ArticleTechnological forecasting and social change2021
Using COVID-19 mortality to select among hospital plant capacity models: An exploratory empirical application to Hubei province.
Article in Technological forecasting and social change, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Data-driven test strategy for COVID-19 using machine learning: A study in Lahore, Pakistan.Socio-economic planning sciences · 2022Article
- Social-economic impacts of epidemic diseases.Technological forecasting and social change · 2022Article
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2 authors.
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Abstract
This contribution defines short- and long-run output- and input-oriented plant capacity measures and evaluates them relative to convex and nonconvex technologies. By applying these different plant capacity concepts, the authors seek to measure the use of existing capacities, as well as the evolution and build-up of extra hospital capacity in the Chinese province of Hubei during the outbreak of the COVID-19 epidemic in early 2020. Furthermore, medical literature has established that mortality rates increase with high capacity utilization rates, an insight that this study leverages to select the most plausible of eight plant capacity concepts. The preliminary results indicate that a relatively new, input-oriented plant capacity concept correlates best with mortality.
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