Natalie Kwit
Impact in
- Infectious Diseases top 5%
- Viral Infections and Vectors
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
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- Viral Infections and Vectors 10
-
- Mosquito-borne diseases and control 8
- Co-authors
- Paul S. Mead (5 shared papers)Morgan Hennessey (3 shared papers)John T. Brooks (1 shared paper)Jessica C. Smith (1 shared paper)Wendy M. Chung (1 shared paper)Christina A. Nelson (8 shared papers)Ryan Max (1 shared paper)Kiersten J. Kugeler (4 shared papers)
- Journals
- MMWR Morbidity and Mortality Weekly Report (6 papers)Zoonoses and Public Health (3 papers)Vector-Borne and Zoonotic Diseases (2 papers)Emerging infectious diseases (2 papers)Annals of Internal Medicine (1 paper)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Natalie Kwit
18 papers receiving 395 citations
Peers
Comparison fields: 5 of 61
- Infectious Diseases 295
- Modeling and Simulation 54
- Parasitology 67
- Public Health, Environmental and Occupational Health 296
- Virology 16
Countries citing papers authored by Natalie Kwit
This map shows the geographic impact of Natalie Kwit'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 Natalie Kwit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalie Kwit more than expected).
Fields of papers citing papers by Natalie Kwit
This network shows the impact of papers produced by Natalie Kwit. 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 Natalie Kwit. The network helps show where Natalie Kwit may publish in the future.
Co-authors
The 25 scholars most cited alongside Natalie Kwit, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 237 | |
| 2 | 2016 | 46 | |
| 3 | 2020 | 28 | |
| 4 | 2018 | 20 | |
| 5 | 2017 | 19 | |
| 6 | 2019 | 10 | |
| 7 | 2019 | 8 | |
| 8 | 2023 | 7 | |
| 9 | 2024 | 6 | |
| 10 | 2017 | 6 | |
| 11 | 2018 | 5 | |
| 12 | 2019 | 4 | |
| 13 | 2022 | 3 | |
| 14 | 2020 | 3 | |
| 15 | 2022 | 3 | |
| 16 | 2016 | 2 | |
| 17 | 2017 | 2 | |
| 18 | 2024 | 1 | |
| 19 | 2022 | 0 |
About Natalie Kwit
Natalie Kwit is a scholar working on Infectious Diseases, Public Health, Environmental and Occupational Health, Parasitology, Molecular Biology and Genetics, having authored 19 papers that have together received 410 indexed citations. Recurring topics across this work include Viral Infections and Vectors (10 papers), Vector-borne infectious diseases (8 papers), Mosquito-borne diseases and control (8 papers), Yersinia bacterium, plague, ectoparasites research (5 papers), Bacillus and Francisella bacterial research (5 papers), Poxvirus research and outbreaks (3 papers), Vector-Borne Animal Diseases (2 papers) and Plant Pathogens and Fungal Diseases (1 paper). The work is most often cited by research in Infectious Diseases (295 citations), Modeling and Simulation (54 citations), Parasitology (67 citations), Public Health, Environmental and Occupational Health (296 citations) and Virology (16 citations). Natalie Kwit has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Paul S. Mead, Morgan Hennessey, John T. Brooks, Jessica C. Smith, Wendy M. Chung, Christina A. Nelson, Ryan Max, Kiersten J. Kugeler, Amy Schwartz and Paige A. Armstrong. Their work appears in journals such as MMWR Morbidity and Mortality Weekly Report, Zoonoses and Public Health, Vector-Borne and Zoonotic Diseases, Emerging infectious diseases and Annals of Internal Medicine.
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.