Qifang Bi
- Modeling and Simulation top 0.05%
- COVID-19 epidemiological studies 8
- Infectious Diseases top 0.5%
- Viral Infections and Vectors 4
- SARS-CoV-2 and COVID-19 Research 2
- COVID-19 Clinical Research Studies 2
- General Dentistry top 2%
- Health Informatics top 5%
- Economics and Econometrics top 1%
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- Mosquito-borne diseases and control 5
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- Vibrio bacteria research studies 2
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- Influenza Virus Research Studies 1
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- Bacteriophages and microbial interactions 1
- Co-authors
- Justin LesslerKyra H. GrantzNicholas G ReichAndrew S. AzmanStephen A. LauerForrest K. JonesQulu ZhengHannah R. Meredith
- Journals
- Science (1 paper)Proceedings of the National Academy of Sciences (1 paper)Annals of Internal Medicine (1 paper)
- Partner nations
- United StatesThailandChina
In The Last Decade
Qifang Bi
12 papers receiving 4.5k citations
Hit Papers
Peers
Comparison fields: 5 of 186
- Modeling and Simulation 2.0k
- Infectious Diseases 2.2k
- General Dentistry 90
- Health Informatics 43
- Economics and Econometrics 743
Countries citing papers authored by Qifang Bi
This map shows the geographic impact of Qifang Bi'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 Qifang Bi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qifang Bi more than expected).
Fields of papers citing papers by Qifang Bi
This network shows the impact of papers produced by Qifang Bi. 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 Qifang Bi. The network helps show where Qifang Bi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Qifang Bi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2021 | 23 | |
| 3 | 2021 | 55 | |
| 4 | 2020 | 3 | |
| 5 | The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Applicationbreakdown → | 2020 | 3773 |
| 6 | What is Machine Learning? A Primer for the Epidemiologistbreakdown → | 2019 | 342 |
| 7 | 2018 | 50 | |
| 8 | 2018 | 10 | |
| 9 | 2016 | 17 | |
| 10 | 2016 | 16 | |
| 11 | 2016 | 72 | |
| 12 | Assessing the global threat from Zika virusbreakdown → | 2016 | 297 |
| 13 | 2016 | 8 |
About Qifang Bi
Qifang Bi is a scholar working on Modeling and Simulation, Endocrinology and Infectious Diseases, having authored 13 papers that have together received 4.7k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (8 papers), Mosquito-borne diseases and control (5 papers), Viral Infections and Vectors (4 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Vibrio bacteria research studies (2 papers), COVID-19 Clinical Research Studies (2 papers), Influenza Virus Research Studies (1 paper) and Bacteriophages and microbial interactions (1 paper). The work is most often cited by research in Modeling and Simulation (2.0k citations), Infectious Diseases (2.2k citations) and General Dentistry (90 citations). Qifang Bi has collaborated with scholars based in United States, Thailand and China. Frequent co-authors include Justin Lessler, Kyra H. Grantz, Nicholas G Reich, Andrew S. Azman, Stephen A. Lauer, Forrest K. Jones, Qulu Zheng, Hannah R. Meredith, Joshua Kaminsky and Katherine E Goodman. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Annals of Internal Medicine.
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.