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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/5639| COVID-19: Modelling Local Transmission and Morbidity effects to provide an estimate of overall Relative Healthcare Resource Impact by General Practice Granularity | |
| Michael Stedman. Mark Lunt. Mark Davies. Martin Gibson. Adrian Heald. | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| 10.1101/2020.03.20.20039024 | |
| Introduction Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the name given to the 2019 novel coronavirus. COVID-19 is the name given to the disease associated with the virus. SARS-CoV-2 is a new strain of coronavirus that has not been previously identified in humans. Methods Two key factors were analysed which when multiplied together would give an estimate of relative demand on healthcare utilisation. These factors were case incidence and case morbidity. GP Practice data was used as this provided the most geographically granular source of published public population data. To analyse case incidence, the latest values for indicators that could be associated with infection transmission rates were collected from the Office of National Statistics (ONS) and Quality Outcome Framework (QOF) sources. These included population density, % age >16 at fulltime work/education, % age over 60, % BME ethnicity, social deprivation as IMD 2019, Location as latitude/longitude, and patient engagement as % self-confident in their own long term condition management. Average case morbidity was calculated by applying the international mortality Odds Ratio to the local population relevant age and disease prevalences and then summing and dividing by the equivalent national figure. To provide a comparative measure of overall healthcare resource impact, individual GP practice impact scores were compared against the median practice. Results The case incidence regression is a dynamic situation with the significance of specific factors moderating over time as the balance between external infection, community transmission and impact of mitigation measures feeds through to the number of cases. It showed that currently Urban, % Working and age >60 were the strongest determinants of case incidence. The local population comorbidity remains unchanged. The range of relative HC impact was wide with 80% of practices falling between 20%-250% of the national median. Once practice population numbers were included it showed that the top 33% of GP practices supporting 45% of the patient population would require 68% of COVID-19 healthcare resources. The model provides useful information about the relative impact of Covid-19 on healthcare workload at GP practice granularity in all parts of England. Conclusion Covid-19 is impacting on the utilisation of health and social care resources across the country. This model provides a method for predicting relative local levels of disease burden based on defined criteria and thereby providing a method for targeting limited (and perhaps soon to be scarce) care resources to optimise national, regional and local responses to the COVID-19 outbreak. | |
| www.medrxiv.org | |
| 2020 | |
| Artículo | |
| https://www.medrxiv.org/content/10.1101/2020.03.20.20039024v1.full.pdf | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
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| 1109602.pdf | 1.35 MB | Adobe PDF | Visualizar/Abrir |