Mark Jit
Impact in
- Modeling and Simulation top 0.01%
- COVID-19 epidemiological studies
- Health top 0.05%
- Vaccine Coverage and Hesitancy
Papers in
- Epidemiology 190
- Cervical Cancer and HPV Research 77
- Influenza Virus Research Studies 43
- Respiratory viral infections research 29
- Pneumonia and Respiratory Infections 26
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- COVID-19 epidemiological studies 67
- Co-authors
- W. John Edmunds (31 shared papers)Raymond C. W. Hutubessy (35 shared papers)Marc Brisson (32 shared papers)Philippe Beutels (22 shared papers)Alex Richard Cook (7 shared papers)Yot Teerawattananon (10 shared papers)Kiesha Prem (14 shared papers)Niel Hens (3 shared papers)
- Journals
- Vaccine (73 papers)BMC Medicine (41 papers)The Lancet Global Health (20 papers)Value in Health (14 papers)BMJ Global Health (14 papers)
- Partner nations
- United KingdomUnited StatesHong Kong
In The Last Decade
Mark Jit
421 papers receiving 29.2k citations
Mark Jit's Hit Papers
Peers
Comparison fields: 5 of 209
- Modeling and Simulation 9.2k
- Health 3.6k
- Infectious Diseases 8.2k
- Epidemiology 9.0k
- Applied Microbiology and Biotechnology 345
Countries citing papers authored by Mark Jit
This map shows the geographic impact of Mark Jit'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 Mark Jit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Jit more than expected).
Fields of papers citing papers by Mark Jit
This network shows the impact of papers produced by Mark Jit. 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 Mark Jit. The network helps show where Mark Jit may publish in the future.
Co-authors
The 25 scholars most cited alongside Mark Jit, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 433 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases Hit paper breakdown → | 2008 | 2130 |
| 2 | Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts Hit paper breakdown → | 2020 | 1775 |
| 3 | Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England Hit paper breakdown → | 2021 | 1719 |
| 4 | Early dynamics of transmission and control of COVID-19: a mathematical modelling study Hit paper breakdown → | 2020 | 1706 |
| 5 | The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study Hit paper breakdown → | 2020 | 1482 |
| 6 | Age-dependent effects in the transmission and control of COVID-19 epidemics Hit paper breakdown → | 2020 | 1154 |
| 7 | Challenges in ensuring global access to COVID-19 vaccines: production, affordability, allocation, and deployment Hit paper breakdown → | 2021 | 942 |
| 8 | Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study Hit paper breakdown → | 2020 | 795 |
| 9 | Impact of HPV vaccination and cervical screening on cervical cancer elimination: a comparative modelling analysis in 78 low-income and lower-middle-income countries Hit paper breakdown → | 2020 | 652 |
| 10 | Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study Hit paper breakdown → | 2020 | 621 |
| 11 | Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study Hit paper breakdown → | 2020 | 592 |
| 12 | Projecting social contact matrices in 152 countries using contact surveys and demographic data Hit paper breakdown → | 2017 | 545 |
| 13 | 2012 | 348 | |
| 14 | Routine childhood immunisation during the COVID-19 pandemic in Africa: a benefit–risk analysis of health benefits versus excess risk of SARS-CoV-2 infection Hit paper breakdown → | 2020 | 274 |
| 15 | Contribution of vaccination to improved survival and health: modelling 50 years of the Expanded Programme on Immunization Hit paper breakdown → | 2024 | 262 |
| 16 | The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories Hit paper breakdown → | 2021 | 257 |
| 17 | 2008 | 248 | |
| 18 | 2016 | 243 | |
| 19 | COVID-19 vaccine challenges: What have we learned so far and what remains to be done? Hit paper breakdown → | 2021 | 238 |
| 20 | 2019 | 229 |
About Mark Jit
Mark Jit is a scholar working on Epidemiology, Modeling and Simulation, Health, Infectious Diseases and Economics and Econometrics, having authored 433 papers that have together received 29.9k indexed citations. Recurring topics across this work include Cervical Cancer and HPV Research (77 papers), COVID-19 epidemiological studies (67 papers), Vaccine Coverage and Hesitancy (62 papers), Influenza Virus Research Studies (43 papers), Viral gastroenteritis research and epidemiology (30 papers), Respiratory viral infections research (29 papers), Pneumonia and Respiratory Infections (26 papers) and Health Systems, Economic Evaluations, Quality of Life (20 papers). The work is most often cited by research in Modeling and Simulation (9.2k citations), Health (3.6k citations), Infectious Diseases (8.2k citations), Epidemiology (9.0k citations) and Applied Microbiology and Biotechnology (345 citations). Mark Jit has collaborated with scholars based in United Kingdom, United States and Hong Kong. Frequent co-authors include W. John Edmunds, Raymond C. W. Hutubessy, Marc Brisson, Philippe Beutels, Alex Richard Cook, Yot Teerawattananon, Kiesha Prem, Niel Hens, Jacco Wallinga and Joël Mossong. Their work appears in journals such as Vaccine, BMC Medicine, The Lancet Global Health, Value in Health and BMJ Global Health.
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.