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Perofsky AC, Hansen CL, Burstein R, Boyle S, Prentice R, Marshall C, Reinhart D, Capodanno B, Truong M, Schwabe-Fry K, Kuchta K, Pfau B, Acker Z, Lee J, Sibley TR, McDermot E, Rodriguez-Salas L, Stone J, Gamboa L, Han PD, Adler A, Waghmare A, Jackson ML, Famulare M, Shendure J, Bedford T, Chu HY, Englund JA, Starita LM, Viboud C. Impacts of human mobility on the citywide transmission dynamics of 18 respiratory viruses in pre- and post-COVID-19 pandemic years. Nat Commun 2024; 15:4164. [PMID: 38755171 PMCID: PMC11098821 DOI: 10.1038/s41467-024-48528-2] [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: 12/11/2023] [Accepted: 05/02/2024] [Indexed: 05/18/2024] Open
Abstract
Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.
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Affiliation(s)
- Amanda C Perofsky
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
| | - Chelsea L Hansen
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
- PandemiX Center, Department of Science & Environment, Roskilde University, Roskilde, Denmark
| | - Roy Burstein
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Shanda Boyle
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Robin Prentice
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Cooper Marshall
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - David Reinhart
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Ben Capodanno
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Melissa Truong
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Kristen Schwabe-Fry
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Kayla Kuchta
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Brian Pfau
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Zack Acker
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Jover Lee
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Thomas R Sibley
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Evan McDermot
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Leslie Rodriguez-Salas
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Jeremy Stone
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Luis Gamboa
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Peter D Han
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Amanda Adler
- Seattle Children's Research Institute, Seattle, WA, USA
| | - Alpana Waghmare
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | | | - Michael Famulare
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Janet A Englund
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Lea M Starita
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
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Hunter PR, Brainard J. Changing risk factors for developing SARS-CoV-2 infection from Delta to Omicron. PLoS One 2024; 19:e0299714. [PMID: 38748651 PMCID: PMC11095668 DOI: 10.1371/journal.pone.0299714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 02/14/2024] [Indexed: 05/19/2024] Open
Abstract
BACKGROUND One of the few studies to estimate infection risk with SARS-CoV-2 in the general population was the UK Office of National Statistics Infection Survey. This survey provided data that allowed us to describe and interpret apparent risk factors for testing positive for SARS-CoV-2 in a period when variants and COVID-19 controls experienced large changes. METHOD The ONS published estimates of likelihood of individuals testing positive in two week monitoring periods between 21st November 2021 and 7th May 2022, relating this positivity to social and behavioural factors. We applied meta-regression to these estimates of likelihood of testing positive to determine whether the monitored potential risk factors remained constant during the pandemic. RESULTS Some risk factors had consistent relationship with risk of infection (always protective or always linked to higher risk, throughout monitoring period). Other risk factors had variable relationship with risk of infection, with changes seeming to especially correlate with the emergence of Omicron BA.2 dominance. These variable factors were mask-wearing habits, history of foreign travel, household size, working status (retired or not) and contact with children or persons age over 70. CONCLUSION Relevance of some risk factors to likelihood of testing positive for SARS-CoV-2 may relate to reinfection risk, variant infectiousness and status of social distancing regulations.
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Affiliation(s)
- Paul R. Hunter
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Julii Brainard
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
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Rhoden J, Hoffmann AT, Stein JF, Rocha BSD, Barros VMD, Silva EVD, Fleck JD, Rigotto C. Viral coinfection in hospitalized patients during the COVID-19 pandemic in Southern Brazil: a retrospective cohort study. Respir Res 2024; 25:71. [PMID: 38317218 PMCID: PMC10840208 DOI: 10.1186/s12931-024-02708-2] [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: 12/18/2023] [Accepted: 01/25/2024] [Indexed: 02/07/2024] Open
Abstract
PURPOSE Since the worldwide spread of SARS-CoV-2, different strategies have been followed to combat the pandemic and limit virus transmission. In the meantime, other respiratory viruses continued to circulate, though at decreased rates. METHODS This study was conducted between June and July 2022, in a hospital in the metropolitan region of Rio Grande do Sul state, in the southernmost state of Brazil. The 337 hospitalized patients included those with respiratory symptoms without delimitation of age. Reverse transcription-quantitative real-time polymerase chain reaction detected 15 different respiratory viruses and confirmed coinfections in the samples. Different statistical tests were applied to evaluate the association between associations of clinical characteristics and coinfection. RESULTS Sampling corresponds to 337 selected and 330 patients analyzed. The principal clinical outcome found was hospital discharge in 309 (94%) cases, while 21 (6%) resulted in death. The principal viral agents related to coinfections were Human rhinovirus, Human enterovirus, and Respiratory syncytial virus. The most frequent viral agent detected was SARS-CoV-2, with 60 (18%) infections, followed by 51 (15%) cases of Respiratory syncytial virus B (15%) and 44 (13%) cases of Human rhinovirus 1. Coinfection was mainly observed in children, while adults and the elderly were more affected by a single infection. Analyzing COVID-19 vaccination, 175 (53%) were unvaccinated while the remainder had at least one dose of the vaccine. CONCLUSIONS This study presents information to update the understanding of viral circulation in the region. Furthermore, the findings clarify the behavior of viral infections and possible coinfections in hospitalized patients, considering different ages and clinical profiles. In addition, this knowledge can help to monitor the population's clinical manifestations and prevent future outbreaks of respiratory viruses.
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Affiliation(s)
- Jaqueline Rhoden
- Laboratório de Microbiologia Molecular, Universidade Feevale, Rodovia ERS-239, N◦ 2755, Prédio Vermelho, Piso 1, Sala 103, Vila Nova, Novo Hamburgo, Rio Grande Do Sul, CEP 93525-075, Brazil.
- Santa Casa de Misericórdia de Porto Alegre, Hospital Dom Vicente Scherer, Centro Histórico, Av. Independência, Nº 155, Porto Alegre, Rio Grande Do Sul, CEP 90035- 074, Brazil.
| | - Andressa Taíz Hoffmann
- Santa Casa de Misericórdia de Porto Alegre, Hospital Dom Vicente Scherer, Centro Histórico, Av. Independência, Nº 155, Porto Alegre, Rio Grande Do Sul, CEP 90035- 074, Brazil
| | - Janaína Franciele Stein
- Laboratório de Microbiologia Molecular, Universidade Feevale, Rodovia ERS-239, N◦ 2755, Prédio Vermelho, Piso 1, Sala 103, Vila Nova, Novo Hamburgo, Rio Grande Do Sul, CEP 93525-075, Brazil
| | - Bruna Seixas da Rocha
- Laboratório de Microbiologia Molecular, Universidade Feevale, Rodovia ERS-239, N◦ 2755, Prédio Vermelho, Piso 1, Sala 103, Vila Nova, Novo Hamburgo, Rio Grande Do Sul, CEP 93525-075, Brazil
| | - Vinícius Monteagudo de Barros
- Laboratório de Microbiologia Molecular, Universidade Feevale, Rodovia ERS-239, N◦ 2755, Prédio Vermelho, Piso 1, Sala 103, Vila Nova, Novo Hamburgo, Rio Grande Do Sul, CEP 93525-075, Brazil
| | - Eduardo Viegas da Silva
- Centro Estadual de Vigilância em Saúde do Rio Grande Do Sul, Av. Ipiranga, 5400, Jardim Botânico, Porto Alegre, Rio Grande Do Sul, CEP 90450-190, Brazil
| | - Juliane Deise Fleck
- Laboratório de Microbiologia Molecular, Universidade Feevale, Rodovia ERS-239, N◦ 2755, Prédio Vermelho, Piso 1, Sala 103, Vila Nova, Novo Hamburgo, Rio Grande Do Sul, CEP 93525-075, Brazil
| | - Caroline Rigotto
- Laboratório de Microbiologia Molecular, Universidade Feevale, Rodovia ERS-239, N◦ 2755, Prédio Vermelho, Piso 1, Sala 103, Vila Nova, Novo Hamburgo, Rio Grande Do Sul, CEP 93525-075, Brazil
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Tseng YJ, Olson KL, Bloch D, Mandl KD. Smart Thermometer-Based Participatory Surveillance to Discern the Role of Children in Household Viral Transmission During the COVID-19 Pandemic. JAMA Netw Open 2023; 6:e2316190. [PMID: 37261828 PMCID: PMC10236238 DOI: 10.1001/jamanetworkopen.2023.16190] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 04/18/2023] [Indexed: 06/02/2023] Open
Abstract
Importance Children's role in spreading virus during the COVID-19 pandemic is yet to be elucidated, and measuring household transmission traditionally requires contact tracing. Objective To discern children's role in household viral transmission during the pandemic when enveloped viruses were at historic lows and the predominance of viral illnesses were attributed to COVID-19. Design, Setting, and Participants This cohort study of a voluntary US cohort tracked data from participatory surveillance using commercially available thermometers with a companion smartphone app from October 2019 to October 2022. Eligible participants were individuals with temperature measurements in households with multiple members between October 2019 and October 2022 who opted into data sharing. Main Outcomes and Measures Proportion of household transmissions with a pediatric index case and changes in transmissions during school breaks were assessed using app and thermometer data. Results A total of 862 577 individuals from 320 073 households with multiple participants (462 000 female [53.6%] and 463 368 adults [53.7%]) were included. The number of febrile episodes forecast new COVID-19 cases. Within-household transmission was inferred in 54 506 (15.4%) febrile episodes and increased from the fourth pandemic period, March to July 2021 (3263 of 32 294 [10.1%]) to the Omicron BA.1/BA.2 wave (16 516 of 94 316 [17.5%]; P < .001). Among 38 787 transmissions in 166 170 households with adults and children, a median (IQR) 70.4% (61.4%-77.6%) had a pediatric index case; proportions fluctuated weekly from 36.9% to 84.6%. A pediatric index case was 0.6 to 0.8 times less frequent during typical school breaks. The winter break decrease was from 68.4% (95% CI, 57.1%-77.8%) to 41.7% (95% CI, 34.3%-49.5%) at the end of 2020 (P < .001). At the beginning of 2022, it dropped from 80.3% (95% CI, 75.1%-84.6%) to 54.5% (95% CI, 51.3%-57.7%) (P < .001). During summer breaks, rates dropped from 81.4% (95% CI, 74.0%-87.1%) to 62.5% (95% CI, 56.3%-68.3%) by August 2021 (P = .02) and from 83.8% (95% CI, 79.2%-87.5) to 62.8% (95% CI, 57.1%-68.1%) by July 2022 (P < .001). These patterns persisted over 2 school years. Conclusions and Relevance In this cohort study using participatory surveillance to measure within-household transmission at a national scale, we discerned an important role for children in the spread of viral infection within households during the COVID-19 pandemic, heightened when schools were in session, supporting a role for school attendance in COVID-19 spread.
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Affiliation(s)
- Yi-Ju Tseng
- Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts
- Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Karen L. Olson
- Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
| | | | - Kenneth D. Mandl
- Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
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Kurskaya OG, Prokopyeva EA, Sobolev IA, Solomatina MV, Saroyan TA, Dubovitskiy NA, Derko AA, Nokhova AR, Anoshina AV, Leonova NV, Simkina OA, Komissarova TV, Shestopalov AM, Sharshov KA. Changes in the Etiology of Acute Respiratory Infections among Children in Novosibirsk, Russia, between 2019 and 2022: The Impact of the SARS-CoV-2 Virus. Viruses 2023; 15:934. [PMID: 37112913 PMCID: PMC10141072 DOI: 10.3390/v15040934] [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: 02/24/2023] [Revised: 03/27/2023] [Accepted: 04/04/2023] [Indexed: 04/29/2023] Open
Abstract
A wide range of human respiratory viruses are known that may cause acute respiratory infections (ARIs), such as influenza A and B viruses (HIFV), respiratory syncytial virus (HRSV), coronavirus (HCoV), parainfluenza virus (HPIV), metapneumovirus (HMPV), rhinovirus (HRV), adenovirus (HAdV), bocavirus (HBoV), and others. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COronaVIrus Disease (COVID) that lead to pandemic in 2019 and significantly impacted on the circulation of ARIs. The aim of this study was to analyze the changes in the epidemic patterns of common respiratory viruses among children and adolescents hospitalized with ARIs in hospitals in Novosibirsk, Russia, from November 2019 to April 2022. During 2019 and 2022, nasal and throat swabs were taken from a total of 3190 hospitalized patients 0-17 years old for testing for HIFV, HRSV, HCoV, HPIV, HMPV, HRV, HAdV, HBoV, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by real-time PCR. The SARS-CoV-2 virus dramatically influenced the etiology of acute respiratory infections among children and adolescents between 2019 and 2022. We observed dramatic changes in the prevalence of major respiratory viruses over three epidemic research seasons: HIFV, HRSV, and HPIV mainly circulated in 2019-2020; HMPV, HRV, and HCoV dominated in 2020-2021; and HRSV, SARS-CoV-2, HIFV, and HRV were the most numerous agents in 2021-2022. Interesting to note was the absence of HIFV and a significant reduction in HRSV during the 2020-2021 period, while HMPV was absent and there was a significant reduction of HCoV during the following epidemic period in 2021-2022. Viral co-infection was significantly more frequently detected in the 2020-2021 period compared with the other two epidemic seasons. Certain respiratory viruses, HCoV, HPIV, HBoV, HRV, and HAdV, were registered most often in co-infections. This cohort study has revealed that during the pre-pandemic and pandemic periods, there were dramatic fluctuations in common respiratory viruses registered among hospitalized patients 0-17 years old. The most dominant virus in each research period differed: HIFV in 2019-2020, HMPV in 2020-2021, and HRSV in 2021-2022. Virus-virus interaction was found to be possible between SARS-CoV-2 and HRV, HRSV, HAdV, HMPV, and HPIV. An increase in the incidence of COVID-19 was noted only during the third epidemic season (January to March 2022).
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Affiliation(s)
- Olga G. Kurskaya
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
| | - Elena A. Prokopyeva
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
| | - Ivan A. Sobolev
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
| | - Mariya V. Solomatina
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
| | - Tereza A. Saroyan
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
| | - Nikita A. Dubovitskiy
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
| | - Anastasiya A. Derko
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
| | - Alina R. Nokhova
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
| | - Angelika V. Anoshina
- Department of Children’s Diseases, Novosibirsk Children’s Municipal Clinical Hospital No 6, Novosibirsk 630015, Russia
| | - Natalya V. Leonova
- Department of Children’s Diseases, Novosibirsk Children’s Municipal Clinical Hospital No 6, Novosibirsk 630015, Russia
| | - Olga A. Simkina
- Department of Children’s Diseases, Novosibirsk Children’s Municipal Clinical Hospital No 3, Novosibirsk 630040, Russia
| | - Tatyana V. Komissarova
- Department of Children’s Diseases, Novosibirsk Children’s Municipal Clinical Hospital No 3, Novosibirsk 630040, Russia
| | - Alexander M. Shestopalov
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
| | - Kirill A. Sharshov
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Federal Research Center of Fundamental and Translational Medicine, Novosibirsk 630060, Russia
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Racial Disparities and Common Respiratory Infectious Diseases in Children of the United States: A Systematic Review and Meta-Analysis. Diseases 2023; 11:diseases11010023. [PMID: 36810537 PMCID: PMC9944874 DOI: 10.3390/diseases11010023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 01/20/2023] [Accepted: 01/27/2023] [Indexed: 02/05/2023] Open
Abstract
Due to the lack of sufficient data on the relationship between racial disparities and the occurrence of infectious respiratory diseases in children, the aim of this systematic review and meta-analysis is to evaluate the presence of racial gaps in the occurrence of respiratory infectious diseases in children. This study follows the PRISMA flow guidelines for systematic reviews and the standards of meta-analysis for 20 quantitative studies conducted from 2016 to 2022 including 2,184,407 participants. As evidenced from the review, in the U.S., racial disparities are present among children, with Hispanic and Black children carrying the burden of infectious respiratory disease occurrence. Several factors are contributory to these outcomes among Hispanic and Black children, including higher rates of poverty; higher rates of chronic conditions, such as asthma and obesity; and seeking care outside of the home. However, vaccinations can be used to reduce the risk of infection among Black and Hispanic children. Whether a child is very young or a teen, racial disparities are present in occurrence rates of infectious respiratory diseases, with the burden resting among minorities. Therefore, it is important for parents to be aware of the risk of infectious diseases and to be aware of resources, such as vaccines.
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von Bartheld CS, Wang L. Prevalence of Olfactory Dysfunction with the Omicron Variant of SARS-CoV-2: A Systematic Review and Meta-Analysis. Cells 2023; 12:430. [PMID: 36766771 PMCID: PMC9913864 DOI: 10.3390/cells12030430] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 01/19/2023] [Accepted: 01/25/2023] [Indexed: 01/31/2023] Open
Abstract
The omicron variant is thought to cause less olfactory dysfunction than previous variants of SARS-CoV-2, but the reported prevalence differs greatly between populations and studies. Our systematic review and meta-analysis provide information regarding regional differences in prevalence as well as an estimate of the global prevalence of olfactory dysfunction based on 62 studies reporting information on 626,035 patients infected with the omicron variant. Our estimate of the omicron-induced prevalence of olfactory dysfunction in populations of European ancestry is 11.7%, while it is significantly lower in all other populations, ranging between 1.9% and 4.9%. When ethnic differences and population sizes are considered, the global prevalence of omicron-induced olfactory dysfunction in adults is estimated to be 3.7%. Omicron's effect on olfaction is twofold to tenfold lower than that of the alpha or delta variants according to previous meta-analyses and our analysis of studies that directly compared the prevalence of olfactory dysfunction between omicron and previous variants. The profile of the prevalence differences between ethnicities mirrors the results of a recent genome-wide association study that connected a gene locus encoding an odorant-metabolizing enzyme, UDP glycosyltransferase, to the extent of COVID-19-related loss of smell. Our analysis is consistent with the hypothesis that this enzyme contributes to the observed population differences.
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Affiliation(s)
- Christopher S. von Bartheld
- Department of Physiology and Cell Biology, Reno School of Medicine, University of Nevada, Reno, NV 89557-0352, USA
| | - Lingchen Wang
- School of Public Health, University of Nevada, Reno, NV 89557-0275, USA
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