Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS

Haw, David; Forchini, Giovanni; Doohan, Patrick; Christen, Paula; Pianella, Matteo; Johnson, Robert A.; Bajaj, Sumali; Hogan, Alexandra B.; Winskill, Peter; Miraldo, Marisa; White, Peter J; Ghani, Azra C; Ferguson, Neil; Smith, Peter; Hauck, Katharina

doi:10.1038/s43588-022-00233-0

Cited by 30 publications

(25 citation statements)

References 27 publications

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“…We find, counterintuitively, but consistently with previous studies [18], that larger hospital capacity is associated with greater excess deaths. This association may arise because a higher healthcare capacity allows policy makers to delay introduction of more intensive, but ultimately necessary, NPIs for longer than smaller capacity would allow, resulting in more infections and deaths.…”

Section: Discussionsupporting

confidence: 90%

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The interaction of transmission intensity, mortality, and the economy: a retrospective analysis of the COVID-19 pandemic

Morgenstern

Laydon

Whittaker

et al. 2022

Preprint

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The COVID-19 pandemic has caused over 6.4 million registered deaths to date, and has had a profound impact on economic activity. Here, we study the interaction of transmission, mortality, and the economy during the SARS-CoV-2 pandemic from January 2020 to December 2022 across 25 European countries. We adopt a Bayesian vector autoregressive model with both fixed and random effects. We find that increases in disease transmission intensity decreases Gross domestic product (GDP) and increases daily excess deaths, with a longer lasting impact on excess deaths in comparison to GDP, which recovers more rapidly. Broadly, our results reinforce the intuitive phenomenon that significant economic activity arises from diverse person-to-person interactions. We report on the effectiveness of non-pharmaceutical interventions (NPIs) on transmission intensity, excess deaths and changes in GDP, and resulting implications for policy makers. Our results highlight a complex cost-benefit trade off from individual NPIs. For example, banning international travel increases GDP however reduces excess deaths. We consider country random effects and their associations with excess changes in GDP and excess deaths. For example, more developed countries in Europe typically had more cautious approaches to the COVID-19 pandemic, prioritising healthcare and excess deaths over economic performance. Long term economic impairments are not fully captured by our model, as well as long term disease effects (Long Covid). Our results highlight that the impact of disease on a country is complex and multifaceted, and simple heuristic conclusions to extract the best outcome from the economy and disease burden are challenging.

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Section: Discussionsupporting

confidence: 90%

“…[14][15][16][17]). A minority of studies, e.g, [18], estimate epidemiological parameters by fitting models to pandemic data. This approach is useful to study different counterfactual scenarios and the impact of potential interventions, while assuming the dynamics which are imposed on the system.…”

Section: Introductionmentioning

confidence: 99%

The interaction of transmission intensity, mortality, and the economy: a retrospective analysis of the COVID-19 pandemic

Morgenstern

Laydon

Whittaker

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…1 ). Sectors of particular note are: education (in which pupils/students are the customer), hospitality/entertainment and travel/hotels, as these sectors, when open, correlate strongly with contact and therefore transmission ( Haw et al, 2022 ). As we see a wealth of data emerge including simple metrics for behavioural change (mobility ( Google, 2022 ), mask wearing ( Riley et al, 2021 ) etc.…”

Section: The Interface Of Economics and Epidemiologymentioning

confidence: 99%

“…Our discussion assumes a readership familiar with the basic underlying models. Many of our observations are rooted in the integrated model DAEDALUS ( Haw et al, 2022 ), though broader literature searches of relevant models ( Brodeur et al, 2021 ) have shown these observations to be somewhat universal. Many of the existing datasets identified are unique to the United Kingdom, though our focus is on the nature of the variables and the scope of the study, rather than the population from which such data was obtained.…”

Section: Introductionmentioning

confidence: 98%

“…Economic disruption during the COVID-19 pandemic has led to a wealth of mathematical models that integrate the fields of economics and epidemiology, e.g. Haw et al, 2022 , Eichenbaum et al, 2022 , Acemoglu et al, 2020 , Çakmaklı et al, 2020 , Pichler et al, 2020 . A common theme across such studies is the association of an economic cost to the efforts made in mitigating the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

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Data needs for integrated economic-epidemiological models of pandemic mitigation policies

et al. 2022

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Understanding the role of energy sector in the outbreak of epidemic in China: An analysis based on SEIDR epidemic model, dynamic input-output model and resource allocation DEA model

Zhou,

Zhang,

Zhang

et al. 2024

Energy

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Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS

Cited by 30 publications

References 27 publications

The interaction of transmission intensity, mortality, and the economy: a retrospective analysis of the COVID-19 pandemic

The interaction of transmission intensity, mortality, and the economy: a retrospective analysis of the COVID-19 pandemic

Data needs for integrated economic-epidemiological models of pandemic mitigation policies

Understanding the role of energy sector in the outbreak of epidemic in China: An analysis based on SEIDR epidemic model, dynamic input-output model and resource allocation DEA model

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