| 1. |
- Forchini, Giovanni, et al.
(author)
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Report 28 : Excess non-COVID-19 deaths in England and Wales between 29th February and 5th June 2020
- 2020
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Reports (other academic/artistic)abstract
- There were 189,403 deaths from any cause reported in England from 29th February to 5th June 2020 inclusive, and 11,278 all-cause deaths in Wales over the same period. Of those deaths, 44,736 (23.6%) registered COVID-19 on the death certificate in England, and 2,294 (20.3%) in Wales, while 144,667 (76.4%) were not recorded as having been due to COVID-19 in England, and 8,984 (79.7%) in Wales. However, it could be that some of the ‘non-COVID-19’ deaths have in fact also been caused by COVID-19, either as the direct cause of death, or indirectly through provisions for the pandemic impeding access to care for other conditions. There is uncertainty in how many of the non-COVID-19 deaths were directly or indirectly caused by the pandemic. We estimated the excess deaths that were not recorded as associated with COVID-19 in the death certificate (excess non-COVID-19 deaths) as the deaths for which COVID-19 was not reported as the cause, compared to those we would have expected to occur had the pandemic not happened. Expected deaths were forecast with an analysis of historic trends in deaths between 2010 and April 2020 using data by the Office of National Statistics and a statistical time series model.According to the model, we expected 136,294 (95% CI 133,882 - 138,696) deaths in England, and 8,983 (CI 8,051 - 9,904) in Wales over this period, significantly fewer than the number of deaths reported. This means that there were 8,983 (95% CI 5,971 - 10,785) total excess non-COVID-19 deaths in England. For every 100 COVID-19 deaths during the period from 29th February to 5th June 2020 there were 19 (95% CI 13 – 24) cumulative excess non-COVID-19 deaths. The proportion of cumulative excess non-COVID-19 deaths of all reported deaths during this period was 4.4% (95% CI 3.2% - 5.7%) in England, with small regional variations. Excess deaths were highest in the South East at 2,213 (95% CI 327 - 4,047) and in London at 1,937 (95% CI 896 - 3,010), respectively. There is no evidence of non-COVID-19 excess deaths in Wales. Excess non-COVID-19 deaths are occurring in individuals aged 85+ and 75-84, and those aged 45-64. For those aged 85+, excess non-COVID-19 deaths are driven by females, with 6,115 (95% CI 206 – 11,795) deaths in total but no significant findings for males of those ages. For ages 75-84, excess non-COVID-19 deaths are nearly double for females at 2,070 (95% CI 393 – 3,887) than for males at 1,336 (95% CI 938 – 1,710), while for ages 45-64, excess non-COVID-19 deaths for females are at 347 (95% CI 90 – 603), almost half those of males at 681 (95% CI 282 – 1,091). There is no evidence of excess non-COVID-19 deaths for ages 65-74, and those below 45.Excess non-COVID-19 deaths could be due to non-reporting of COVID-19 on the death certificate or an increase in mortality for non-COVID-19 conditions. Severely ill patients may have been unable to access life-saving emergency treatment because of constraints in healthcare provision, or because they avoided seeking care due to concern over hospital-acquired infection, or to avoid burdening healthcare providers. Further research into reasons for excess non-COVID-19 deaths is warranted.This report accompanies the weekly update of excess death estimates on the Github website of the Abdul Latif Jameel Institute of Disease and Emergency Analytics (J-IDEA) (https://j-idea.github.io/ONSdeaths/) which has been set up to be regularly updated until June 2022.
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| 2. |
- Haw, David J., et al.
(author)
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Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS
- 2022
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In: Nature Computational Science. - : Springer Science and Business Media LLC. - 2662-8457. ; 2:4, s. 223-233
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Journal article (peer-reviewed)abstract
- To study the trade-off between economic, social and health outcomes in the management of a pandemic, DAEDALUS integrates a dynamic epidemiological model of SARS-CoV-2 transmission with a multi-sector economic model, reflecting sectoral heterogeneity in transmission and complex supply chains. The model identifies mitigation strategies that optimize economic production while constraining infections so that hospital capacity is not exceeded but allowing essential services, including much of the education sector, to remain active. The model differentiates closures by economic sector, keeping those sectors open that contribute little to transmission but much to economic output and those that produce essential services as intermediate or final consumption products. In an illustrative application to 63 sectors in the United Kingdom, the model achieves an economic gain of between £161 billion (24%) and £193 billion (29%) compared to a blanket lockdown of non-essential activities over six months. Although it has been designed for SARS-CoV-2, DAEDALUS is sufficiently flexible to be applicable to pandemics with different epidemiological characteristics.
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| 4. |
- Ohrnberger, Julius, et al.
(author)
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The impact of a COVID-19 lockdown on work productivity under good and poor compliance
- 2021
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In: European Journal of Public Health. - : European Public Health Association. - 1101-1262 .- 1464-360X. ; 31:5, s. 1009-1015
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Journal article (peer-reviewed)abstract
- BACKGROUND: In response to the COVID-19 pandemic, governments across the globe have imposed strict social distancing measures. Public compliance to such measures is essential for their success, yet the economic consequences of compliance are unknown. This is the first study to analyze the effects of good compliance compared with poor compliance to a COVID-19 suppression strategy (i.e. lockdown) on work productivity.METHODS: We estimate the differences in work productivity comparing a scenario of good compliance with one of poor compliance to the UK government COVID-19 suppression strategy. We use projections of the impact of the UK suppression strategy on mortality and morbidity from an individual-based epidemiological model combined with an economic model representative of the labour force in Wales and England.RESULTS: We find that productivity effects of good compliance significantly exceed those of poor compliance and increase with the duration of the lockdown. After 3 months of the lockdown, work productivity in good compliance is £398.58 million higher compared with that of poor compliance; 75% of the differences is explained by productivity effects due to morbidity and non-health reasons and 25% attributed to avoided losses due to pre-mature mortality.CONCLUSION: Good compliance to social distancing measures exceeds positive economic effects, in addition to health benefits. This is an important finding for current economic and health policy. It highlights the importance to set clear guidelines for the public, to build trust and support for the rules and if necessary, to enforce good compliance to social distancing measures.
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