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Sci Rep ; 11(1): 15271, 2021 07 27.
Article in English | MEDLINE | ID: covidwho-1328859


COVID-19 has widely spread around the world, impacting the health systems of several countries in addition to the collateral damage that societies will face in the next years. Although the comparison between countries is essential for controlling this disease, the main challenge is the fact of countries are not simultaneously affected by the virus. Therefore, from the COVID-19 dataset by the Johns Hopkins University Center for Systems Science and Engineering, we present a temporal analysis on the number of new cases and deaths among countries using artificial intelligence. Our approach incrementally models the cases using a hierarchical clustering that emphasizes country transitions between infection groups over time. Then, one can compare the current situation of a country against others that have already faced previous waves. By using our approach, we designed a transition index to estimate the most probable countries' movements between infectious groups to predict next wave trends. We draw two important conclusions: (1) we show the historical infection path taken by specific countries and emphasize changing points that occur when countries move between clusters with small, medium, or large number of cases; (2) we estimate new waves for specific countries using the transition index.

Artificial Intelligence , COVID-19/epidemiology , Forecasting/methods , Cluster Analysis , Databases, Factual , Humans , Pandemics
Proc Natl Acad Sci U S A ; 118(27)2021 07 06.
Article in English | MEDLINE | ID: covidwho-1276013


The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays a key role in viral infectivity. It is also the major antigen stimulating the host's protective immune response, specifically, the production of neutralizing antibodies. Recently, a new variant of SARS-CoV-2 possessing multiple mutations in the S protein, designated P.1, emerged in Brazil. Here, we characterized a P.1 variant isolated in Japan by using Syrian hamsters, a well-established small animal model for the study of SARS-CoV-2 disease (COVID-19). In hamsters, the variant showed replicative abilities and pathogenicity similar to those of early and contemporary strains (i.e., SARS-CoV-2 bearing aspartic acid [D] or glycine [G] at position 614 of the S protein). Sera and/or plasma from convalescent patients and BNT162b2 messenger RNA vaccinees showed comparable neutralization titers across the P.1 variant, S-614D, and S-614G strains. In contrast, the S-614D and S-614G strains were less well recognized than the P.1 variant by serum from a P.1-infected patient. Prior infection with S-614D or S-614G strains efficiently prevented the replication of the P.1 variant in the lower respiratory tract of hamsters upon reinfection. In addition, passive transfer of neutralizing antibodies to hamsters infected with the P.1 variant or the S-614G strain led to reduced virus replication in the lower respiratory tract. However, the effect was less pronounced against the P.1 variant than the S-614G strain. These findings suggest that the P.1 variant may be somewhat antigenically different from the early and contemporary strains of SARS-CoV-2.

COVID-19/virology , SARS-CoV-2/physiology , SARS-CoV-2/pathogenicity , Virus Replication , Animals , Antibodies, Neutralizing , COVID-19/diagnostic imaging , COVID-19/pathology , Cricetinae , Humans , Immunogenicity, Vaccine , Lung/pathology , Mesocricetus , Mice , Spike Glycoprotein, Coronavirus/genetics , X-Ray Microtomography
Proc Natl Acad Sci U S A ; 117(28): 16587-16595, 2020 07 14.
Article in English | MEDLINE | ID: covidwho-611003


At the end of 2019, a novel coronavirus (severe acute respiratory syndrome coronavirus 2; SARS-CoV-2) was detected in Wuhan, China, that spread rapidly around the world, with severe consequences for human health and the global economy. Here, we assessed the replicative ability and pathogenesis of SARS-CoV-2 isolates in Syrian hamsters. SARS-CoV-2 isolates replicated efficiently in the lungs of hamsters, causing severe pathological lung lesions following intranasal infection. In addition, microcomputed tomographic imaging revealed severe lung injury that shared characteristics with SARS-CoV-2-infected human lung, including severe, bilateral, peripherally distributed, multilobular ground glass opacity, and regions of lung consolidation. SARS-CoV-2-infected hamsters mounted neutralizing antibody responses and were protected against subsequent rechallenge with SARS-CoV-2. Moreover, passive transfer of convalescent serum to naïve hamsters efficiently suppressed the replication of the virus in the lungs even when the serum was administrated 2 d postinfection of the serum-treated hamsters. Collectively, these findings demonstrate that this Syrian hamster model will be useful for understanding SARS-CoV-2 pathogenesis and testing vaccines and antiviral drugs.

Coronavirus Infections/virology , Disease Models, Animal , Lung/pathology , Pneumonia, Viral/virology , Animals , Antibodies, Neutralizing/blood , Antibodies, Viral/blood , Betacoronavirus/pathogenicity , Betacoronavirus/physiology , COVID-19 , Cell Line , Chlorocebus aethiops , Coronavirus Infections/pathology , Coronavirus Infections/therapy , Cricetinae , Humans , Immunization, Passive , Lung/diagnostic imaging , Lung/virology , Mesocricetus , Pandemics , Pneumonia, Viral/pathology , Ribonucleoproteins/chemistry , SARS-CoV-2 , Vero Cells , Viral Proteins/chemistry , Virus Replication , COVID-19 Serotherapy