China CDC Weekly

641 papers and 6.8k indexed citations i.

About

The 641 papers published in China CDC Weekly in the last decades have received a total of 6.8k indexed citations. Papers published in China CDC Weekly usually cover Infectious Diseases (196 papers), Epidemiology (144 papers) and Modeling and Simulation (92 papers) specifically the topics of COVID-19 epidemiological studies (92 papers), SARS-CoV-2 and COVID-19 Research (86 papers) and COVID-19 Clinical Research Studies (34 papers). The most active scholars publishing in China CDC Weekly are China CDC Weekly, Qun Li, George F. Gao, Na He, Guizhen Wu, Wenbo Xu, Matthew E. Dupre, Kirill Andreev, Danan Gu and Xiang Zhao.

In The Last Decade

Fields of papers published in China CDC Weekly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in China CDC Weekly. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in China CDC Weekly.

Countries where authors publish in China CDC Weekly

Since Specialization
Citations

This map shows the geographic impact of research published in China CDC Weekly. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in China CDC Weekly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites China CDC Weekly more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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2025