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- Sherratt, K., et al.
(författare)
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Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- 2023
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Ingår i: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.
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| 2. |
- Baloch, Ramen Munir, et al.
(författare)
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Indoor air pollution, physical and comfort parameters related to schoolchildren's health : Data from the European SINPHONIE study
- 2020
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Ingår i: Science of the Total Environment. - : ELSEVIER. - 0048-9697 .- 1879-1026. ; 739
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Tidskriftsartikel (refereegranskat)abstract
- Substantial knowledge is available on the association of the indoor school environment and its effect among schoolchildren. In the same context, the SINPHONIE (School indoor pollution and health: Observatory network in Europe) conducted a study to collect data and determine the distribution of several indoor air pollutants (IAPs), physical and thermal parameters and their association with eye, skin, upper-, lower respiratory and systemic disorder symptoms during the previous three months. Finally, data from 115 schools in 54 European cities from 23 countries were collected and included 5175 schoolchildren using a harmonized and standardized protocol. The association between exposures and the health outcomes were examined using logistic regression models on the environmental stressors assessed in classroom while adjusting for several confounding factors; a VOC (volatile organic compound) score defined as the sum of the number of pollutants to which the children were highly exposed (concentration > median of the distribution) in classroom was also introduced to evaluate the mul tiexposu re - outcome association. Schoolchildren while adjusting for several confounding factors. Schoolchildren exposed to above or equal median concentration of PM2.5, benzene, limonene, ozone and radon were at significantly higher odds of suffering from upper, lower airways, eye and systemic disorders. Increased odds were also observed for any symptom (sick school syndrome) among schoolchildren exposed to concentrations of limonene and ozone above median values. Furthermore, the risks for upper and lower airways and systemic disorders significantly increased with the VOCs score. Results also showed that increased ventilation rate was significantly associated with decreased odds of suffering from eye and skin disorders whereas similar association was observed between temperature and upper airways symptoms. The present study provides evidence that exposure to IAPs in schools is associated with various health problems in children. Further investigations are needed to confirm our findings. (C) 2020 Elsevier B.V. All rights reserved.
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