What Will Be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios

Atkeson, Andrew

doi:10.3386/w26867

Cited by 801 publications

(682 citation statements)

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“…Yet, this risk is known to vary widely with access to healthcare and demographic traits [3,4,7]. Although the extent of sub-lethal impacts of the virus are still not known, deaths attributed to infection are of great concern and are used as a measure of disease burden, being a more reliable metric than the number of confirmed infections as the latter is 10 notoriously dependent on testing capacity [8].…”

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confidence: 99%

“…Counter-measures to inhibit the transmission of the virus are in place in most countries, and economic decline has resulted from the closure of businesses and travel restrictions [9,10]. With pressure to re-open economies to reduce job losses and downstream repercussions, leaders of countries and localities are 15 weighing the health risks of COVID-19 with economic risks of control measures [11].…”

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confidence: 99%

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Estimating the Global Infection Fatality Rate of COVID-19

Grewelle¹,

Leo²

2020

Preprint

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COVID-19 has become a global pandemic, resulting in nearly three hundred thousand deaths distributed heterogeneously across countries. Estimating the infection fatality rate (IFR) has been elusive due to the presence of asymptomatic or mildly symptomatic infections and lack of testing capacity. We analyze global data to derive the IFR of COVID-19. Estimates of COVID-19 IFR in each country or locality differ due to variable sampling regimes, demographics, and healthcare resources. We present a novel statistical approach based on sampling effort and the reported case fatality rate of each country. The asymptote of this function gives the global IFR. Applying this asymptotic estimator to cumulative COVID-19 data from 139 countries reveals a global IFR of 1.04% (CI: 0.77%,1.38%). Deviation of countries' reported CFR from the estimator does not correlate with demography or per capita GDP, suggesting variation is due to differing testing regimes or reporting guidelines by country. Estimates of IFR through seroprevalence studies and point estimates from case studies or sub-sampled populations are limited by sample coverage and cannot inform a global IFR, as mortality is known to vary dramatically by age and treatment availability. Our estimated IFR aligns with many previous estimates and is the first attempt at a global estimate of COVID-19 IFR. : medRxiv preprint PCR-based tests with the number of individuals with a detectable SARS-COV-2 immune response in sampled populations [17]. Universally, seroprevalence surveys confirm the presence of unreported infections, though the extent of the unreported infections and associated adjustment to IFR is debated due to the non-random nature of population sampling, low sample size, and questioned 35 specificity of serological assays. Case studies reporting IFR from whole population sampling, such as the Diamond Princess cruise where all patrons were tested and the calculated IFR is near 2% are not necessarily representative of global demographics, incomes, or healthcare availability [7, 18]. In the absence of high resolution information of case demographics, seroprevalence, or stan-40 dardization of healthcare and underlying risk factors to COVID-19 morbidity and mortality, there exists no method to assess the global IFR. A robust estimate is essential to inform policy and interventions [8,19]. We provide a new statistical approach to estimate the global IFR using reported data, despite variability in reporting and risk factors. Differences in reported country-level 45 CFR from the estimator are compared to national demographic and economic profiles to determine whether the reported CFR reflects known risk factors for COVID-19 mortality. MethodsReporting standards and testing procedures vary widely across countries, 50

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confidence: 99%

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confidence: 99%

Estimating the Global Infection Fatality Rate of COVID-19

Grewelle¹,

Leo²

2020

Preprint

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“…This probability, modeled via contact rates as in the classic SEIR model, is affected by various aspects, e.g., how likely people meet or whether they show symptoms of to have different probabilities, depending on their category of infectiousness as well as their group membership. 1 We denote the contact rate between symptomatic individuals of group k and individuals of group j by β sym kj , and by β asym kj the corresponding contact rate for infectious but asymptomatic individuals. Finally, we also model potentially group-specific average durations of the infection for the symptomatic and severely ill individuals.…”

Section: The Modelsmentioning

confidence: 99%

Extensions of the SEIR Model for the Analysis of Tailored Social Distancing and Tracing Approaches to Cope with COVID-19

Grimm

Mengel

Schmidt

2020

Preprint

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In the context of the COVID-19 pandemic, governments worldwide face the challenge of designing tailored measures of epidemic control to provide reliable health protection while allowing more societal and economic activity. In this paper, we propose an extension of the epidemiological SEIR model to enable a detailed analysis of commonly discussed tailored measures of epidemic control-among them group-specific protection and the use of tracing apps. We introduce groups into the SEIR model that may differ both, in their underlying parameters as well as in their behavioral response to public health interventions. We allow for different infectiousness parameters within and across groups, different asymptomatic, hospitalization, and lethality rates, as well as different take-up rates of tracing apps. Our results visualize the sharp trade-offs between different goals of epidemic control, namely a low death toll, avoiding overload of the health system, and a short duration of the epidemic. We show that a combination of tailored mechanisms, e.g., the protection of vulnerable groups together with a "trace & isolate" approach, can be effective in preventing a high death toll. Protection of vulnerable groups without further measures requires unrealistically strict isolation. A key insight is that high compliance is critical for the effectiveness of a "trace & isolate" approach. Our model allows to analyze the interplay of group-specific social distancing and tracing also beyond our case study in scenarios with a large number of groups reflecting, e.g., sectoral, regional, or age differentiation and group-specific take-up rates for tracing apps.

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“…Modelling and simulation are at the forefront of determining the efficacy of these measures in reducing SARS-CoV-2 transmission and quantifying risk of future outbreaks along with their potential severity [2,8,16,31]. Understanding of these effects is crucial given the potential deleterious sociological and economic impacts of many NPIs [3][4][5]9].…”

Section: Introductionmentioning

confidence: 99%

Hindsight is 2020 vision: a characterisation of the global response to the COVID-19 pandemic

Warne

Ebert

Drovandi

et al. 2020

Preprint

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Since the initial outbreak in Wuhan (Hubei, China) in December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), has rapidly spread to cause one of the most pressing challenges facing our world today: the COVID-19 pandemic. Within four months of the first reported cases, more than two and a half million cases were confirmed with over two hundred thousand deaths globally, and many countries had taken extreme measures to stop the spread. In this work, we analyse the response to the COVID-19 outbreak for 103 countries over the period 22 January to 13 April 2020. We utilise a novel stochastic epidemiological model that includes a regulatory mechanism that captures the level of tolerance to rising confirmed cases within the response behaviour. Using approximate Bayesian computation, we identify that the top ten outbreaks as of 31 March are characterised by a high tolerance to rising cases tallies, whereas countries that avoided severe outbreak have a low tolerance. Countries that recovered rapidly also have a higher identification rate. As of 13 April, almost all countries show declines in transmission rates and basic reproductive numbers. Furthermore, countries approaching recovery also increased their identification rate between 31 March and 13 April. We also demonstrate that uncertainty in undocumented infections dramatically impacts uncertainty in predictions. Overall, we recommend that broader testing is required to understand the magnitude of undocumented infections.

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What Will Be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios

Cited by 801 publications

References 0 publications

Estimating the Global Infection Fatality Rate of COVID-19

Estimating the Global Infection Fatality Rate of COVID-19

Extensions of the SEIR Model for the Analysis of Tailored Social Distancing and Tracing Approaches to Cope with COVID-19

Hindsight is 2020 vision: a characterisation of the global response to the COVID-19 pandemic

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