Rivka Sheffer

618 citations
35 papers · 433 · h-index 13

Impact in

Papers in

    • SARS-CoV-2 and COVID-19 Research 4
    • Virology and Viral Diseases 5
    • HIV, Drug Use, Sexual Risk 4
    • Hepatitis B Virus Studies 2

Rivka Sheffer

33 papers receiving 415 citations

Peers

Rivka Sheffer
Comparison fields: 5 of 77
  • Modeling and Simulation 56
  • Infectious Diseases 163
  • Hepatology 62
  • Health 37
  • Parasitology 31
Replace Anke L. Stuurman with:
Anke L. Stuurman Belgium
Maria Grazia Dente Italy
Kévin Jean France
Émilie Mosnier France
Snežana Medić Serbia
W. William Schluter United States
Tarik Derrough Sweden
Saulo Duarte Passos Brazil
Tarissa Mitchell United States
Muhammad Shakir Balogun Nigeria
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Citations per field
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Citations per year

Countries citing papers authored by Rivka Sheffer

Since Specialization
Citations

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

Fields of papers citing papers by Rivka Sheffer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Rivka Sheffer, 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 Rivka Sheffer Line = papers co-authored together Rivka Sheffer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021106
2 200445
3 201741
4 200540
5 201125
6 201816
7 201815
8 200712
9 201212
10 202012
11 201612
12 201812
13 201612
14 202410
15 20189
16 20189
17 20229
18 20175
19 20214
20 20234

About Rivka Sheffer

Rivka Sheffer is a scholar working on Infectious Diseases, Epidemiology, Public Health, Environmental and Occupational Health, Health and Hepatology, having authored 35 papers that have together received 433 indexed citations. Recurring topics across this work include Virology and Viral Diseases (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Vaccine Coverage and Hesitancy (4 papers), HIV, Drug Use, Sexual Risk (4 papers), Mosquito-borne diseases and control (3 papers), COVID-19 epidemiological studies (2 papers), Hepatitis B Virus Studies (2 papers) and Immune responses and vaccinations (2 papers). The work is most often cited by research in Modeling and Simulation (56 citations), Infectious Diseases (163 citations), Hepatology (62 citations), Health (37 citations) and Parasitology (31 citations). Rivka Sheffer has collaborated with scholars based in Israel and United States. Frequent co-authors include Zohar Mor, Ronit Calderon‐Margalit, Tamar Shohat, Ella Mendelson, Guy Katriel, Yair Goldberg, Amit Huppert, Itai Dattner, Rami Yaari and Arnona Ziv. Their work appears in journals such as Eurosurveillance, Epidemiology and Infection, Travel Medicine and Infectious Disease, Vaccine and Alcohol and Alcoholism.

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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