Kyeongah Nah

611 total citations
24 papers, 395 citations indexed

About

Kyeongah Nah is a scholar working on Modeling and Simulation, Infectious Diseases and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Kyeongah Nah has authored 24 papers receiving a total of 395 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Modeling and Simulation, 12 papers in Infectious Diseases and 9 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Kyeongah Nah's work include COVID-19 epidemiological studies (14 papers), Influenza Virus Research Studies (7 papers) and Viral Infections and Vectors (7 papers). Kyeongah Nah is often cited by papers focused on COVID-19 epidemiological studies (14 papers), Influenza Virus Research Studies (7 papers) and Viral Infections and Vectors (7 papers). Kyeongah Nah collaborates with scholars based in Canada, South Korea and Hungary. Kyeongah Nah's co-authors include Hiroshi Nishiura, Ryo Kinoshita, Kenji Mizumoto, Jian Wu, Nicola Luigi Bragazzi, Biao Tang, Yongkuk Kim, Attila J. Trájer, Ákos Bede‐Fazekas and Gergely Röst and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Kyeongah Nah

24 papers receiving 381 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kyeongah Nah Canada 12 221 207 196 59 44 24 395
Joel Hellewell United Kingdom 9 285 1.3× 137 0.7× 261 1.3× 76 1.3× 26 0.6× 19 540
Chaeshin Chu South Korea 12 123 0.6× 129 0.6× 179 0.9× 94 1.6× 38 0.9× 49 443
Luciana Lobato Cardim Brazil 12 93 0.4× 194 0.9× 124 0.6× 42 0.7× 41 0.9× 33 361
Pablo M. De Salazar United States 12 128 0.6× 290 1.4× 190 1.0× 117 2.0× 59 1.3× 31 508
Faraimunashe Chirove South Africa 11 150 0.7× 125 0.6× 136 0.7× 38 0.6× 14 0.3× 39 313
N. Morris South Africa 9 105 0.5× 136 0.7× 125 0.6× 66 1.1× 31 0.7× 14 340
Nicholas F. Brazeau United States 14 90 0.4× 235 1.1× 111 0.6× 49 0.8× 65 1.5× 29 529
Christiaan Marais Belgium 6 149 0.7× 232 1.1× 123 0.6× 106 1.8× 37 0.8× 9 407
Guihong Fan China 11 130 0.6× 178 0.9× 145 0.7× 26 0.4× 19 0.4× 39 416
Attila Dénes Hungary 11 359 1.6× 176 0.9× 241 1.2× 58 1.0× 7 0.2× 32 549

Countries citing papers authored by Kyeongah Nah

Since Specialization
Citations

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

Fields of papers citing papers by Kyeongah Nah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyeongah Nah. 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 Kyeongah Nah. The network helps show where Kyeongah Nah may publish in the future.

Co-authorship network of co-authors of Kyeongah Nah

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

All Works

20 of 20 papers shown
1.
Kim, Yongkuk, et al.. (2024). Predicting seasonal influenza outbreaks with regime shift-informed dynamics for improved public health preparedness. Scientific Reports. 14(1). 12698–12698. 1 indexed citations
2.
Hwang, Dong‐Uk, et al.. (2023). Evaluation of COVID-19 intervention policies in South Korea using the stochastic individual-based model. Scientific Reports. 13(1). 18945–18945. 3 indexed citations
3.
Wang, Xiunan, Hao Wang, Pouria Ramazi, Kyeongah Nah, & Mark A. Lewis. (2022). From Policy to Prediction: Forecasting COVID-19 Dynamics Under Imperfect Vaccination. Bulletin of Mathematical Biology. 84(9). 90–90. 21 indexed citations
4.
Wang, Xiunan, Hao Wang, Pouria Ramazi, Kyeongah Nah, & Mark A. Lewis. (2022). A Hypothesis-Free Bridging of Disease Dynamics and Non-pharmaceutical Policies. Bulletin of Mathematical Biology. 84(5). 57–57. 12 indexed citations
5.
Tang, Biao, et al.. (2020). Quantifying the role of social distancing, personal protection and case detection in mitigating COVID-19 outbreak in Ontario, Canada. SHILAP Revista de lepidopterología. 10(1). 15–15. 63 indexed citations
6.
Xiao, Yanyu, Francesca Scarabel, Biao Tang, et al.. (2020). Quantifying the shift in social contact patterns in response to non-pharmaceutical interventions. SHILAP Revista de lepidopterología. 10(1). 28–28. 15 indexed citations
7.
Nah, Kyeongah, et al.. (2020). Are host control strategies effective to eradicate tick-borne diseases (TBD)?. Journal of Theoretical Biology. 508. 110483–110483. 9 indexed citations
8.
Nah, Kyeongah, et al.. (2020). Impact of influenza vaccine-modified infectivity on attack rate, case fatality ratio and mortality. Journal of Theoretical Biology. 492. 110190–110190. 5 indexed citations
9.
Nah, Kyeongah, Ákos Bede‐Fazekas, Attila J. Trájer, & Jian Wu. (2020). The potential impact of climate change on the transmission risk of tick-borne encephalitis in Hungary. BMC Infectious Diseases. 20(1). 34–34. 20 indexed citations
10.
11.
Nah, Kyeongah, F. M. G. Magpantay, Ákos Bede‐Fazekas, et al.. (2019). Assessing systemic and non-systemic transmission risk of tick-borne encephalitis virus in Hungary. PLoS ONE. 14(6). e0217206–e0217206. 21 indexed citations
12.
Nah, Kyeongah, Hiroshi Nishiura, Naho Tsuchiya, et al.. (2017). Test-and-treat approach to HIV/AIDS: a primer for mathematical modeling. Theoretical Biology and Medical Modelling. 14(1). 16–16. 20 indexed citations
13.
Nishiura, Hiroshi, et al.. (2016). Transmission potential of Zika virus infection in the South Pacific. International Journal of Infectious Diseases. 45. 95–97. 74 indexed citations
14.
Nah, Kyeongah, et al.. (2016). Estimating risks of importation and local transmission of Zika virus infection. PeerJ. 4. e1904–e1904. 43 indexed citations
15.
Nah, Kyeongah, et al.. (2016). Predicting the international spread of Middle East respiratory syndrome (MERS). BMC Infectious Diseases. 16(1). 356–356. 29 indexed citations
16.
Nah, Kyeongah & Gergely Röst. (2016). Stability Threshold for Scalar Linear Periodic Delay Differential Equations. Canadian Mathematical Bulletin. 59(4). 849–857. 3 indexed citations
17.
Nah, Kyeongah, Yukihiko Nakata, & Gergely Röst. (2014). Malaria dynamics with long incubation period in hosts. Computers & Mathematics with Applications. 68(9). 915–930. 8 indexed citations
18.
Nah, Kyeongah, et al.. (2012). Optimal Control Strategy of Plasmodium vivax Malaria Transmission in Korea. Osong Public Health and Research Perspectives. 3(3). 128–136. 17 indexed citations
19.
Nah, Kyeongah, et al.. (2010). Estimation of the incubation period of P. vivax malaria in Korea from 2006 to 2008. Journal of the Korean Data and Information Science Society. 21(6). 1237–1242. 1 indexed citations
20.
Nah, Kyeongah, Yongkuk Kim, & Jung Min Lee. (2010). The dilution effect of the domestic animal population on the transmission of P. vivax malaria. Journal of Theoretical Biology. 266(2). 299–306. 19 indexed citations

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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