Common Pitfalls in the Interpretation of COVID-19 Data and Statistics

Author:

Backhaus Andreas

Publisher

Springer Science and Business Media LLC

Subject

Economics, Econometrics and Finance (miscellaneous),Business, Management and Accounting (miscellaneous)

Reference14 articles.

1. Backhaus, A. (2020, 13 March), Coronavirus: Why it’s so deadly in Italy, Medium, https://medium.com/@andreasbackhausab/coronavirus-why-its-so-deadly-in-italy-c4200a15a7bf (15 May 2020).

2. Bayer, C. and M. Kuhn (2020), Intergenerational ties and case fatality rates: A cross-country analysis, IZA Discussion Paper Series, 13114.

3. Docherty, A. B., E. M. Harrison, C. A. Green, H. Hardwick, R. Pius, L. Norman, K. A. Holden, J. M. Read, F. Dondelinger, G. Carson, L. Merson, J. Lee, D. Plotkin, L. Sigfrid, S. Halpin, C. Jackson, C. Gamble, P. W. Horby, J. S. Nguyen-Van-Tam, J. Dunning, P. J. Openshaw, J. K. Baillie and M. G. Semple (2020), Features of 16,749 hospitalised UK patients with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol, medRxiv, 2020.04.23.20076042.

4. Dowd, J. B., L. Andriano, D. M. Brazel, V. Rotondi, P. Block, X. Ding, Y. Liu and M. C. Mills (2020), Demographic science aids in understanding the spread and fatality rates of COVID-19, Proceedings of the National Academy of Sciences, 117(18), 9696–9698.

5. Dudel, C., T. Riffe, E. Acosta, A. van Raalte, C. Strozza and M. Myrskylä (2020), Monitoring trends and differences in COVID-19 case-fatality rates using decomposition methods: Contributions of age structure and age-specific fatality, medRxiv, 2020.03.31.20048397.

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