... Would you like me to generate a simple workflow to get you started?

There is an obvious solution here Sam - only communicate with humans via an LLM intermediary

We are really grateful to all the people who worked hard to process the wastewater samples and resulting data as part of this national monitoring program. Particular shout out to those at @eawag.bsky.social and the Swiss FOPH. You can find more about Swiss wastewater surveillance here: wise.ethz.ch

Analysing the regional and local deviations, we found varying evidence for correlations with hospitalisation data and geographical clustering through the different phases of the epidemic, which broadly reflect changes in infection prevalence and population mobility patterns.

Applying a Bayesian spatio-temporal model, we quantified the contributions of various factors to the observed variability in the time series considering covariates related to processing protocol, socioeconomic factors and regional and local deviations from the global trend.

We analysed SARS-CoV-2 RNA concentrations quantified in wastewater samples taken regularly from 120 treatment plants between February 2022 and December 2023.

We promote further investigation of integrating expert opinion in short-term forecasting, especially the development of scalable systems to elicit forecasts. 5/5

In general, the experts tended to over-predict small numbers of cases in more geographical regions than the models but were less likely to predict larger flare-ups. 4/5

We found that while no individual expert could consistently compete with the mathematical models, the performance of the ensemble forecast of the experts was comparable. 3/5

We evaluated the relative performance of a panel of experts with two mathematical models when forecasting the number and spatial distribution of future cases of Ebola Virus Disease in real-time during the 2018-2020 outbreak in North-eastern DRC. 2/5

We found that while no individual expert could consistently compete with the mathematical models, the performance of the ensemble forecast of the experts was comparable. 3/5

We evaluated the relative performance of a panel of experts with two mathematical models when forecasting the number and spatial distribution of future cases of Ebola Virus Disease in real-time during the 2018-2020 outbreak in North-eastern DRC. 2/5

The study provides a nice insight into the pathway between respiratory outbreaks in schools and voluntary absence. Further research is warranted to understand the role of asymptomatic students in transmission and the potential of promoting voluntary absence as part of infection control.

In students who took absence, those testing positive for Influenza B almost all reported a fever, runny nose and cough, whereas those testing positive for Influenza A were more likely to report fatigue, with a lower proportion (~60%) reporting fever.

Absences were most clearly correlated with Influenza B (mean of 80% of infections [37 - 96% CI)] associated with absence) followed by Parainfluenza virus and Influenza A with means of 50% and 48% of episodes associated with absence.

Using data from a longitudinal study in four classes in a secondary school, molecular (sputum) samples were tested for 24 resp. pathogens. Children who took time off school due to symptoms were surveyed for symptoms.

We evaluate outbreak risk across the school network in each academic year. We find that while the first children born since the previous outbreak remain in primary school, outbreaks remain small. As they enter secondary school the expected outbreak sizes return to the order of that seen in 2013/14.

We constructed a school-household network for the Netherlands using national school records data. Using school level MMR coverage estimates from 2013 we propagate susceptible children through schools affected by the outbreak as new cohorts progress through the school system.

This follows our previous work on understanding risk of measles outbreaks in Dutch schools: doi.org/10.1371/jour....