Sam Abbott (@[email protected])
@seabbs
Real-time infectious disease modelling. Developing methods for outbreak response, surveillance, and pandemic preparedness. https://t.co/qIESZxy6rY
ID:3900399077
http://samabbott.co.uk 08-10-2015 14:55:16
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On #InternationalWomensDay we invite contributions to a special issue of Epidemics co-edited with Paula Christen, PhD on research culture in ID modelling tiny.cc/IDEculture. Also, here are (again) my thoughts on being a woman/minority in academia tiny.cc/SIRorMADAM
Tomorrow at 3pm UK time we have Tomás León speaking at the #epinowcast seminar on:
CalCAT: Past, Present, and Future for California’s Use of Infectious Disease Modeling in Public Health Response
epinowcast.org/seminars/2024-…
Exciting new work in #ecologicalforecasting from my PhD student (authors.elsevier.com/sd/article/S03….). We use Bayesian Dynamic GAMs to model time series of captures for desert rodents. A short thread:
Our examination of modellers' working practices during COVID-19 is now out in WellcomeOpenResearch.
Frustratingly, I think it's at least as relevant now as when we conducted the work ~year ago. Let's make it obsolete.
wellcomeopenresearch.org/articles/9-12
Anna Carnegie💖 Yang 刘扬 Sam Abbott (@[email protected])
Useful new paper on estimating delay distributions during epidemics by Sang Woo Park, Sam Abbott (@[email protected]) and co: medrxiv.org/content/10.110…
Below point is key one I think for simple methods - either you use more of your data and (often) introduce bias, or use less and get more uncertainty.