Berit Lange

3.4k citations
55 papers · 779 · h-index 15

Impact in

Papers in

    • Tuberculosis Research and Epidemiology 12
    • SARS-CoV-2 and COVID-19 Research 8
    • COVID-19 Clinical Research Studies 7
    • Mycobacterium research and diagnosis 6
    • Pneumocystis jirovecii pneumonia detection and treatment 5

Berit Lange

47 papers receiving 764 citations

Peers

Berit Lange
Comparison fields: 5 of 99
  • Modeling and Simulation 179
  • Hepatology 134
  • Infectious Diseases 284
  • Sensory Systems 69
  • Epidemiology 318
Replace Stéphanie Haïm‐Boukobza with:
Stéphanie Haïm‐Boukobza France
Erin E. Conners United States
Saied Ghorbani Iran
Molly Steele United States
Giorgio Bozzi Italy
Davide Mangioni Italy
Victoria Indenbaum Israel
Rodrigo Feliciano do Carmo Brazil
Winston E. Abara United States
Berit Lange relative to Stéphanie Haïm‐Boukobza France Stéphanie Haïm‐Boukobza's profile →
Citations per field
00.5×4.1×
Stéphanie Haïm‐Boukobza · 1×
Citations per year

Countries citing papers authored by Berit Lange

Since Specialization
Citations

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

Fields of papers citing papers by Berit Lange

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020127
2 202097
3 201776
4 201769
5 202151
6 202129
7 202126
8 202223
9 202123
10 202120
11 202117
12 202317
13 202216
14 201714
15 201914
16 201214
17 202212
18 202311
19 202010
20 20229

About Berit Lange

Berit Lange is a scholar working on Infectious Diseases, Epidemiology, Modeling and Simulation, Clinical Psychology and Surgery, having authored 55 papers that have together received 779 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (16 papers), Tuberculosis Research and Epidemiology (12 papers), SARS-CoV-2 and COVID-19 Research (8 papers), COVID-19 Clinical Research Studies (7 papers), COVID-19 and Mental Health (7 papers), Diagnosis and treatment of tuberculosis (6 papers), Mycobacterium research and diagnosis (6 papers) and Pneumocystis jirovecii pneumonia detection and treatment (5 papers). The work is most often cited by research in Modeling and Simulation (179 citations), Hepatology (134 citations), Infectious Diseases (284 citations), Sensory Systems (69 citations) and Epidemiology (318 citations). Berit Lange has collaborated with scholars based in Germany, Switzerland and United Kingdom. Frequent co-authors include Dirk Wagner, Stephan Glöckner, Winfried V. Kern, Maren Dreier, Siegbert Rieg, Patrizio Vanella, Nils Schröter, Daniel Hornuß, Gérard Krause and Teri Roberts. Their work appears in journals such as BMC Infectious Diseases, Infection, BMC Medicine, European Respiratory Journal and Journal of Infection.

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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