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1.
Lancet Infect Dis ; 23(5): 556-567, 2023 05.
Artículo en Inglés | MEDLINE | ID: covidwho-2184728

RESUMEN

BACKGROUND: The global surge in the omicron (B.1.1.529) variant has resulted in many individuals with hybrid immunity (immunity developed through a combination of SARS-CoV-2 infection and vaccination). We aimed to systematically review the magnitude and duration of the protective effectiveness of previous SARS-CoV-2 infection and hybrid immunity against infection and severe disease caused by the omicron variant. METHODS: For this systematic review and meta-regression, we searched for cohort, cross-sectional, and case-control studies in MEDLINE, Embase, Web of Science, ClinicalTrials.gov, the Cochrane Central Register of Controlled Trials, the WHO COVID-19 database, and Europe PubMed Central from Jan 1, 2020, to June 1, 2022, using keywords related to SARS-CoV-2, reinfection, protective effectiveness, previous infection, presence of antibodies, and hybrid immunity. The main outcomes were the protective effectiveness against reinfection and against hospital admission or severe disease of hybrid immunity, hybrid immunity relative to previous infection alone, hybrid immunity relative to previous vaccination alone, and hybrid immunity relative to hybrid immunity with fewer vaccine doses. Risk of bias was assessed with the Risk of Bias In Non-Randomized Studies of Interventions Tool. We used log-odds random-effects meta-regression to estimate the magnitude of protection at 1-month intervals. This study was registered with PROSPERO (CRD42022318605). FINDINGS: 11 studies reporting the protective effectiveness of previous SARS-CoV-2 infection and 15 studies reporting the protective effectiveness of hybrid immunity were included. For previous infection, there were 97 estimates (27 with a moderate risk of bias and 70 with a serious risk of bias). The effectiveness of previous infection against hospital admission or severe disease was 74·6% (95% CI 63·1-83·5) at 12 months. The effectiveness of previous infection against reinfection waned to 24·7% (95% CI 16·4-35·5) at 12 months. For hybrid immunity, there were 153 estimates (78 with a moderate risk of bias and 75 with a serious risk of bias). The effectiveness of hybrid immunity against hospital admission or severe disease was 97·4% (95% CI 91·4-99·2) at 12 months with primary series vaccination and 95·3% (81·9-98·9) at 6 months with the first booster vaccination after the most recent infection or vaccination. Against reinfection, the effectiveness of hybrid immunity following primary series vaccination waned to 41·8% (95% CI 31·5-52·8) at 12 months, while the effectiveness of hybrid immunity following first booster vaccination waned to 46·5% (36·0-57·3) at 6 months. INTERPRETATION: All estimates of protection waned within months against reinfection but remained high and sustained for hospital admission or severe disease. Individuals with hybrid immunity had the highest magnitude and durability of protection, and as a result might be able to extend the period before booster vaccinations are needed compared to individuals who have never been infected. FUNDING: WHO COVID-19 Solidarity Response Fund and the Coalition for Epidemic Preparedness Innovations.


Asunto(s)
COVID-19 , Humanos , COVID-19/prevención & control , SARS-CoV-2 , Estudios Transversales , Reinfección/prevención & control , Inmunidad Adaptativa
2.
Mueller, Mark, Sharma, Minakshi, Maus, Jeff, Ran, Taiqi, Sabaliauskas, Kelly, Xu, Jielan, Yang, Sabrena, Young, Michael, Toronto Public Health Web Services, Team, Sharma, Minakshi, Cheyne, Jill, Cheyne, Jill, Corallo, Ashley, Bianco, Tracey Dal, Dearing-Vollett, Julia, Liddy, Ann, Pacht, Chloe, Ran, Taiqi, Seto, Marisa, Toronto Public Health Web Services, Team, Young, Michael, Faulkner, Amy, Sharma, Minakshi, Aulicino, Maria, Pach, Beata, McArthur, Allison, Kapetanos, Domna, Skinner, Hannah, Harker, Lindsay, Massarella, Susan, Osborne, Zack, Myers, Michael, Kishibe, Teruko, Thorne, Lydia, Bartlett, Joan C.; Bowen-Ziecheck, Aaron, Tsatas, Sofie, Boruff, Jill T.; Rod, Alisa B.; Bradley-Ridout, Glyneva, Nekolaichuk, Erica, Springall, Elena, Mierzwinski-Urban, Monika, Kaunelis, David, Ford, Caitlyn, Phinney, Jackie, Parker, Robin, Walter, Melissa, Horton, Jennifer, Hodgson, Amanda, Phinney, Jackie, Rothfus, Melissa, Helwig, Melissa, Hancock, Kristy, Pepper, Catherine, Halling, T. Derek, Epworth, Alissa, Nault, Caleb, Paladines, Melissa, Reansbury, Micheal, Serban, Raluca, Kennedy, Megan, Kung, Janice, Serban, Raluca, Nault, Caleb, Anderson, Melanie, Parker, Robin, Tippett, Marisa, Goodman, Maren, Stanley, Meagan, Isard, Roxanne, Sich, Christy, Horoky, Denise, Marson, Alanna, O’Reily, Shannon, Demaine, Jeffrey, Taylor, Mike, Truax, Morgan, Ross-White, Amanda, Wilson, Rosemary, Beck, Charlotte, Fischer, Meredith, Fournier, Karine, Sikora, Lindsey, Martyniuk, Julia, Iro, Chidiebere Michael, Bartlett, Joan C.; Hagerman, Leah, Clark, Emily, Neil-Sztramko, Sarah, Colangeli, Taylor, Dobbins, Maureen, George, Chloe, Leonard, Ashley Jane, Blanchard, Jeanette, Miller, Alanna, Read, Kristin, Husson, Heather, Dobbins, Maureen, Cunningham, Heather, Slaght, Graeme, Wall, Margaret, Premji, Zahra, Hayden, K. Alix, Amar-Zifkin, Alexandre, Quaiattini, Andrea, Winther, Connie, Hamonic, Laura, Dennett, Liz, Campbell, Sandy, Winther, Connie, Campbell, Sandy, Tocock, Adam, Gorring, Helene, Campbell, Alanna, Thormodson, Kelly, Cisney, Lori, Hoover, Benjamin, Kennedy, Megan, Thompson, Janice, Paladines, Melissa, Mann, Anna, Creaser, Julie, Bradley-Ridout, Glyneva, Mitchell, Mikaela, Wu, Jiewen, Nevison, Maggie, Zhang, Xiaoqian, Bartlett, Joan, Winther, Connie, Zvyagintseva, Lydia, Kung, Janice, Zych, Maria Maddalena, Malik, Usman, Boden, Catherine, Horton, Jennifer.
The journal of the Canadian Health Libraries Association ; 43(2):68-91, 2022.
Artículo en Inglés | EuropePMC | ID: covidwho-1989839

RESUMEN

This workshop will provide health science librarians and information professionals at any level/context with an overview of the best practices in finding and identifying the best scientific evidence during novel public health emergencies. Attendees will be presented with an overview of a best practices statement developed by the Librarian Reserve Corps. Attendees will then apply the recommendations from the best practices statement in designing a plan to respond to real-life case study/information request during a public health emergency. A discussion period will follow on how to apply the best practices in other contexts, environments, and cultures. Attendees will also be invited to share their own experiences and best practices during the discussion session. Through hands-on learning and discussion, librarians and information professionals at any level/context will develop strategies to find and critically appraise the best evidence in any novel public health emergency situation. Introduction: To inform the design of a consumer health strategy for a provincial health library system, the library sought to understand patient challenges and barriers in accessing quality sources of health information. Description: Over a period of three months in the winter of 2020-2021, the library engaged in semi-structured interviews with relevant clinical and corporate stakeholders. Program leads were asked about their role in consumer health information provision and support, and where they saw gaps and opportunities within the organization. Answers were themed and analyzed, and an internal report was produced to guide next steps in developing a consumer health strategy. Outcomes: The environmental scan showed that there are clear challenges and barriers for patients in accessing quality health information. Barriers include the duration of interaction with a healthcare practitioner;the specificity of patient information needs;and the organizational emphasis on a single enterprise-wide patient information resource. More significant challenges include language;lack of health information literacy skills;and low digital literacy among certain populations. Discussion: The environmental scan results provided strong rationale for developing a cohesive consumer health strategy for the library. They highlighted valuable but disjointed resources and programs throughout the organization. A Consumer Health Framework was drafted to guide the library in setting achievable goals and leveraging existing supports. Due to the Covid-19 pandemic it was not possible to engage directly with patients for the initial scan, however consultation with patient advisory groups is now being planned to check and validate the library’s direction.

3.
Elife ; 102021 08 20.
Artículo en Inglés | MEDLINE | ID: covidwho-1368024

RESUMEN

Background: Previously, we conducted a systematic review and analyzed the respiratory kinetics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Chen et al., 2021). How age, sex, and coronavirus disease 2019 (COVID-19) severity interplay to influence the shedding dynamics of SARS-CoV-2, however, remains poorly understood. Methods: We updated our systematic dataset, collected individual case characteristics, and conducted stratified analyses of SARS-CoV-2 shedding dynamics in the upper (URT) and lower respiratory tract (LRT) across COVID-19 severity, sex, and age groups (aged 0-17 years, 18-59 years, and 60 years or older). Results: The systematic dataset included 1266 adults and 136 children with COVID-19. Our analyses indicated that high, persistent LRT shedding of SARS-CoV-2 characterized severe COVID-19 in adults. Severe cases tended to show slightly higher URT shedding post-symptom onset, but similar rates of viral clearance, when compared to nonsevere infections. After stratifying for disease severity, sex and age (including child vs. adult) were not predictive of respiratory shedding. The estimated accuracy for using LRT shedding as a prognostic indicator for COVID-19 severity was up to 81%, whereas it was up to 65% for URT shedding. Conclusions: Virological factors, especially in the LRT, facilitate the pathogenesis of severe COVID-19. Disease severity, rather than sex or age, predicts SARS-CoV-2 kinetics. LRT viral load may prognosticate COVID-19 severity in patients before the timing of deterioration and should do so more accurately than URT viral load. Funding: Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant, NSERC Senior Industrial Research Chair, and the Toronto COVID-19 Action Fund.


Asunto(s)
COVID-19/fisiopatología , Sistema Respiratorio/fisiopatología , SARS-CoV-2/fisiología , Esparcimiento de Virus , Adulto , COVID-19/diagnóstico , COVID-19/virología , Niño , Femenino , Humanos , Masculino , Pronóstico , Sistema Respiratorio/virología , Índice de Severidad de la Enfermedad , Carga Viral
4.
Elife ; 102021 04 16.
Artículo en Inglés | MEDLINE | ID: covidwho-1190616

RESUMEN

Background: Which virological factors mediate overdispersion in the transmissibility of emerging viruses remains a long-standing question in infectious disease epidemiology. Methods: Here, we use systematic review to develop a comprehensive dataset of respiratory viral loads (rVLs) of SARS-CoV-2, SARS-CoV-1 and influenza A(H1N1)pdm09. We then comparatively meta-analyze the data and model individual infectiousness by shedding viable virus via respiratory droplets and aerosols. Results: The analyses indicate heterogeneity in rVL as an intrinsic virological factor facilitating greater overdispersion for SARS-CoV-2 in the COVID-19 pandemic than A(H1N1)pdm09 in the 2009 influenza pandemic. For COVID-19, case heterogeneity remains broad throughout the infectious period, including for pediatric and asymptomatic infections. Hence, many COVID-19 cases inherently present minimal transmission risk, whereas highly infectious individuals shed tens to thousands of SARS-CoV-2 virions/min via droplets and aerosols while breathing, talking and singing. Coughing increases the contagiousness, especially in close contact, of symptomatic cases relative to asymptomatic ones. Infectiousness tends to be elevated between 1 and 5 days post-symptom onset. Conclusions: Intrinsic case variation in rVL facilitates overdispersion in the transmissibility of emerging respiratory viruses. Our findings present considerations for disease control in the COVID-19 pandemic as well as future outbreaks of novel viruses. Funding: Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant program, NSERC Senior Industrial Research Chair program and the Toronto COVID-19 Action Fund.


To understand how viruses spread scientists look at two things. One is ­ on average ­ how many other people each infected person spreads the virus to. The other is how much variability there is in the number of people each person with the virus infects. Some viruses like the 2009 influenza H1N1, a new strain of influenza that caused a pandemic beginning in 2009, spread pretty uniformly, with many people with the virus infecting around two other people. Other viruses like SARS-CoV-2, the one that causes COVID-19, are more variable. About 10 to 20% of people with COVID-19 cause 80% of subsequent infections ­ which may lead to so-called superspreading events ­ while 60-75% of people with COVID-19 infect no one else. Learning more about these differences can help public health officials create better ways to curb the spread of the virus. Chen et al. show that differences in the concentration of virus particles in the respiratory tract may help to explain why superspreaders play such a big role in transmitting SARS-CoV-2, but not the 2009 influenza H1N1 virus. Chen et al. reviewed and extracted data from studies that have collected how much virus is present in people infected with either SARS-CoV-2, a similar virus called SARS-CoV-1 that caused the SARS outbreak in 2003, or with 2009 influenza H1N1. Chen et al. found that as the variability in the concentration of the virus in the airways increased, so did the variability in the number of people each person with the virus infects. Chen et al. further used mathematical models to estimate how many virus particles individuals with each infection would expel via droplets or aerosols, based on the differences in virus concentrations from their analyses. The models showed that most people with COVID-19 infect no one because they expel little ­ if any ­ infectious SARS-CoV-2 when they talk, breathe, sing or cough. Highly infectious individuals on the other hand have high concentrations of the virus in their airways, particularly the first few days after developing symptoms, and can expel tens to thousands of infectious virus particles per minute. By contrast, a greater proportion of people with 2009 influenza H1N1 were potentially infectious but tended to expel relatively little infectious virus when the talk, sing, breathe or cough. These results help explain why superspreaders play such a key role in the ongoing pandemic. This information suggests that to stop this virus from spreading it is important to limit crowd sizes, shorten the duration of visits or gatherings, maintain social distancing, talk in low volumes around others, wear masks, and hold gatherings in well-ventilated settings. In addition, contact tracing can prioritize the contacts of people with high concentrations of virus in their airways.


Asunto(s)
Aerosoles , COVID-19/transmisión , Subtipo H1N1 del Virus de la Influenza A/fisiología , Gripe Humana/transmisión , SARS-CoV-2/fisiología , Síndrome Respiratorio Agudo Grave/transmisión , Coronavirus Relacionado al Síndrome Respiratorio Agudo Severo/fisiología , Esparcimiento de Virus , Transmisión de Enfermedad Infecciosa , Humanos , Carga Viral
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