Name: Jinxin ZHENG, Post-doctoral Researcher
Email: [email protected]
Tel: +86 15250950595
Research Interest：Public health, epidemiology, Machine learning, infectious diseases
Jin-xin Zheng completed his Ph.D. at The National Institute of Parasitic Diseases, China CDC (2018-2021). He obtained his bachelor’s degree from Anhui Medical University in 2015, followed by a one-year master’s program at Nanjing Medical University before joining the Jiangsu Institute of Parasitic Diseases in 2016 to complete his master’s studies. With three years of experience in Public Health, Dr. Zheng has specialized in biostatistics and modeling methods within the field of infectious diseases. His research focuses on global One Health issues, where he utilizes machine learning algorithms and ecological modeling to investigate infectious diseases such as COVID-19, malaria, dengue, schistosomiasis, and liver fluke, as well as non-infectious diseases. Dr. Zheng also collaborates closely with clinicians, applying machine learning to optimize clinical trial design and data analysis. He has a passion for using R and Python to perform medical data analysis and visualization. Dr. Zheng has been involved in the International Development Research Centre (IDRC) project, which focuses on disease modeling in South Asia, and has played a key role in the control and elimination of Helminth Zoonoses in the Greater Mekong Subregion, primarily focusing on data collection and developing models to assess risk areas for parasitic diseases.
Publications
1.Zheng JX, Lv S, Tian LG, Guo ZY, Zheng PY, Chen YL, Guan SY, Wang WM, Zhang SX. The rapid and efficient strategy for SARS-CoV-2 Omicron transmission control: analysis of outbreaks at the city level. Infect Dis Poverty. 2022 Nov 24;11(1):114.
2.Zhang D, Zheng JX. The Burden of Childhood Asthma by Age Group, 1990-2019: A Systematic Analysis of Global Burden of Disease 2019 Data. Front Pediatr. 2022 Feb 16;10:823399.
3.Liu Y, Zheng JX, Hao J, Wang RR, Liu X, Gu P, Yu H, Yu Y, Wu C, Ou B, Peng Z. Global burden of primary liver cancer by five etiologies and global prediction by 2035 based on global burden of disease study 2019. Cancer Med. 2022 Mar;11(5):1310-1323.
4.Li Y, Zheng JX, Deng Y, Deng X, Lou W, Wei B, Xiang D, Hu J, Zheng Y, Xu P, Yao J, Zhai Z, Zhou L, Yang S, Wu Y, Kang H, Dai Z. Global Burden of Female Breast Cancer: Age-Period-Cohort Analysis of Incidence Trends From 1990 to 2019 and Forecasts for 2035. Front Oncol. 2022 Jun 9;12:891824.
5.Liu TX, Zheng JX, Chen Z, Zhang ZC, Li D, Shi LP. An interpretable machine-learning model for predicting the efficacy of nonsteroidal anti-inflammatory drugs for closing hemodynamically significant patent ductus arteriosus in preterm infants. Front Pediatr. 2023 Apr
6.Hui-Hui Zhu, Ji-lei Huang , Chang-Hai Zhou , Ting-Jun Zhu , Zheng JX , Mi-Zhen Zhang , Men-Bao Qian ,Ying-Dan Chen ,Shi-zhu Li “Soil-transmitted helminthiasis in mainland China from 2016 to 2020: a population-based study.” The Lancet Regional Health–Western Pacific (2023).
7.Zheng JX, Xia S, Lv S, Zhang Y, Bergquist R, Zhou XN. Infestation risk of the intermediate snail host of Schistosoma japonicum in the Yangtze River Basin: improved results by spatial reassessment and a random forest approach. Infect Dis Poverty. 2021 May 20;10(1):74.
8.Zheng JX, Shi B, Xia S, Yang G, Zhou XN. Spatial patterns of Plasmodium vivax transmission explored by multivariate auto-regressive state-space modelling - A case study in Baoshan Prefecture in southern China. Geospat Health. 2021 Mar 12;16(1).
9.Zhu J, Zheng JX, Li L, Huang R, Ren H, Wang D, Dai Z, Su X. Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma. Front Med (Lausanne). 2021 Mar 9;8: 635771.
10.Shi B, Zheng JX, Xia S, Lin S, Wang X, Liu Y, Zhou XN, Liu J. Accessing the syndemic of COVID-19 and malaria intervention in Africa. Infect Dis Poverty. 2021 Jan 7;10(1):5.
11.Tian N, Zheng JX, Guo ZY, Li LH, Xia S, Lv S, Zhou XN. Dengue Incidence Trends and Its Burden in Major Endemic Regions from 1990 to 2019. Trop Med Infect Dis. 2022 Aug 12;7(8):180.
12.Yue Y, Zheng JX, Sheng M, Liu X, Hao Q, Zhang S, Xu S, Liu Z, Hou X, Jing H, Liu Y, Zhou X, Li Z. Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study. Infect Dis Poverty. 2023 Apr 21;12(1):41.
