SARS: the struggle for containment.
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ABSTRACT:
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PROVIDER: S-EPMC154159 | biostudies-literature | 2003 May
REPOSITORIES: biostudies-literature
Publications
SARS: the struggle for containment.
CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne 20030501 10
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Project description:SARS-CoV-2 enters host cells through its viral spike protein binding to angiotensin-converting enzyme 2 (ACE2) receptors on the host cells. Here, we show that functionalized nanoparticles, termed "Nanotraps," completely inhibited SARS-CoV-2 infection by blocking the interaction between the spike protein of SARS-CoV-2 and the ACE2 of host cells. The liposomal-based Nanotrap surfaces were functionalized with either recombinant ACE2 proteins or anti-SARS-CoV-2 neutralizing antibodies and phagocytosis-specific phosphatidylserines. The Nanotraps effectively captured SARS-CoV-2 and completely blocked SARS-CoV-2 infection to ACE2-expressing human cell lines and primary lung cells; the phosphatidylserine triggered subsequent phagocytosis of the virus-bound, biodegradable Nanotraps by macrophages, leading to the clearance of pseudotyped and authentic virus in vitro. Furthermore, the Nanotraps demonstrated an excellent biosafety profile in vitro and in vivo. Finally, the Nanotraps inhibited pseudotyped SARS-CoV-2 infection in live human lungs in an ex vivo lung perfusion system. In summary, Nanotraps represent a new nanomedicine for the inhibition of SARS-CoV-2 infection.
| S-EPMC8062026 | biostudies-literature
Project description:BackgroundDespite substantial resources deployed to curb SARS-CoV-2 transmission, controlling the COVID-19 pandemic has been a major challenge. New variants of the virus are frequently emerging leading to new waves of infection and re-introduction of control measures. In this study, we assessed the effectiveness of containment strategies implemented in the early phase of the pandemic.MethodsReal-world data for COVID-19 cases was retrieved for the period Jan 1 to May 1, 2020 from a number of different sources, including PubMed, MEDLINE, Facebook, Epidemic Forecasting and Google Mobility Reports. We analyzed data for 18 countries/regions that deployed containment strategies such as travel restrictions, lockdowns, stay-at-home requests, school/public events closure, social distancing, and exposure history information management (digital contact tracing, DCT). Primary outcome measure was the change in the number of new cases over 30 days before and after deployment of a control measure. We also compared the effectiveness of centralized versus decentralized DCT. Time series data for COVID-19 were analyzed using Mann-Kendall (M-K) trend tests to investigate the impact of these measures on changes in the number of new cases. The rate of change in the number of new cases was compared using M-K z-values and Sen's slope.ResultsIn spite of the widespread implementation of conventional strategies such as lockdowns, travel restrictions, social distancing, school closures, and stay-at-home requests, analysis revealed that these measures could not prevent the spread of the virus. However, countries which adopted DCT with centralized data storage were more likely to contain the spread.ConclusionsCentralized DCT was more effective in containing the spread of COVID-19. Early implementation of centralized DCT should be considered in future outbreaks. However, challenges such as public acceptance, data security and privacy concerns will need to be addressed.
| S-EPMC9052634 | biostudies-literature
Project description:The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remain unclear. Here, we combine a multiomics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies.
2022-01-17 | GSE193708 | GEO
Project description:During the COVID-19 pandemic, several countries have resorted to self-adaptive mechanisms that tailor non-pharmaceutical interventions to local epidemiological and health care indicators. These mechanisms reinforce the mutual influence between containment measures and the evolution of the epidemic. To account for such interplay, we develop an epidemiological model that embeds an algorithm mimicking the self-adaptive policy mechanism effective in Italy between November 2020 and March 2022. This extension is key to tracking the historical evolution of health outcomes and restrictions in Italy. Focusing on the epidemic wave that started in mid-2021 after the diffusion of Delta, we compare the functioning of alternative mechanisms to show how the policy framework may affect the trade-off between health outcomes and the restrictiveness of mitigation measures. Mechanisms based on the reproduction number are generally highly responsive to early signs of a surging wave but entail severe restrictions. The emerging trade-off varies considerably depending on specific conditions (e.g., vaccination coverage), with less-reactive mechanisms (e.g., those based on occupancy rates) becoming more appealing in favorable contexts.
| S-EPMC9312378 | biostudies-literature
Project description:BackgroundSevere acute respiratory syndrome (SARS) is continuing to spread around the world. All hospitals must be prepared to care for patients with SARS. Thus, it is important to understand the transmission of this disease in hospitals and to evaluate methods for its containment in health care institutions. We describe how we cared for the first 2 patients with SARS admitted to our 419-bed community hospital in Richmond Hill, Ont., and the response to a SARS outbreak within our institution.MethodsWe collected clinical and epidemiological data about patients and health care workers at our institution who during a 13-day period had a potential unprotected exposure to 2 patients whose signs and symptoms were subsequently identified as meeting the case definition for probable SARS. The index case at our hospital was a patient who was transferred to our intensive care unit (ICU) from a referral hospital on Mar. 16, 2003, where he had been in close proximity to the son of the individual with the first reported case of SARS in Toronto. After 13 days in the ICU, a diagnosis of probable SARS was reached for our index case. Immediately upon diagnosis of our index case, respiratory isolation and barrier precautions were instituted throughout our hospital and maintained for a period of 10 days, which is the estimated maximum incubation period reported for this disease. Aggressive surveillance measures among hospital staff, patients and visitors were also maintained during this time.ResultsDuring the surveillance period, 15 individuals (10 hospital staff, 3 patients and 2 visitors) were identified as meeting the case definition for probable or suspected SARS, in addition to our index case. All but 1 individual had had direct contact with a symptomatic patient with SARS during the period of unprotected exposure. No additional cases were identified after infection control precautions had been implemented for 8 days. No cases of secondary transmission were identified in the 21 days following the implementation of these precautions at our institution.InterpretationSARS can easily be spread by direct personal contact in the hospital setting. We found that the implementation of aggressive infection control measures is effective in preventing further transmission of this disease.
| S-EPMC155957 | biostudies-literature
Project description: Not available
| S-EPMC7984294 | biostudies-literature
Project description:ObjectiveThe Omicron variant of SARS-COV-2 is replacing previously circulating variants around the world in 2022. Sporadic outbreaks of the Omicron variant into China have posed a concern how to properly response to battle against evolving coronavirus disease 2019 (COVID-19).MethodsBased on the epidemic data from website announced by Beijing Center for Disease Control and Prevention for the recent outbreak in Beijing from April 22nd to June 8th in 2022, we developed a modified SEPIR model to mathematically simulate the customized dynamic COVID-zero strategy and project transmissions of the Omicron epidemic. To demonstrate the effectiveness of dynamic-changing policies deployment during this outbreak control, we modified the transmission rate into four parts according to policy-changing dates as April 22nd to May 2nd, May 3rd to 11st, May 12th to 21st, May 22nd to June 8th, and we adopted Markov chain Monte Carlo (MCMC) to estimate different transmission rate. Then we altered the timing and scaling of these measures used to understand the effectiveness of these policies on the Omicron variant.ResultsThe estimated effective reproduction number of four parts were 1.75 (95% CI 1.66-1.85), 0.89 (95% CI 0.79-0.99), 1.15 (95% CI 1.05-1.26) and 0.53 (95% CI 0.48 -0.60), respectively. In the experiment, we found that till June 8th the cumulative cases would rise to 132,609 (95% CI 59,667-250,639), 73.39 times of observed cumulative cases number 1,807 if no policy were implemented on May 3rd, and would be 3,235 (95% CI 1,909 - 4,954), increased by 79.03% if no policy were implemented on May 22nd. A 3-day delay of the implementation of policies would led to increase of cumulative cases by 58.28% and a 7-day delay would led to increase of cumulative cases by 187.00%. On the other hand, taking control measures 3 or 7 days in advance would result in merely 38.63% or 68.62% reduction of real cumulative cases. And if lockdown implemented 3 days before May 3rd, the cumulative cases would be 289 (95% CI 211-378), reduced by 84%, and the cumulative cases would be 853 (95% CI 578-1,183), reduced by 52.79% if lockdown implemented 3 days after May 3rd.ConclusionThe dynamic COVID-zero strategy might be able to effectively minimize the scale of the transmission, shorten the epidemic period and reduce the total number of infections.
| S-EPMC9677562 | biostudies-literature
Project description: Not available
| S-EPMC8989390 | biostudies-literature
Project description:The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remains unclear. Here, we combine a multi-omics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype associated with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies.
| S-EPMC8866527 | biostudies-literature
Project description:Generative machine learning models have shown notable success in identifying architectures for metamaterials-materials whose behavior is determined primarily by their internal organization-that match specific target properties. By examining kirigami metamaterials, in which dependencies between cuts yield complex design restrictions, we demonstrate that this perceived success in the employment of generative models for metamaterials might be akin to survivorship bias. We assess the performance of the four most popular generative models-the Variational Autoencoder (VAE), the Generative Adversarial Network (GAN), the Wasserstein GAN (WGAN), and the Denoising Diffusion Probabilistic Model (DDPM)-in generating kirigami structures. Prohibiting cut intersections can prevent the identification of an appropriate similarity measure for kirigami metamaterials, significantly impacting the effectiveness of VAE and WGAN, which rely on the Euclidean distance-a metric shown to be unsuitable for considered geometries. This imposes significant limitations on employing modern generative models for the creation of diverse metamaterials.
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