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Thomas A. Mellan

Imperial College London · GB
Area of research
Modeling and Simulation · Infectious Diseases
Research interest
Research interests include COVID-19 epidemiological studies, SARS-CoV-2 and COVID-19 Research, COVID-19 Clinical Research Studies, and COVID-19 Pandemic Impacts.
h-index
37
citations
13,771
works
82
NIH funding
primary concept
Medicine
email

Recent publications

Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals
Nature Medicine 2022cited by 61position: middledoi
Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil
Science 2021cited by 1,538position: middledoi
SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion
Nature 2021cited by 1,416position: middledoi
Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil.
2021cited by 1,147position: contributordoi
Genomic characterization and epidemiology of an emerging SARS-CoV-2 variant in Delhi, India.
2021cited by 263position: contributordoi
Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe
Nature Communications 2021cited by 228position: middledoi
Age groups that sustain resurging COVID-19 epidemics in the United States.
2021cited by 207position: contributordoi
Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria
Nature Communications 2021cited by 77position: middledoi
Quantifying Online News Media Coverage of the COVID-19 Pandemic: Text Mining Study and Resource.
2021cited by 37position: contributordoi
Correction: Quantifying Online News Media Coverage of the COVID-19 Pandemic: Text Mining Study and Resource.
2021cited by 1position: contributordoi
Correction: Quantifying Online News Media Coverage of the COVID-19 Pandemic: Text Mining Study and Resource (Preprint)
2021cited by 1position: contributordoi
Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe
Nature 2020cited by 3,798position: middledoi
Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe.
2020cited by 2,093position: contributordoi
Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’
Nature 2020cited by 1,026position: middledoi
Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo'.
2020cited by 691position: contributordoi
Evolution and epidemic spread of SARS-CoV-2 in Brazil
Science 2020cited by 658position: middledoi
Potential impact of the COVID-19 pandemic on HIV, tuberculosis, and malaria in low-income and middle-income countries: a modelling study.
2020cited by 588position: contributordoi
Evolution and epidemic spread of SARS-CoV-2 in Brazil.
2020cited by 427position: contributordoi
Comparison of molecular testing strategies for COVID-19 control: a mathematical modelling study
The Lancet Infectious Diseases 2020cited by 217position: middledoi
State-level tracking of COVID-19 in the United States
Nature Communications 2020cited by 171position: middledoi
Response to COVID-19 in South Korea and implications for lifting stringent interventions.
2020cited by 128position: contributordoi
Inference of COVID-19 epidemiological distributions from Brazilian hospital data.
2020cited by 22position: contributordoi
Atomistic modeling approach to the thermodynamics of sodium silicate glasses
Journal of the American Ceramic Society 2020cited by 11position: contributordoi
Evolution and epidemic spread of SARS-CoV-2 in Brazil
2020cited by 7position: contributordoi
SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China.
2020cited by 6position: contributordoi
Inference of COVID-19 epidemiological distributions from Brazilian hospital data
2020cited by 1position: contributordoi
Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK
2020cited by 0position: contributordoi
The effectiveness of reference-free modified embedded atom method potentials demonstrated for NiTi and NbMoTaW
Modelling and Simulation in Materials Science and Engineering 2019cited by 28position: middledoi
The effectiveness of reference-free modified embedded atom method potentials demonstrated for NiTi and NbMoTaW
Modelling and Simulation in Materials Science and Engineering 2019cited by 27position: contributordoi

Grants

No grants ingested yet.

Frequent collaborators

S. Bhatt · Illumina (United States)9 papers (2020–2021) · 8 papers (2019–2021)Swapnil Mishra · National University Hospital7 papers (2020–2021)Daniel J. Laydon · Imperial College London7 papers (2020–2021)Seth Flaxman · Tehran University of Medical Sciences6 papers (2020–2021)H. Juliette T. Unwin · University of Birmingham6 papers (2020–2021)Katy A. M. Gaythorpe · World Health Organization6 papers (2020–2021)Richard G. FitzJohn · Institute of Public Health Bengaluru5 papers (2020–2020)Robert Verity · Imperial College London5 papers (2020–2020)Lucy Okell · National Centre for Infectious Diseases4 papers (2020–2021)Oliver J. Watson · London School of Hygiene & Tropical Medicine4 papers (2020–2020)Pierre Nouvellet · Imperial College London4 papers (2020–2020)Zulma M. Cucunubá · Pontificia Universidad Javeriana4 papers (2020–2021)Natsuko Imai · Wellcome Trust Centre for the History of Medicine4 papers (2020–2020)Denise Xifara · 3 papers (2021–2021)Benjamin Gibert · 3 papers (2021–2021)Christl A. Donnelly · Johns Hopkins Hospital3 papers (2020–2020)Johannes T Hadsund · Syddansk Universitet3 papers (2021–2021)Veit Schwämmle · University of Southern Denmark3 papers (2021–2021)Tadeusz Chelkowski · Kozminski University3 papers (2021–2021)