Weibing Wang

5.5k citations
157 papers · 3.6k · h-index 30

Impact in

Papers in

    • Tuberculosis Research and Epidemiology 33
    • SARS-CoV-2 and COVID-19 Research 10
    • Vaccine Coverage and Hesitancy 13

Weibing Wang

148 papers receiving 3.5k citations

Peers

Weibing Wang
Comparison fields: 5 of 169
  • Modeling and Simulation 445
  • Health, Toxicology and Mutagenesis 886
  • Infectious Diseases 591
  • Health 137
  • Global and Planetary Change 381
Replace Randeep Guleria with:
Randeep Guleria India
Ting‐Wu Chuang Taiwan
Víctor Hugo Borja‐Aburto Mexico
Jinjun Ran China
Guozhang Xu China
Otavio Ranzani Brazil
Fengming Huang China
Joseph Lazar Mathew India
Seyed Saeed Hashemi Nazari Iran
Wei Ma China
Weibing Wang relative to Randeep Guleria India Randeep Guleria's profile →
Citations per field
00.5×2×4×5.9×
Randeep Guleria · 1×
Citations per year

Countries citing papers authored by Weibing Wang

Since Specialization
Citations

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

Fields of papers citing papers by Weibing Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Weibing Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Weibing Wang Line = papers co-authored together Weibing Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 157 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020266
2 2010214
3 2020204
4 2017125
5 2014119
6 2017107
7 2018105
8
Type 2 diabetes mellitus in China: a preventable economic burden.
2009104
9 2014101
10 201493
11 201488
12 202088
13 201672
14 202172
15 201667
16 202365
17 202064
18 202264
19 200959
20 201656

About Weibing Wang

Weibing Wang is a scholar working on Infectious Diseases, Health, Modeling and Simulation, Health, Toxicology and Mutagenesis and Epidemiology, having authored 157 papers that have together received 3.6k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (33 papers), Vaccine Coverage and Hesitancy (13 papers), COVID-19 epidemiological studies (12 papers), Climate Change and Health Impacts (12 papers), SARS-CoV-2 and COVID-19 Research (10 papers), Air Quality and Health Impacts (7 papers), Hepatitis B Virus Studies (7 papers) and Respiratory viral infections research (5 papers). The work is most often cited by research in Modeling and Simulation (445 citations), Health, Toxicology and Mutagenesis (886 citations), Infectious Diseases (591 citations), Health (137 citations) and Global and Planetary Change (381 citations). Weibing Wang has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Haidong Kan, Biao Xu, Chaowei Fu, Zhixi Liu, Ye Yao, Renjie Chen, Xia Meng, Jinhua Pan, Zhaolan Liu and Weidong Wang. Their work appears in journals such as Infectious Diseases of Poverty, BMC Infectious Diseases, BMJ Open, The Science of The Total Environment and International Journal of Environmental Research and Public Health.

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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