Test Sensitivity for Infection versus Infectiousness of SARS-CoV-2

Gans, Joshua S.

doi:10.1101/2020.08.30.20184739

Cited by 3 publications

(1 citation statement)

References 15 publications

(18 reference statements)

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“…In reality, such predictions are rarely perfect and this has implications for decisions made, for example,Lowenthal (1982) andGans (2022b). Here, however, because of the complexity of the pricing and quantity decisions, the focus is on the first-order impacts of the adoption of perfect AI prediction of demand.5Lim (1980) refers to this as P-behaviour.…”

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confidence: 99%

Artificial intelligence adoption in a monopoly market

Gans

2022

Manage Decis Econ

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The adoption of artificial intelligence (AI) prediction of demand by a monopolist firm is examined. It is shown that, in the absence of AI prediction, firms face complex trade‐offs in setting price and quantity ahead of demand that impact on the returns of AI adoption. Different industrial environments with differing flexibility of prices and/or quantity ex post also impact on AI returns as does the time horizon of AI prediction. While AI has positive benefits for firms in terms of profitability, its impact on average price and quantity, as well as consumer welfare, is more nuanced and critically dependent on environmental characteristics.

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confidence: 99%

Artificial intelligence adoption in a monopoly market

Gans

2022

Manage Decis Econ

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Frequency and accuracy of proactive testing for COVID-19

Bergstrom

2020

Preprint

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The SARS-CoV-2 coronavirus has proven difficult to control not only because of its high transmissibility, but because those who are infected readily spread the virus before symptoms appear, and because some infected individuals, though contagious, never exhibit symptoms. Proactive testing of asymptomatic individuals is therefore a powerful, and probably necessary, tool for preventing widespread infection in many settings. This paper explores the effectiveness of alternative testing regimes, in which the frequency, the accuracy, and the delay between testing and results determine the time path of infection. For a simple model of disease transmission, we present analytic formulas that determine the effect of testing on the expected number of days of during which an infectious individual is exposed to the population at large. This allows us to estimate the frequency of testing that would be required to prevent uncontrolled outbreaks, and to explore the trade-offs between frequency, accuracy, and delay in achieving this objective. We conclude by discussing applications to outbreak control on college and university campuses.

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Economic Benefits of COVID-19 Screening Tests

Atkeson¹,

Droste

Mina

et al. 2020

Preprint

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We assess the economic value of screening testing programs as a policy response to the ongoing COVID-19 pandemic. We find that the fiscal, macroeconomic, and health benefits of rapid SARS-CoV-2 screening testing programs far exceed their costs, with the ratio of economic benefits to costs typically in the range of 4-15 (depending on program details), not counting the monetized value of lives saved. Unless the screening test is highly specific, however, the signal value of the screening test alone is low, leading to concerns about adherence. Confirmatory testing increases the net economic benefits of screening tests by reducing the number of healthy workers in quarantine and by increasing adherence to quarantine measures. The analysis is undertaken using a behavioral SIR model for the United States with 5 age groups, 66 economic sectors, screening and diagnostic testing, and partial adherence to instructions to quarantine or to isolate.

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Test Sensitivity for Infection versus Infectiousness of SARS-CoV-2

Cited by 3 publications

References 15 publications

Artificial intelligence adoption in a monopoly market

Artificial intelligence adoption in a monopoly market

Frequency and accuracy of proactive testing for COVID-19

Economic Benefits of COVID-19 Screening Tests

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