The South Australian Branch of The Statistical Society of Australia is delighted to invite you to the 2023 E. A. Cornish Memorial Lecture. Held every two years, this lecture is the highlight of our Branch’s speaker program. The 2023 lecture will be presented by Professor Julie Simpson on the topic "Integration of statistical modelling and mathematical biology to improve the treatment of malaria."
Date: Wednesday, 15 November 2023
Time: 5:30 PM ACDT for lecture at 6:00 PM.
Venue: Schulz 214/218 Lecture Room, Level 2 Schulz Building, North Terrace Campus at The University of Adelaide.
Registration: Please register your attendance to the lecture with the Eventbrite link: https://tinyurl.com/3ktnmwyx
Feel free to forward this meeting notice to colleagues, all welcome. We look forward to seeing you there!
Agenda
5:30-6:00 - Pre-lecture light refreshments
6:00:7:15 - E.A. Cornish Lecture by Professor Julie Simpson
7:45-9:45 - Dinner (Separate RSVP for dinner required)
Post-lecture dinner: For attendees who wish to join Professor Simpson and the colleagues at the Branch, a dinner will be held at La Buvette Bistro, 27 Gresham Street, Adelaide SA 5000. RSVP is essential as reservation spaces are limited. To confirm your attendance to the dinner, please email the Branch Secretary at statsoc.sa.branch@gmail.com by COB Monday 13 November.
Lecture Abstract
The widespread emergence of drug-resistant parasites now threatens the efficacy of first-line treatments of malaria, necessitating the urgent development of novel regimens and combinations of existing and new therapeutic agents to ensure adequate cure of malaria.
To address this challenge, biostatisticians and mathematical biologists often approach the determination of optimal treatment regimens from a different starting point. Biostatisticians primarily analyse clinical data to estimate the effects of different treatment regimens on patient outcomes. While this approach provides valuable insights into the investigated dosing regimens, it doesn’t provide an appropriate model for predicting patient outcomes under different mechanisms of drug resistance or explore alternative dosing schemes. Mathematical biologists begin by developing a model for prediction that captures the biological mechanisms of the infection, such as the life cycle of the malaria parasite within the red blood cell. However, when these “mechanistic” mathematical models are expanded to incorporate treatment actions and patient immunity, they often become highly complex, impeding their validation against clinical data within a proper statistical framework.
This presentation will outline an interdisciplinary approach using mathematical biology and Bayesian statistical methods, to determine optimal treatment regimens and how this work has informed WHO treatment guidelines for malaria.
About the Speaker
Professor Julie Simpson is Head of Biostatistics at the Melbourne School of Population and Global Health and Director of the Methods and Implementation Support for Clinical and Health research (MISCH) Hub at the University of Melbourne. She has 30 years’ experience collaborating on multidisciplinary research projects with clinicians, laboratory scientists, epidemiologists and health policy-makers at universities and hospitals (and even refugee camps) worldwide. Her main area of research is the integration of biostatistics and mathematical modelling to improve the control of infectious diseases and statistical methods for handling missing data. She is a lead investigator of ViCBiostat (Victorian Centre of Biostatistics), ACREME (Australian Centre for Research Excellence in Malaria Elimination) and IDDO (Infectious Diseases Data Observatory).
@StatSocAus
