Imperial College London

Dr Nina J. Zhu

Faculty of MedicineDepartment of Infectious Disease

Research Associate
 
 
 
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Contact

 

jiayue.zhu09 Website

 
 
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Location

 

Commonwealth BuildingHammersmith Campus

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Summary

 

Summary

Dr Nina Zhu, PhD, MPH, MSc, BEng, is the Research Associate in Health Systems and System Dynamics in the National Institute of Health Research Health Protection Research Unit in Healthcare Associated Infection and Antimicrobial Resistance. The HPRU is a partnership between Imperial College London, Public Health England, Cambridge University, Warwick University and Imperial College Health Partners. The Unit was funded, along with 14 others in priority areas from immunisation to radiation hazards, to bring Universities to work in partnership with Public Health England to support excellent health protection research relevant to the needs of Public Health England. It commenced 01 April 2020 for a 5 year period and builds on the legacy of the previous HPRU which ran from 01 April 2014 -31 March 2020.

Research


System Dynamics modelling

Nina's research in the Organisational Change, Health Economics and Evaluation Theme in the HPRU primarily focuses on applying System Dynamics (SD) modelling to examine doctors’ and patients' decision-making processes to inform design, implementation, and evaluation of antimicrobial stewardship (AMS) interventions. She aims to establish meta-methodology to help identify and develop optimal systems thinking tools, combined with other simulation methods, including discrete event simulation (DES), and agent-based modelling (ABM), to solve real-life problems in system management in general.

She is the SD modeller and quantitative data analyst of the ESRC funded multi-national research project, ASPIRES (Antibiotic use across Surgical Pathways - Investigating, Redesigning and Evaluating Systems), to model the impact on patient, health systems, and health economic outcomes of interventions proposed to optimise antibiotic use along surgical pathways. 

Before joining HPRU, she was a visiting researcher at Harvard T. H. Chan School of Public Health. She has employed the same modelling methodology to investigate evidence in health system strengthening and healthcare intervention evaluation in low- and mid- income countries (LMICs).


Applied data linkage and MODELLING

Nina is currently conducting the investigation project in the AMR/HCAI Division at Public Health England (PHE) to assess underlying risk factors of Gram-negative blood stream infections (GN BSIs) in England. This is for the first time national scale patient-level data linkage has been performed using prescribing data, laboratory surveillance data, and hospital administrative data to produce baseline description and regression models for GN BSIs. 

Background


Nina has a PhD in Clinical Medicine Research. Her doctoral research focused on investigating factors influencing doctors' antibiotic prescribing decision-making processes in secondary care using System Dynamics. Nina has a Bachelor of Engineering (BEng) (hons) of Biomedical Engineering and a Master of Public Health (MPH) from Imperial College London, and is a candidate of MSc in Economic Evaluation in Healthcare from City, University of London. 

Publications

Journals

Zhu J, Ahmad R, Holmes A, et al., 2020, System dynamics modelling to formulate policy interventions to optimise antibiotic prescribing in hospitals, Journal of the Operational Research Society, ISSN:0160-5682

Rawson TM, Moore L, Zhu N, et al., 2020, Bacterial and fungal co-infection in individuals with coronavirus: A rapid review to support COVID-19 antimicrobial prescribing, Clinical Infectious Diseases, ISSN:1058-4838

Ahmad R, Zhu NJ, Leather AJM, et al., 2019, Strengthening strategic management approaches to address antimicrobial resistance in global human health: a scoping review, Bmj Global Health, Vol:4, ISSN:2059-7908

Ahmad R, Zhu J, Lebcir MR, et al., 2019, How the health-seeking behaviour of pregnant women affects neonatal outcomes: findings of System Dynamics modelling in Pakistan, Bmj Global Health, Vol:4, ISSN:2059-7908

Naylor NR, Atun R, Zhu N, et al., 2018, Estimating the burden of antimicrobial resistance: a systematic literature review, Antimicrobial Resistance and Infection Control, Vol:7, ISSN:2047-2994

More Publications