Ka Chun Chong

310 total papers · 5.2k total citations
203 papers, 3.0k citations indexed

About

Ka Chun Chong is a scholar working on Infectious Diseases, Epidemiology and Modeling and Simulation. According to data from OpenAlex, Ka Chun Chong has authored 203 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Infectious Diseases, 64 papers in Epidemiology and 61 papers in Modeling and Simulation. Recurrent topics in Ka Chun Chong's work include COVID-19 epidemiological studies (61 papers), SARS-CoV-2 and COVID-19 Research (45 papers) and Influenza Virus Research Studies (29 papers). Ka Chun Chong is often cited by papers focused on COVID-19 epidemiological studies (61 papers), SARS-CoV-2 and COVID-19 Research (45 papers) and Influenza Virus Research Studies (29 papers). Ka Chun Chong collaborates with scholars based in Hong Kong, China and United States. Ka Chun Chong's co-authors include Benny Zee, Maggie Haitian Wang, Shi Zhao, Paul K.S. Chan, Martin C. S. Wong, Zigui Chen, Eliza Lai‐Yi Wong, Christopher K.C. Lai, Rita W. Y. Ng and Daihai He and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Nature Communications.

In The Last Decade

Ka Chun Chong

186 papers receiving 2.9k citations

Hit Papers

Acceptance of the COVID-1... 2021 2026 2022 2024 2021 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ka Chun Chong 926 822 553 469 390 203 3.0k
Nazrul Islam 593 0.6× 486 0.6× 628 1.1× 300 0.6× 328 0.8× 151 3.4k
Pascal Geldsetzer 773 0.8× 365 0.4× 562 1.0× 421 0.9× 443 1.1× 152 3.3k
Diane K. Wagener 313 0.3× 870 1.1× 814 1.5× 301 0.6× 241 0.6× 93 3.4k
Michael L. Pennell 506 0.5× 274 0.3× 270 0.5× 848 1.8× 288 0.7× 101 3.1k
Howard Markel 390 0.4× 436 0.5× 473 0.9× 231 0.5× 290 0.7× 149 2.6k
Carlo Signorelli 871 0.9× 346 0.4× 1.0k 1.8× 1.1k 2.4× 285 0.7× 223 4.2k
Jacqui Wise 1.1k 1.1× 306 0.4× 249 0.5× 416 0.9× 221 0.6× 579 2.9k
Stefan Ma 1.1k 1.2× 1.4k 1.7× 1.5k 2.6× 424 0.9× 367 0.9× 114 5.1k
Hilda Razzaghi 1.2k 1.2× 470 0.6× 1.3k 2.3× 1.0k 2.2× 272 0.7× 65 4.8k
Joshua L. Warren 1.3k 1.4× 250 0.3× 678 1.2× 243 0.5× 124 0.3× 178 3.9k

Countries citing papers authored by Ka Chun Chong

Since Specialization
Citations

This map shows the geographic impact of Ka Chun Chong's research. 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 Ka Chun Chong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ka Chun Chong more than expected).

Fields of papers citing papers by Ka Chun Chong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ka Chun Chong. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ka Chun Chong. The network helps show where Ka Chun Chong may publish in the future.

Co-authorship network of co-authors of Ka Chun Chong

This figure shows the co-authorship network connecting the top 25 collaborators of Ka Chun Chong. A scholar is included among the top collaborators of Ka Chun Chong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ka Chun Chong. Ka Chun Chong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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