Eric J. Haas

49 papers receiving 1.9k citations

Eric J. Haas's Hit Papers

Impact and effectiveness of mRNA BNT162b2 vaccine against SARS-CoV-2 infections and COVID-19 cases, hospitalisations, and deaths following a nationwide vaccination campaign in Israel: an observational study using national surveillance data 2021 · 1.0k citations
1.0k0+1+3Years since publication2505007501000

Peers

Eric J. Haas
Comparison fields: 5 of 130
  • Modeling and Simulation 227
  • Health 366
  • Infectious Diseases 840
  • Clinical Psychology 158
  • Agronomy and Crop Science 75
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Citations per year

Countries citing papers authored by Eric J. Haas

Since Specialization
Citations

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

Fields of papers citing papers by Eric J. Haas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric J. Haas. 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 Eric J. Haas. The network helps show where Eric J. Haas may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Impact and effectiveness of mRNA BNT162b2 vaccine against SARS-CoV-2 infections and COVID-19 cases, hospitalisations, and deaths following a nationwide vaccination campaign in Israel: an observational study using national surveillance data
Hit paper breakdown →
20211049
2 2009153
3 2002146
4 202181
5 199753
6 201245
7 200939
8 200434
9 199432
10 198524
11
Switchgrass Contains Two Cinnamyl Alcohol\nDehydrogenases Involved in Lignin Formation
201123
12 201023
13 202322
14 197822
15 202119
16 201218
17 199917
18 201815
19 201414
20 201712

About Eric J. Haas

Eric J. Haas is a scholar working on Epidemiology, Infectious Diseases, Immunology, Molecular Biology and Health, having authored 49 papers that have together received 2.0k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (7 papers), Vaccine Coverage and Hesitancy (6 papers), Biofuel production and bioconversion (5 papers), Insect Utilization and Effects (4 papers), Autism Spectrum Disorder Research (4 papers), Virology and Viral Diseases (4 papers), Invertebrate Immune Response Mechanisms (3 papers) and Lignin and Wood Chemistry (3 papers). The work is most often cited by research in Modeling and Simulation (227 citations), Health (366 citations), Infectious Diseases (840 citations), Clinical Psychology (158 citations) and Agronomy and Crop Science (75 citations). Eric J. Haas has collaborated with scholars based in United States, Israel and Argentina. Frequent co-authors include Emilia Anis, Shepherd Roee Singer, Frederick J. Angulo, Luis Jódar, John M. McLaughlin, Gabriel Mircus, Jo Southern, Sharon Alroy‐Preis, Kaijie Pan and David L. Swerdlow. Their work appears in journals such as Archives of Insect Biochemistry and Physiology, Eurosurveillance, Insects, Archives of Biochemistry and Biophysics and BioEnergy Research.

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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