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Email

jessica.ramsay@unimelb.edu.au

Credentials


Position
Research Officer
Department of Microbiology and Immunology
ORCID

0000-0003-4005-9886

Jessica Ramsay

Research Officer
Department of Microbiology and Immunology

17 Scholarly works
0 Projects

HIGHLIGHTS

  • 2026

    Journal article

    FeBRILe3: Caregiver Satisfaction With Early Discharge of Febrile Infants Under 3 Months Old
    DOI: 10.1542/hpeds.2025-008971
  • 2025

    Journal article

    FeBRILe3: Risk-Stratification and Diagnosis of Serious Bacterial Infections in Febrile Infants Less Than 3 Months Old
    DOI: 10.1111/jpc.70041
  • 2024

    Journal article

    Public health audit of vaccine cold chain management in general practice and community pharmacy in Western Australia
    DOI: 10.1016/j.anzjph.2024.100168
  • 2023

    Journal article

    Core protocol for the adaptive Platform Trial In COVID-19 Vaccine priming and BOOsting (PICOBOO)
    DOI: 10.1186/s13063-023-07225-z
  • 2023

    Journal article

    Modeling COVID-19 disease processes by remote elicitation of causal Bayesian networks from medical experts
    DOI: 10.1186/s12874-023-01856-1
  • 2023

    Journal article

    A single blinded, phase IV, adaptive randomised control trial to evaluate the safety of coadministration of seasonal influenza and COVID-19 vaccines (The FluVID study)
    DOI: 10.1016/j.vaccine.2023.10.050
  • 2023

    Journal article

    FeBRILe3: Safety Evaluation of Febrile Infant Guidelines Through Prospective Bayesian Monitoring
    DOI: 10.1542/hpeds.2023-007160
Jessica Ramsay

RECENT SCHOLARLY WORKS

  • 2022

    Journal article

    Urinary tract infections in children: building a causal model-based decision support tool for diagnosis with domain knowledge and prospective data
    DOI: 10.1186/s12874-022-01695-6
  • 2021

    Journal article

    Whole-cell pertussis vaccine in early infancy for the prevention of allergy in children
    DOI: 10.1002/14651858.CD013682.pub2
  • 2021

    Journal article

    Bridging the gaps in test interpretation of SARS-CoV-2 through Bayesian network modelling
    DOI: 10.1017/S0950268821001357

Acknowledgement of Country

We acknowledge Aboriginal and Torres Strait Islander people as the Traditional Owners of the unceded lands on which we work, learn and live. We pay respect to Elders past, present and future, and acknowledge the importance of Indigenous knowledge in the Academy.

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Victoria, 3010, Australia

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