James Munday
@jdmunday.bsky.social
Infectious disease epidemiology and surveillance at Swiss TPH • jdmunday.github.io
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.
November 4, 2025 at 1:39 PM
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.
![Fig 2. (A) Association between laboratories or changes in methods within laboratories and SARS-CoV-2 wastewater viral load [VL] (reference is laboratory A).
(B) Association between characteristics of the population living in the wastewater treatment plants catchment area and VL (per unit-increase in standard deviation). (C) Association between calendar changes and VL (reference is no public holiday and week day, respectively).](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:5vwtyzhuiv5j6zmzf4tudhyu/bafkreig6hjhcdj76uex3gphvsrw44u2huctsh4dza5tlyxnqfss3xmajhq@jpeg)
November 4, 2025 at 1:39 PM
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.
![Fig 1. (A) Catchment areas of wastewater treatment plants [WWTPs] participating to SARS-CoV-2 surveillance by region, with the number of measurements in each WWTP over the study period (light grey <200, grey 200 to 500, black ≥500).
(B) All measurements of SARS-CoV-2 viral load in wastewater (values below the limit of quantification are removed; labels 1 to 5 correspond to ad hoc periods aligned with epidemic waves). (C) Weekly median SARS-CoV-2 viral load by WWTP (WWTPs are numbered alphabetically within regions indicated by the coloured scale on the right side; vertical dashed lines delimit the five periods labelled in panel B).](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:5vwtyzhuiv5j6zmzf4tudhyu/bafkreiampfhoyrbq3kala2p3gfaloxrzxocbbbqhwji2uc2z6yamcq3ale@jpeg)
November 4, 2025 at 1:39 PM
We analysed SARS-CoV-2 RNA concentrations quantified in wastewater samples taken regularly from 120 treatment plants between February 2022 and December 2023.
New Paper🚀! Our work analysing the Swiss national SARS-CoV-2 wastewater 🚱 monitoring data is now published in PLOS Water 💧 @plos.org journals.plos.org/water/articl... (Julien Riou, @tanjastadler.bsky.social @trj2.bsky.social Christoph Ort et al)
November 4, 2025 at 1:39 PM
New Paper🚀! Our work analysing the Swiss national SARS-CoV-2 wastewater 🚱 monitoring data is now published in PLOS Water 💧 @plos.org journals.plos.org/water/articl... (Julien Riou, @tanjastadler.bsky.social @trj2.bsky.social Christoph Ort et al)
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
October 13, 2025 at 12:00 PM
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
October 13, 2025 at 12:00 PM
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
October 13, 2025 at 12:00 PM
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
October 13, 2025 at 10:06 AM
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
October 13, 2025 at 10:06 AM
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
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.
September 30, 2025 at 12:07 PM
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.
September 30, 2025 at 12:07 PM
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.
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.
September 4, 2025 at 7:42 AM
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.
September 4, 2025 at 7:42 AM
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.
We found that while close contact contributed to elevated risk (rate ratio 1.16 per doubling daily time, 95%-CI 1.01–1.33), time spent in shared classrooms and poor air quality had larger effects (RR 8.96, 95%-CI 4.85–16.88 and RR 5.59 95%-CI 3.25–9.83 respectively).
August 22, 2025 at 9:24 AM
We found that while close contact contributed to elevated risk (rate ratio 1.16 per doubling daily time, 95%-CI 1.01–1.33), time spent in shared classrooms and poor air quality had larger effects (RR 8.96, 95%-CI 4.85–16.88 and RR 5.59 95%-CI 3.25–9.83 respectively).
Combining these data we inferred the relative contributions of 🧑🤝🧑 close contact, 🧑🏫 shared class rooms and 🍃 air quality on transmission risk using a pairwise survival analysis framework.
August 22, 2025 at 9:24 AM
Combining these data we inferred the relative contributions of 🧑🤝🧑 close contact, 🧑🏫 shared class rooms and 🍃 air quality on transmission risk using a pairwise survival analysis framework.
We collected molecular (saliva 3x weekly), contact (prox. sens.) and air quality data in a school in Switzerland over 7 weeks. We tested saliva samples using a respiratory panel RT-PCR (24 respiratory viruses) and sequenced SARS-CoV-2, IAV, IBV and RSV positive (targeted Illumina panel).
August 22, 2025 at 9:24 AM
We collected molecular (saliva 3x weekly), contact (prox. sens.) and air quality data in a school in Switzerland over 7 weeks. We tested saliva samples using a respiratory panel RT-PCR (24 respiratory viruses) and sequenced SARS-CoV-2, IAV, IBV and RSV positive (targeted Illumina panel).
Just when you think you are beginning to understand a sport...
July 12, 2025 at 10:27 AM
Just when you think you are beginning to understand a sport...
Using our model to estimate the number of measurements that fell below quantifiable limits as a result of delays, we found that when baseline concentrations are low degradation can substantially impact data quality, losing as much as two weeks of measurements early in the seasonal epidemic.
June 9, 2025 at 9:05 AM
Using our model to estimate the number of measurements that fell below quantifiable limits as a result of delays, we found that when baseline concentrations are low degradation can substantially impact data quality, losing as much as two weeks of measurements early in the seasonal epidemic.
We found that delays between collection and processing were associated with reduced RNA concentrations. The rate at which RNA concentrations reduced was variable between pathogens and treatment plants. Our results were broadly consistent across two seasons of monitoring.
June 9, 2025 at 9:05 AM
We found that delays between collection and processing were associated with reduced RNA concentrations. The rate at which RNA concentrations reduced was variable between pathogens and treatment plants. Our results were broadly consistent across two seasons of monitoring.
We analysed viral concentration time series from a national wastewater-based pathogen monitoring program. We made use of variable delays between sample collection an processing to estimate the degradation rates of RNA in four resp. pathogens.
![Left, map of Switzerland with monitored wastewater treatment plant catchments highlighted and colour coded. Key cities and lakes included for reference. Right, viral concentrations in genome copies per ml for four pathogens (IAV, IBV, RSV and SARS-CoV-2 [top to bottom]) and six treatment plants [left to right]](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:5vwtyzhuiv5j6zmzf4tudhyu/bafkreifcqjh3eebfd7odyqgnvlpcfzj2w3lb6n2q5xnghkuri3sod4j73e@jpeg)
June 9, 2025 at 9:05 AM
We analysed viral concentration time series from a national wastewater-based pathogen monitoring program. We made use of variable delays between sample collection an processing to estimate the degradation rates of RNA in four resp. pathogens.
Had to abandon my bike at a friend's flat last night. I think the towel I put over my saddle did the trick!
November 22, 2024 at 10:14 AM
Had to abandon my bike at a friend's flat last night. I think the towel I put over my saddle did the trick!
We combined this network with estimates of MMR uptake per school and found that the outbreaks simulated on our network were able to explain the national spread and closely replicate the geographic distribution of cases observed in 2013. 6/8
October 15, 2024 at 6:40 AM
We combined this network with estimates of MMR uptake per school and found that the outbreaks simulated on our network were able to explain the national spread and closely replicate the geographic distribution of cases observed in 2013. 6/8
We found that the connections between schools who have specific affiliation with the particular population group were much more connected to each other than the rest of the network. 5/8
October 15, 2024 at 6:39 AM
We found that the connections between schools who have specific affiliation with the particular population group were much more connected to each other than the rest of the network. 5/8
We used national school records data to quantify the connection between schools through households shared by siblings attending different schools. 4/8
October 15, 2024 at 6:38 AM
We used national school records data to quantify the connection between schools through households shared by siblings attending different schools. 4/8
It has been a real pleasure to engage with the fabulous scientists at #GEOMED24 this week. So much fascinating science and great conversation. And a delight to share and discuss two of my own projects with a smart, rigorous and kind community! Slides here: jdmunday.github.io/index.html#Conferences
September 12, 2024 at 10:52 AM
It has been a real pleasure to engage with the fabulous scientists at #GEOMED24 this week. So much fascinating science and great conversation. And a delight to share and discuss two of my own projects with a smart, rigorous and kind community! Slides here: jdmunday.github.io/index.html#Conferences