Marcelo Medeiros, Alexandre Street, Davi Valladão, Gabriel Vasconcelos, Eduardo Zilberman
arXiv 16 Apr 2020 · Statistics — Applications · publishedInternational Journal of Forecasting (2021) · 3 citations (OpenAlex)
arXiv:2004.07977 · PDF · DOI · OpenAlex · Extracted main text
The number of Covid-19 cases is increasing dramatically worldwide. Therefore, the availability of reliable forecasts for the number of cases in the coming days is of fundamental importance. We propose a simple statistical method for short-term real-time forecasting of the number of Covid-19 cases and fatalities in countries that are latecomers -- i.e., countries where cases of the disease started to appear some time after others. In particular, we propose a penalized (LASSO) regression with an error correction mechanism to construct a model of a latecomer in terms of the other countries that were at a similar stage of the pandemic some days before. By tracking the number of cases and deaths in those countries, we forecast through an adaptive rolling-window scheme the number of cases and deaths in the latecomer. We apply this methodology to Brazil, and show that (so far) it has been performing very well. These forecasts aim to foster a better short-run management of the health system capacity.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Coroneo, L., F. Iacone, A. Paccagnini, and P. Monteiro (2020) Testing the predictive accuracy of Covid-19 forecasts | 0.737 | 3 | 2 | 100% |
| 2 | Giacomini, R. and H. White (2006) Tests of conditional predictive ability | 0.511 | 3 | 2 | 33% |
| Mariani | unmatched citation key Mariani | 0.511 | 2 | 1 | 100% |
| Ribeiro | unmatched citation key Ribeiro | 0.511 | 2 | 1 | 100% |
| and Coelho | unmatched citation key and Coelho | 0.511 | 2 | 1 | 100% |
| da~Silva | unmatched citation key da~Silva | 0.511 | 2 | 1 | 100% |
| 7 | Hendry, J. D. J. C. D (2020) Short-term forecasting of the coronavirus pandemic | 0.511 | 2 | 1 | 100% |
| et~al. | unmatched citation key et~al. | 0.511 | 2 | 1 | 100% |
| Atkeson | unmatched citation key Atkeson | 0.405 | 1 | 1 | 100% |
| Bastos and Cajueiro | unmatched citation key Bastos and Cajueiro | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 79 scored citations. 7 of these could not be matched to a bibliography entry, so only the citation key is shown.