Meet Fengzhuo Cheng, statistical programmer, TGI China
Fengzhuo Cheng is a Statistical Programmer at the George Institute China.
How long have you been working at the George Institute?
Over a year. I started working at TGI China in August last year.
What is your professional background? Why did you decide to pursue global health research?
I graduated from Southern Medical University with a bachelor’s degree in preventive medicine, then obtained my master degree in public health from Queen's University of Belfast. Having the opportunity to contribute to improving the health of the population is extremely meaningful to me. Moreover, I like dealing with data and epidemiology fundamentally revolves around the relationship between things. In order to get precise and accurate conclusions, scientific and reasonable exploration of data is essential. And statistical analysis is the task of combining data with methodologies.
What attracted you to work at The George Institute?
The George Institute for Global Health is a research organization dedicated to the study of clinical, population and health systems in various fields, so being able to participate in different types of epidemiological trials is the primary reason that attracted me to work here. Diversity in trial research design implies that different statistical schemes will have to be designed. Different types of data also poses demands and challenges for the diversity of analytical methods, which is also attractive to me.
Which research project are you currently working on? How will they affect health care?
I’m currently working on the ROADMAP research project under the diabetes research unit. This study is based on diabetes as a breakthrough point. It attempts to establish a platform for the diagnosis and hierarchical management for diabetes in primary care settings. From the operational level, it establishes and explores the model and builds knowledge for the promotion of diabetes diagnosis and hierarchical management in China.
In your opinion, what is the biggest challenge for statistical analysis in global health research today?
Because large-scale cluster randomized controlled trials implies a large number of subjects, and each individual has different levels of enthusiasm for understanding and participating in the trial, there will be risks leading to low compliance and the integrity of subsequent data. As a data analyst, it is a big challenge to attain a conclusion that is close to reality on the basis that the completeness and authenticity of the data cannot be measured. However, with the use of portable devices such as mobile phones in the data collection process, this problem is gradually being improved.