1
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Shubin M, Brustad HK, Midtbø JE, Günther F, Alessandretti L, Ala-Nissila T, Scalia Tomba G, Kivelä M, Chan LYH, Leskelä L. The influence of cross-border mobility on the COVID-19 epidemic in Nordic countries. PLoS Comput Biol 2024; 20:e1012182. [PMID: 38865414 PMCID: PMC11198903 DOI: 10.1371/journal.pcbi.1012182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 06/25/2024] [Accepted: 05/20/2024] [Indexed: 06/14/2024] Open
Abstract
Restrictions of cross-border mobility are typically used to prevent an emerging disease from entering a country in order to slow down its spread. However, such interventions can come with a significant societal cost and should thus be based on careful analysis and quantitative understanding on their effects. To this end, we model the influence of cross-border mobility on the spread of COVID-19 during 2020 in the neighbouring Nordic countries of Denmark, Finland, Norway and Sweden. We investigate the immediate impact of cross-border travel on disease spread and employ counterfactual scenarios to explore the cumulative effects of introducing additional infected individuals into a population during the ongoing epidemic. Our results indicate that the effect of inter-country mobility on epidemic growth is non-negligible essentially when there is sizeable mobility from a high prevalence country or countries to a low prevalence one. Our findings underscore the critical importance of accurate data and models on both epidemic progression and travel patterns in informing decisions related to inter-country mobility restrictions.
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Affiliation(s)
- Mikhail Shubin
- Department of Mathematics and Systems Analysis, Aalto University, Espoo, Finland
| | | | - Jørgen Eriksson Midtbø
- Department of Method Development and Analytics, Norwegian Institute of Public Health, Oslo, Norway
| | - Felix Günther
- Department of Mathematics, Stockholm University, Stockholm, Sweden
| | | | - Tapio Ala-Nissila
- Quantum Technology Finland Center of Excellence, Department of Applied Physics, Aalto University, Espoo, Finland
- Interdisciplinary Centre for Mathematical Modelling and Department of Mathematical Sciences, Loughborough University, Loughborough, United Kingdom
| | - Gianpaolo Scalia Tomba
- Department of Mathematics, Stockholm University, Stockholm, Sweden
- Department of Mathematics, University of Rome Tor Vergata, Rome, Italy
| | - Mikko Kivelä
- Department of Computer Science, Aalto University, Espoo, Finland
| | - Louis Yat Hin Chan
- Department of Method Development and Analytics, Norwegian Institute of Public Health, Oslo, Norway
| | - Lasse Leskelä
- Department of Mathematics and Systems Analysis, Aalto University, Espoo, Finland
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2
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Wegner F, Cabrera-Gil B, Tanguy A, Beckmann C, Beerenwinkel N, Bertelli C, Carrara M, Cerutti L, Chen C, Cordey S, Dumoulin A, du Plessis L, Friedli M, Gerth Y, Greub G, Härri A, Hirsch H, Howald C, Huber M, Imhof A, Kaiser L, Kufner V, Leib SL, Leuzinger K, Lleshi E, Martinetti G, Mäusezahl M, Moraz M, Neher R, Nolte O, Ramette A, Redondo M, Risch L, Rohner L, Roloff T, Schläepfer P, Schneider K, Singer F, Spina V, Stadler T, Studer E, Topolsky I, Trkola A, Walther D, Wohlwend N, Zehnder C, Neves A, Egli A. How much should we sequence? An analysis of the Swiss SARS-CoV-2 surveillance effort. Microbiol Spectr 2024; 12:e0362823. [PMID: 38497714 PMCID: PMC11064629 DOI: 10.1128/spectrum.03628-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 03/01/2024] [Indexed: 03/19/2024] Open
Abstract
During the SARS-CoV-2 pandemic, many countries directed substantial resources toward genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic data set from Switzerland, comprising more than 143k sequences. We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. The impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage-dependent-something that is unknown at the time of sequencing-and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.IMPORTANCESwitzerland had one of the most comprehensive genomic surveillance systems during the COVID-19 pandemic. Such programs need to strike a balance between societal benefits and program costs. Our study aims to answer the question: How would surveillance outcomes have changed had we sequenced less? We find that some outcomes but also certain viral lineages are more affected than others by sequencing less. However, sequencing to around a third of the original effort still captured many important outcomes for the variants of concern such as their first detection but affected more strongly other measures like the detection of first transmission clusters for some lineages. Our work highlights the importance of setting predefined targets for a national genomic surveillance program based on which sequencing effort should be determined. Additionally, the use of a centralized surveillance platform facilitates aggregating data on a national level for rapid public health responses as well as post-analyses.
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Affiliation(s)
- Fanny Wegner
- Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland
| | - Blanca Cabrera-Gil
- Clinical Bioinformatics, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
| | | | | | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Claire Bertelli
- Clinical Microbiology, University Hospital, Lausanne, Switzerland
| | - Matteo Carrara
- NEXUS Personalized Health Technologies, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | | | - Chaoran Chen
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Samuel Cordey
- Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland
| | | | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | | | - Yannick Gerth
- Humanmedizinische Mikrobiologie, Zentrum für Labormedizin, St. Gallen, Switzerland
| | - Gilbert Greub
- Clinical Microbiology, University Hospital, Lausanne, Switzerland
| | | | - Hans Hirsch
- Clinical Virology, University Hospital, Basel, Switzerland
| | | | - Michael Huber
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | | | - Laurent Kaiser
- Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland
| | - Verena Kufner
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Stephen L. Leib
- Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland
| | | | - Etleva Lleshi
- Microbiology Department, Synlab, Bioggio, Switzerland
| | - Gladys Martinetti
- Department of Laboratory Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | | | - Milo Moraz
- Valais Hospital, Central Institute, Sion, Switzerland
| | - Richard Neher
- Biozentrum, University of Basel, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Oliver Nolte
- Humanmedizinische Mikrobiologie, Zentrum für Labormedizin, St. Gallen, Switzerland
| | - Alban Ramette
- Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland
| | | | | | | | - Tim Roloff
- Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland
| | | | | | - Franziska Singer
- NEXUS Personalized Health Technologies, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Valeria Spina
- Department of Laboratory Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Erik Studer
- Federal Office of Public Health, Bern, Switzerland
| | - Ivan Topolsky
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Alexandra Trkola
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Daniel Walther
- Clinical Bioinformatics, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
| | | | | | - Aitana Neves
- Clinical Bioinformatics, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
| | - Adrian Egli
- Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland
| | - the SPSP consortium
- Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland
- Clinical Bioinformatics, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
- Genesupport, Geneva, Switzerland
- Viollier AG, Allschwil, Switzerland
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
- Clinical Microbiology, University Hospital, Lausanne, Switzerland
- NEXUS Personalized Health Technologies, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
- Health2030 Genome Center, Geneva, Switzerland
- Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland
- Valais Hospital, Central Institute, Sion, Switzerland
- Humanmedizinische Mikrobiologie, Zentrum für Labormedizin, St. Gallen, Switzerland
- Biolytix, Witterswil, Switzerland
- Clinical Virology, University Hospital, Basel, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
- Spitalregion Oberaargau, Langenthal, Switzerland
- Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland
- Microbiology Department, Synlab, Bioggio, Switzerland
- Department of Laboratory Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Federal Office of Public Health, Bern, Switzerland
- Biozentrum, University of Basel, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
- Labor Dr. Risch, Buchs, Switzerland
- Clinical Microbiology, University Hospital, Basel, Switzerland
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3
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Revell LJ. phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ 2024; 12:e16505. [PMID: 38192598 PMCID: PMC10773453 DOI: 10.7717/peerj.16505] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 10/31/2023] [Indexed: 01/10/2024] Open
Abstract
Phylogenetic comparative methods comprise the general endeavor of using an estimated phylogenetic tree (or set of trees) to make secondary inferences: about trait evolution, diversification dynamics, biogeography, community ecology, and a wide range of other phenomena or processes. Over the past ten years or so, the phytools R package has grown to become an important research tool for phylogenetic comparative analysis. phytools is a diverse contributed R library now consisting of hundreds of different functions covering a variety of methods and purposes in phylogenetic biology. As of the time of writing, phytools included functionality for fitting models of trait evolution, for reconstructing ancestral states, for studying diversification on trees, and for visualizing phylogenies, comparative data, and fitted models, as well numerous other tasks related to phylogenetic biology. Here, I describe some significant features of and recent updates to phytools, while also illustrating several popular workflows of the phytools computational software.
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Affiliation(s)
- Liam J. Revell
- Department of Biology, University of Massachusetts Boston, Boston, MA, USA
- Facultad de Ciencias, Universidad Católica de la Santísima Concepción, Concepción, Chile
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4
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Chen Z, Lemey P, Yu H. Approaches and challenges to inferring the geographical source of infectious disease outbreaks using genomic data. THE LANCET. MICROBE 2024; 5:e81-e92. [PMID: 38042165 DOI: 10.1016/s2666-5247(23)00296-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 09/03/2023] [Accepted: 09/13/2023] [Indexed: 12/04/2023]
Abstract
Genomic data hold increasing potential in the elucidation of transmission dynamics and geographical sources of infectious disease outbreaks. Phylogeographic methods that use epidemiological and genomic data obtained from surveillance enable us to infer the history of spatial transmission that is naturally embedded in the topology of phylogenetic trees as a record of the dispersal of infectious agents between geographical locations. In this Review, we provide an overview of phylogeographic approaches widely used for reconstructing the geographical sources of outbreaks of interest. These approaches can be classified into ancestral trait or state reconstruction and structured population models, with structured population models including popular structured coalescent and birth-death models. We also describe the major challenges associated with sequencing technologies, surveillance strategies, data sharing, and analysis frameworks that became apparent during the generation of large-scale genomic data in recent years, extending beyond inference approaches. Finally, we highlight the role of genomic data in geographical source inference and clarify how this enhances understanding and molecular investigations of outbreak sources.
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Affiliation(s)
- Zhiyuan Chen
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Clinical and Evolutionary Virology, KU Leuven, Leuven, Belgium
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
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5
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Matteson NL, Hassler GW, Kurzban E, Schwab MA, Perkins SA, Gangavarapu K, Levy JI, Parker E, Pride D, Hakim A, De Hoff P, Cheung W, Castro-Martinez A, Rivera A, Veder A, Rivera A, Wauer C, Holmes J, Wilson J, Ngo SN, Plascencia A, Lawrence ES, Smoot EW, Eisner ER, Tsai R, Chacón M, Baer NA, Seaver P, Salido RA, Aigner S, Ngo TT, Barber T, Ostrander T, Fielding-Miller R, Simmons EH, Zazueta OE, Serafin-Higuera I, Sanchez-Alavez M, Moreno-Camacho JL, García-Gil A, Murphy Schafer AR, McDonald E, Corrigan J, Malone JD, Stous S, Shah S, Moshiri N, Weiss A, Anderson C, Aceves CM, Spencer EG, Hufbauer EC, Lee JJ, King AJ, Ramesh KS, Nguyen KN, Saucedo K, Robles-Sikisaka R, Fisch KM, Gonias SL, Birmingham A, McDonald D, Karthikeyan S, Martin NK, Schooley RT, Negrete AJ, Reyna HJ, Chavez JR, Garcia ML, Cornejo-Bravo JM, Becker D, Isaksson M, Washington NL, Lee W, Garfein RS, Luna-Ruiz Esparza MA, Alcántar-Fernández J, Henson B, Jepsen K, Olivares-Flores B, Barrera-Badillo G, Lopez-Martínez I, Ramírez-González JE, Flores-León R, Kingsmore SF, Sanders A, Pradenas A, White B, Matthews G, Hale M, McLawhon RW, Reed SL, Winbush T, McHardy IH, Fielding RA, Nicholson L, Quigley MM, Harding A, Mendoza A, Bakhtar O, Browne SH, Olivas Flores J, Rincon Rodríguez DG, Gonzalez Ibarra M, Robles Ibarra LC, Arellano Vera BJ, Gonzalez Garcia J, Harvey-Vera A, Knight R, Laurent LC, Yeo GW, Wertheim JO, Ji X, Worobey M, Suchard MA, Andersen KG, Campos-Romero A, Wohl S, Zeller M. Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics. Cell 2023; 186:5690-5704.e20. [PMID: 38101407 PMCID: PMC10795731 DOI: 10.1016/j.cell.2023.11.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 08/21/2023] [Accepted: 11/21/2023] [Indexed: 12/17/2023]
Abstract
The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.
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Affiliation(s)
| | - Gabriel W Hassler
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ezra Kurzban
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Madison A Schwab
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Sarah A Perkins
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Karthik Gangavarapu
- Department of Biomathematics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA; Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Joshua I Levy
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Edyth Parker
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - David Pride
- Department of Pathology, University of California, San Diego, La Jolla, CA, USA; Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Abbas Hakim
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, La Jolla, CA, USA; COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Peter De Hoff
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, La Jolla, CA, USA; COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Willi Cheung
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, La Jolla, CA, USA; COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Anelizze Castro-Martinez
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, La Jolla, CA, USA; Sanford Consortium of Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Andrea Rivera
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Anthony Veder
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Ariana Rivera
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Cassandra Wauer
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Jacqueline Holmes
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Jedediah Wilson
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Shayla N Ngo
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Ashley Plascencia
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Elijah S Lawrence
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Elizabeth W Smoot
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Emily R Eisner
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Rebecca Tsai
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Marisol Chacón
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Nathan A Baer
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Phoebe Seaver
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Rodolfo A Salido
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Stefan Aigner
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Toan T Ngo
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Tom Barber
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Tyler Ostrander
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Rebecca Fielding-Miller
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA; Division of Infectious Disease and Global Public Health, University of California, San Diego, La Jolla, CA, USA
| | | | - Oscar E Zazueta
- Department of Epidemiology, Secretaria de Salud de Baja California, Tijuana, Baja California, Mexico
| | | | - Manuel Sanchez-Alavez
- Centro de Diagnostico COVID-19 UABC, Tijuana, Baja California, Mexico; Department of Molecular Medicine, Scripps Research, La Jolla, CA, USA
| | | | - Abraham García-Gil
- Clinical Laboratory Department, Salud Digna, A.C, Tijuana, Baja California, Mexico
| | | | - Eric McDonald
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Jeremy Corrigan
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - John D Malone
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Sarah Stous
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Seema Shah
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Niema Moshiri
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Alana Weiss
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Catelyn Anderson
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Christine M Aceves
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Emily G Spencer
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Emory C Hufbauer
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Justin J Lee
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Alison J King
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Karthik S Ramesh
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Kelly N Nguyen
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Kieran Saucedo
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | | | - Kathleen M Fisch
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, La Jolla, CA, USA; Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
| | - Steven L Gonias
- Department of Pathology, University of California, San Diego, La Jolla, CA, USA
| | - Amanda Birmingham
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Smruthi Karthikeyan
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Natasha K Martin
- Division of Infectious Disease and Global Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Robert T Schooley
- Division of Infectious Disease and Global Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Agustin J Negrete
- Facultad de Ciencias de la Salud Universidad Autonoma de Baja California Valle de Las Palmas, Tijuana, Baja California, Mexico
| | - Horacio J Reyna
- Facultad de Ciencias de la Salud Universidad Autonoma de Baja California Valle de Las Palmas, Tijuana, Baja California, Mexico
| | - Jose R Chavez
- Facultad de Ciencias de la Salud Universidad Autonoma de Baja California Valle de Las Palmas, Tijuana, Baja California, Mexico
| | - Maria L Garcia
- Facultad de Ciencias de la Salud Universidad Autonoma de Baja California Valle de Las Palmas, Tijuana, Baja California, Mexico
| | - Jose M Cornejo-Bravo
- Facultad de Ciencias Quimicas e Ingenieria, Universidad Autonoma de Baja California, Tijuana, Baja California, Mexico
| | | | | | | | | | - Richard S Garfein
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA
| | | | | | - Benjamin Henson
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Kristen Jepsen
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Beatriz Olivares-Flores
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE), Ciudad de México, CDMX, Mexico
| | - Gisela Barrera-Badillo
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE), Ciudad de México, CDMX, Mexico
| | - Irma Lopez-Martínez
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE), Ciudad de México, CDMX, Mexico
| | - José E Ramírez-González
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE), Ciudad de México, CDMX, Mexico
| | - Rita Flores-León
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE), Ciudad de México, CDMX, Mexico
| | | | - Alison Sanders
- Return to Learn, University of California, San Diego, La Jolla, CA, USA
| | - Allorah Pradenas
- Return to Learn, University of California, San Diego, La Jolla, CA, USA
| | - Benjamin White
- Return to Learn, University of California, San Diego, La Jolla, CA, USA
| | - Gary Matthews
- Return to Learn, University of California, San Diego, La Jolla, CA, USA
| | - Matt Hale
- Return to Learn, University of California, San Diego, La Jolla, CA, USA
| | - Ronald W McLawhon
- Return to Learn, University of California, San Diego, La Jolla, CA, USA
| | - Sharon L Reed
- Return to Learn, University of California, San Diego, La Jolla, CA, USA
| | - Terri Winbush
- Return to Learn, University of California, San Diego, La Jolla, CA, USA
| | | | | | | | | | | | | | | | - Sara H Browne
- Division of Infectious Disease and Global Public Health, University of California, San Diego, La Jolla, CA, USA; Specialist in Global Health, Encinitas, CA, USA
| | - Jocelyn Olivas Flores
- Facultad de Ciencias Quimicas e Ingenieria, Universidad Autonoma de Baja California, Tijuana, Baja California, Mexico; University of HealthMx, Tijuana, Baja California, Mexico
| | - Diana G Rincon Rodríguez
- University of HealthMx, Tijuana, Baja California, Mexico; Facultad de Medicina, Universidad Xochicalco, Tijuana, Baja California, Mexico
| | - Martin Gonzalez Ibarra
- University of HealthMx, Tijuana, Baja California, Mexico; Facultad de Medicina, Universidad Xochicalco, Tijuana, Baja California, Mexico
| | - Luis C Robles Ibarra
- University of HealthMx, Tijuana, Baja California, Mexico; Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado, Tijuana, Baja California, Mexico
| | - Betsy J Arellano Vera
- University of HealthMx, Tijuana, Baja California, Mexico; Instituto Mexicano del Seguro Social, Tijuana, Baja California, Mexico
| | - Jonathan Gonzalez Garcia
- University of HealthMx, Tijuana, Baja California, Mexico; SIMNSA, Tijuana, Baja California, Mexico
| | | | - Rob Knight
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Louise C Laurent
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, La Jolla, CA, USA; Sanford Consortium of Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Gene W Yeo
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Sanford Consortium of Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Joel O Wertheim
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Xiang Ji
- Department of Mathematics, School of Science and Engineering, Tulane University, New Orleans, LA, USA
| | - Michael Worobey
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA
| | - Marc A Suchard
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kristian G Andersen
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA.
| | - Abraham Campos-Romero
- Innovation and Research Department, Salud Digna, A.C, Tijuana, Baja California, Mexico
| | - Shirlee Wohl
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Mark Zeller
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA.
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6
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Pozza G, Casalini G, Ciubotariu CL, Giacomelli A, Galimberti M, Zacheo M, Rabbione A, Pieruzzi M, Oreni L, Galimberti L, Colombo R, Rizzardini G, Pagani C, Rimoldi SG, Bonazzetti C, Ridolfo AL, Antinori S. Bloodstream Infections in Intensive Care Unit during Four Consecutive SARS-CoV-2 Pandemic Waves. Antibiotics (Basel) 2023; 12:1448. [PMID: 37760744 PMCID: PMC10525187 DOI: 10.3390/antibiotics12091448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 09/10/2023] [Accepted: 09/13/2023] [Indexed: 09/29/2023] Open
Abstract
Critically ill COVID-19 patients are at an increased risk of bloodstream infections (BSIs). We performed a retrospective observational single-center study on COVID-19 patients admitted to intensive care unit (ICU) to assess the incidence of BSIs in four consecutive periods: 21 February-31 July 2020 (W1), 1 August 2020-31 January 2021 (W2), 1 February-30 September 2021 (W3) and 1 October 2021 and 30 April 2022 (W4). BSIs that occurred 48 h after ICU admission were included. The crude incidence of BSIs was estimated by means of Poisson distribution normalized to 1000 patient-days. A total of 404 critically ill COVID-19 patients were admitted to ICU, of whom 284 (61%) developed at least one episode of BSI with an overall crude incidence of 87 events every 1000 patient-days (95% CI 77-98) without a significant difference in consecutive epidemic periods (p = 0.357). Gram-positive bacteria were the most frequent etiological agents of BSIs, contributing to 74.6% episodes. A progressive decrease in BSIs due to Enterococcus spp. was observed (W1 57.4%, W2 43.7%, W3 35.7% and W4 32.7%; p = 0.004). The incidence of BSIs remained stable during different epidemic periods. Enterococcus spp. prevalence was significantly reduced, although still accounted for one third of BSIs in more recent epidemic periods.
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Affiliation(s)
- Giacomo Pozza
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
- Department of Biomedical Sciences and Clinics, Università degli Studi di Milano, 20157 Milan, Italy
| | - Giacomo Casalini
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
- Department of Biomedical Sciences and Clinics, Università degli Studi di Milano, 20157 Milan, Italy
| | - Cosmin Lucian Ciubotariu
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
- Department of Biomedical Sciences and Clinics, Università degli Studi di Milano, 20157 Milan, Italy
| | - Andrea Giacomelli
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
| | - Miriam Galimberti
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
- Department of Biomedical Sciences and Clinics, Università degli Studi di Milano, 20157 Milan, Italy
| | - Martina Zacheo
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
- Department of Biomedical Sciences and Clinics, Università degli Studi di Milano, 20157 Milan, Italy
| | - Andrea Rabbione
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
- Department of Biomedical Sciences and Clinics, Università degli Studi di Milano, 20157 Milan, Italy
| | - Margherita Pieruzzi
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
- Department of Biomedical Sciences and Clinics, Università degli Studi di Milano, 20157 Milan, Italy
| | - Letizia Oreni
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
| | - Laura Galimberti
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
| | - Riccardo Colombo
- Intensive Care Unit, ASST Fatebenefratelli Sacco, 20157 Milan, Italy;
| | - Giuliano Rizzardini
- I Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy;
| | - Cristina Pagani
- Clinical Microbiology, Virology and Bioemergency, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (C.P.); (S.G.R.)
| | - Sara Giordana Rimoldi
- Clinical Microbiology, Virology and Bioemergency, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (C.P.); (S.G.R.)
| | - Cecilia Bonazzetti
- Infectious Diseases Unit IRCCS, Policlinico Sant’Orsola, Department Medical Surgical Science, University of Bologna, 40138 Bologna, Italy;
| | - Anna Lisa Ridolfo
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
| | - Spinello Antinori
- III Division of Infectious Diseases, Luigi Sacco Hospital, ASST Fatebenefratelli Sacco, 20157 Milan, Italy; (G.P.); (G.C.); (C.L.C.); (M.G.); (M.Z.); (A.R.); (M.P.); (L.O.); (L.G.); (A.L.R.); (S.A.)
- Department of Biomedical Sciences and Clinics, Università degli Studi di Milano, 20157 Milan, Italy
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7
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Misra G, Manzoor A, Chopra M, Upadhyay A, Katiyar A, Bhushan B, Anvikar A. Genomic epidemiology of SARS-CoV-2 from Uttar Pradesh, India. Sci Rep 2023; 13:14847. [PMID: 37684328 PMCID: PMC10491582 DOI: 10.1038/s41598-023-42065-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 09/05/2023] [Indexed: 09/10/2023] Open
Abstract
The various strains and mutations of SARS-CoV-2 have been tracked using several forms of genomic classification systems. The present study reports high-throughput sequencing and analysis of 99 SARS-CoV-2 specimens from Western Uttar Pradesh using sequences obtained from the GISAID database, followed by phylogeny and clade classification. Phylogenetic analysis revealed that Omicron lineages BA-2-like (55.55%) followed by Delta lineage-B.1.617.2 (45.5%) were predominantly circulating in this area Signature substitution at positions S: N501Y, S: D614G, S: T478K, S: K417N, S: E484A, S: P681H, and S: S477N were commonly detected in the Omicron variant-BA-2-like, however S: D614G, S: L452R, S: P681R and S: D950N were confined to Delta variant-B.1.617.2. We have also identified three escape variants in the S gene at codon position 19 (T19I/R), 484 (E484A/Q), and 681 (P681R/H) during the fourth and fifth waves in India. Based on the phylogenetic diversification studies and similar changes in other lineages, our analysis revealed indications of convergent evolution as the virus adjusts to the shifting immunological profile of its human host. To the best of our knowledge, this study is an approach to comprehensively map the circulating SARS-CoV-2 strains from Western Uttar Pradesh using an integrated approach of whole genome sequencing and phylogenetic analysis. These findings will be extremely valuable in developing a structured approach toward pandemic preparedness and evidence-based intervention plans in the future.
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Affiliation(s)
- Gauri Misra
- Molecular Diagnostics and COVID-19 Kit Testing Laboratory, National Institute of Biologicals (Ministry of Health and Family Welfare), A-32, Sector-62, Institutional Area, Noida, UP, 201309, India.
| | - Ashrat Manzoor
- Molecular Diagnostics and COVID-19 Kit Testing Laboratory, National Institute of Biologicals (Ministry of Health and Family Welfare), A-32, Sector-62, Institutional Area, Noida, UP, 201309, India
| | - Meenu Chopra
- National Dairy Research Institute, Karnal, Haryana, India
| | - Archana Upadhyay
- Molecular Diagnostics and COVID-19 Kit Testing Laboratory, National Institute of Biologicals (Ministry of Health and Family Welfare), A-32, Sector-62, Institutional Area, Noida, UP, 201309, India
| | - Amit Katiyar
- Bioinformatics Facility, Centralized Core Research Facility, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Brij Bhushan
- Molecular Diagnostics and COVID-19 Kit Testing Laboratory, National Institute of Biologicals (Ministry of Health and Family Welfare), A-32, Sector-62, Institutional Area, Noida, UP, 201309, India
| | - Anup Anvikar
- Molecular Diagnostics and COVID-19 Kit Testing Laboratory, National Institute of Biologicals (Ministry of Health and Family Welfare), A-32, Sector-62, Institutional Area, Noida, UP, 201309, India
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8
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Justo Arevalo S, Uribe Calampa CS, Jimenez Silva C, Quiñones Aguilar M, Bouckaert R, Rebello Pinho JR. Phylodynamic of SARS-CoV-2 during the second wave of COVID-19 in Peru. Nat Commun 2023; 14:3557. [PMID: 37322028 PMCID: PMC10272135 DOI: 10.1038/s41467-023-39216-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 06/02/2023] [Indexed: 06/17/2023] Open
Abstract
At over 0.6% of the population, Peru has one of the highest SARS-CoV-2 mortality rate in the world. Much effort to sequence genomes has been done in this country since mid-2020. However, an adequate analysis of the dynamics of the variants of concern and interest (VOCIs) is missing. We investigated the dynamics of the COVID-19 pandemic in Peru with a focus on the second wave, which had the greatest case fatality rate. The second wave in Peru was dominated by Lambda and Gamma. Analysis of the origin of Lambda shows that it most likely emerged in Peru before the second wave (June-November, 2020). After its emergence it reached Argentina and Chile from Peru where it was locally transmitted. During the second wave in Peru, we identify the coexistence of two Lambda and three Gamma sublineages. Lambda sublineages emerged in the center of Peru whereas the Gamma sublineages more likely originated in the north-east and mid-east. Importantly, it is observed that the center of Peru played a prominent role in transmitting SARS-CoV-2 to other regions within Peru.
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Affiliation(s)
- Santiago Justo Arevalo
- Facultad de Ciencias Biológicas, Universidad Ricardo Palma, Lima, Peru.
- Laboratório Clínico do Hospital Israelita Albert Einstein, São Paulo, Brasil.
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brasil.
| | | | | | | | - Remco Bouckaert
- School of Computer Science, University of Auckland, Auckland, New Zealand
| | - Joao Renato Rebello Pinho
- Laboratório Clínico do Hospital Israelita Albert Einstein, São Paulo, Brasil
- LIM03/07, Department of Gastroenterology and Pathology, University of São Paulo School of Medicine, São Paulo, Brazil
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9
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Niveditha D, Khan S, Khilari A, Nadkarni S, Bhalerao U, Kadam P, Yadav R, Kanekar JB, Shah N, Likhitkar B, Sawant R, Thakur S, Tupekar M, Nagar D, Rao AG, Jagtap R, Jogi S, Belekar M, Pathak M, Shah P, Ranade S, Phadke N, Das R, Joshi S, Karyakarte R, Ghose A, Kadoo N, Shashidhara LS, Monteiro JM, Shanmugam D, Raghunathan A, Karmodiya K. A tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India. J Infect Public Health 2023; 16:1290-1300. [PMID: 37331277 DOI: 10.1016/j.jiph.2023.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 05/30/2023] [Accepted: 06/06/2023] [Indexed: 06/20/2023] Open
Abstract
BACKGROUND Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data. METHODS A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a "band of five" outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5). RESULTS The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. CONCLUSIONS The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.
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Affiliation(s)
- Divya Niveditha
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Soumen Khan
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Ajinkya Khilari
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Sanica Nadkarni
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Unnati Bhalerao
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Pradnya Kadam
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Ritu Yadav
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Jugal B Kanekar
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Nikita Shah
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Bhagyashree Likhitkar
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Rutuja Sawant
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Shikha Thakur
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Manisha Tupekar
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Dhriti Nagar
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Anjani G Rao
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Rutuja Jagtap
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Shraddha Jogi
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Madhuri Belekar
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Maitreyee Pathak
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Priyanki Shah
- The Pune Knowledge Cluster (PKC), Savitribai Phule Pune University, Ganeshkhind Road, 411007 Pune, India
| | | | - Nikhil Phadke
- GenePath Diagnostics India Private Limited, Pune 411004, India
| | - Rashmita Das
- Byramjee Jeejeebhoy Government Medical College (BJGMC), Jai Prakash Narayan Road, Pune 411001, India
| | - Suvarna Joshi
- Byramjee Jeejeebhoy Government Medical College (BJGMC), Jai Prakash Narayan Road, Pune 411001, India
| | - Rajesh Karyakarte
- Byramjee Jeejeebhoy Government Medical College (BJGMC), Jai Prakash Narayan Road, Pune 411001, India
| | - Aurnab Ghose
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Narendra Kadoo
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - L S Shashidhara
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India; The Pune Knowledge Cluster (PKC), Savitribai Phule Pune University, Ganeshkhind Road, 411007 Pune, India
| | - Joy Merwin Monteiro
- Department of Earth and Climate Science, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India; Department of Data Science, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Dhanasekaran Shanmugam
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Anu Raghunathan
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India.
| | - Krishanpal Karmodiya
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India.
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Distribution and Current State of Molecular Genetic Characterization in Pathogenic Free-Living Amoebae. Pathogens 2022; 11:pathogens11101199. [PMID: 36297255 PMCID: PMC9612019 DOI: 10.3390/pathogens11101199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 10/03/2022] [Accepted: 10/15/2022] [Indexed: 11/17/2022] Open
Abstract
Free-living amoebae (FLA) are protozoa widely distributed in the environment, found in a great diversity of terrestrial biomes. Some genera of FLA are linked to human infections. The genus Acanthamoeba is currently classified into 23 genotypes (T1-T23), and of these some (T1, T2, T4, T5, T10, T12, and T18) are known to be capable of causing granulomatous amoebic encephalitis (GAE) mainly in immunocompromised patients while other genotypes (T2, T3, T4, T5, T6, T10, T11, T12, and T15) cause Acanthamoeba keratitis mainly in otherwise healthy patients. Meanwhile, Naegleria fowleri is the causative agent of an acute infection called primary amoebic meningoencephalitis (PAM), while Balamuthia mandrillaris, like some Acanthamoeba genotypes, causes GAE, differing from the latter in the description of numerous cases in patients immunocompetent. Finally, other FLA related to the pathologies mentioned above have been reported; Sappinia sp. is responsible for one case of amoebic encephalitis; Vermamoeba vermiformis has been found in cases of ocular damage, and its extraordinary capacity as endocytobiont for microorganisms of public health importance such as Legionella pneumophila, Bacillus anthracis, and Pseudomonas aeruginosa, among others. This review addressed issues related to epidemiology, updating their geographic distribution and cases reported in recent years for pathogenic FLA.
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11
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Mathaha T, Mafu M, Mabikwa OV, Ndenda J, Hillhouse G, Mellado B. Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa. Front Artif Intell 2022; 5:1013010. [PMID: 36311551 PMCID: PMC9606810 DOI: 10.3389/frai.2022.1013010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 08/24/2022] [Indexed: 11/26/2022] Open
Abstract
The outbreak of coronavirus in the year 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prompted widespread illness, death, and extended economic devastation worldwide. In response, numerous countries, including Botswana and South Africa, instituted various clinical public health (CPH) strategies to mitigate and control the disease. However, the emergence of variants of concern (VOC), vaccine hesitancy, morbidity, inadequate and inequitable vaccine supply, and ineffective vaccine roll-out strategies caused continuous disruption of essential services. Based on Botswana and South Africa hospitalization and mortality data, we studied the impact of age and gender on disease severity. Comparative analysis was performed between the two countries to establish a vaccination strategy that could complement the existing CPH strategies. To optimize the vaccination roll-out strategy, artificial intelligence was used to identify the population groups in need of insufficient vaccines. We found that COVID-19 was associated with several comorbidities. However, hypertension and diabetes were more severe and common in both countries. The elderly population aged ≥60 years had 70% of major COVID-19 comorbidities; thus, they should be prioritized for vaccination. Moreover, we found that the Botswana and South Africa populations had similar COVID-19 mortality rates. Hence, our findings should be extended to the rest of Southern African countries since the population in this region have similar demographic and disease characteristics.
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Affiliation(s)
- Thuso Mathaha
- School of Physics and Institute for Collider Particle Physics, University of the Witwatersrand, Johannesburg, South Africa,*Correspondence: Thuso Mathaha
| | - Mhlambululi Mafu
- Department of Physics, Case Western Reserve University, Cleveland, OH, United States
| | - Onkabetse V. Mabikwa
- Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, Botswana
| | - Joseph Ndenda
- Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, Botswana
| | - Gregory Hillhouse
- Department of Physics and Astronomy, Botswana International University of Science and Technology, Palapye, Botswana
| | - Bruce Mellado
- School of Physics and Institute for Collider Particle Physics, University of the Witwatersrand, Johannesburg, South Africa,iThemba LABS, National Research Foundation, Somerset West, South Africa
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