How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19

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Wastewater-based epidemiology offers a complementary approach to clinical case-based surveillance of emergent diseases and can help identify regions with infected people to prioritize clinical surveillance strategies. However, tracking emergent diseases in ...

We conduct two survey experiments to study which information people choose to consume and how it affects their beliefs. In the first experiment, respondents choose between optimistic and pessimistic article headlines related to the COVID-19 pandemic and ar ...

We introduce and derive the Fourier -enhanced 3D electrostatic field solver of the gyrokinetic full -f PIC code PICLS. The solver makes use of a Fourier representation in one periodic direction of the domain to make the solving of the system easily paralle ...

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

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We propose an interpretable model to score the subjective bias present in documents, based only on their textual content. Our model is trained on pairs of revisions of the same Wikipedia article, where one version is more biased than the other. Although pr ...

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and ...

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Decisions about a current visual stimulus are systematically biased by recently encountered stimuli, a phenomenon known as serial dependence. In human vision, for instance, we tend to report the features of current images as more similar â i.e., an attra ...

Before the COVID-19 pandemic, viruses were not a major priority for the scientific community. Today, many events have changed the world and the importance of studying viruses, vaccines, and antiviral drugs is fully appreciated. The development of effective ...

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How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19

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Monitoring an Emergent Pathogen at Low Incidence in Wastewater Using qPCR: Mpox in Switzerland

Biases in Information Selection and Processing: Survey Evidence from the Pandemic

Verification of the Fourier-enhanced 3D finite element Poisson solver of the gyrokinetic full-f code PICLS

Exploiting the Signal-Leak Bias in Diffusion Models

Using automated design appraisal to model building-specific devaluation risk due to land-use change

It’s All Relative: Learning Interpretable Models for Scoring Subjective Bias in Documents from Pairwise Comparisons

Challenges of COVID-19 Case Forecasting in the US, 2020-2021

Osmosis-driven stiffening of structured hydrogels

Waterborne Virus Transport and Risk Assessment in Lake Geneva Under Climate Change

Using Negative Control Populations to Assess Unmeasured Confounding and Direct Effects

Epidemicity indices and reproduction numbers from infectious disease data in connected human populations

A common NFKB1 variant detected through antibody analysis in UK Biobank predicts risk of infection and allergy

Dual-frame optimization for informationally complete quantum measurements

The role of spatial epidemiology to support public health policies : case studies applied to health promotion, noncommunicable and infectious diseases in the canton of Vaud, Switzerland

Inactivation of influenza A virus in expiratory droplets and aerosol particles and the associated physicochemical drivers

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Serial Dependence in Human Visual Perception and Decision-Making

Peptide-based virucidal drugs

Quartiers rhodaniens en transition

Microfluidic systems for infectious disease diagnostics