHE data summaries .
RESULTS: Deaths with COVID-19 significantly contributed to, yet do not entirely explain, abnormally elevated all-cause mortality in the UK from weeks 12-18 of 2020 . Early in the UK epidemic, COVID-19 was the greatest threat to those with underlying illness, rarely endangering people aged under 40 years . COVID-19-related death rates differed by region, possibly reflecting underlying population structure . Risk of COVID-19-related death was greater for healthcare and social care staff and black, Asian and minority ethnic individuals, having allowed for documented risk factors .
CONCLUSION: Early contextualisation of public health data is critical to recognising who gets sick, when and why . Understanding at-risk groups facilitates a targeted response considering indirect consequences of society's reaction to a pandemic alongside disease-related impacts . COVID-19-related deaths mainly mirror historical patterns, and excess non-COVID-19-related deaths partly reflect reduced access to and uptake of healthcare during lockdown . Future outbreak response will improve through better understanding of connectivity between disease monitoring systems to aid interpretation of disease risk patterns, facilitating nuanced mitigation measures.
Index: COVID-19, epidemiology, public health, statistics & research methods