publication . Preprint . 2021

An ensemble model based on early predictors to forecast COVID-19 healthcare demand in France

Paireau, Juliette; Andronico, Alessio; Hozé, Nathanaël; Layan, Maylis; Crepey, Pascal; Roumagnac, Alix; Lavielle, Marc; Boëlle, Pierre-Yves; Cauchemez, Simon;
English
  • Published: 01 Feb 2021
  • Publisher: HAL CCSD
  • Country: France
Abstract
Short-term forecasting of the COVID-19 pandemic is required to facilitate the planning of COVID-19 healthcare demand in hospitals. Here, we evaluate the performance of 12 individual models and 22 predictors to anticipate French COVID-19 related healthcare needs from September 7th 2020 to January 7th 2021, and build an ensemble model that outperforms all individual models. We find that inclusion of early predictors (epidemiological, mobility and meteorological predictors) can halve the relative error for 14-day ahead forecasts, with epidemiological and mobility predictors contributing the most to the improvement. Our approach facilitates the comparison and benchm...
Subjects
free text keywords: [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Funded by
EC| VEO
Project
VEO
Versatile Emerging infectious disease Observatory
  • Funder: European Commission (EC)
  • Project Code: 874735
  • Funding stream: H2020 | RIA
Communities
COVID-19
17 references, page 1 of 2

1. S. Funk, et al., Short-term forecasts to inform the response to the Covid-19 epidemic in the UK. medRxiv, 2020.11.11.20220962 (2020).

2. P. Mecenas, R. T. da Rosa Moreira Bastos, A. C. R. Vallinoto, D. Normando, Effects of temperature and humidity on the spread of COVID-19: A systematic review. PLoS One 15, e0238339 (2020).

3. Á. Briz-Redón, Á. Serrano-Aroca, The effect of climate on the spread of the COVID-19 pandemic: A review of findings, and statistical and modelling techniques. Progress in Physical Geography: Earth and Environment 44, 591-604 (2020).

4. M. U. G. Kraemer, et al., The effect of human mobility and control measures on the COVID19 epidemic in China. Science 368, 493-497 (2020).

5. J. Landier, et al., Colder and drier winter conditions are associated with greater SARS-CoV2 transmission: a regional study of the first epidemic wave in north-west hemisphere countries. medRxiv, 2021.01.26.21250475 (2021).

6. A. Roumagnac, E. De Carvalho, R. Bertrand, A.-K. Banchereau, G. Lahache, Étude de l'influence potentielle de l'humidité et de la température dans la propagation de la pandémie COVID-19. Medecine De Catastrophe, Urgences Collectives (2021) https:/doi.org/10.1016/j.pxur.2021.01.002 (February 3, 2021).

7. H. Salje, et al., Estimating the burden of SARS-CoV-2 in France. Science 369, 208-211 (2020). [OpenAIRE]

8. Ferguson NM, Laydon D, Nedjati-Gilani G, Imai N, Ainslie K, Baguelin M, Bhatia S, Boonyasiri A, Cucunubá Z, Cuomo-Dannenburg G, Dighe A, Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College COVID-19 Response Team (March, 16 2020) https:/doi.org/10.25561/77482.

9. M. A. Johansson, et al., An open challenge to advance probabilistic forecasting for dengue epidemics. Proc. Natl. Acad. Sci. U. S. A. 116, 24268-24274 (2019).

10. N. G. Reich, et al., Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S. PLoS Comput. Biol. 15, e1007486 (2019).

11. C. Viboud, et al., The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt. Epidemics 22, 13-21 (2018).

12. E. Y. Cramer, et al., Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US. medRxiv, 2021.02.03.21250974 (2021).

13. E. Volz, et al., Transmission of SARS-CoV-2 Lineage B.1.1.7 in England: Insights from linking epidemiological and genetic data. medRxiv, 2020.12.30.20249034 (2021).

14. R. Polikar, Ensemble based systems in decision making. IEEE Circuits and Systems Magazine 6, 21-45 (2006). [OpenAIRE]

15. E. L. Ray, et al., Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the U.S. medRxiv, 2020.08.19.20177493 (2020).

17 references, page 1 of 2
Any information missing or wrong?Report an Issue