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1.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21265140

RESUMEN

The Covid-19 pandemic has created an unprecedented need for epidemiological monitoring using diverse strategies. We conducted a project combining prevalence, seroprevalence, and genomic surveillance approaches to describe the initial pandemic stages in Betim City, Brazil. We collected 3239 subjects in a population-based age-, sex- and neighbourhood-stratified, household, prospective; cross-sectional study divided into three surveys 21 days apart sampling the same geographical area. In the first survey, overall prevalence (participants positive in serological or molecular tests) reached 0.46% (90% CI 0.12% - 0.80%), followed by 2.69% (90% CI 1.88% - 3.49%) in the second survey and 6.67% (90% CI 5.42% - 7.92%) in the third. The underreporting reached 11, 19.6, and 20.4 times in each survey, respectively. We observed increased odds to test positive in females compared to males (OR 1.88 95% CI 1.25 - 2.82), while the single best predictor for positivity was ageusia/ anosmia (OR 8.12, 95% CI 4.72 - 13.98). Thirty-five SARS-CoV-2 genomes were sequenced, of which 18 were classified as lineage B.1.1.28, while 17 were B.1.1.33. Multiple independent viral introductions were observed. Integration of multiple epidemiological strategies was able to describe Covid-19 dispersion in the city adequately. Presented results have helped local government authorities to guide pandemic management.

2.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21262393

RESUMEN

Genomic sequencing provides critical information to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments and vaccines, and guide public health responses. To investigate the spatiotemporal heterogeneity in the global SARS-CoV-2 genomic surveillance, we estimated the impact of sequencing intensity and turnaround times (TAT) on variant detection in 167 countries. Most countries submit genomes >21 days after sample collection, and 77% of low and middle income countries sequenced <0.5% of their cases. We found that sequencing at least 0.5% of the cases, with a TAT <21 days, could be a benchmark for SARS-CoV-2 genomic surveillance efforts. Socioeconomic inequalities substantially impact our ability to quickly detect SARS-CoV-2 variants, and undermine the global pandemic preparedness. One-Sentence SummarySocioeconomic inequalities impacted the SARS-CoV-2 genomic surveillance, and undermined the global pandemic preparedness.

3.
Darlan da Silva Candido; Ingra Morales Claro; Jaqueline Goes de Jesus; William Marciel de Souza; Filipe Romero Rebello Moreira; Simon Dellicour; Thomas A. Mellan; Louis du Plessis; Rafael Henrique Moraes Pereira; Flavia Cristina da Silva Sales; Erika Regina Manuli; Julien Theze; Luis Almeida; Mariane Talon de Menezes; Carolina Moreira Voloch; Marcilio Jorge Fumagalli; Thais de Moura Coletti; Camila Alves Maia Silva; Mariana Severo Ramundo; Mariene Ribeiro Amorim; Henrique Hoeltgebaum; Swapnil Mishra; Mandev Gill; Luiz Max Carvalho; Lewis Fletcher Buss; Carlos Augusto Prete Jr.; Jordan Ashworth; Helder Nakaya; Pedro da Silva Peixoto; Oliver J Brady; Samuel M. Nicholls; Amilcar Tanuri; Atila Duque Rossi; Carlos Kaue Vieira Braga; Alexandra Lehmkuhl Gerber; Ana Paula Guimaraes; Nelson Gaburo Jr.; Cecilia Salete Alencar; Alessandro Clayton de Souza Ferreira; Cristiano Xavier Lima; Jose Eduardo Levi; Celso Granato; Giula Magalhaes Ferreira; Ronaldo da Silva Francisco Jr.; Fabiana Granja; Marcia Teixeira Garcia; Maria Luiza Moretti; Mauricio Wesley Perroud Jr.; Terezinha Marta Pereira Pinto Castineiras; Carolina Dos Santos Lazari; Sarah C Hill; Andreza Aruska de Souza Santos; Camila Lopes Simeoni; Julia Forato; Andrei Carvalho Sposito; Angelica Zaninelli Schreiber; Magnun Nueldo Nunes Santos; Camila Zolini Sa; Renan Pedra Souza; Luciana Cunha Resende Moreira; Mauro Martins Teixeira; Josy Hubner; Patricia Asfora Falabella Leme; Rennan Garcias Moreira; Mauricio Lacerda Nogueira; - CADDE-Genomic-Network; Neil Ferguson; Silvia Figueiredo Costa; Jose Luiz Proenca-Modena; Ana Tereza Vasconcelos; Samir Bhatt; Philippe Lemey; Chieh-Hsi Wu; Andrew Rambaut; Nick J Loman; Renato Santana Aguiar; Oliver G Pybus; Ester Cerdeira Sabino; Nuno Rodrigues Faria.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20128249

RESUMEN

Brazil currently has one of the fastest growing SARS-CoV-2 epidemics in the world. Due to limited available data, assessments of the impact of non-pharmaceutical interventions (NPIs) on virus transmission and epidemic spread remain challenging. We investigate the impact of NPIs in Brazil using epidemiological, mobility and genomic data. Mobility-driven transmission models for Sao Paulo and Rio de Janeiro cities show that the reproduction number (Rt) reached below 1 following NPIs but slowly increased to values between 1 to 1.3 (1.0-1.6). Genome sequencing of 427 new genomes and analysis of a geographically representative genomic dataset from 21 of the 27 Brazilian states identified >100 international introductions of SARS-CoV-2 in Brazil. We estimate that three clades introduced from Europe emerged between 22 and 27 February 2020, and were already well-established before the implementation of NPIs and travel bans. During this first phase of the epidemic establishment of SARS-CoV-2 in Brazil, we find that the virus spread mostly locally and within-state borders. Despite sharp decreases in national air travel during this period, we detected a 25% increase in the average distance travelled by air passengers during this time period. This coincided with the spread of SARS-CoV-2 from large urban centers to the rest of the country. In conclusion, our results shed light on the role of large and highly connected populated centres in the rapid ignition and establishment of SARS-CoV-2, and provide evidence that current interventions remain insufficient to keep virus transmission under control in Brazil. One Sentence SummaryJoint analysis of genomic, mobility and epidemiological novel data provide unique insight into the spread and transmission of the rapidly evolving epidemic of SARS-CoV-2 in Brazil.

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