| 1. |
|
|
| 2. |
|
|
| 3. |
- Sherratt, K., et al.
(författare)
-
Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- 2023
-
Ingår i: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 12
-
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.
|
|
| 4. |
- Bohlin, P., et al.
(författare)
-
Outdoor passive air monitoring of semi volatile organic compounds (SVOCs) : a critical evaluation of performance and limitations of polyurethane foam (PUF) disks
- 2014
-
Ingår i: Environmental Science. - : Royal Society of Chemistry (RSC). - 2050-7887 .- 2050-7895. ; 16:3, s. 433-444
-
Tidskriftsartikel (refereegranskat)abstract
- The most commonly used passive air sampler (PAS) (i.e. polyurethane foam (PUF) disk) is cheap, versatile, and capable of accumulating compounds present both in gas and particle phases. Its performance for particle associated compounds is however disputable. In this study, twelve sets of triplicate PUF-PAS were deployed outdoors for exposure periods of 1-12 weeks together with continuously operated active samplers, to characterize sampling efficiency and derive sampling rates (R-S) for compounds belonging to 7 SVOC classes (including particle associated compounds). PUF-PAS efficiently and consistently sampled polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), polycyclic aromatic hydrocarbons (PAHs), and eight novel brominated flame retardant (nBFR) compounds. Low accuracy and lack of sensitivity was observed for most polychlorinated dibenzo-p-dioxins/furans PCDD/Fs and polybrominated diphenyl ethers (PBDEs) (under the conditions of this study), with the exception of some congeners which may be used as qualitative markers for their respective classes. Application of compound specific R-S was found crucial for all compounds except PCBs. Sampling efficiency of the particle associated compounds was often low.
|
|
| 5. |
- Mayer, Ludovic, et al.
(författare)
-
Widespread Pesticide Distribution in the European Atmosphere Questions their Degradability in Air
- 2024
-
Ingår i: Environmental Science and Technology. - 0013-936X. ; 58:7, s. 3342-3352
-
Tidskriftsartikel (refereegranskat)abstract
- Risk assessment of pesticide impacts on remote ecosystems makes use of model-estimated degradation in air. Recent studies suggest these degradation rates to be overestimated, questioning current pesticide regulation. Here, we investigated the concentrations of 76 pesticides in Europe at 29 rural, coastal, mountain, and polar sites during the agricultural application season. Overall, 58 pesticides were observed in the European atmosphere. Low spatial variation of 7 pesticides suggests continental-scale atmospheric dispersal. Based on concentrations in free tropospheric air and at Arctic sites, 22 pesticides were identified to be prone to long-range atmospheric transport, which included 15 substances approved for agricultural use in Europe and 7 banned ones. Comparison between concentrations at remote sites and those found at pesticide source areas suggests long atmospheric lifetimes of atrazine, cyprodinil, spiroxamine, tebuconazole, terbuthylazine, and thiacloprid. In general, our findings suggest that atmospheric transport and persistence of pesticides have been underestimated and that their risk assessment needs to be improved.
|
|
