Coronavirus (COVID-19) is a threat to individuals and health systems in all countries. Many countries have implemented social isolation policies to reduce spread of disease and to protect the people at highest risk of dying from COVID-19. On 16 March, the Chief Medical Officer announced a list of underlying conditions, such as chronic heart disease and lung disease, which put people at even higher risk of severe illness from COVID-19, recommending reduced social interaction (social distancing). On 22 March, further guidance added a group of 1.5 million individuals who were particularly vulnerable, such as organ transplant recipients, who should be having minimal contact with other people (shielding).
In order to understand an individuals risk of dying from COVID-19, we will develop and openly report definitions of these conditions in a reliable transparent way that can be used by others. We will estimate the frequency in the general population of each of the conditions on the high risk and vulnerable patient lists. It is important to understand their background risk of dying, even without COVID-19. We will use UK GP data and hospital records to study the risk of dying over 1 year from the conditions listed as high risk or extremely vulnerable for COVID-19 infection. We will then estimate the risk of dying from COVID-19 infection. We will explore with patients and health care professionals under what circumstances sharing information on risk might under different scenarios might help with adhering to the current lifechanging guidelines, and have other benefits. It is hoped that this information will enable people to make decisions about staying at home to prevent the spread of coronavirus, and to have conversations with your family and health professionals.
As countries around the world implement lockdown in the face of the COVID-19 epidemic, there are concerns about the sustainability and acceptability of such interventions. On 22 March the government announced that a life-changing intervention(shielding) was to be offered to 1.5million citizens in England who were extremely vulnerable, based on one of a wide range of serious health conditions, which is an historic development.
We aim to understand these underlying conditions using NHS records, specifically to: (i) develop and validate EHR phenotypes for each condition and share with the international research community on the HDR UK- CALIBER portal; (ii) estimate the age- and sex- specific prevalence of these conditions (iii) estimate age-, sex- and condition- specific background (pre-COVID-19) risk of 1-year mortality; (iv) estimate 1-year mortality risk under different assumptions of COVID-19 infection and (v) the importance of government policies regarding COVID-19 and social isolation interventions.
Using population-based linked primary and secondary care electronic health records in England (CPRD and HES, HDR UK - CALIBER), we will study underlying conditions defined by UK Public Health England COVID-19 guidelines (16 March 2020: high risk and 22 March 2020: extremely vulnerable) in individuals of all ages from 1997-2017. Using previously validated phenotypes (openly available for each condition using ICD-10 diagnosis, Read, procedure and medication codes), we will estimate age- and sex-specific background and COVID-19-related 1-year mortality in each condition, assuming a range of potential impact of the emergency (compared to background mortality): relative risk 1 to 5, and a population infection rate of 0.0001-80%.
We will explore the co-design an online tool with patients, public, researchers, clinicians, policymakers and public health professionals to provide information about COVID-19-related policies, background risk of mortality and risk of COVID-related mortality. Subject to stakeholder feedback and iterative improvement, we will work with policy makers to explore implementation of the tool for public use to inform the public of their own risk of baseline and COVID-related mortality.
- All-cause mortality
- cause specific mortality (respiratory, cardiovascular, chronic kidney disease, cancer, diabetes)
- critical care admissions
- cause specific hospital admissions (respiratory, cardiovascular, chronic kidney disease, cancer, diabetes)
Amitava Banerjee - Chief Investigator - University College London ( UCL )
Laura Pasea - Corresponding Applicant - University College London ( UCL )
Aasiyah Rashan - Collaborator - University College London ( UCL )
Alvina Lai - Collaborator - University College London ( UCL )
Amugoda Kankanamge Jayathri Manuja Wijayarathne - Collaborator - University College London ( UCL )
Ana Torralbo - Collaborator - University College London ( UCL )
Ana-Catarina Pinho-Gomes - Collaborator - University College London ( UCL )
Andrej Ivanovic - Collaborator - University College London ( UCL )
Anika Cawthorn (formerly Oellrich) - Collaborator - University College London ( UCL )
Anoop Shah - Collaborator - University College London ( UCL )
Arturo Gonzalez-Izquierdo - Collaborator - University College London ( UCL )
Chris Finan - Collaborator - University College London ( UCL )
Dominic Crocombe - Collaborator - University College London ( UCL )
Evaleen Malgapo - Collaborator - University College London ( UCL )
Hanane Issa - Collaborator - University College London ( UCL )
Harry Hemingway - Collaborator - University College London ( UCL )
Johan Thygesen - Collaborator - University College London ( UCL )
Jorgen Engmann - Collaborator - University College London ( UCL )
Jurgita Kaubryte - Collaborator - University College London ( UCL )
Linghui Gong - Collaborator - University College London ( UCL )
Matiwalakumbura Dilan - Collaborator - University College London ( UCL )
Maureen Ng'etich - Collaborator - University College London ( UCL )
Mehrdad Alizadeh Mizani - Collaborator - University College London ( UCL )
Michail Katsoulis - Collaborator - Farr Institute of Health Informatics Research
Mohamed Mohamed - Collaborator - University College London ( UCL )
Muhammad (Ashkan) Dashtban - Collaborator - University College London ( UCL )
Muhammad Qummer ul Arfeen - Collaborator - University College London ( UCL )
Nel Swanepoel - Collaborator - University College London ( UCL )
Sheng-Chia Chung - Collaborator - University College London ( UCL )
Spiros Denaxas - Collaborator - University College London ( UCL )
Stefanie Mueller - Collaborator - University College London ( UCL )
Suliang Chen - Collaborator - University College London ( UCL )
Vaclav Papez - Collaborator - University College London ( UCL )
Valerie Kuan - Collaborator - University College London ( UCL )
Weerakkody Mudiyanselage Ravi Rajith Wickramaratne - Collaborator - University College London ( UCL )
Yen Yi Tan - Collaborator - University College London ( UCL )
Anoop Shah - Collaborator - University College London ( UCL )
Nel Swanepoel - Collaborator - University College London ( UCL )
Evaleen Malgapo - Collaborator - University College London ( UCL )
Hanane Issa - Collaborator - University College London ( UCL )
Muhammad Qummer ul Arfeen - Collaborator - University College London ( UCL )
Vaclav Papez - Collaborator - University College London ( UCL )
HES Accident and Emergency;HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation