Category: Mental Health

Current awareness updates

Face coverings and COVID-19: statement from an expert panel .
UK Health Security Agency (UKHSA); 2021.
[An expert panel statement, informed by evidence and expertise, on the role of face coverings in mitigating COVID-19 transmission.]

Impact evaluation of the Coronavirus Community Support Fund: final report.
The National Lottery Community Fund; 2021.
[Ipsos MORI, in partnership with New Philanthropy Capital (NPC) and The Tavistock Institute of Human Relations (TIHR), was commissioned to undertake an evaluation of the Coronavirus Community Support Fund (CCSF). This document summarises the findings from an assessment of the impact the CCSF had on the people and communities that were supported, the organisations that were funded, and the volunteers involved.]

COVID-19: impact on childhood vaccinations: data to August 2021.
UK Health Security Agency (UKHSA); 2021.
[Final report of the series providing an early assessment of the impact of COVID-19 on delivery of childhood vaccination programmes in England.]

Covid and beyond: confronting the unequal access to type 1 diabetes healthcare.
Juvenile Diabetes Research Foundation; 2021.
[JDRF surveyed more than 1,000 people living with type 1 diabetes, or caring for a child living with it, to reveal their experiences through the upheavals of the Covid pandemic. The findings of the report reveal the impact of the withdrawal and repurposing of many NHS diabetes services on people with type 1. The report sets out a series of recommendations, anchored in the needs of people living with type 1.]

Assessing the impact of COVID-19 on the clinically extremely vulnerable population.
The Health Foundation; 2021.
[This briefing presents analysis from the Networked Data Lab on the impact the pandemic has had on the clinically extremely vulnerable population; assesses the mental health of people identified as clinically extremely vulnerable; examines the data on access to care for clinically extremely vulnerable;
assess the limitations to the use of an algorithm-driven approach to identifying the clinically extremely vulnerable population which were exacerbated by poor availability of high-quality data.]