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Statistics and modelling for policy in a COVID-zero setting

Tuesday, 23 November 2021, 9.15am to 10.30am

In the latest of the Turing-RSS Lab international distinguished lecture series, Prof Jodie McVernon and colleagues will be presenting on their experience in Australia. Australia and other countries in the Asia-Pacific Region have had a very different experience of COVID-19 over the past two years from the ‘global north’. Border measures and strong public health controls focused on zero community transmission have resulted in effective elimination in many settings, interspersed with periods of low disease activity. Estimation of COVID-19 risks and the likely impact of public health interventions including vaccination in this context required development of innovative statistical and modelling methods for scenario preparedness and situational assessment. Members of a nationally distributed team of modellers who have supported COVID-19 policy decision making in Australia and the Western Pacific Region will present some of these approaches.

Agenda

0915-0930  Introductions: Prof Peter Diggle (Turing-RSS Technical Director) & Dr Johanna Hutchinson (UKHSA Director of Analytics and Data Science)

0930-1015  Presentation: Prof McVernon and colleagues

1015-1030  Q&A

Register in advance:

https://turing-uk.zoom.us/webinar/register/WN_kZja5eyGSlOvgvTXEYhK-Q

Jodie McVernon

Prof Jodie McVernon is a public health physician and epidemiologist, with a focus on translating model-informed evidence into policy. Her work undertaken with large multi-disciplinary teams has informed policy for the control of emerging, vaccine preventable and neglected tropical infectious diseases in Australia, the Asia Pacific region and globally.

Nick Golding

Prof Nick Golding is an statistically-inclined infectious disease modeller with wide-ranging experience in policy-relevant modelling on neglected tropical diseases, and emerging diseases such as avian influenza and Ebola. He is interested in Bayesian inference software and semi-mechanistic models of disease transmission.

Freya Shearer

Dr Freya Shearer is an infectious disease modeller. Her research interests include the critical relationships between epidemiological data, situational assessment, and preparedness planning in guiding effective and evidence-informed pandemic response.

David Price

Dr David Price is a biostatistician and stochastic modeller with a keen interest in infectious diseases. Since March 2020, he has been part of a team providing situational assessment and model-based evidence to support policy decisions in Australia and neighbouring countries.

Please contact healthprogramme@turing.ac.uk should you have any questions.

Forthcoming talks

Achieving Consistent Low Latency for Wireless Real-Time Communications with the Shortest Control Loop

Thursday, 18 August 2022, 4.00pm to 5.00pm
Speaker: Zili Meng, Tsinghua Unversity
Venue: FW11 and https://cl-cam-ac-uk.zoom.us/j/97216272378?pwd=M2diTFhMTnppckJtNWhFVTBKK0REZz09

Real-time communication (RTC) applications like video conferencing or cloud gaming require consistent low latency to provide a seamless interactive experience. However, wireless networks including WiFi and cellular, albeit providing a satisfactory median latency, drastically degrade at the tail due to frequent and substantial wireless bandwidth fluctuations. We observe that the control loop for the sending rate of RTC applications is inflated when congestion happens at the wireless access point (AP), resulting in untimely rate adaption to wireless dynamics. Existing solutions, however, suffer from the inflated control loop and fail to quickly adapt to bandwidth fluctuations. In this paper, we propose Zhuge, a pure wireless AP based solution that reduces the control loop of RTC applications by separating congestion feedback from congested queues. We design a Fortune Teller to precisely estimate per-packet wireless latency upon its arrival at the wireless AP. To make Zhuge deployable at scale, we also design a Feedback Updater that translates the estimated latency to comprehensible feedback messages for various protocols and immediately delivers them back to senders for rate adaption. Trace-driven and real-world evaluation shows that Zhuge reduces the ratio of large tail latency and RTC performance degradation by 17% to 95%.

Speaker Bio: Zili is a 3rd-year PhD student in Tsinghua University. His current research interest focuses on real-time video communications. He has published several papers in SIGCOMM / NSDI and received the Microsoft Research Asia PhD Fellowship, Gold Medal of SIGCOMM 2018 Student Research Competition, and two best paper awards.

BSU Seminar: "Genome-wide genetic models for association, heritability analyses and prediction"

Monday, 22 August 2022, 4.30pm to 5.30pm
Speaker: David Balding, Honorary Professor of Statistical Genetics at UCL Genetics Institute and University of Melbourne
Venue: Seminar Rooms 1 & 2, School of Clinical Medicine, Hills Road, Cambridge CB2 0SP

Although simultaneous analysis of genome-wide SNPs has been popular for over a decade, the problems posed by more SNPs than study participants (more parameters than data points), and correlations among the SNPs, have not been adequately overcome so that almost all published genome-wide analyses are suboptimal. While there has been much attention paid to the shape of prior distributions for SNP effect sizes, we argue that this attention is misplaced. We focus on what we call the "heritability model": a low-dimensional model for the expected heritability at each SNP, which is key to both individual-data and summary-statistic analyses. The 1-df uniform heritability model has been implicitly adopted in a wide range of analyses. Replacing it with better heritability models, using predictors based on allele frequency, linkage disequilibrium and functional annotations, leads to substantial improvements in estimates of heritability and selection parameters over traits, and over genome regions, as well as improvements in gene-based association testing and prediction. Key collaborators Doug Speed, Aarhus, Denmark and Melbourne PhD student Anubhav Kaphle.

Statistics Clinic Summer 2022 III

Wednesday, 31 August 2022, 5.30pm to 7.00pm
Speaker: Speaker to be confirmed
Venue: Venue to be confirmed

If you would like to participate, please fill in the following "form":https://forms.gle/b1UzrTNBig7hkr1e7. The deadline for signing up for a session is 12pm on Monday the 29th of August. Subject to availability of members of the Statistics Clinic team, we will confirm your in-person or remote appointment.

This event is open only to members of the University of Cambridge (and affiliated institutes). Please be aware that we are unable to offer consultations outside clinic hours.

Statistics Clinic Summer 2022 IV

Wednesday, 21 September 2022, 5.30pm to 7.00pm
Speaker: Speaker to be confirmed
Venue: Venue to be confirmed

Abstract not available

Title to be confirmed

Monday, 26 September 2022, 3.00pm to 4.00pm
Speaker: Christopher Yau, University of Manchester
Venue: CRUK CI Lecture Theatre

Abstract not available