Healthcare planners need important epidemiological metrics for vascular diseases like heart attack and stroke. For example, they need to know how often people have diseases of different types (‘incidence’), how severe these diseases are (‘case fatality’), and how many people are living with different diseases (‘prevalence’). The COVID 19 pandemic has influenced all of these measures through a combination of direct and indirect impacts on cardiovascular diseases. We aim to see how a range of diseases changed before, during, and after the COVID-19 pandemic.
With this application, we will use data collected by NHS England from hospitals, GPs and pharmacists. This means that we can use consistent methods in each region of the England. By using data from several sources, we will be able to find as many people who are affected by vascular diseases as possible for the time periods before, during and after the COVID 19 pandemic.
We will calculate the incidence, case fatality and prevalence for a wide range of vascular diseases, from the very rare to the very common. We will also see whether the estimates for commoner diseases like stroke and heart attack are different in people of different ethnicities, ages, levels of deprivation and sex in different regions of England. We will look at epidemiological metrics by years prior to the pandemic (before 2020), by months during the main phase of the pandemic (2020, 2021, 2022) and by years after the pandemic.
We will produce a report providing key epidemiological statistics, and make sure that we can easily produce subsequent reports, should the data continue to be available. These statistics will be used by researchers to plan new studies of treatment and causes of disease, and by healthcare planners to make decisions about investment in healthcare services, including to help ensure optimum recovery from the effects of the pandemic.
The issues stated above will be addressed in outputs from a number of related sub-projects. Follow the links below to view repositories containing the protocol, data curation and analysis code, and phenotyping algorithms and codelists for each sub-project:
This project has been approved by the CVD-COVID-UK/COVID-IMPACT Approvals & Oversight Board (Project ID: CCU072).