ODeSI – Operational Research and Decision Support for Prevention, Control and Elimination of Infectious Diseases


Our mission

Our mission is to optimise infectious disease prevention, control and elimination by generating new evidence, providing innovative solutions, and supporting clinical and public health decision making. 

We develop strong multidisciplinary partnerships with clinical and public health decision makers in order to co-create and design research questions and programs, collaborate on the implementation and evaluation of research interventions, and explore the application of innovative methods and new technologies to disease prevention and control.

We have extensive experience in infectious diseases and clinical epidemiology, including: operational research and field surveys, predictive risk mapping and modelling (spatial epidemiology), clinical trials, disease surveillance, systematic reviews and meta-analyses and the use of novel methods to aid inference, including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools.

Twitter handle: @IDNET_UQ



  • Deborah Mills

    Dr Deborah Mills

    Dr Deb’s The Travel Doctor
  • Hammad Ali

    Dr Hammad Ali

    Adjunct Associate Professor
    School of Public Health
    US Centers for Disease Control and Prevention
  • Dr Sarah Sheridan

    National Centre for Immunisation Research and Surveillance (NCIRS)
  • Nicolas Smoll

    Dr Nicolas Smoll

    Sunshine Coast Health
  • Jessica Chellappah

    Dr Jessica Chellappah

    Australian Defence Force Malaria and Infectious Disease Institute


Patricia GravesProfessor Patricia Graves (James Cook University)



Meru SheelAssociate Professor Meru Sheel (The University of Sydney)



Angus McLureDr Angus McLure (Australian National University)



Brady McphersonLt Col Brady McPherson (Australian Defence Force Malaria and Infectious Disease Institute)



Peter SlyProfessor Peter Sly (Child Health Research Centre, UQ)



Paul JagalsProfessor Paul Jagals (Child Health Research Centre, UQ)




Aminath Shausan Dr Aminath Shausan (CSIRO E-Health)




Current students

Thomas CallaghanThomas Callaghan (PhD, UQ School of Veterinary Sciences): A big data food-chain approach to the epidemiology of zoonotic foodborne illness in Queensland



Sophie WenDr Sophie Wen (PhD, UQ School of Medicine): Gram negative blood stream infections in children



Jane SinclairJane Sinclair (PhD, UQ School of Chemistry and Molecular Biosciences): The long-term cardiovascular complications of COVID-19



Ama WakwellaAma Wakwella (PhD, UQ Centre for Biodiversity and Conservation Science): Delivering human and ecosystem health co‐benefits through integrated watershed management: improving disease prevention, fisheries, and marine environments in Fiji



Jemma RowlandsJemma Rowlands (PhD, School of Public Health): Enhancing infectious disease surveillance through the integration of routinely collected data



Nicky FoxleeNicky Foxlee (PhD, ANU School of Population Health, NCEPH): Developing Pathways to Improving Antibiotic Stewardship in Vanuatu



Beatris MartinDr Beatris Martin (PhD, School of Public Health): Spatio-temporal epidemiology of vector-borne diseases in the Dominican Republic



Ramona MuttucumaruRamona Muttucumaru (Master of Philosophy in Applied Epidemiology (MAE) student)



WondimenehWondimeneh Shiferaw (PhD, UQ Centre for Clinical Research): Assessing risk of importation of sexually transmitted infections into Australia by international travellers



Selina WardSelina Ward (PhD, UQ Centre for Clinical Research) - Integrated Surveillance of Neglected Tropical Diseases and Vaccine-Preventable Diseases




Yan ZhuDr Yan Zhu (Visiting Research Student)

Subject expertise

  • Neglected Tropical Diseases – lymphatic filariasis & others
  • Emerging Infectious Diseases – leptospirosis, arboviruses, & others
  • Travel medicine –malaria prophylaxis, vaccines, health & wellbeing of travellers
  • Other infectious diseases

Methodological expertise

  • Field surveys – electronic data collection & management, field laboratories
  • Spatial epidemiology & predictive risk mapping & modelling
  • Eco-epidemiology – environmental & sociodemographic drivers of disease transmission
  • Clinical epidemiology, including clinical trials in travel clinic settings
  • Surveillance
  • Systematic reviews & meta-analyses
  • Bayesian networks
  • Novel epidemiological methods – machine learning, social network analysis, interactive & dynamic data visualisation tools

We collaborate with a variety of partner organisations. These include the World Health Organization, US Centers for Disease Control and Prevention, Ministries of Health and governments, and many leading universities and research institutions including Harvard, Yale, and London School of Hygiene & Tropical Medicine.

Australian partners include:

We have a number of current international study partnerships in Samoa, American Samoa, Fiji, and the Dominican Republic.

International partners include:

Available student projects and staff contacts

Across our research team we have multiple student research projects available. Some examples are listed below, but please feel free to contact our team to discuss other options.

Dr Helen Mayfield and Prodessor Colleen Lau  - Supervisors

2023 Semester one student projects for lymphatic filariasis

Lymphatic filariasis is a globally prevalent, vector-borne disease affecting millions of people.  In the Samoan Islands, the elimination programs have been active for decades, administering anti-filarial drugs to entire populations over multiple rounds.  Despite this, elimination has still not been achieved.  The ID-NET team is currently has several opportunities for students to contribute to operation research in the Pacific region as part of the ‘Surveillance and monitoring for elimination of LF in Samoa (SaMELFS) project. Students whose work is of a sufficient quality could expect to publish the results in a peer-reviewed scientific journal.   

Project 1: Microfilaraemia in the Samoan Islands - Supervisor Colleen Lau and Helen Mayfield

The gold standard for detecting LF infection in humans is the detection of circulating parasite microfilaremia (Mf) in the blood. Mf prevalence is generally significantly lower than other indicators, such as antigen or antibodies, meaning that confidence intervals for estimating prevalence are wider, and results can be challenging to interpret.  This project will analyse data from four field surveys, two each in Samoa and American Samoa, to answer the following questions; 

  • What is the spatial distribution of Mf in the Samoan Islands, and to what extent are the results clustered 
  • Counts of Mf in the blood slides are conducted manually by two independent observers.  Is there are significant between observers? 

This project will require a literature review, basic statistical analysis and spatial mapping skills (ArcGIS or similar) 

 Project 2: Comparison of Microfilaraemia and molecular xenomonitoring in Samoa  - Supervisor Colleen Lau and Helen Mayfield

Molecular xenomonitoring (MX), which is surveying mosquitoes, for LF is often compared to the results of human antigen surveys. However, the actual prevalence of infection in mosquitoes is often closer to that of circulating microfilaraemia (Mf). Often this comparison is not carried out, as the low infection rates make the analysis challenging - around ~40/5000 participant.  This project will analysis data from two surveys in Samoa, in 2018 and 2019 to; 

  • Compare the estimates and spatial patterns of Mf and MX  
  • Examine correlations: 
    • Prevalence at the vilalge/region/national level 
    • Presence/absence at the household/village level 
  • Analyse clustering at the household/village/region level for Antigen, Mf, and MX 

This project will require a literature review, basic statistical analysis and spatial mapping skills (ArcGIS or similar) 

Project 3: Comparison of LF indicators in Samoa using Bayesian Networks  - Supervisor Helen Mayfield and Colleen Lau

The standard diagnostic field- test for LF is Antigen.  However, preliminary results from Myanmar and American Samoa indicate that antibody test (BM14, Bm33 and wb123) could provide an earlier indicator of resurgence. Bayesian network models have provided a simple and effective tool for analysing the different combinations of indicators to help inform on-the-ground programmatic decisions. This project will look to repeat this analysis using recently available data from Samoa, and compare the results to findings from Myanmar and American Samoa. 

This project will require a literature review, and basic coding skills (R, python or similar). Previous knowledge of Bayesian networks is not essential. 


Professor Colleen Lau - Supervisor

  • Integrated surveillance of neglected tropical diseases and vaccine preventable diseases in Samoa
  • Epidemiology of notifiable diseases in Australia
  • Vaccine preventable diseases in travellers
  • Decision support tools for COVID-19 vaccines

Dr Amalie Dyda - Supervisor

  • Social Media and Vaccination: How does the way citizens access, understand, use, and share information about adult vaccines impact attitudes and behaviour?
  • Enhancing the use of routinely collected infectious disease surveillance data for public health action.

Dr Lisa McHugh – Supervisor

  • 2023: Evaluating Australian maternal vaccination programs; including the uptake, safety and effectiveness of influenza, pertussis and COVID-19 vaccines in pregnancy. There are multiple projects within this NHMRC-funded grant that would suit a PhD or MPhil student, and a clinical background in midwifery or epidemiology would be helpful.