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2.
Cell Host Microbe ; 30(8): 1112-1123.e3, 2022 Aug 10.
Article in English | MEDLINE | ID: covidwho-1894865

ABSTRACT

Although recombination is a feature of coronavirus evolution, previously detected recombinant lineages of SARS-CoV-2 have shown limited circulation thus far. Here, we present a detailed phylogenetic analysis of four SARS-CoV-2 lineages to investigate the possibility of virus recombination among them. Our analyses reveal well-supported phylogenetic differences between the Orf1ab region encoding viral non-structural proteins and the rest of the genome, including Spike (S) protein and remaining reading frames. By accounting for several deletions in NSP6, Orf3a, and S, we conclude that the B.1.628 major cluster, now designated as lineage XB, originated from a recombination event between viruses of B.1.631 and B.1.634 lineages. This scenario is supported by the spatiotemporal distribution of these lineages across the USA and Mexico during 2021, suggesting that the recombination event originated in this geographical region. This event raises important questions regarding the role and potential effects of recombination on SARS-CoV-2 evolution.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Genome, Viral , Humans , Phylogeny , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/genetics
3.
Nat Med ; 28(7): 1476-1485, 2022 07.
Article in English | MEDLINE | ID: covidwho-1830084

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used individual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates were primarily associated with geographic inequities and shortages in healthcare capacity. We estimate that approximately half of the COVID-19 deaths in hospitals in the 14 cities could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization and pandemic preparedness are critical to minimize population-wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries.


Subject(s)
COVID-19 , Aged , Aged, 80 and over , Bayes Theorem , Brazil/epidemiology , COVID-19/epidemiology , Hospitals , Humans , SARS-CoV-2
4.
Life (Basel) ; 12(3)2022 Feb 22.
Article in English | MEDLINE | ID: covidwho-1708054

ABSTRACT

The COVID-19 pandemic hit Ecuador severely. The country caught the attention of international media due to its high death toll and overwhelmed healthcare system. The clinical diagnostics system was rapidly overloaded, and the import of PCR tests was delayed. The case of Ecuador illustrates how middle-income countries rely heavily on the importation of biotechnological products for their healthcare systems. The Ecuadorian experience during the COVID-19 pandemic serves as a call for the formation of policies for the development of the biotechnological industry.

5.
Nat Rev Phys ; 2(6): 279-281, 2020.
Article in English | MEDLINE | ID: covidwho-1684119

ABSTRACT

As the COVID-19 pandemic continues, mathematical epidemiologists share their views on what models reveal about how the disease has spread, the current state of play and what work still needs to be done.

6.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-292948

ABSTRACT

Genetic recombination is an important driving force of coronavirus evolution. While some degree of virus recombination has been reported during the COVID-19 pandemic, previously detected recombinant lineages of SARS-CoV-2 have shown limited circulation and been observed only in restricted areas. Prompted by reports of unusual genetic similarities among several Pango lineages detected mainly in North and Central America, we present a detailed phylogenetic analysis of four SARS-CoV-2 lineages (B.1.627, B.1.628, B.1.631 and B.1.634) in order to investigate the possibility of virus recombination among them. Two of these lineages, B.1.628 and B.1.631, are split into two distinct clusters (here named major and minor). Our phylogenetic and recombination analyses of these lineages find well-supported phylogenetic differences between the Orf1ab region and the rest of the genome (S protein and remaining reading frames). The lineages also contain several deletions in the NSP6, Orf3a and S proteins that can augment reconstruction of reliable evolutionary histories. By reconciling the deletions and phylogenetic data, we conclude that the B.1.628 major cluster originated from a recombination event between a B.1.631 major virus and a lineage B.1.634 virus. This scenario inferred from genetic data is supported by the spatial and temporal distribution of the three lineages, which all co-circulated in the USA and Mexico during 2021, suggesting this region is where the recombination event took place. We therefore support the designation of the B.1.628 major cluster as recombinant lineage XB in the Pango nomenclature. The widespread circulation of lineage XB across multiple countries over a longer timespan than the previously designated recombinant XA lineage raises important questions regarding the role and potential effects of recombination on the evolution of SARS-CoV-2 during the ongoing COVID-19 pandemic.

7.
Virus Evol ; 7(2): veab051, 2021.
Article in English | MEDLINE | ID: covidwho-1412522

ABSTRACT

Characterisation of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic diversity through space and time can reveal trends in virus importation and domestic circulation and permit the exploration of questions regarding the early transmission dynamics. Here, we present a detailed description of SARS-CoV-2 genomic epidemiology in Ecuador, one of the hardest hit countries during the early stages of the coronavirus-19 pandemic. We generated and analysed 160 whole genome sequences sampled from all provinces of Ecuador in 2020. Molecular clock and phylogeographic analysis of these sequences in the context of global SARS-CoV-2 diversity enable us to identify and characterise individual transmission lineages within Ecuador, explore their spatiotemporal distributions, and consider their introduction and domestic circulation. Our results reveal a pattern of multiple international importations across the country, with apparent differences between key provinces. Transmission lineages were mostly introduced before the implementation of non-pharmaceutical interventions, with differential degrees of persistence and national dissemination.

8.
Science ; 373(6557): 889-895, 2021 08 20.
Article in English | MEDLINE | ID: covidwho-1322770

ABSTRACT

Understanding the causes and consequences of the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern is crucial to pandemic control yet difficult to achieve because they arise in the context of variable human behavior and immunity. We investigated the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based polymerase chain reaction data. We identified a multistage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explored how B.1.1.7 spread was shaped by nonpharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , SARS-CoV-2 , COVID-19/prevention & control , COVID-19/transmission , COVID-19 Nucleic Acid Testing , Communicable Disease Control , Genome, Viral , Humans , Incidence , Phylogeography , SARS-CoV-2/genetics , SARS-CoV-2/pathogenicity , Spatio-Temporal Analysis , Travel , United Kingdom/epidemiology
9.
Front Public Health ; 9: 662842, 2021.
Article in English | MEDLINE | ID: covidwho-1295720

ABSTRACT

Background: When a new pathogen emerges, consistent case reporting is critical for public health surveillance. Tracking cases geographically and over time is key for understanding the spread of an infectious disease and effectively designing interventions to contain and mitigate an epidemic. In this paper we describe the reporting systems on COVID-19 in Southeast Asia during the first wave in 2020, and highlight the impact of specific reporting methods. Methods: We reviewed key epidemiological variables from various sources including a regionally comprehensive dataset, national trackers, dashboards, and case bulletins for 11 countries during the first wave of the epidemic in Southeast Asia. We recorded timelines of shifts in epidemiological reporting systems and described the differences in how epidemiological data are reported across countries and timepoints. Results: Our findings suggest that countries in Southeast Asia generally reported precise and detailed epidemiological data during the first wave of the pandemic. Changes in reporting rarely occurred for demographic data, while reporting shifts for geographic and temporal data were frequent. Most countries provided COVID-19 individual-level data daily using HTML and PDF, necessitating scraping and extraction before data could be used in analyses. Conclusion: Our study highlights the importance of more nuanced analyses of COVID-19 epidemiological data within and across countries because of the frequent shifts in reporting. As governments continue to respond to impacts on health and the economy, data sharing also needs to be prioritised given its foundational role in policymaking, and in the implementation and evaluation of interventions.


Subject(s)
COVID-19 , Pandemics , Asia, Southeastern/epidemiology , Humans , Information Dissemination , SARS-CoV-2
11.
Microbiol Resour Announc ; 9(41)2020 Oct 08.
Article in English | MEDLINE | ID: covidwho-1166375

ABSTRACT

We report the metagenome analysis of a bronchoalveolar lavage (BAL) fluid sample from a confirmed coronavirus disease 2019 (COVID-19) case in Quito, Ecuador. Sequencing was performed using MinION technology.

12.
Science ; 371(6530): 708-712, 2021 02 12.
Article in English | MEDLINE | ID: covidwho-1066806

ABSTRACT

The United Kingdom's COVID-19 epidemic during early 2020 was one of world's largest and was unusually well represented by virus genomic sampling. We determined the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses combined with epidemiological and travel data, we quantified the size, spatiotemporal origins, and persistence of genetically distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whereas lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Genome, Viral , SARS-CoV-2/genetics , COVID-19/prevention & control , COVID-19/transmission , Chain of Infection , Communicable Disease Control , Communicable Diseases, Imported/epidemiology , Communicable Diseases, Imported/virology , Epidemics , Humans , Phylogeny , Travel , United Kingdom/epidemiology
13.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-4729

ABSTRACT

The permanence of rt-PCR positivity after a long time in COVID-19 patients has prompted the question of whether SARS-CoV-2 could cause a persistent infection or patients can become re-infected by this virus. Both possibilities could have critical implications for the management and control of COVID-19. Here we present the first confirmed case of SARS-CoV-2 reinfection in Ecuador and South America. Materials and methods: Our diagnostic laboratory detected a potential re-infection in one patient who was SARS-COv2 rt-PCR positive twice (in May and July 2020). The first laboratory-confirmed infection presented with mild symptoms and full recovery, reaffirmed by a negative RT-PCR test result obtained two weeks after symptom onset. More severe COVID-19-like symptoms presented again four weeks after the first event, and a third RT-PCR test was performed which resulted positive. The total RNA extraction (from the samples collected on both occasions) was sequenced in an Oxford Nanopore MinION using a tilling PCR protocol developed by the ARTIC-Network, and the reads were analyzed using the artic-medaka consensus generation tool. Anti SARS-CoV-2 IgM and IgG antibodies were investigated. Results: different SARS-CoV-2 variants were identified in each infection event. For the first infection, the genome was assigned to the B1.p9 GISAID clade while the variant associated with the second episode was assigned to the A.1.1 GISAID clade. High levels of both SARS-CoV-2 specific IgM and IgG were observed during the second event. Discussion: a patient with two COVID-19 events presented two different SARS-CoV-2 variants on each event, confirming reinfection. This phenomenon is still considered rare.

14.
Nat Med ; 26(12): 1829-1834, 2020 12.
Article in English | MEDLINE | ID: covidwho-834900

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread1-4. During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China5,6. Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking7. In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics.


Subject(s)
COVID-19/epidemiology , COVID-19/etiology , Crowding , Pandemics , China/epidemiology , Cities/epidemiology , Contact Tracing , Demography/standards , Demography/statistics & numerical data , Disease Outbreaks , Forecasting/methods , Geography , Human Activities/statistics & numerical data , Humans , Physical Distancing , Population Density , Public Policy/trends , SARS-CoV-2/physiology , Travel/statistics & numerical data
15.
Nat Hum Behav ; 4(8): 856-865, 2020 08.
Article in English | MEDLINE | ID: covidwho-690410

ABSTRACT

The first case of COVID-19 was detected in Brazil on 25 February 2020. We report and contextualize epidemiological, demographic and clinical findings for COVID-19 cases during the first 3 months of the epidemic. By 31 May 2020, 514,200 COVID-19 cases, including 29,314 deaths, had been reported in 75.3% (4,196 of 5,570) of municipalities across all five administrative regions of Brazil. The R0 value for Brazil was estimated at 3.1 (95% Bayesian credible interval = 2.4-5.5), with a higher median but overlapping credible intervals compared with some other seriously affected countries. A positive association between higher per-capita income and COVID-19 diagnosis was identified. Furthermore, the severe acute respiratory infection cases with unknown aetiology were associated with lower per-capita income. Co-circulation of six respiratory viruses was detected but at very low levels. These findings provide a comprehensive description of the ongoing COVID-19 epidemic in Brazil and may help to guide subsequent measures to control virus transmission.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections , Disease Transmission, Infectious , Influenza, Human , Pandemics , Pneumonia, Viral , Adult , Aged , Brazil/epidemiology , COVID-19 , COVID-19 Testing , Child , Clinical Laboratory Techniques/methods , Clinical Laboratory Techniques/statistics & numerical data , Coinfection/epidemiology , Coronavirus Infections/diagnosis , Coronavirus Infections/drug therapy , Coronavirus Infections/mortality , Coronavirus Infections/therapy , Coronavirus Infections/transmission , Disease Transmission, Infectious/prevention & control , Disease Transmission, Infectious/statistics & numerical data , Female , Hospitalization/statistics & numerical data , Humans , Infant , Influenza, Human/diagnosis , Influenza, Human/epidemiology , Influenza, Human/virology , Male , Mortality , Pneumonia, Viral/diagnosis , Pneumonia, Viral/mortality , Pneumonia, Viral/therapy , Pneumonia, Viral/transmission , SARS-CoV-2 , Socioeconomic Factors
16.
Science ; 368(6490): 493-497, 2020 05 01.
Article in English | MEDLINE | ID: covidwho-18400

ABSTRACT

The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Travel/statistics & numerical data , Age Distribution , Betacoronavirus , COVID-19 , China , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Epidemiological Monitoring , Humans , Linear Models , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , SARS-CoV-2 , Sex Distribution , Spatial Analysis
17.
Sci Data ; 7(1): 106, 2020 03 24.
Article in English | MEDLINE | ID: covidwho-15533

ABSTRACT

Cases of a novel coronavirus were first reported in Wuhan, Hubei province, China, in December 2019 and have since spread across the world. Epidemiological studies have indicated human-to-human transmission in China and elsewhere. To aid the analysis and tracking of the COVID-19 epidemic we collected and curated individual-level data from national, provincial, and municipal health reports, as well as additional information from online reports. All data are geo-coded and, where available, include symptoms, key dates (date of onset, admission, and confirmation), and travel history. The generation of detailed, real-time, and robust data for emerging disease outbreaks is important and can help to generate robust evidence that will support and inform public health decision making.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , COVID-19 , China , Epidemics , Geographic Mapping , Geography , Humans , Pandemics , Public Health , SARS-CoV-2
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