Itamar Megiddo

37 papers receiving 651 citations

Peers

Itamar Megiddo
Comparison fields: 5 of 125
  • Modeling and Simulation 78
  • Applied Microbiology and Biotechnology 24
  • Health 87
  • Family Practice 8
  • Infectious Diseases 80
Replace KM Saif‐Ur‐Rahman with:
KM Saif‐Ur‐Rahman Bangladesh
Kamarul Imran Musa Malaysia
Aman Verma Canada
Dawei Zhu China
Daniel K. Sewell United States
Miyuki Kawado Japan
Shoaib Ahmad Pakistan
Walid Al‐Qerem Jordan
Maryam Taghdir Iran
Aleksandra Marinkovic Nigeria
Itamar Megiddo relative to KM Saif‐Ur‐Rahman Bangladesh KM Saif‐Ur‐Rahman's profile →
Citations per field
00.5×2.7×
KM Saif‐Ur‐Rahman · 1×
Citations per year

Countries citing papers authored by Itamar Megiddo

Since Specialization
Citations

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

Fields of papers citing papers by Itamar Megiddo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016139
2 202197
3 201660
4 201436
5 202232
6 202029
7 202123
8 202423
9 201421
10 202121
11 201920
12 201518
13 201918
14 201616
15 201816
16 201814
17 201913
18 202213
19 20219
20 20169

About Itamar Megiddo

Itamar Megiddo is a scholar working on General Health Professions, Management Science and Operations Research, Economics and Econometrics, Pediatrics, Perinatology and Child Health and Modeling and Simulation, having authored 42 papers that have together received 682 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (6 papers), Global Maternal and Child Health (6 papers), Geriatric Care and Nursing Homes (5 papers), Healthcare Systems and Reforms (5 papers), Complex Systems and Decision Making (5 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers), Healthcare Policy and Management (3 papers) and Vaccine Coverage and Hesitancy (3 papers). The work is most often cited by research in Modeling and Simulation (78 citations), Applied Microbiology and Biotechnology (24 citations), Health (87 citations), Family Practice (8 citations) and Infectious Diseases (80 citations). Itamar Megiddo has collaborated with scholars based in United Kingdom, United States and India. Frequent co-authors include Ramanan Laxminarayan, Arindam Nandi, Abigail Colson, Susan Howick, Alec Morton, Dan Chisholm, Tarun Dua, Justice Nonvignon, Abdur Razzaque Sarker and Amit Kumar Verma. Their work appears in journals such as Social Science & Medicine, BMJ Global Health, PLoS ONE, Health Policy and Planning and American Journal of Infection Control.

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.

Explore authors with similar magnitude of impact