Title: RESTORE - Research for Equitable SySTem RespOnse and REcovery
Funder: Department of Health and Social Care

Abstract: Background The COVID-19 crisis has hit the most disadvantaged hardest, increasing inequalities. The emerging risks to health are multiple, complex, cross-sectoral, and rapidly changing. The control measures have led to delays in screening and diagnoses for cancer, vaccination uptake, and interruption to schooling and child protection services. The economic recession caused by the pandemic has led to increased poverty, homelessness and food poverty. To effectively respond to these risks local systems are using linked data to segment the population, for example through the COVID-19 shielding programme, to identify at-risk population groups in order to target limited resources to prevent adverse outcomes. The health and health inequalities impact of these approaches is not known. We do not know the most effective approaches for identifying &ldquo;at risk&rdquo; groups for many of these outcomes or whether better targeting of support at these groups effectively reduces their risk. Research questions Which population groups are at increased risk of (1) hospitalisation and mortality (2) mental health problems, (3) adverse childhood outcomes during the COVID-19 crisis and what are the mechanisms driving increased risk and how are they changing over time? How effective have current approaches to risk segmentation been at protecting vulnerable groups during the COVID crisis, and how could they be improved? What is the best way to embed segmentation models derived from this causal analysis within health systems to effectively target support to reduce health inequalities? Methods. Utilising a whole population dataset in Cheshire and Merseyside linking data from primary health care, secondary health care, mental health care, social care, schools, homelessness services, welfare services, Citizens Advice and the police, we will use multilevel (individual, household and neighbourhood) longitudinal regression models, to investigate the factors associated with increased risk of (1) hospitalisation and mortality (2) mental health problems and (3) adverse childhood outcomes during the COVID-19 crisis. These will be used to identify population segments that are at higher and/or increasing risk of these outcome during pandemic and recovery phases. We will additionally evaluate the health impact of existing risk segmentation tools that have been used during the pandemic. This evidence will be used to develop new tools to support the targeting of resources and interventions at groups most at risk and we will work with the NHS, local government and the community sector to establish the use of these tools in decision making. Timeline, impact and dissemination. The research will be delivered over 24 months. As results emerge we will work with the NHS and local governments to help them use these tools in responding to the current crisis. Since all areas are experiencing similar issues, the results will be useful across the country. More effective early identification of groups at risk during the crisis will enable them to be provided with effective support to prevent escalation, this has the potential to have a major impact on peoples health particularly more disadvantaged groups who have been most adversely affected by the pandemic.

Lay abstract: We know that COVID-19 has caused more deaths in more disadvantaged areas due to differences in age, ethnicity, levels of other chronic illnesses, over-crowded housing and employment. The lockdown itself has led to delays in screening and diagnoses for cancer and vaccination uptake; and interruption to schooling and child protection services. The economic recession caused by the pandemic has led to increased poverty, homelessness and food poverty. In order address these problems we need to use data from peoples previous use of health and local government services to work out which groups are more vulnerable to these different problems. We don t know the best way to do this, so in this project we will assess whether current approaches are working and develop more effective ways of identifying these groups. In Cheshire and Merseyside we are working with health, social care, education services and the public to link together different databases that collect data from hospitals, GPs, schools and social care services on the 2.5 million people who live in the area. Firstly we will use these data to identify which groups are being adversely affected in the current crisis, including increased risk of death, mental health problems and problems with child health and education. Secondly we will assess whether the current approaches the NHS and local authorities are using to identify vulnerable groups and protect them, such as the shielding programme, are working. Finally we will use these analyses to develop new tools that better identify vulnerable groups so that they can be provided with support, and try these new approaches out with NHS and local government organisations in Cheshire and Merseyside. We will involve members of the public working alongside researchers and people working in the NHS and local government at each stage of this research. Since all regions are experiencing similar issues, the results of this research will be useful across the country. As soon as we have results from the research that are useful to other places we will work with the NHS and local government to help them use these tools in responding to the current crisis.

Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS;8.1 ORGANISATION AND DELIVERY OF SERVICES;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: INFECTION