Imperial College London
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Professor Nuno R. Faria

Faculty of Medicine, School of Public Health

Professor in Virus Genomic Epidemiology
 
 
 
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Contact

 

+44 (0)20 7594 3560n.faria

 
 
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Location

 

Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Mellan:2020:10.1101/2020.05.09.20096701,
author = {Mellan, TA and Hoeltgebaum, HH and Mishra, S and Whittaker, C and Schnekenberg, RP and Gandy, A and Unwin, HJT and Vollmer, MAC and Coupland, H and Hawryluk, I and Faria, NR and Vesga, J and Zhu, H and Hutchinson, M and Ratmann, O and Monod, M and Ainslie, KEC and Baguelin, M and Bhatia, S and Boonyasiri, A and Brazeau, N and Charles, G and Cucunuba, Z and Cuomo-Dannenburg, G and Dighe, A and Eaton, J and Elsland, SLV and Gaythorpe, KAM and Green, W and Knock, E and Laydon, D and Lees, JA and Mousa, A and Nedjati-Gilani, G and Nouvellet, P and Parag, KV and Thompson, HA and Verity, R and Walters, CE and Wang, H and Wang, Y and Watson, OJ and Whittles, L and Xi, X and Dorigatti, I and Walker, P and Ghani, AC and Riley, S and Ferguson, NM and Donnelly, CA and Flaxman, S and Bhatt, S},
doi = {10.1101/2020.05.09.20096701},
title = {Subnational analysis of the COVID-19 epidemic in Brazil},
url = {http://dx.doi.org/10.1101/2020.05.09.20096701},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <jats:label>1</jats:label><jats:title>Abstract</jats:title><jats:p>Brazil is currently reporting the second highest number of COVID-19 deaths in the world. Here we characterise the initial dynamics of COVID-19 across the country and assess the impact of non-pharmaceutical interventions (NPIs) that were implemented using a semi-mechanistic Bayesian hierarchical modelling approach. Our results highlight the significant impact these NPIs had across states, reducing an average <jats:italic>R<jats:sub>t</jats:sub> ></jats:italic> 3 to an average of 1.5 by 9-May-2020, but that these interventions failed to reduce <jats:italic>R<jats:sub>t</jats:sub></jats:italic> < 1, congruent with the worsening epidemic Brazil has experienced since. We identify extensive heterogeneity in the epidemic trajectory across Brazil, with the estimated number of days to reach 0.1% of the state population infected since the first nationally recorded case ranging from 20 days in São Paulo compared to 60 days in Goiás, underscoring the importance of sub-national analyses in understanding asynchronous state-level epidemics underlying the national spread and burden of COVID-19.</jats:p>
AU  - Mellan,TA
AU  - Hoeltgebaum,HH
AU  - Mishra,S
AU  - Whittaker,C
AU  - Schnekenberg,RP
AU  - Gandy,A
AU  - Unwin,HJT
AU  - Vollmer,MAC
AU  - Coupland,H
AU  - Hawryluk,I
AU  - Faria,NR
AU  - Vesga,J
AU  - Zhu,H
AU  - Hutchinson,M
AU  - Ratmann,O
AU  - Monod,M
AU  - Ainslie,KEC
AU  - Baguelin,M
AU  - Bhatia,S
AU  - Boonyasiri,A
AU  - Brazeau,N
AU  - Charles,G
AU  - Cucunuba,Z
AU  - Cuomo-Dannenburg,G
AU  - Dighe,A
AU  - Eaton,J
AU  - Elsland,SLV
AU  - Gaythorpe,KAM
AU  - Green,W
AU  - Knock,E
AU  - Laydon,D
AU  - Lees,JA
AU  - Mousa,A
AU  - Nedjati-Gilani,G
AU  - Nouvellet,P
AU  - Parag,KV
AU  - Thompson,HA
AU  - Verity,R
AU  - Walters,CE
AU  - Wang,H
AU  - Wang,Y
AU  - Watson,OJ
AU  - Whittles,L
AU  - Xi,X
AU  - Dorigatti,I
AU  - Walker,P
AU  - Ghani,AC
AU  - Riley,S
AU  - Ferguson,NM
AU  - Donnelly,CA
AU  - Flaxman,S
AU  - Bhatt,S
DO  - 10.1101/2020.05.09.20096701
PY  - 2020///
TI  - Subnational analysis of the COVID-19 epidemic in Brazil
UR  - http://dx.doi.org/10.1101/2020.05.09.20096701
ER  -
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