Ahumada, Hildegart and Espina, Santos and Navajas, Fernando H. (2020): COVID-19 with uncertain phases: estimation issues with an illustration for Argentina.
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Abstract
We use an approach to assess COVID-19 performance that starts from what we consider is the most likely set of hypotheses about the uncertain evolution of the pandemic, that envisage a sequence of different cycles with unknown duration and magnitude over 18-24 months. This pattern implies a research strategy where short-term time series forecasting of the evolution of observed cases and deaths play a central role in both detecting transitions from phase to phase of infections and the estimation of necessarily changing structural parameters and indicators of a SIRD model. We illustrate our approach with Buenos Aires City performance, which represents a significant share of the Argentine case with an early introduction of a lockdown followed by a second wave latter on. This approach can be extended to include measures of the intensity and compliance of lockdowns, as well as the heterogeneity across areas. We find that mobility (as a proxy for the effectiveness of the lockdown) has an impact on observed cases in Buenos Aires City with a lag of 8 days and deaths relate with new cases registered 16 to 19 days before. Mobility has a clear impact on the growth rate of cases and by extension deaths. Our approach and results have implications for policy dialogue issues.
Item Type: | MPRA Paper |
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Original Title: | COVID-19 with uncertain phases: estimation issues with an illustration for Argentina |
Language: | English |
Keywords: | COVID-19, Forecasting, SIRD, Lockdown, Mobility |
Subjects: | C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods I - Health, Education, and Welfare > I1 - Health > I10 - General |
Item ID: | 101466 |
Depositing User: | Fernando H. Navajas |
Date Deposited: | 05 Jul 2020 18:58 |
Last Modified: | 05 Jul 2020 18:58 |
References: | Ahumada H, S. Espina-Mairal and F. Navajas (2020), “Modelos y pronósticos de la dinámica del COVID-19: Mirando la Argentina”, mimeo, FIEL, Abril 10. Alon T., M. Kim, D. Lagakos and M. Vuren (2020), “How Should Policy Responses to the COVID-19 Pandemic Differ in the Developing World?”, Working Paper 27273, National Bureau of Economic Research, May. Alvarez F., D. Argente, and F. Lippi, (2020) “A Simple Planning Problem for COVID-19 Lockdown,” Working Paper 26981, National Bureau of Economic Research, April. Aronson J., J. Brassey and K. Mahtani (2020), “When will it be over?”: An introduction to viral reproduction numbers, R0 and Re”, Centre for Evidence-Based Medicine, Oxford University. Atkeson, A. (2020) “What Will Be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios,” Working Paper 26867, National Bureau of Economic Research, March Batista, M. (2020). “Estimation of the final size of the coronavirus epidemic by the SIR model”, MedRxiv, Feb.28, https://doi.org/10.1101/2020.02.16.20023606. Barnett M., G. Buchak and C. Yannelis (2020), “Epidemic responses under uncertainty”, Working Paper 26867, National Bureau of Economic Research, May. Baum, C. and M. Henry, “Socioeconomic Factors influencing the Spatial Spread of COVID-19 in the United States”, May 29, https://ssrn.com/abstract=3614877 Bavel et al (2020), “Using social and behavioural science to support COVID-19 pandemic response”, Nature Human Behavior, April 30, https://www.nature.com/articles/s41562-020-0884-z Biggerstaff, M., Cauchemez, S., Reed, C. et al. (2014) “Estimates of the reproduction number for seasonal, pandemic, and zoonotic influenza: a systematic review of the literature”. BMC Infectious Diseases 14, 480 https://doi.org/10.1186/1471-2334-14-480 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/101466 |