| 1. |
- Arguedas Cuendis, S., et al.
(författare)
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First results on the search for chameleons with the KWISP detector at CAST
- 2019
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Ingår i: Physics of the Dark Universe. - : Elsevier. - 2212-6864. ; 26
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Tidskriftsartikel (refereegranskat)abstract
- We report on a first measurement with a sensitive opto-mechanical force sensor designed for the direct detection of coupling of real chameleons to matter. These dark energy candidates could be produced in the Sun and stream unimpeded to Earth. The KWISP detector installed on the CAST axion search experiment at CERN looks for tiny displacements of a thin membrane caused by the mechanical effect of solar chameleons. The displacements are detected by a Michelson interferometer with a homodyne readout scheme. The sensor benefits from the focusing action of the ABRIXAS X-ray telescope installed at CAST, which increases the chameleon flux on the membrane. A mechanical chopper placed between the telescope output and the detector modulates the incoming chameleon stream. We present the results of the solar chameleon measurements taken at CAST in July 2017, setting an upper bound on the force acting on the membrane of 80pN at 95% confidence level. The detector is sensitive for direct coupling to matter 104≤βm≤108, where the coupling to photons is locally bound to βγ≤1011.
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| 2. |
- Kappes, Raphael, et al.
(författare)
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Safety4Bikes : Assistance Systems for Cycling Children to Increase Safety
- 2019
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Ingår i: Proceedings, 8th International Cycling SafetyConference, ICSC2019.
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Konferensbidrag (refereegranskat)abstract
- Cycling is a popular urban mobility solution. However, cyclists are more vulnerable and relatively unprotected compared to other road users. In Germany, the number of accidents withcycling children increases dramatically from age 8 to 14. This is not least due to their insufficient cycling skills and understanding of traffic, which is a detriment to their safety. The project Safety4Bikes, which is funded by the German Federal Ministry of Education and Research(BMBF), grant no 16SV7669, aims at mitigating the risk of young cyclists by developing appropriate modular assistance systems that detect situational hazards and promote safe behaviour. Within the project, we are developing novel visual, tactile and acoustic signals integrated in bicycles and helmets to convey information for children in an understandable andnon-distracting way. Embedding the cyclist into the surrounding context, we develop andinvestigate sensor technologies, algorithms and routing strategies needed for identificationof the behaviour of cyclists on the road, traffic signs, safest routes and trajectory corrections.Additionally, we focus on the enhancements of Car2X communication to enable the exchange of information with other vehicles. The project follows a user centric approach inwhich the developed system components are continuously tested and adapted to the needsand characteristics of the target group. Answering the question of how the components willhave to interact with the user is an important part of the research. Therefore, we evaluate theefficacy of the designed interaction and recognition methods as well as sensors, algorithmsand routing strategies through laboratory experiments and bicycle simulators. With controlled test-track experiments on a test route, the components are further evaluated and optimised.
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| 3. |
- O'Reilly, Kathleen M., et al.
(författare)
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Projecting the end of the Zika virus epidemic in Latin America : a modelling analysis
- 2018
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Ingår i: BMC Medicine. - : BioMed Central. - 1741-7015. ; 16
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Tidskriftsartikel (refereegranskat)abstract
- Background: Zika virus (ZIKV) emerged in Latin America and the Caribbean (LAC) region in 2013, with serious implications for population health in the region. In 2016, the World Health Organization declared the ZIKV outbreak a Public Health Emergency of International Concern following a cluster of associated neurological disorders and neonatal malformations. In 2017, Zika cases declined, but future incidence in LAC remains uncertain due to gaps in our understanding, considerable variation in surveillance and the lack of a comprehensive collation of data from affected countries.Methods: Our analysis combines information on confirmed and suspected Zika cases across LAC countries and a spatio-temporal dynamic transmission model for ZIKV infection to determine key transmission parameters and projected incidence in 90 major cities within 35 countries. Seasonality was determined by spatio-temporal estimates of Aedes aegypti vectorial capacity. We used country and state-level data from 2015 to mid-2017 to infer key model parameters, country-specific disease reporting rates, and the 2018 projected incidence. A 10-fold cross-validation approach was used to validate parameter estimates to out-of-sample epidemic trajectories.Results: There was limited transmission in 2015, but in 2016 and 2017 there was sufficient opportunity for wide-spread ZIKV transmission in most cities, resulting in the depletion of susceptible individuals. We predict that the highest number of cases in 2018 would present within some Brazilian States (Sao Paulo and Rio de Janeiro), Colombia and French Guiana, but the estimated number of cases were no more than a few hundred. Model estimates of the timing of the peak in incidence were correlated (p < 0.05) with the reported peak in incidence. The reporting rate varied across countries, with lower reporting rates for those with only confirmed cases compared to those who reported both confirmed and suspected cases.Conclusions: The findings suggest that the ZIKV epidemic is by and large over within LAC, with incidence projected to be low in most cities in 2018. Local low levels of transmission are probable, but the estimated rate of infection suggests that most cities have a population with high levels of herd immunity.
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| 4. |
- Thompson, Robin N., et al.
(författare)
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Key questions for modelling COVID-19 exit strategies
- 2020
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Ingår i: Proceedings of the Royal Society of London. Biological Sciences. - : The Royal Society. - 0962-8452 .- 1471-2954. ; 287:1932
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Tidskriftsartikel (refereegranskat)abstract
- Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.
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| 5. |
- Wolffram, Daniel, et al.
(författare)
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Collaborative nowcasting of COVID-19 hospitalization incidences in Germany
- 2023
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Ingår i: PloS Computational Biology. - 1553-734X .- 1553-7358. ; 19:8
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Tidskriftsartikel (refereegranskat)abstract
- Real-time surveillance is a crucial element in the response to infectious disease outbreaks. However, the interpretation of incidence data is often hampered by delays occurring at various stages of data gathering and reporting. As a result, recent values are biased downward, which obscures current trends. Statistical nowcasting techniques can be employed to correct these biases, allowing for accurate characterization of recent developments and thus enhancing situational awareness. In this paper, we present a preregistered real-time assessment of eight nowcasting approaches, applied by independent research teams to German 7-day hospitalization incidences during the COVID-19 pandemic. This indicator played an important role in the management of the outbreak in Germany and was linked to levels of non-pharmaceutical interventions via certain thresholds. Due to its definition, in which hospitalization counts are aggregated by the date of case report rather than admission, German hospitalization incidences are particularly affected by delays and can take several weeks or months to fully stabilize. For this study, all methods were applied from 22 November 2021 to 29 April 2022, with probabilistic nowcasts produced each day for the current and 28 preceding days. Nowcasts at the national, state, and age-group levels were collected in the form of quantiles in a public repository and displayed in a dashboard. Moreover, a mean and a median ensemble nowcast were generated. We find that overall, the compared methods were able to remove a large part of the biases introduced by delays. Most participating teams underestimated the importance of very long delays, though, resulting in nowcasts with a slight downward bias. The accompanying prediction intervals were also too narrow for almost all methods. Averaged over all nowcast horizons, the best performance was achieved by a model using case incidences as a covariate and taking into account longer delays than the other approaches. For the most recent days, which are often considered the most relevant in practice, a mean ensemble of the submitted nowcasts performed best. We conclude by providing some lessons learned on the definition of nowcasting targets and practical challenges.
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