Imperial College London

Dr Nina J. Zhu

Faculty of MedicineDepartment of Infectious Disease

Research Associate



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Dr Nina Zhu, PhD, MPH, MSc, BEng, is the Research Lead for Population Health & Policy Theme 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.


System Dynamics modelling

Nina's research in the Population Health & Policy 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. 


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. 



Zhu J, Holmes A, 2021, Changing patterns of bloodstream infections in the community and acute care across two COVID-19 epidemic waves: a retrospective analysis using data linkage, Clinical Infectious Diseases, ISSN:1058-4838

Abbas M, Zhu NJ, Mookerjee S, et al., 2021, Hospital-onset COVID-19 infection surveillance systems: a systematic review, Journal of Hospital Infection, Vol:115, ISSN:0195-6701, Pages:44-50

Charani E, McKee M, Ahmad R, et al., 2021, Optimising antimicrobial use in humans-review of current evidence and an interdisciplinary consensus on key priorities for research, Lancet Regional Health-europe, Vol:7, ISSN:2666-7762

Ahmad R, Atun R, Birgand G, et al., 2021, Macro level influences on strategic responses to the COVID-19 pandemic – an international survey and tool for national assessments, Journal of Global Health, Vol:11, ISSN:2047-2978, Pages:1-11

Zhu J, Ferlie E, Castro-Sánchez E, et al., 2021, Macro level factors influencing strategic responses to emergent pandemics: a scoping review, Journal of Global Health, Vol:11, ISSN:2047-2978, Pages:1-16

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