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1.
Applied Physics Letters ; 121(6):1-7, 2022.
Article in English | Academic Search Complete | ID: covidwho-1991756

ABSTRACT

The analysis and detection of nucleic acid and specific antigens and antibodies are the most basic technologies for virus monitoring. However, the potential window for applying these technologies exists within a late specific period in the early monitoring and control of unknown viruses, especially human and animal pathogenic viruses transmitted via aerosols, e.g., SARS-CoV-2 and its variants. This is because early, real-time, and convenient monitoring of unknown viruses in the air or exhaled gas cannot be directly achieved through existing technologies. Herein, we report a weak light spectral imaging technology based on Tesla discharge (termed T-DAI) that can quickly monitor for viruses in real time in simulated aerosols with 71% sensitivity and 76% specificity for aerosol virus concentrations exceeding approximately 2800 vp/μl. This technology realizes the rapid detection of low concentrations of viruses in aerosols and could provide an important means for predicting, screening, and monitoring unknown or pandemic pathogenic viruses in the air or exhaled breath of humans and animals. [ FROM AUTHOR] Copyright of Applied Physics Letters is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

2.
Preprint in English | medRxiv | ID: ppmedrxiv-22275053

ABSTRACT

ObjectiveIn September 2020, records of 15,861 SARS-CoV-2 cases failed to upload from the Second Generation Laboratory Surveillance System (SGSS) to the Contact Tracing Advisory Service (CTAS) tool, resulting in a delay in the contact tracing of these cases. This study used CTAS data to determine the impact of this delay on health outcomes: transmission events, hospitalisations, and mortality. Previously, a modelling study had suggested a substantial impact. DesignObservational study SettingEngland. PopulationIndividuals testing positive for SARS-CoV-2 and their reported contacts. Main outcome measuresSecondary attack rates (SARs), hospitalisations, and deaths amongst primary and secondary contacts were calculated, compared to all other concurrent, unaffected cases. SGSS records affected by the event were matched to CTAS records and successive contacts and cases were identified. ResultsThe initiation of contact tracing was delayed by 3 days on average in the primary cases in the delay group (6 days) compared to the control group (3 days). This was associated with lower completion of contact tracing of primary cases in the delay group: 80% (95%CI: 79-81%) in the delay group and 83% (95%CI: 83-84%) in the control group. There was some evidence to suggest an increase in transmission to non-household contacts amongst those affected by the delay. The SAR for non-household contacts was higher amongst secondary contacts in the delay group than the control group (delay group: 7.9%, 95%CI:6.4% to 9.2%; control group: 5.9%, 95%CI: 5.3% to 6.6%). There was no evidence of a difference between the delay and control groups in the odds of hospitalisation (crude odds ratio: 1.1 (95%CI: 0.9 to 1.2) or death (crude odds ratio: 0.7 (0.1 to 4.0)) amongst secondary contacts. ConclusionsThe delay in contact tracing had a limited impact on population health outcomes. Strengths and limitations of the studyO_LIShows empirical data on the health impact of an event leading to a delay in contact tracing so can test hypotheses generated by models of the potential impact of a delay in contact tracing C_LIO_LIEstimates the extent of further transmission and odds of increased mortality or hospitalisation in up to the third generation of cases affected by the event C_LIO_LIThe event acts as a natural experiment to describe the possible impact of contact tracing, comparing a group affected by chance by delayed contact tracing to a control group who experienced no delay C_LIO_LIContact tracing was not completed for all individuals, so the study might not capture all affected contacts or transmissions C_LI

3.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-332665

ABSTRACT

A global sentiment in early 2022 is that the COVID-19 virus could become endemic just like common cold flu viruses soon. The most optimistic view is that, with minimal precautions, such as vaccination, boosters and optional masking, life for most people will proceed as normal soon. However, as warned by A. Katzourakis of Oxford University recently [1], we must set aside lazy optimism, and must be realistic about the likely levels of death, disability and sickness that will be brought on by a ‘COVID-19’ endemic. Moreover, the world must also consider that continual circulation of the virus could give rise to new variants such as the new BA.2 variant (a subvariant of Omicron) continues to spread across the US and parts of Europe. Data from the CDC is already showing that BA.2 has been tripling in prevalence every two weeks [2]. Hence, globally, we must use available and proven weapons to continue to fight the COVID-19 viruses, i.e., effective vaccines, antiviral medications, diagnostic tests and stop an airborne virus transmission through social distancing, and mask wearing . For this work, we have demonstrated a smart mask with an optimally-coupled ultra-thin flexible soundwave sensors for tracking, classifying, and recognizing different respiratory activities, including breathing, speaking , and two-/tri-phase coughing ;the mask’s functionality can also be augmented in the future to monitor other human physiological signals. Although researchers have integrated sensors into masks to detect respiratory activities in the past, they only based on measuring temperature and air flow during coughing, i.e., counting only the number of coughs. However, coughing is a process consisting of several phases, including an explosion of the air with glottal opening producing some noise-like waveform, a decrease of airflow to decrease sound amplitude, and a voiced stage which is the interruption of the air flow due to the closure of glottal and periodical vibration of partly glottis, which is not always present. Therefore, sensors used for cough detection should not be only sensitive to subtle air pressure but also the high-frequency vibrations, i.e., a pressure sensor that needs to be responsive to a wide input amplitude and bandwidth range, in order to detect air flows between hundreds of hertz from breath, and acoustic signals from voice that could reach ∼ 8000 Hz. Respiratory activities data from thirty-one (31) human subjects were collected. Machine learning methods such as Support Vector Machines and Convolutional Neural Networks were used to classify the collected sensor data from the smart mask, which show an overall macro-recall of about 93.88% for the three respiratory sounds among all 31 subjects. For individual subjects, the 31 human subjects have the average macro-recall of 95.23% (ranging from 90% to 100%) for these 3 respiratory activities. Our work bridges the technological gap between ultra-lightweight but high-frequency response sensor material fabrication, signal transduction and conditioning, and applying machining learning algorithms to demonstrate a reliable wearable device for potential applications in continual healthy monitoring of subjects with cough symptoms during the eventual COVID-19 endemic. The monitoring and analysis of cough sound should be highly beneficial for human health management. These health monitoring data could then be shared with doctors via cloud storage and transmission technique to help disease diagnosis more effectively. Also, communication barriers caused by wearing masks can be alleviated by combining with the speech recognition techniques. In general, this research helps to advance the wearable device technology for tracking respiratory activities, similar to an Apple Watch or a Fitbit smartwatch in tracking physical and physiological activities.

4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-307612

ABSTRACT

Purpose: To describe the correlation between the clinical, laboratory and radiological findings with hospitalization days in Coronavirus Infected Disease-19 (COVID-19) discharged patients. Method In this multicenter study, we retrospectively identified 153 discharged patients with COVID-19 pneumonia from Jan 16, 2020 to Feb 26, 2020 in Hunan province. Patients were grouped based on the hospitalization days: Group 1 (hospitalization days≦12 days) and Group 2((hospitalization days> 12days). Demographic, clinical characteristics and laboratory findings on admission and the imaging features of the first Chest CT on admission were analyzed. The differences between groups were analyzed using univariate logistic regression to find the impact factors. Results The cohort included 153 discharged patients (85 males and 68 females, with the mean age of 42.32±14.03 years old). 90(58.8%) patients had hospitalization days≦12 and 63(41.2%) patients had hospitalization days>12. 44(48.9%) patients in Group1 and 28(44.4%) in Group 2 had been to Wuhan. In both Group1 and Group2, most common symptoms at onset were fever (62.2%, 60.3%) and cough (33.3%, 50.8%). Cough was occurred more common in Group 2(50.8%) than Group 1(33.3%) with a significant difference (p=0.03). 6(6.7%) patients in Group1 and 10(15.9%) in Group2 had admitting diagnosis as non-pneumonia (p=0.07), some of them occurred mild pneumonia during hospital stay. White blood cell (2.2%, 9.5%) and neutrophil (9.5%) count above normal were more common on in Group 2 (p=0.04, p=0.04). Patients in Group 2 had higher concentration of aspartate aminotransferase (P=0.04) than Group 1. Most of patients had multiple lesions (75.6%, 69.8%) with bilateral distribution (73.3%, 58.7%) in both groups. Mixed ground-glass opacity (GGO) and consolidation appearance were seen in most patients. GGO components > consolidation appearance were more common in Group 1(31.1%) than in Group 2(8.0%) with a significant difference between groups (P<0.01). Patients had cough at onset disease (OR, 0.47;95%CI, 0.23 to 0.96, p=0.04) and CT represented as GGO components more than consolidation (OR, 4.84;95%CI, 1.80 to 13.04, p<0.01) were associated with hospitalization days. Conclusions COVID-19 non-pneumonia patients with longer hospitalization days might have the persistent symptoms or pneumonia occurrence after admission. Chest CT could help prompt diagnosis and monitor disease progression, GGO/consolidation >1 in mixed lesions was associated with shorter hospitalization days. Special attention should be paid to the role of radiological features in monitoring disease prognosis.

5.
Preprint in English | medRxiv | ID: ppmedrxiv-22271001

ABSTRACT

BackgroundThe SARS-CoV-2 Omicron variant (B.1.1.529) has rapidly replaced the Delta variant (B.1.617.2) to become dominant in England. This epidemiological study assessed differences in transmissibility between the Omicron and Delta using two methods and data sources. MethodsOmicron and Delta cases were identified through genomic sequencing, genotyping and S-gene target failure in England from 5-11 December 2021. Secondary attack rates for Omicron and Delta using named contacts and household clustering were calculated using national surveillance and contact tracing data. We used multivariable logistic regression was used to control for factors associated with transmission. FindingsAnalysis of contact tracing data identified elevated secondary attack rates for Omicron vs Delta in household (15.0% vs 10.8%) and non-household (8.2% vs 3.7%) settings. The proportion of index cases resulting in residential clustering was twice as high for Omicron (16.1%) compared to Delta (7.3%). Transmission was significantly less likely from cases, or in named contacts, in receipt of three compared to two vaccine doses in household settings, but less pronounced for Omicron (aRR 0.78 and 0.88) compared to Delta (aRR 0.62 and 0.68). In non-household settings, a similar reduction was observed for Delta cases and contacts (aRR 0.84 and 0.51) but only for Omicron contacts (aRR 0.76, 95% CI: 0.58-0.93) and not cases in receipt of three vs two doses (aRR 0.95, 0.77-1.16). InterpretationOur study identified increased risk of onward transmission of Omicron, consistent with its successful global displacement of Delta. We identified a reduced effectiveness of vaccination in lowering risk of transmission, a likely contributor for the rapid propagation of Omicron. FundingStudy funded by the UK Health Security Agency.

6.
Mathematical Problems in Engineering ; : 1-11, 2021.
Article in English | Academic Search Complete | ID: covidwho-1322858

ABSTRACT

When the outbreak of COVID-19 began, people could not go out. It was not allowed to provide agricultural machinery services in different places across regions to reduce the flow and gathering of people. Improvement of utilization efficiency of agricultural machinery resources is required through scientific scheduling of agricultural machinery. With seizing the farming season and stabilizing production as the goal, this paper studied the scientific scheduling of tractors within the scope of town and established agricultural machinery operation scheduling model with the minimization of total scheduling cost as the optimization objective. Factors such as farmland area, agricultural machinery, and farmland location information and operating time window are considered in this model to improve the accuracy of the agricultural machinery operation scheduling model. The characteristics of multiple scheduling algorithms are analyzed comprehensively. The scheduling requirements of agricultural machinery operation to ensure spring ploughing are combined to design the agricultural machinery scheduling algorithm based on the SA algorithm. With Hushu Street, Jiangning District, Nanjing City, as an example, a comparative experiment is conducted on the simulated annealing algorithm (SA) designed in this paper and the empirical algorithm and genetic algorithm (GA). The results suggest that the total cost of the scheduling scheme generated by the SA algorithm is 19,042.07 yuan lower than that by the empirical scheduling algorithm and 779.19 yuan lower than that by the genetic algorithm on average. Compared with the GA algorithm, the transfer distance, waiting cost, and delay cost of the SA algorithm are reduced by 11.6%, 100%, and 98.1% on average, indicating that the transfer distance of agricultural machinery in the scheduling scheme generated by the SA algorithm is shorter, so is the waiting and delay time. Meanwhile, it can effectively obtain the near-optimal solution that meets the time window constraint, with good convergence, stability, and adaptability. [ABSTRACT FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

7.
Preprint in English | medRxiv | ID: ppmedrxiv-21253590

ABSTRACT

BackgroundMitigation of SARS-CoV-2 transmission from international travel is a priority. Travellers from countries with travel restrictions (closed travel-corridors) were required to quarantine for 14 days over Summer 2020 in England. We describe the genomic epidemiology of travel-related cases in England and evaluate the effectiveness of this travel policy. MethodsBetween 27/05/2020 and 13/09/2020, probable travel-related SARS-CoV-2 cases and their contacts were identified and combined with UK SARS-CoV-2 sequencing data. The epidemiology and demographics of cases was identified, and the number of contacts per case modelled using negative binomial regression to estimate the effect of travel restriction, and any variation by age, sex and calendar date. Unique travel-related SARS-CoV-2 genomes in the COG-UK dataset were identified to estimate the effect travel restrictions on cluster size generated from these. The Polecat Clustering Tool was used to identify a travel-related SARS-CoV-2 cluster of infection. Findings4,207 travel-related SARS-CoV-2 cases are identified. 51.2% (2155/4207) of cases reported travel to one of three countries; 21.0% (882) Greece, 16.3% (685) Croatia and 14.0% (589) Spain. Median number of contacts per case was 3 (IQR 1-5), and greatest for the 16-20 age-group (9.0, 95% C.I.=5.6-14.5), which saw the largest attenuation by travel restriction. Travel restriction was associated with a 40% (rate ratio=0.60, 95% C.I.=0.37-0.95) lower rate of contacts. 827/4207 (19.7%) of cases had high-quality SARS-CoV-2 genomes available. Fewer genomically-linked cases were observed for index cases related to countries with travel restrictions compared to cases from non-travel restriction countries (rate ratio=0.17, 95% C.I.=0.05-0.52). A large travel-related cluster dispersed across England is identified through genomics, confirmed with contact-tracing data. InterpretationThis study demonstrates the efficacy of travel restriction policy in reducing the onward transmission of imported cases. FundingWellcome Trust, Biotechnology and Biological Sciences Research Council, UK Research & Innovation, National Institute of Health Research, Wellcome Sanger Institute. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, medRxiv, bioRxiv, Web of Science and Scopus for the terms (COVID-19 OR SARS-COV-2) AND (imported or importation) AND (sequenc* OR genom* or WGS). We filtered the 55 articles identified through this search and rejected any that did not undertake SARS-CoV-2 sequencing as part of an epidemiological investigation for importation into a different country. The remaining 20 papers were reviewed in greater detail to understand the patterns of importation and the methods used in each case. Added value of this studyThis is the first published study on importations of SARS-CoV-2 into England using genomics. Plessis et al., (2021) used a predictive model to infer the number of importations in to the UK from all SARS-CoV-2 genomes generated before 26th June 2020. The current study assesses the period 27/05/2020 to 13/09/2020 and presents findings of case-reported travel linked to genomic data. Two unpublished reports exist for Wales and Scotland, although only examine a comparatively small number of importations. Implications of all the available evidenceThis large-scale study has a number of findings that are pertinent to public health and of global significance, not available from prior evidence to our knowledge. The study demonstrates travel restrictions, through the implementation of travel-corridors, are effective in reducing the number of contacts per case based on observational data. Age has a significant effect on the number of contacts and this can be mitigated with travel restrictions. Analysis of divergent clusters indicates travel restrictions can reduce the number of onwards cases following a travel-associated case. Analysis of divergent clusters can allow for importations to be identified from genomics, as subsequently evidenced by cluster characteristics derived from contact tracing. The majority of importations of SARS-CoV-2 in England over Summer 2020 were from coastal European countries. The highest number of cases and onward contacts were from Greece, which was largely exempt from self-isolation requirements (bar some islands in September at the end of the study period). Systematic monitoring of imported SARS-CoV-2 cases would help refine implementation of travel restrictions. Finally, along with multiple studies, this study highlights the use of genomics to monitor and track importations of SARS-CoV-2 mutations of interest; this will be of particular use as the repertoire of clinically relevant SARS-CoV-2 variants expand over time and globally.

8.
Preprint in English | medRxiv | ID: ppmedrxiv-20201178

ABSTRACT

We estimate the impact of indoor face mask mandates and other non-pharmaceutical interventions (NPI) on COVID-19 case growth in Canada. Mask mandate introduction was staggered from mid-June to mid-August 2020 in the 34 public health regions in Ontario, Canadas largest province by population. Using this variation, we find that mask mandates are associated with a 22 percent weekly reduction in new COVID-19 cases, relative to the trend in absence of mandate. Province-level data provide corroborating evidence. We control for mobility behaviour using Google geo-location data and for lagged case totals and case growth as information variables. Our analysis of additional survey data shows that mask mandates led to an increase of about 27 percentage points in self-reported mask wearing in public. Counterfactual policy simulations suggest that adopting a nationwide mask mandate in June could have reduced the total number of diagnosed COVID-19 cases in Canada by over 50,000 over the period July-November 2020. Jointly, our results indicate that mandating mask wearing in indoor public places can be a powerful policy tool to slow the spread of COVID-19. JEL codesI18, I12, C23

9.
Preprint in English | medRxiv | ID: ppmedrxiv-20042382

ABSTRACT

BackgroundA pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been spreading over the world. However, the viral dynamics, host serologic responses, and their associations with clinical manifestations, have not been well described in prospective cohort. MethodsWe conducted a prospective cohort and enrolled 67 COVID-19 patients admitting between Jan 26 and Feb 5, 2020. Clinical specimens including nasopharyngeal swab, sputum, blood, urine and stool were tested periodically according to standardized case report form with final follow-up on February 27. The routes and duration of viral shedding, antibody response, and their associations with disease severity and clinical manifestations were systematically evaluated. Coronaviral particles in clinical specimens were observed by transmission electron microscopy (TEM). ResultsThe median duration of SARS-CoV-2 RNA shedding were 12 (3-38), 19 (5-37), and 18 (7-26) days in nasopharyngeal swabs, sputum and stools, respectively. Only 13 urines (5.6%) and 12 plasmas (5.7%) were viral positive. Prolonged viral shedding was observed in severe patients than that of non-severe patients. Cough but not fever, aligned with viral shedding in clinical respiratory specimens, meanwhile the positive stool-RNA appeared to align with the proportion who concurrently had cough and sputum production, but not diarrhea. Typical coronaviral particles could be found directly in sputum by TEM. The anti-nucleocapsid-protein IgM started on day 7 and positive rate peaked on day 28, while that of IgG was on day 10 and day 49 after illness onset. IgM and IgG appear earlier, and their titers are significantly higher in severe patients than non-severe patients (p<0.05). The weak responders for IgG had a significantly higher viral clearance rate than that of strong responders (p= 0.011). ConclusionsNasopharyngeal, sputum and stools rather than blood and urine, were the major shedding routes for SARS-CoV-2, and meanwhile sputum had a prolonged viral shedding. Symptom cough seems to be aligned with viral shedding in clinical respiratory and fecal specimens. Stronger antibody response was associated with delayed viral clearance and disease severity. Summary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSAs a newly appearing infectious disease, early efforts have focused on virus identification, describing the epidemiologic characteristics, clinical course, prognostics for critically illed cases and mortality. Among COVID-19 cases reported in mainland China (72 314 cases, updated through February 11, 2020), 81% are mild, 14% are severe, and 5% are critical. The estimated overall case fatality rate (CFR) is 2.3%. Some case series reported had shown that SARS-CoV-2 could shed in upper/lower respiratory specimens, stools, blood and urines of patients. However, important knowledge gaps remain, particularly regarding full kinetics of viral shedding and host serologic responses in association with clinical manifestations and host factors. What this study addsThe incubation period has no change after spreading out of Wuhan, and has no sex or age differences, however, children had prolonged incubation period. Due to early recognition and intervention, COVID-19 illness of Chongqing cohort is milder than that of Wuhan patients reported. This prospective cohort study on SARS-CoV-2 infection shows clearly that the viral and serological kinetics were related in duration of infection, disease severity, and clinical manifestations of COVID-19. Our data demonstrate that nasopharyngeal, sputum and stools are major shedding routes for SARS-CoV-2, and stronger NP antibody response is associated with delayed viral clearance and disease severity.

10.
Preprint in English | medRxiv | ID: ppmedrxiv-20035246

ABSTRACT

We conducted a retrospective study among 417 confirmed COVID-19 cases from Jan 1 to Feb 28, 2020 in Shenzhen, the largest migrant city of China, to identify the epidemiological and clinical features in settings of high population mobility. We estimated the median incubation time to be 5.0 days. 342 (82.0%) cases were imported, 161 (38.6%) cases were identified by surveillance, and 247 (59.2%) cases were reported from cluster events. The main symptoms on admission were fever and dry cough. Most patients (91.4%) had mild or moderate illnesses. Age of 50 years or older, breathing problems, diarrhea, and longer time between the first medical visit and admission were associated with higher level of clinical severity. Surveillance-identified cases were much less likely to progress to severe illness. Although the COVID-19 epidemic has been contained in Shenzhen, close monitoring and risk assessments are imperative for prevention and control of COVID-19 in future. Article Summary LineWe characterized epidemiological and clinical features of a large population-based sample of COVID-19 cases in the largest migrant city of China, and our findings could provide knowledge of SARS-CoV-2 transmission in the context of comprehensive containment and mitigation efforts in similar settings.

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