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- Sherratt, K., et al.
(author)
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Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- 2023
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In: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 12
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Journal article (peer-reviewed)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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- Turja, R., et al.
(author)
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A multibiomarker approach to the assessment of pollution impacts in two Baltic Sea coastal areas in Sweden using caged mussels (Mytilus trossulus)
- 2014
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In: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 473, s. 398-409
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Journal article (peer-reviewed)abstract
- Blue mussels (Mytilus trossulus) were transplanted in cages for three months in two Swedish coastal areas in the Bothnian Sea (northern Baltic Sea) to investigate the interactions between analysed environmental chemicals and biological responses. A wide array of biological parameters (biomarkers) including antioxidant and biotransformation activity, geno-, cyto- and neurotoxic effects, phagocytosis, bioenergetic status and heart rate were measured to detect the possible effects of contaminants. Integrated Biomarker Response index and Principal Component Analysis performed on the individual biological response data were able to discriminate between the two study areas as well as the contaminated sites from their respective local reference sites. The two contaminated sites outside the cities of Sundsvall (station 51) and Gavle (station G1) were characterised by different biomarker response patterns. Mussels at station S1 showed a low condition index, increased heart rate recovery time and phagocytosis activity coinciding with the highest tissue concentrations of some trace metals, polycyclic aromatic hydrocarbons and organotins. At station G1 the highest organochlorine pesticide concentration was recorded as well as elevations in glutathione S-transferase activity, thiamine content and low lysosomal membrane stability. Significant variability in the geno- and cytotoxic responses and bioenergetic status was also observed at the different caging stations. The results obtained suggest that different chemical mixtures present in the study areas cause variable biological response patterns in organisms.
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- Yamaguchi, H., et al.
(author)
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History of NAMRI and NAMRC
- 2019
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In: Procedia Manufacturing. - : Elsevier B.V.. - 2351-9789. ; 34, s. 3-5
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Journal article (peer-reviewed)
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