Nadia Nisar

452 total citations
32 papers, 307 citations indexed

About

Nadia Nisar is a scholar working on Epidemiology, Infectious Diseases and Modeling and Simulation. According to data from OpenAlex, Nadia Nisar has authored 32 papers receiving a total of 307 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Epidemiology, 16 papers in Infectious Diseases and 6 papers in Modeling and Simulation. Recurrent topics in Nadia Nisar's work include Respiratory viral infections research (12 papers), Influenza Virus Research Studies (11 papers) and Viral gastroenteritis research and epidemiology (8 papers). Nadia Nisar is often cited by papers focused on Respiratory viral infections research (12 papers), Influenza Virus Research Studies (11 papers) and Viral gastroenteritis research and epidemiology (8 papers). Nadia Nisar collaborates with scholars based in Pakistan, Norway and India. Nadia Nisar's co-authors include Syed Sohail Zahoor Zaidi, Muhammad Masroor Alam, Uzma Bashir Aamir, Nazish Badar, Adnan Khurshid, Shahzad Shaukat, Salmaan Sharif, Mehar Angez, Muhammad Naeem and Muhammad Suleman Rana and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Medical Virology.

In The Last Decade

Nadia Nisar

29 papers receiving 298 citations

Peers

Nadia Nisar
Comparison fields: 5 of 48
  • Infectious Diseases 177
  • Epidemiology 174
  • Cardiology and Cardiovascular Medicine 50
  • Animal Science and Zoology 47
  • Public Health, Environmental and Occupational Health 45
Replace Danying Yan with:
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Christevy Vouvoungui Republic of the Congo
Laura Bubba Italy
Gabriela Abelenda-Alonso Spain
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Satoshi Kamidani United States
Sarbelio Moreno‐Espinosa Mexico
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Danying Yan China View profile →
Citations per field, relative to Nadia Nisar
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Citations per year, relative to Nadia Nisar
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Countries citing papers authored by Nadia Nisar

Since Specialization
Citations

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

Fields of papers citing papers by Nadia Nisar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nadia Nisar

This figure shows the co-authorship network connecting the top 25 collaborators of Nadia Nisar. A scholar is included among the top collaborators of Nadia Nisar 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 Nadia Nisar. Nadia Nisar 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
# Work Indexed citations
1 0
2 2
3 0
4 1
5 7
6 2
7 1
8 3
9 13
10 8
11 19
12 14
13 28
14 14
15 20
16 15
17 11
18 14
19 14
20
Hypertensive disorders of pregnancy: frequency, maternal and fetal outcomes
2

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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