Caspar Geenen
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caspargeenen.bsky.social
Caspar Geenen
@caspargeenen.bsky.social
93 followers 130 following 15 posts
Working on a PhD at Clinical Microbiology Lab, KU Leuven. Investigating new ways to track the spread of infections. #IDEpi
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caspargeenen.bsky.social
New study: analysing indoor air to detect outbreaks.

“… Air sampling could provide sensitive, responsive #epidemiology indicators for surveillance of respiratory pathogens…”

See thread for details and previous air sampling work with @emmanuel-microb.bsky.social…

#IDEpi #IDsky #PedsID #KULeuven 🛟
Heatmap chart showing the detection of various pathogens over different sampling weeks (W9 to W30). Pathogens are listed on the y-axis, including viruses and bacteria such as Streptococcus pneumoniae, human coronaviruses, influenza viruses, and others. The x-axis represents the sampling weeks. Black dots indicate detection of the pathogen in the air. The colour gradient, ranging from white to dark red, represents the proportion of positive paper tissue samples, with darker shades indicating higher proportions. This alt text was generated by ChatGPT. A chart showing the relative detection of pathogens in air versus paper tissues, with pathogens listed on the y-axis (e.g., Pneumocystis jirovecii, herpes simplex virus type 1, SARS-CoV-2). The x-axis represents ∆Ct values, where negative values indicate higher detection in air and positive values indicate higher detection in paper tissues. Red dots represent the mean ∆Ct for each pathogen, and horizontal red error bars represent the 95% confidence intervals. Individual grey dots indicate data points for each sample. Pathogens are arranged by their relative prevalence in air and paper tissues. This alt text was generated by ChatGPT.
January 30, 2025 at 10:55 AM