Kucharski, Adam J

Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England

Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2021) · Science

COVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 Research

Cited by 2,581

Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England

Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2020) · Science

COVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 Research

Cited by 2,557

Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

Hellewell, J., Abbott, S., Gimma, A., Bosse, N. I., Jarvis, C. I., Russell, T. W., Munday, J. D., Kucharski, A. J., Edmunds, W. J., Sun, F., et al. (2020) · The Lancet Global Health

COVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology Models

Cited by 2,550

Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study

Kucharski, A. J., Klepac, P., Conlan, A. J. K., Kissler, S. M., Tang, M. L., Fry, H., Gog, J. R., Edmunds, W. J., Emery, J. C., Medley, G., et al. (2020) · The Lancet Infectious Diseases

COVID-19 epidemiological studiesCOVID-19 Digital Contact Tracing

Cited by 900

Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study

Davies, N. G., Kucharski, A. J., Eggo, R. M., Gimma, A., Edmunds, W. J., Jombart, T., O'Reilly, K., Endo, A., Hellewell, J., Nightingale, E. S., et al. (2020) · The Lancet Public Health

COVID-19 epidemiological studiesCOVID-19 Prevention and Impact

Cited by 848

Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence

Sabino, E. C., Buss, L. F., Carvalho, M. P. S., Prete, C. A., Crispim, M. A. E., Fraiji, N. A., Pereira, R. H. M., Parag, K. V., da Silva Peixoto, P., Kraemer, M. U. G., et al. (2021) · The Lancet

SARS-CoV-2 and COVID-19 ResearchCOVID-19 epidemiological studies

Cited by 758

Estimated effectiveness of symptom and risk screening to prevent the spread of COVID-19

Gostic, K., Gomez, A. C., Mummah, R. O., Kucharski, A. J., & Lloyd-Smith, J. O. (2020) · eLife

COVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology Models

Cited by 417

Secondary attack rate and superspreading events for SARS-CoV-2

Liu, Y., Eggo, R. M., & Kucharski, A. J. (2020) · The Lancet

COVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 Research

Cited by 350

Contacts in context: large-scale setting-specific social mixing matrices from the BBC Pandemic project

Klepac, P., Kucharski, A. J., Conlan, A. J., Kissler, S., Tang, M. L., Fry, H., & Gog, J. R. (2020) · medRxiv

COVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology Models

Cited by 144

Infodemics: a new challenge for public health

Briand, S. C., Cinelli, M., Nguyen, T., Lewis, R., Prybylski, D., Valensise, C. M., Colizza, V., Tozzi, A. E., Perra, N., Baronchelli, A., et al. (2021) · Cell

Misinformation and Its ImpactsCommunication and COVID-19 Impact

Cited by 125

Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era

Barnard, R. C., Davies, N. G., Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group, Munday, J. D., Lowe, R., Knight, G. M., Leclerc, Q. J., Tully, D. C., Hodgson, D., Pung, R., et al. (2022) · Nature Communications

COVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 Research

Cited by 68