Shitong Huan

1.0k total citations
26 papers, 652 citations indexed

About

Shitong Huan is a scholar working on Infectious Diseases, Epidemiology and Finance. According to data from OpenAlex, Shitong Huan has authored 26 papers receiving a total of 652 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Infectious Diseases, 17 papers in Epidemiology and 5 papers in Finance. Recurrent topics in Shitong Huan's work include Tuberculosis Research and Epidemiology (17 papers), Mycobacterium research and diagnosis (7 papers) and Pneumonia and Respiratory Infections (6 papers). Shitong Huan is often cited by papers focused on Tuberculosis Research and Epidemiology (17 papers), Mycobacterium research and diagnosis (7 papers) and Pneumonia and Respiratory Infections (6 papers). Shitong Huan collaborates with scholars based in China, United States and United Kingdom. Shitong Huan's co-authors include Daniel P. Chin, Yanlin Zhao, Shiwen Jiang, Xiaoqiu Liu, Katherine Fielding, James Lewis, Hui Xia, Xichao Ou, Junchen Li and Hui Zhang and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Clinical Microbiology.

In The Last Decade

Shitong Huan

26 papers receiving 642 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shitong Huan China 13 470 316 154 96 80 26 652
Malik Parmar India 17 739 1.6× 567 1.8× 42 0.3× 171 1.8× 9 0.1× 46 848
Dag Gundersen Storla Norway 7 662 1.4× 495 1.6× 57 0.4× 226 2.4× 8 0.1× 9 794
Pren Naidoo South Africa 14 555 1.2× 387 1.2× 144 0.9× 94 1.0× 11 0.1× 40 634
Nimalan Arinaminpathy United Kingdom 10 277 0.6× 171 0.5× 30 0.2× 45 0.5× 7 0.1× 23 376
A. Sreenivas India 10 334 0.7× 238 0.8× 47 0.3× 58 0.6× 7 0.1× 17 440
Melanie Lo United States 5 337 0.7× 179 0.6× 59 0.4× 77 0.8× 27 0.3× 5 427
S Egwaga Tanzania 12 430 0.9× 352 1.1× 36 0.2× 125 1.3× 14 0.2× 21 486
Rebecca Berhanu South Africa 15 564 1.2× 350 1.1× 45 0.3× 144 1.5× 8 0.1× 47 656
Eliud Wandwalo Tanzania 9 361 0.8× 233 0.7× 46 0.3× 72 0.8× 5 0.1× 18 419
Michel Gasana Rwanda 14 432 0.9× 361 1.1× 26 0.2× 138 1.4× 7 0.1× 28 527

Countries citing papers authored by Shitong Huan

Since Specialization
Citations

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

Fields of papers citing papers by Shitong Huan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shitong Huan

This figure shows the co-authorship network connecting the top 25 collaborators of Shitong Huan. A scholar is included among the top collaborators of Shitong Huan 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 Shitong Huan. Shitong Huan 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.
2.
Liu, Xiaoqiu, JA Thompson, Sedona Sweeney, et al.. (2023). Digital adherence technologies to improve tuberculosis treatment outcomes in China: a cluster-randomised superiority trial. The Lancet Global Health. 11(5). e693–e703. 28 indexed citations
3.
Long, Qian, et al.. (2021). Scale-up of a comprehensive model to improve tuberculosis control in China: lessons learned and the way forward. Infectious Diseases of Poverty. 10(1). 41–41. 4 indexed citations
4.
Xia, Yinyin, Fei Huang, Hui Chen, et al.. (2021). The Impact of COVID-19 on Tuberculosis Patients’ Behavior of Seeking Medical Care — China, 2020. China CDC Weekly. 3(26). 553–556. 10 indexed citations
5.
Huang, Fei, Hui Chen, Ni Wang, et al.. (2020). The impact of the COVID-19 epidemic on tuberculosis control in China. The Lancet Regional Health - Western Pacific. 3. 100032–100032. 69 indexed citations
6.
Wang, Ni, Tao Li, Xin Du, et al.. (2020). Effectiveness of the Integrated TB Surveillance System — China, 2018–2019. China CDC Weekly. 2(12). 190–193. 4 indexed citations
7.
Stagg, Helen R., James Lewis, Xiaoqiu Liu, et al.. (2019). Temporal Factors and Missed Doses of Tuberculosis Treatment. A Causal Associations Approach to Analyses of Digital Adherence Data. Annals of the American Thoracic Society. 17(4). 438–449. 20 indexed citations
8.
Sun, Yixin, Hui Xia, Zhike Liu, et al.. (2019). Accuracy of Commercial Molecular Diagnostics for the Detection of Pulmonary Tuberculosis in China: A Systematic Review. Scientific Reports. 9(1). 4553–4553. 17 indexed citations
9.
10.
Zhou, Chengchao, Qian Long, Jiaying Chen, et al.. (2016). The effect of NCMS on catastrophic health expenditure and impoverishment from tuberculosis care in China. International Journal for Equity in Health. 15(1). 172–172. 29 indexed citations
11.
Ou, Xichao, Shengfen Wang, Haiyan Dong, et al.. (2016). Multicenter evaluation of a real-time loop-mediated isothermal amplification (RealAmp) test for rapid diagnosis of Mycobacterium tuberculosis. Journal of Microbiological Methods. 129. 39–43. 11 indexed citations
12.
Pang, Yu, Haiyan Dong, Yaoju Tan, et al.. (2016). Rapid diagnosis of MDR and XDR tuberculosis with the MeltPro TB assay in China. Scientific Reports. 6(1). 25330–25330. 45 indexed citations
13.
Huang, Fei, Hui Zhang, Qing Lv, et al.. (2016). Use of anti-tuberculosis drugs among newly diagnosed pulmonary tuberculosis inpatients in China: a retrospective study. Infectious Diseases of Poverty. 5(1). 2–2. 7 indexed citations
14.
Li, Renzhong, Yunzhou Ruan, Qiang Sun, et al.. (2015). Effect of a comprehensive programme to provide universal access to care for sputum-smear-positive multidrug-resistant tuberculosis in China: a before-and-after study. The Lancet Global Health. 3(4). e217–e228. 37 indexed citations
15.
Liu, Xiaoqiu, James Lewis, Hui Zhang, et al.. (2015). Effectiveness of Electronic Reminders to Improve Medication Adherence in Tuberculosis Patients: A Cluster-Randomised Trial. PLoS Medicine. 12(9). e1001876–e1001876. 152 indexed citations
16.
Ou, Xichao, Hui Xia, Qiang Li, et al.. (2014). A feasibility study of the Xpert MTB/RIF test at the peripheral level laboratory in China. International Journal of Infectious Diseases. 31. 41–46. 20 indexed citations
17.
Ou, Xichao, Qiang Li, Hui Xia, et al.. (2014). Diagnostic Accuracy of the PURE-LAMP Test for Pulmonary Tuberculosis at the County-Level Laboratory in China. PLoS ONE. 9(5). e94544–e94544. 50 indexed citations
18.
Pang, Yu, Hui Xia, Zhiying Zhang, et al.. (2013). Multicenter Evaluation of Genechip for Detection of Multidrug-Resistant Mycobacterium tuberculosis. Journal of Clinical Microbiology. 51(6). 1707–1713. 43 indexed citations
19.
Pang, Yu, Qiang Li, Xichao Ou, et al.. (2013). Cost-Effectiveness Comparison of Genechip and Conventional Drug Susceptibility Test for Detecting Multidrug-Resistant Tuberculosis in China. PLoS ONE. 8(7). e69267–e69267. 10 indexed citations
20.
Huan, Shitong, et al.. (2012). Operational feasibility of medication monitors in monitoring treatment adherence among TB patients. 34(7). 419. 5 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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