King-Pan Chan

1.5k total citations · 1 hit paper
9 papers, 1.0k citations indexed

About

King-Pan Chan is a scholar working on Epidemiology, Modeling and Simulation and Health, Toxicology and Mutagenesis. According to data from OpenAlex, King-Pan Chan has authored 9 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Epidemiology, 4 papers in Modeling and Simulation and 3 papers in Health, Toxicology and Mutagenesis. Recurrent topics in King-Pan Chan's work include Influenza Virus Research Studies (6 papers), Respiratory viral infections research (4 papers) and COVID-19 epidemiological studies (4 papers). King-Pan Chan is often cited by papers focused on Influenza Virus Research Studies (6 papers), Respiratory viral infections research (4 papers) and COVID-19 epidemiological studies (4 papers). King-Pan Chan collaborates with scholars based in Hong Kong, China and Australia. King-Pan Chan's co-authors include Anthony J. Hedley, TQ Thach, TH Lam, Laith J. Abu‐Raddad, William Ho, Roy M. Anderson, Christl A. Donnelly, Steven Riley, Christophe Fraser and LM Ho and has published in prestigious journals such as Science, PLoS ONE and The Science of The Total Environment.

In The Last Decade

King-Pan Chan

9 papers receiving 967 citations

Hit Papers

Transmission Dynamics of the Etiological Agent of SARS in... 2003 2026 2010 2018 2003 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
King-Pan Chan Hong Kong 7 602 365 257 242 103 9 1.0k
Sunmi ‍Lee South Korea 19 556 0.9× 434 1.2× 132 0.5× 375 1.5× 98 1.0× 95 1.3k
Xiangjun Du China 14 803 1.3× 405 1.1× 563 2.2× 100 0.4× 41 0.4× 54 1.6k
Su‐Vui Lo Hong Kong 16 1.1k 1.8× 700 1.9× 834 3.2× 314 1.3× 52 0.5× 24 2.1k
Jia Rui China 15 617 1.0× 493 1.4× 118 0.5× 304 1.3× 34 0.3× 82 1.3k
Olivia Prosper United States 12 830 1.4× 312 0.9× 261 1.0× 286 1.2× 26 0.3× 23 1.3k
Nita Bharti United States 12 448 0.7× 195 0.5× 490 1.9× 204 0.8× 38 0.4× 36 1.3k
Caitlin Rivers United States 15 494 0.8× 567 1.6× 257 1.0× 211 0.9× 16 0.2× 31 1.2k
Anuj Mubayi United States 16 326 0.5× 242 0.7× 236 0.9× 426 1.8× 23 0.2× 51 1.0k
Kiesha Prem United Kingdom 16 939 1.6× 570 1.6× 526 2.0× 134 0.6× 38 0.4× 48 1.6k
Flávio Codeço Coelho Brazil 18 340 0.6× 287 0.8× 134 0.5× 361 1.5× 22 0.2× 65 1.1k

Countries citing papers authored by King-Pan Chan

Since Specialization
Citations

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

Fields of papers citing papers by King-Pan Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by King-Pan Chan. 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 King-Pan Chan. The network helps show where King-Pan Chan may publish in the future.

Co-authorship network of co-authors of King-Pan Chan

This figure shows the co-authorship network connecting the top 25 collaborators of King-Pan Chan. A scholar is included among the top collaborators of King-Pan Chan 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 King-Pan Chan. King-Pan Chan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Ran, Jinjun, Shengzhi Sun, Aimin Yang, et al.. (2018). Effects of ambient benzene and toluene on emergency COPD hospitalizations: A time series study in Hong Kong. The Science of The Total Environment. 657. 28–35. 19 indexed citations
2.
Yang, Lin, Daihai He, Alice P. Y. Chiu, et al.. (2017). Different responses of influenza epidemic to weather factors among Shanghai, Hong Kong, and British Columbia. International Journal of Biometeorology. 61(6). 1043–1053. 29 indexed citations
3.
Cao, Peihua, Chit-Ming Wong, Kwok‐Hung Chan, et al.. (2016). Age-specific genetic and antigenic variations of influenza A viruses in Hong Kong, 2013–2014. Scientific Reports. 6(1). 30260–30260. 2 indexed citations
4.
Yang, Lin, Kwok‐Hung Chan, King-Pan Chan, et al.. (2015). Age and Sex Differences in Rates of Influenza-Associated Hospitalizations in Hong Kong. American Journal of Epidemiology. 182(4). 335–344. 49 indexed citations
5.
Wong, Chit-Ming, et al.. (2014). Hospitalization risk of the 2009 H1N1 pandemic cases in Hong Kong. BMC Infectious Diseases. 14(1). 32–32. 4 indexed citations
6.
Yang, Lin, Susan S. Chiu, King-Pan Chan, et al.. (2011). Validation of Statistical Models for Estimating Hospitalization Associated with Influenza and Other Respiratory Viruses. PLoS ONE. 6(3). e17882–e17882. 31 indexed citations
7.
Thach, TQ, Chit-Ming Wong, King-Pan Chan, et al.. (2010). Daily visibility and mortality: Assessment of health benefits from improved visibility in Hong Kong. Environmental Research. 110(6). 617–623. 45 indexed citations
8.
Thach, TQ, Chit-Ming Wong, King-Pan Chan, et al.. (2010). Air pollutants and health outcomes: Assessment of confounding by influenza. Atmospheric Environment. 44(11). 1437–1442. 26 indexed citations
9.
Riley, Steven, Christophe Fraser, Christl A. Donnelly, et al.. (2003). Transmission Dynamics of the Etiological Agent of SARS in Hong Kong: Impact of Public Health Interventions. Science. 300(5627). 1961–1966. 810 indexed citations breakdown →

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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