Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil
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DOI: 10.1038/s41562-020-0928-4
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- Sandra A Asner & Michelle E Science & Dat Tran & Marek Smieja & Arnaud Merglen & Dominik Mertz, 2014. "Clinical Disease Severity of Respiratory Viral Co-Infection versus Single Viral Infection: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-10, June.
- Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
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Cited by:
- Bazzo Vieira, João Pedro & Vieira Braga, Carlos Kauê & Pereira, Rafael H.M., 2022. "The impact of COVID-19 on air passenger demand and CO2 emissions in Brazil," Energy Policy, Elsevier, vol. 164(C).
- Raphael Bruce & Alexsandros Cavgias & Luis Meloni & Mario Remigio, 2021. "Under Pressure: Women's Leadership During the COVID-19 Crisis," Working Papers, Department of Economics 2021_19, University of São Paulo (FEA-USP).
- Bo Huang & Jionghua Wang & Jixuan Cai & Shiqi Yao & Paul Kay Sheung Chan & Tony Hong-wing Tam & Ying-Yi Hong & Corrine W. Ruktanonchai & Alessandra Carioli & Jessica R. Floyd & Nick W. Ruktanonchai & , 2021. "Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities," Nature Human Behaviour, Nature, vol. 5(6), pages 695-705, June.
- Pereira, Rafael H.M. & Braga, Carlos Kauê Vieira & Servo, Luciana Mendes & Serra, Bernardo & Amaral, Pedro & Gouveia, Nelson & Paez, Antonio, 2021. "Geographic access to COVID-19 healthcare in Brazil using a balanced float catchment area approach," Social Science & Medicine, Elsevier, vol. 273(C).
- Bruce, Raphael & Cavgias, Alexsandros & Meloni, Luis & Remígio, Mário, 2022. "Under pressure: Women’s leadership during the COVID-19 crisis," Journal of Development Economics, Elsevier, vol. 154(C).
- Van Niekerk, Janet & Krainski, Elias & Rustand, Denis & Rue, Håvard, 2023. "A new avenue for Bayesian inference with INLA," Computational Statistics & Data Analysis, Elsevier, vol. 181(C).
- Chen, Kexin & Pun, Chi Seng & Wong, Hoi Ying, 2023. "Efficient social distancing during the COVID-19 pandemic: Integrating economic and public health considerations," European Journal of Operational Research, Elsevier, vol. 304(1), pages 84-98.
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