Background: During the course of the COVID-19 pandemic, states were called upon by the World Health Organization to introduce and prioritise the collection of sex-disaggregated data. The collection of sex-disaggregated data on COVID-19 testing, infection rates, hospital admissions, and deaths, when available, has informed our understanding of the biology of the infectious disease. The collection of sex-disaggregated data should also better inform our understanding of the gendered impacts that contribute to risk of exposure to COVID-19. In China, the country with the longest history of fighting the COVID-19 infection, what research was available on the gender-differential impacts of COVID-19 in the first 6 months of the COVID-19 pandemic? Methods: In this scoping review, we examine the first 6 months (January–June 2020) of peer-reviewed publications (n = 451) on sex and gender experiences related to COVID-19 in China. We conducted an exhaustive search of published Chinese and English language research papers on COVID-19 in mainland China. We used a COVID-19 Gender Matrix informed by the JPHIEGO gender analysis toolkit to examine and illuminate research into the gendered impacts of COVID-19 within China. Results: In China, only a small portion of the COVID-19-related research focused on gender experiences and differences. Near the end of the six-month literature review period, a small number of research items emerged on women healthcare workers, women’s mental health, and pregnant women’s access to care. There was an absence of research on the gendered impact of COVID-19 amongst populations. There was minimal consideration of the economic, social and security factors, including gender stereotypes and expectations, that affected different populations’ experiences of infection, treatment, and lockdown during the period of review. Conclusion: At the outset of health emergencies in China, gender research needs to be prioritised during the first stage of an outbreak to assist with evaluation of the most effective public health measures, identifying access to healthcare and social welfare barriers amongst priority communities. Gender stereotypes and gendered differences lead to different patterns of exposure and treatment. The exclusion of this knowledge in real time affects the design of effective prevention and recovery.