Author: Amitava Banerjee; Laura Pasea; Steve Harris; Arturo Gonzalez-Izquierdo; Ana Torralbo; Laura Shallcross; Mahdad Noursadeghi; Deenan Pillay; Christina Pagel; Wai Keong Wong; Claudia Langenberg; Bryan Williams; Spiros Denaxas; Harry Hemingway
Title: Estimating excess 1- year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adults Document date: 2020_3_24
ID: 11hi1jel_63
Snippet: This rapid communication was developed over a 72-hour period prior to posting the results on 22 March 2020; and will be peer reviewed in due course. We seek to work with others to report further estimates of prevalence and mortality for cancer, pregnancy and chemotherapy, cause-specific mortality and cause specific hospital admissions (particularly respiratory) and critical care admissions, as well as the further conditions listed today (22 March.....
Document: This rapid communication was developed over a 72-hour period prior to posting the results on 22 March 2020; and will be peer reviewed in due course. We seek to work with others to report further estimates of prevalence and mortality for cancer, pregnancy and chemotherapy, cause-specific mortality and cause specific hospital admissions (particularly respiratory) and critical care admissions, as well as the further conditions listed today (22 March 2020) (organ transplants, cystic fibrosis, specific cancers of the blood or bone marrow and immunosuppression (12) . There are many avenues for further modelling to better understand how to target different preventive interventions. An (incomplete) list includes statistical aspects (dynamic models, weekly rates of mortality, competing risks), public health aspects (regional variation, social deprivation and ethnicity), clinical aspects (including hospital and critical care admissions) and health service factors (including data on healthcare workers, and operational features). We have assumed that the impact (RR) of COVID-19 on excess mortality is the same across all risk groups, irrespective of how they are combined, which may not be the case. However, we researchers can use the estimate that we provide to allow modelling of such interactions in different subgroups within populations. We prioritised sharing estimates of 1-year mortality at a time when all clinical academics in the UK and around the globe are being called to the frontline (40) . In these times, our science must cross disciplines, disease specialisms and national and jurisdictional borders even more than before and we invite colleagues to improve, develop and validate our models and update estimates and projections using richer, more real time real-world data.
Search related documents:
Co phrase search for related documents- bone marrow and critical care: 1, 2, 3, 4, 5
- bone marrow and cystic fibrosis: 1, 2, 3, 4
- care admission and cause specific mortality: 1
- care admission and clinical academic: 1, 2
- care admission and clinical aspect: 1
- care admission and critical care: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- care admission and critical care admission: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- care admission and critical care hospital: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- care admission and critical care hospital admission: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- care admission and cystic fibrosis: 1, 2, 3, 4, 5
- cause specific mortality and critical care: 1
- clinical academic and critical care: 1, 2, 3, 4, 5, 6, 7, 8
- clinical academic and critical care hospital: 1
- clinical aspect and critical care: 1, 2
- critical care admission and cystic fibrosis: 1
- critical care and cystic fibrosis: 1, 2, 3, 4, 5
- critical care hospital and cystic fibrosis: 1
Co phrase search for related documents, hyperlinks ordered by date