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Ghosh R, Gutierrez JP, de Jesús Ascencio-Montiel I, Juárez-Flores A, Bertozzi SM. SARS-CoV-2 infection by trimester of pregnancy and adverse perinatal outcomes: a Mexican retrospective cohort study. BMJ Open 2024; 14:e075928. [PMID: 38604636 PMCID: PMC11015228 DOI: 10.1136/bmjopen-2023-075928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 03/04/2024] [Indexed: 04/13/2024] Open
Abstract
OBJECTIVE Conflicting evidence for the association between COVID-19 and adverse perinatal outcomes exists. This study examined the associations between maternal COVID-19 during pregnancy and adverse perinatal outcomes including preterm birth (PTB), low birth weight (LBW), small-for-gestational age (SGA), large-for-gestational age (LGA) and fetal death; as well as whether the associations differ by trimester of infection. DESIGN AND SETTING The study used a retrospective Mexican birth cohort from the Instituto Mexicano del Seguro Social (IMSS), Mexico, between January 2020 and November 2021. PARTICIPANTS We used the social security administrative dataset from IMSS that had COVID-19 information and linked it with the IMSS routine hospitalisation dataset, to identify deliveries in the study period with a test for SARS-CoV-2 during pregnancy. OUTCOME MEASURES PTB, LBW, SGA, LGA and fetal death. We used targeted maximum likelihood estimators, to quantify associations (risk ratio, RR) and CIs. We fit models for the overall COVID-19 sample, and separately for those with mild or severe disease, and by trimester of infection. Additionally, we investigated potential bias induced by missing non-tested pregnancies. RESULTS The overall sample comprised 17 340 singleton pregnancies, of which 30% tested positive. We found that those with mild COVID-19 had an RR of 0.89 (95% CI 0.80 to 0.99) for PTB and those with severe COVID-19 had an RR of 1.53 (95% CI 1.07 to 2.19) for LGA. COVID-19 in the first trimester was associated with fetal death, RR=2.36 (95% CI 1.04, 5.36). Results also demonstrate that missing non-tested pregnancies might induce bias in the associations. CONCLUSIONS In the overall sample, there was no evidence of an association between COVID-19 and adverse perinatal outcomes. However, the findings suggest that severe COVID-19 may increase the risk of some perinatal outcomes, with the first trimester potentially being a high-risk period.
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Affiliation(s)
- Rakesh Ghosh
- Institute for Global Health Sciences, University of California San Francisco, San Francisco, California, USA
- School of Public Health, University of California Berkeley, Berkeley, California, USA
| | - Juan Pablo Gutierrez
- Center for Policy, Population & Health Research, National Autonomous University of Mexico, Mexico City, Mexico
| | | | - Arturo Juárez-Flores
- Center for Policy, Population & Health Research, National Autonomous University of Mexico, Mexico City, Mexico
| | - Stefano M Bertozzi
- School of Public Health, University of California Berkeley, Berkeley, California, USA
- University of Washington - Seattle Campus, Seattle, Washington, USA
- National Institute of Public Health, Cuernavaca, Mexico
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Gutierrez JP, Olaiz G, Juárez-Flores A, Borja-Aburto VH, Ascencio-Montiel IJ, Bertozzi SM. How predictive of SARS-CoV-2 infection are clinical characteristics at presentation among individuals with COVID-like symptoms treated at the Mexican Institute of Social Security. PLoS One 2023; 18:e0296320. [PMID: 38128048 PMCID: PMC10735012 DOI: 10.1371/journal.pone.0296320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 12/08/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND The COVID-19 pandemic has progressed rapidly, with the emergence of new virus variants that pose challenges in treating infected individuals. In Mexico, four epidemic waves have been recorded with varying disease severity. To understand the heterogeneity in clinical presentation over time and the sensitivity and specificity of signs and symptoms in identifying COVID-19 cases, an analysis of the changes in the clinical presentation of the disease was conducted. AIM To analyze the changes in the clinical presentation of COVID-19 among 3.38 million individuals tested for SARS-CoV-2 at the Mexican Social Security Institute (IMSS) from March 2020 to October 2021 and evaluate the predictivity of signs and symptoms in identifying COVID-19 cases. METHODS A retrospective analysis of clinical presentation patterns of COVID-19 among individuals treated at IMSS was performed, contrasting the signs and symptoms among SARS-CoV-2-positive individuals with those who tested negative for the virus but had respiratory infection symptoms. The sensitivity and specificity of each sign and symptom in identifying SARS-CoV-2 infection were estimated. RESULTS The set of signs and symptoms reported for COVID-19-suspected patients treated at IMSS were not highly specific for SARS-CoV-2 positivity. The signs and symptoms exhibited variability based on age and epidemic wave. The area under the receiver operating characteristic (ROC) curve was 0.62 when grouping the five main symptoms (headache, dyspnea, fever, arthralgia, and cough). Most of the individual symptoms had ROC values close to 0.5 (16 out of 22 between 0.48 and 0.52), indicating non-specificity. CONCLUSIONS The results highlight the difficulty in making a clinical diagnosis of COVID-19 due to the lack of specificity of signs and symptoms. The variability of clinical presentation over time and among age groups highlights the need for further research to differentiate whether the changes are due to changes in the virus, who is becoming infected, or the population, particularly with respect to prior infection and vaccination status.
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Affiliation(s)
- Juan Pablo Gutierrez
- Center for Policy, Population and Health Research, School of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Gustavo Olaiz
- Center for Policy, Population and Health Research, School of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Arturo Juárez-Flores
- Center for Policy, Population and Health Research, School of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Víctor H. Borja-Aburto
- Education and Research Unit, Mexican Institute of Social Security, Benito Juarez, Mexico City, Mexico
| | - Iván J. Ascencio-Montiel
- Coordination of Epidemiological Surveillance, Mexican Institute of Social Security, Benito Juarez, Mexico City, Mexico
| | - Stefano M. Bertozzi
- University of California, Berkeley, California, United States of America
- University of Washington, Seattle, Washington, United States of America
- National Institute of Public Health, Mexico (INSP), Cuernavaca, Mexico
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Nielsen BF, Saad-Roy CM, Li Y, Sneppen K, Simonsen L, Viboud C, Levin SA, Grenfell BT. Host heterogeneity and epistasis explain punctuated evolution of SARS-CoV-2. PLoS Comput Biol 2023; 19:e1010896. [PMID: 36791146 PMCID: PMC9974118 DOI: 10.1371/journal.pcbi.1010896] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 02/28/2023] [Accepted: 01/25/2023] [Indexed: 02/16/2023] Open
Abstract
Identifying drivers of viral diversity is key to understanding the evolutionary as well as epidemiological dynamics of the COVID-19 pandemic. Using rich viral genomic data sets, we show that periods of steadily rising diversity have been punctuated by sudden, enormous increases followed by similarly abrupt collapses of diversity. We introduce a mechanistic model of saltational evolution with epistasis and demonstrate that these features parsimoniously account for the observed temporal dynamics of inter-genomic diversity. Our results provide support for recent proposals that saltational evolution may be a signature feature of SARS-CoV-2, allowing the pathogen to more readily evolve highly transmissible variants. These findings lend theoretical support to a heightened awareness of biological contexts where increased diversification may occur. They also underline the power of pathogen genomics and other surveillance streams in clarifying the phylodynamics of emerging and endemic infections. In public health terms, our results further underline the importance of equitable distribution of up-to-date vaccines.
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Affiliation(s)
- Bjarke Frost Nielsen
- Department of Science and Environment, Roskilde University, Roskilde, Denmark
- Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
- * E-mail:
| | - Chadi M. Saad-Roy
- Department of Integrative Biology, University of California, Berkeley, California, United States of America
- Miller Institute for Basic Research in Science, University of California, Berkeley, California, United States of America
| | - Yimei Li
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Kim Sneppen
- Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
| | - Lone Simonsen
- Department of Science and Environment, Roskilde University, Roskilde, Denmark
| | - Cécile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Simon A. Levin
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Bryan T. Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
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Gallego-García P, Varela N, Estévez-Gómez N, De Chiara L, Fernández-Silva I, Valverde D, Sapoval N, Treangen TJ, Regueiro B, Cabrera-Alvargonzález JJ, del Campo V, Pérez S, Posada D. OUP accepted manuscript. Virus Evol 2022; 8:veac008. [PMID: 35242361 PMCID: PMC8889950 DOI: 10.1093/ve/veac008] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 12/21/2021] [Accepted: 02/04/2022] [Indexed: 11/23/2022] Open
Abstract
A detailed understanding of how and when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced forty-nine SARS-CoV-2 patient samples from ten local clusters in NW Spain for which partial epidemiological information was available and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be one to two viral particles for sample pairs whose donor–recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.
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Affiliation(s)
| | - Nair Varela
- CINBIO, Universidade de Vigo, Vigo 36310, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
| | - Nuria Estévez-Gómez
- CINBIO, Universidade de Vigo, Vigo 36310, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
| | - Loretta De Chiara
- CINBIO, Universidade de Vigo, Vigo 36310, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
| | - Iria Fernández-Silva
- Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo, Vigo 36310, Spain
| | - Diana Valverde
- CINBIO, Universidade de Vigo, Vigo 36310, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
- Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo, Vigo 36310, Spain
| | | | | | - Benito Regueiro
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
- Department of Microbiology, Complexo Hospitalario Universitario de Vigo (CHUVI), Sergas, Vigo 36213, Spain
- Microbiology and Parasitology Department, Medicine and Odontology, Universidade de Santiago, Santiago de Compostela 15782, Spain
| | - Jorge Julio Cabrera-Alvargonzález
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
- Department of Microbiology, Complexo Hospitalario Universitario de Vigo (CHUVI), Sergas, Vigo 36213, Spain
| | - Víctor del Campo
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
- Department of Preventive Medicine, Complexo Hospitalario Universitario de Vigo (CHUVI), Sergas, Vigo 36213, Spain
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Bertsimas D, Borenstein A, Mingardi L, Nohadani O, Orfanoudaki A, Stellato B, Wiberg H, Sarin P, Varelmann DJ, Estrada V, Macaya C, Gil IJN. Personalized prescription of ACEI/ARBs for hypertensive COVID-19 patients. Health Care Manag Sci 2021; 24:339-355. [PMID: 33721153 PMCID: PMC7958102 DOI: 10.1007/s10729-021-09545-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 01/22/2021] [Indexed: 12/15/2022]
Abstract
The COVID-19 pandemic has prompted an international effort to develop and repurpose medications and procedures to effectively combat the disease. Several groups have focused on the potential treatment utility of angiotensin-converting-enzyme inhibitors (ACEIs) and angiotensin-receptor blockers (ARBs) for hypertensive COVID-19 patients, with inconclusive evidence thus far. We couple electronic medical record (EMR) and registry data of 3,643 patients from Spain, Italy, Germany, Ecuador, and the US with a machine learning framework to personalize the prescription of ACEIs and ARBs to hypertensive COVID-19 patients. Our approach leverages clinical and demographic information to identify hospitalized individuals whose probability of mortality or morbidity can decrease by prescribing this class of drugs. In particular, the algorithm proposes increasing ACEI/ARBs prescriptions for patients with cardiovascular disease and decreasing prescriptions for those with low oxygen saturation at admission. We show that personalized recommendations can improve patient outcomes by 1.0% compared to the standard of care when applied to external populations. We develop an interactive interface for our algorithm, providing physicians with an actionable tool to easily assess treatment alternatives and inform clinical decisions. This work offers the first personalized recommendation system to accurately evaluate the efficacy and risks of prescribing ACEIs and ARBs to hypertensive COVID-19 patients.
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Affiliation(s)
- Dimitris Bertsimas
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA.
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
| | - Alison Borenstein
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Luca Mingardi
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Omid Nohadani
- Benefits Science Technologies, Boston, MA, 02110, USA
| | - Agni Orfanoudaki
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Bartolomeo Stellato
- Operations Research and Financial Engineering, Princeton University, Princeton, NJ, 08544, USA
| | - Holly Wiberg
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Pankaj Sarin
- Brigham and Women's Hospital, Boston, MA, 02115, USA
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6
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Saad-Roy CM, Wagner CE, Baker RE, Morris SE, Farrar J, Graham AL, Levin SA, Mina MJ, Metcalf CJE, Grenfell BT. Immune life history, vaccination, and the dynamics of SARS-CoV-2 over the next 5 years. Science 2020; 370:811-818. [PMID: 32958581 PMCID: PMC7857410 DOI: 10.1126/science.abd7343] [Citation(s) in RCA: 148] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 09/16/2020] [Indexed: 01/08/2023]
Abstract
The future trajectory of the coronavirus disease 2019 (COVID-19) pandemic hinges on the dynamics of adaptive immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); however, salient features of the immune response elicited by natural infection or vaccination are still uncertain. We use simple epidemiological models to explore estimates for the magnitude and timing of future COVID-19 cases, given different assumptions regarding the protective efficacy and duration of the adaptive immune response to SARS-CoV-2, as well as its interaction with vaccines and nonpharmaceutical interventions. We find that variations in the immune response to primary SARS-CoV-2 infections and a potential vaccine can lead to markedly different immune landscapes and burdens of critically severe cases, ranging from sustained epidemics to near elimination. Our findings illustrate likely complexities in future COVID-19 dynamics and highlight the importance of immunological characterization beyond the measurement of active infections for adequately projecting the immune landscape generated by SARS-CoV-2 infections.
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Affiliation(s)
- Chadi M Saad-Roy
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA
| | - Caroline E Wagner
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Princeton Environmental Institute, Princeton University, Princeton, NJ 08544, USA
- Department of Bioengineering, McGill University, Montreal, Quebec H3A 0C3, Canada
| | - Rachel E Baker
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Princeton Environmental Institute, Princeton University, Princeton, NJ 08544, USA
| | - Sinead E Morris
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032, USA
| | | | - Andrea L Graham
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Simon A Levin
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Michael J Mina
- Departments of Epidemiology and Immunology and Infectious Diseases, Harvard School of Public Health, Boston, MA 02115, USA
| | - C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Princeton School of Public and International Affairs, Princeton University, Princeton, NJ 08544, USA
| | - Bryan T Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.
- Princeton School of Public and International Affairs, Princeton University, Princeton, NJ 08544, USA
- Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA
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