Jia Wei

Assistant Professor, PhD Supervisor
jia_wei@bjmu.edu.cn
Xueyuanlu 38., Haidian district, Beijing, China
Peking University

Personal profile

Dr. Jia Wei is an Assistant Professor and PhD Supervisor at the School of Public Health, Peking University. She received her Bachelor’s degree from Peking University Health Science Center in 2019, and completed her DPhil (Oxford’s equivalent of a PhD) in Clinical Medicine from the Nuffield Department of Medicine, University of Oxford, in 2023, under the supervision of Professor David Eyre and Professor Sarah Walker. From 2023 to 2025, she was a Postdoctoral Researcher at Nuffield Department of Medicine, University of Oxford.

Dr. Wei’s research focuses on infectious diseases and health data science. In recent years, she has published in high-impact journals including Nature Medicine, Nature Microbiology, Nature Communications, and Clinical Infectious Diseases. She also peer-reviewed papers for journals including Journal of Infection, eBioMedicine, and Signal Transduction and Targeted Therapy. She actively seeks collaboration with researchers and clinicians in public health, epidemiology, data science, pediatrics, and infectious diseases.

Main research directions

Dr. Wei integrates approaches from epidemiology, statistics, infectious diseases, immunology, and health data science to investigate the epidemiology of emerging infectious diseases and to conduct clinical and epidemiological studies using large-scale health data.

Her main research interests include:

1. Epidemiology, surveillance, and immunization of infectious diseases in children and adolescents

2. Longitudinal modelling of serological responses to infection

3. Real-world evaluation of vaccine effectiveness and correlates of protection

4. Clinical diagnosis and rational antibiotic treatment in infectious diseases

5. Development of predictive models based on clinical big data

Dr. Wei is continuously recruiting research assistants, PhD students, and postdoctoral researchers. Students interested in infectious disease epidemiology, health data science, or maternal, child, and adolescent health are encouraged to get in touch via email.

Representative scientific research projects

10 representative papers

1. Wei J, Pouwels KB, Stoesser N, et al. Antibody responses and correlates of protection in the general population after two doses of the ChAdOx1 or BNT162b2 vaccines. Nature Medicine. 2022, 28(5), 1072-1082.

2. Wei J, Stoesser N, Matthews PC, et al. Antibody responses to SARS-CoV-2 vaccines in 45,965 adults from the general population of the United Kingdom. Nature Microbiology. 2021, 6(9), 1140-1149.

3. Wei J, Matthews PC, Stoesser N, et al. Anti-spike antibody response to natural SARS-CoV-2 infection in the general population. Nature Communications. 2021, 12(1), 6250.

4. Wei J, Matthews PC, Stoesser N, et al. SARS-CoV-2 antibody trajectories after a single COVID-19 vaccination with and without prior infection. Nature Communications. 2022, 13(1), 3748.

5. Wei J, Matthews PC, Stoesser N, et al. Protection against SARS-CoV-2 Omicron BA. 4/5 variant following booster vaccination or breakthrough infection in the UK. Nature Communications. 2023, 14(1), 2799.

6. Wei J, Stoesser N, Matthews PC, et al. Risk of SARS-CoV-2 reinfection during multiple Omicron variant waves in the UK general population. Nature Communications. 2024, 15(1).

7. Lumley SF, Wei J, O’Donnell D, et al. The duration, dynamics, and determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody responses in individual healthcare workers. Clinical Infectious Diseases. 2021, 73(3), e699-e709.

8. Wei J, Uppal A, Nganjimi C, et al. No evidence of difference in mortality with amoxicillin versus co-amoxiclav for hospital treatment of community-acquired pneumonia. J Infect. 2024, Jun;88(6):106161.

9. Wei J, Zhou J, Zhang Z, et al. Predicting individual patient and hospital-level discharge using machine learning. Commun Med, 2024, 4, 236.

10. Wei J, Yuan K, Luk A, Walker AS, Eyre DW. Community-acquired pneumonia identification from electronic health records in the absence of a gold standard: A Bayesian latent class analysis. PLOS Digital Health. 2025, 4(7).