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1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-334226

ABSTRACT

Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the extant and anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) is likely to have greater value as an important diagnostic tool to inform public health. As the widespread adoption of WWS is relatively new at the scale employed for COVID-19, interpretation of data, including the relationship to clinical cases, has yet to be standardized. An in-depth analysis of the metrics derived from WWS is required for public health units/agencies to interpret and utilize WWS-acquired data effectively and efficiently. In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven different cities in Canada over periods ranging from 8 to 21 months. Significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing in these communities. The WC ratio decreased significantly during the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community’s wastewater (40-60% allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community’s wastewater (40-60% allelic proportion). Finally, a rapid and significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant’s greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when vaccine-induced community immunity was high. The WC ratio, used as an additional monitoring metric, complements clinical case counts and wastewater signals as individual metrics in its ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.

2.
Preprint in English | medRxiv | ID: ppmedrxiv-22274052

ABSTRACT

Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the extant and anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) is likely to have greater value as an important diagnostic tool to inform public health. As the widespread adoption of WWS is relatively new at the scale employed for COVID-19, interpretation of data, including the relationship to clinical cases, has yet to be standardized. An in-depth analysis of the metrics derived from WWS is required for public health units/agencies to interpret and utilize WWS-acquired data effectively and efficiently. In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven different cities in Canada over periods ranging from 8 to 21 months. Significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing in these communities. The WC ratio decreased significantly during the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized communitys wastewater (40-60% allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized communitys wastewater (40-60% allelic proportion). Finally, a rapid and significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variants greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when vaccine-induced community immunity was high. The WC ratio, used as an additional monitoring metric, complements clinical case counts and wastewater signals as individual metrics in its ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.

3.
Natural Gas Industry B ; 2022.
Article in English | ScienceDirect | ID: covidwho-1773662

ABSTRACT

China's shale gas production in 2020 exceeds 200 × 108 m³, which creates a miracle in the history of natural gas development in China. The Sichuan Basin has already been and will be the main battlefield of shale gas exploration and development in China. In order to further promote the large-scale efficient development of shale gas in China, under the new situation of global COVID-19 spread and domestic “carbon peak and carbon neutrality” goal, this paper analyzes the progress and challenges of shale gas exploration and development in the Sichuan Basin from four aspects, including resource exploration, gas reservoir engineering, drilling and production engineering and industry regulation, and puts forward countermeasures and suggestions for achieving large-scale efficient development of shale gas. The following research results are obtained: First, the large-scale efficient development of shale gas in the Sichuan Basin has to take the sustainable and stable production of middle–shallow shale gas and the large-scale productivity construction of deep shale gas as the base. Second, compared with the shale gas exploration and development in the North America, the Sichuan Basin has its own characteristics in terms of geographical setting, geological condition, drilling and production technology and industry regulation, which makes it difficult to copy the development pattern of large scale, high density and continuous well deployment from the North America, so it is necessary to adopt the strategy of “high production with few wells”. On the one hand, continue to apply the geology and engineering integration technology to carry out “integrated research, integrated design, integrated implementation and integrated iteration” in the whole life cycle of shale gas well;and on the other hand, carry out problem-oriented continuous researches from the aspects of geological evaluation, development policy, engineering technology and industry regulation, so as to improve geological evaluation theory and technology, innovate gas reservoir engineering theory and method, research and develop engineering technology for cost reduction and efficiency improvement, improve shale gas industry regulation, and form a new pattern of collaborative promotion of technical and non-technical elements. In conclusion, the research results provide important reference and guidance for the large-scale efficient development of shale gas in the Sichuan Basin and even the whole country.

4.
J Nat Prod ; 2022 Mar 16.
Article in English | MEDLINE | ID: covidwho-1747274

ABSTRACT

Eight new aspulvinone analogues, aspulvins A-H (1-8) and aspulvinones D, M, O, and R (9-12), were isolated from cultures of the endophytic fungus Cladosporium sp. 7951. Detailed spectroscopic analyses were conducted to determine the structures of the new compounds. All isolates displayed different degrees of inhibitory activity against the severe acute respiratory syndrome coronavirus 2 main protease (SARS-CoV-2 Mpro) at 10 µM. Notably, compounds 9, 10, and 12 showed potential SARS-CoV-2 Mpro inhibition with IC50 values of 10.3 ± 0.6, 9.4 ± 0.6, and 7.7 ± 0.6 µM, respectively. For all compounds except 3 and 4, the anti-inflammatory activity occurred by inhibiting the release of lactate dehydrogenase (LDH) with IC50 values ranging from 0.7 to 7.4 µM. Compound 10 showed the most potent anti-inflammatory activity by inhibiting Casp-1 cleavage, IL-1ß maturation, NLRP3 inflammasome activation, and pyroptosis. The findings reveal that the aspulvinone analogues 9, 10, and 12 could be promising candidates for coronavirus disease 2019 (COVID-19) treatment as they inhibit SARS-CoV-2 infection and reduce inflammatory reactions caused by SARS-CoV-2.

5.
J Med Virol ; 94(6): 2317-2330, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1694695

ABSTRACT

Pooled data from 2352 hospitalized coronavirus disease 2019 (COVID-19) patients with viral RNA in feces across 46 studies were analyzed and the pooled prevalence of fecal RNA was 46.8% (95% confidence interval [CI]: 0.383-0.554). The pooled analysis showed that the occurrence of total gastrointestinal (GI) symptoms was 28.5% (95% CI: 0.125-0.44) in COVID-19 patients with fecal RNA, that of both respiratory and GI symptoms was 21.9% (95% CI: 0.09-0.346), that of only GI symptoms was 19.8% (95% CI: 0.107-0.288), and that of only respiratory symptoms was 50.5%(95% CI: 0.267-0.744). The pooled data showed no significant difference in positive fecal RNA between severe and nonsevere cases (odds ratio = 2.009, p = 0.079, 95% CI: 0.922-4.378). During hospital admission, after samples from the respiratory system tested negative for viral RNA, 55.4% (95% CI: 0.418-0.669) of the patients with positive fecal RNA had persistent shedding of fecal RNA and pooled results from the other 4 studies including 848 discharged patients with nucleic acid-negative stool samples indicated that the occurrence of repositive stool swabs was 18.1% (95% CI: 0.028-0.335), that of repositive respiratory swabs was 22.8% (95% CI: 0.003-0.452), that of both repositive stool and respiratory swabs was 19.1% (95% CI: 0.019-0.363), and that of only repositive stool swabs was 9.6% (95% CI: 0.010-0.203). The digestive tract may be an important organ involved in COVID-19 infection and in the excretion of the virus. Because of the potential risk of fecal-oral transmission, giving emphasis on stool swab tests can help increase the detection rate of asymptomatic carriers and reduce missed diagnoses.

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325360

ABSTRACT

In December 2019, coronavirus disease 2019 (COVID-19) was first found in Wuhan, China and soon was reported all around the world. Novel coronavirus (COVID-19) is highly infectious and requires early detection, isolation, and treatment. We tried to find some useful information by analyzing the covid-19 screening data, so as to provide help for clinical practice. In this prospective study, we retrospectively analyzed the clinical data of 131 patients with COVID-19 and 119 controls. For confirmed cases, the data of blood routine examination were analyzed among severe patients and non-severe group. The blood routine examination results were dynamically observed in the survivors and nonsurvivors. We find that patients with COVID-19 have lower counts of leucocytes, lymphocytes, eosinophils, which were compared with controls ( P < 0.001). In severe group, patients have the lower count of lymphocytes and eosinophils, but the higher leucocytes count (all P values < 0.01). Eosinophils have high diagnostic efficacy analysis of severe COVID-19, and its area under the curve reached 0.750. Patients whose eosinophils returned to normal early had significantly longer survival times than those who did not( P < 0.001). Patients with COVID-19 have abnormal peripheral blood routine examination results. Dynamic surveillance of peripheral blood system especially eosinophils is helpful in the diagnosis, assess the prognosis and prediction of severe COVID-19 cases.

7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-324551

ABSTRACT

Scarcity of annotated images hampers the building of automated solution for reliable COVID-19 diagnosis and evaluation from CT. To alleviate the burden of data annotation, we herein present a label-free approach for segmenting COVID-19 lesions in CT via pixel-level anomaly modeling that mines out the relevant knowledge from normal CT lung scans. Our modeling is inspired by the observation that the parts of tracheae and vessels, which lay in the high-intensity range where lesions belong to, exhibit strong patterns. To facilitate the learning of such patterns at a pixel level, we synthesize `lesions' using a set of surprisingly simple operations and insert the synthesized `lesions' into normal CT lung scans to form training pairs, from which we learn a normalcy-converting network (NormNet) that turns an 'abnormal' image back to normal. Our experiments on three different datasets validate the effectiveness of NormNet, which conspicuously outperforms a variety of unsupervised anomaly detection (UAD) methods.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324328

ABSTRACT

Objective: to understand the mental resilience and psychosomatic status quo of first-line anti-epidemic medical team members, so as to provide a reference basis for mastering the mental health status of medical team members and promoting the improvement of mental resilience. Methods: a cluster sampling method was used to conduct mobile phone questionnaire survey on the selected subjects using the staff status questionnaire and Chinese version of mental resilience scale (Chinese version of cd-risc). Results: the total score of mental resilience of the medical team was 65.40 ± 13.90 points higher than that of the Chinese community. However, the tenacity of men was higher than that of women (P < 0.05). In terms of psychosomatic state influence score, the psychosomatic influence of first-line task on women was greater than that on men (P < 0.01). Conclusion: the anti-epidemic task has a great influence on the psychosomatic state of the first-line medical personnel, and the first-line medical personnel should be provided with better social and psychological support. Frontline medical personnel should be good at actively seeking social support and learn to adopt a positive way of coping.

9.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315683

ABSTRACT

Background: The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain. Methods: Based on the reported cases, the effective reproduction number (B) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between a and NPIs through a generalized linear model (GLM). Results: Different NPIs were found to have led to different levels of reduction in c. Stay-at-home contributed approximately 51% (95% CI 46%-57%), wearing (face) masks 29% (15%-42%), gathering ban (more than 10 people) 19% (14%-24%), non-essential business closure 16% (10%-21%), declaration of emergency 13% (8%-17%), interstate travel restriction 11% (5%-16%), school closure 10% (7%-14%), initial business closure 10% (6%-14%), and gathering ban (more than 50 people) 7% (2%-11%). Conclusions: : This retrospective assessment of NPIs on k has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

10.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-307265

ABSTRACT

Accurate surveys are the primary tool for understanding public opinion towards and barriers preventing COVID-19 vaccine uptake. We compare three prominent surveys about vaccination in the US: Delphi-Facebook ($n\approx 250,000$ per week), Census Household Pulse ($n\approx 75,000$), and Axios-Ipsos ($n\approx 1,000$). We find that the two larger surveys are biased compared to the benchmark from the Centers for Disease Control and Prevention (CDC), and that their sample sizes lead to devastating overconfidence in those incorrect estimates. By April 26, 2021, Delphi-Facebook and Census Household Pulse estimated that at least 73% and 69% of US adults had received a first dose of COVID-19 vaccine, which was 16 and 12 percentage points higher, respectively, than the CDC's estimate (57%). Moreover, estimates of vaccine hesitancy disagree significantly between surveys -- we find that these differences cannot be explained entirely by Delphi-Facebook's under-representation of racial minorities and non-college educated adults. These are examples of the Big Data Paradox: when a confidence interval based on a large but biased sample exhibits both a seriously displaced center and a grossly underestimated width, thus leading us (confidently) away from the truth. With sufficient attention to quality control, small surveys like Axios-Ipsos can be far more reliable than large ones. We leverage a recently established data quality identity (Meng, Annals of Applied Statistics, 2018) to quantify sources of the estimation errors and to conduct a scenario analysis for implications on vaccine willingness and hesitancy. Our study quantifies how bias in large samples can lead to overconfidence in incorrect inferences, which is particularly problematic in studies, like those examined here, that inform high-stakes public policy decisions.

11.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313451

ABSTRACT

Background: Transarterial chemoembolization (TACE) may not be repeated “on-demand” timely for hepatocellular carcinoma (HCC) patients in the era of the novel coronavirus disease (COVID-19). We aim to evaluate the impact of the COVID-19 pandemic on the intervals and outcomes of TACE in HCC patients. Methods: This retrospective study included HCC patients who underwent TACE from Jan 1, 2020 to March 31, 2020 (study group) and Jan 1, 2019 to Mar 31, 2019 (control group) at two institutions in China. The endpoints included the TACE interval and the overall response rate (ORR). Uni- and multivariate logistic analyses were performed to identify independent risk factors associated with a worse ORR. The cut-off point was determined to divide repeated TACE time into long- and short- intervals. Findings: 154 patients (71 in the study group, 83 in the control group) were enrolled. The median TACE interval in the study group was 82·0 days (IQR, 61–109), longer than 66·0 days (IQR, 51–94) in the control group (p=0·004). The ORR was 23·9% in the study group, while 39·8% in the control group (p=0·037). The cut-off value was 95 days. The group (OR, 2·402;95% CI, 1·040–5·546;p=0·040), the long interval (OR, 2·573;95% CI, 1·022–6·478;p=0·045), and the stage system (OR, 2·500;95% CI, 1·797–3·480;p<0·001) were independent predictors. Interpretation: For HCC patients, the COVID-19 pandemic results in a longer re-TACE schedule, which may further lead to a lower ORR. Patients with a TACE interval of more than 95 days may have a worse prognosis. Funding: This study was supported by the National Key Research and Development Project of China (2018YFA0704100), the National Natural Science Foundation of China (Major Scientific Research Instrument Development Program 81827805, 81441054, 81520108015, 81671796, 81901847), Jiangsu Provincial Medical Youth Talent Program (ZDRCA2016078), the Key Research and Development Project of Jiangsu Province (BE2019750), the Natural Science Foundation of Jiangsu Province (BK20190177), Innovation Platform of Jiangsu Provincial Medical Center (YXZXA2016005), and the Suzhou Science and Technology Youth Plan (KJXW2018003).Declaration of Interests: All authors declare no competing interests.Ethics Approval Statement: The study was approved by the institutional ethics review boards in two participating institutions and the requirement for written informed consent was waived due to its retrospective nature.

12.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313432

ABSTRACT

Background: The aim of this was to analyze 4 chest CT imaging features of patients with coronavirus disease 2019 (COVID-19) in Shenzhen, China so as to improve the diagnosis of COVID-19. Methods: Chest CT of 34 patients with COVID-19 confirmed by the nucleic acid test (NAT) were retrospectively analyzed. Analyses were performed to investigate the pathological basis of four imaging features(“feather sign”,“dandelion sign”,“pomegranate sign”, and “rime sign”) and to summarize the follow-up results. Results: There were 22 patients (65.2 %) with typical “feather sign”and 18 (52.9%) with “dandelion sign”, while few patients had “pomegranate sign” and “rime sign”. The “feather sign” and “dandelion sign” were composed of stripe or round ground-glass opacity(GGO), thickened blood vessels, and small-thickened interlobular septa. The “pomegranate sign” was characterized as follows: the increased range of GGO, the significant thickening of the interlobular septum, complicated with a small amount of punctate alveolar hemorrhage. The “rime sign” was characterized by numerous alveolar edemas. Microscopically, the wall thickening, small vascular proliferation, luminal stenosis, and occlusion, accompanied by interstitial infiltration of inflammatory cells, as well as numerous pulmonary interstitial fibrosis and partial hyaline degeneration were observed. Repeated chest CT revealed the mediastinal lymphadenectasis in one patient. Re-examination of the NAT showed another positive anal swab in two patients. Conclusion: “Feather sign” and “dandelion sign” were typical chest CT features in patients with COVID-19;“pomegranate sign” was an atypical feature, and “rime sign” was a severe feature. In clinical work, accurate identification of various chest CT signs can help to improve the diagnostic accuracy of COVID-19 and reduce the misdiagnosis or missed diagnosis rate.

13.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312739

ABSTRACT

The outbreak of COVID-19 highlights the need for a more harmonized, less privacy-concerning, easily accessible approach to monitoring the human mobility that has been proved to be associated with the viral transmission. In this study, we analyzed 587 million tweets worldwide to see how global collaborative efforts in reducing human mobility are reflected from the user-generated information at the global, country, and the U.S. state scale. Considering the multifaceted nature of mobility, we propose two types of distance: the single-day distance and the cross-day distance. To quantify the responsiveness in certain geographical regions, we further propose a mobility-based responsive index (MRI) that captures the overall degree of mobility changes within a time window. The results suggest that mobility patterns obtained from Twitter data are amendable to quantitatively reflect the mobility dynamics. Globally, the proposed two distances had greatly deviated from their baselines after March 11, 2020, when WHO declared COVID-19 as a pandemic. The considerably less periodicity after the declaration suggests that the protection measures have obviously affected people's travel routines. The country scale comparisons reveal the discrepancies in responsiveness, evidenced by the contrasting mobility patterns in different epidemic phases. We find that the triggers of mobility changes correspond well with the national announcements of mitigation measures. In the U.S., the influence of the COVID-19 pandemic on mobility is distinct. However, the impacts varied substantially among states. The strong mobility recovering momentum is further fueled by the Black Lives Matter protests, potentially fostering the second wave of infections in the U.S.

14.
Nat Med ; 26(6): 845-848, 2020 06.
Article in English | MEDLINE | ID: covidwho-1641979

ABSTRACT

We report acute antibody responses to SARS-CoV-2 in 285 patients with COVID-19. Within 19 days after symptom onset, 100% of patients tested positive for antiviral immunoglobulin-G (IgG). Seroconversion for IgG and IgM occurred simultaneously or sequentially. Both IgG and IgM titers plateaued within 6 days after seroconversion. Serological testing may be helpful for the diagnosis of suspected patients with negative RT-PCR results and for the identification of asymptomatic infections.


Subject(s)
Antibodies, Viral/blood , Antibody Formation/drug effects , Betacoronavirus/pathogenicity , Coronavirus Infections/drug therapy , Pneumonia, Viral/drug therapy , Adult , Aged , Antibody Formation/immunology , Antiviral Agents/therapeutic use , Betacoronavirus/genetics , COVID-19 , Coronavirus Infections/blood , Coronavirus Infections/immunology , Coronavirus Infections/virology , Female , Humans , Immunoglobulin G/blood , Immunoglobulin M/blood , Male , Middle Aged , Pandemics/prevention & control , Pneumonia, Viral/blood , Pneumonia, Viral/immunology , Pneumonia, Viral/virology , SARS-CoV-2
15.
EBioMedicine ; 75: 103803, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1587923

ABSTRACT

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) pandemic has been a great threat to global public health since 2020. Although the advance on vaccine development has been largely achieved, a strategy to alleviate immune overactivation in severe COVID-19 patients is still needed. The NLRP3 inflammasome is activated upon SARS-CoV-2 infection and associated with COVID-19 severity. However, the processes by which the NLRP3 inflammasome is involved in COVID-19 disease remain unclear. METHODS: We infected THP-1 derived macrophages, NLRP3 knockout mice, and human ACE2 transgenic mice with live SARS-CoV-2 in Biosafety Level 3 (BSL-3) laboratory. We performed quantitative real-time PCR for targeted viral or host genes from SARS-CoV-2 infected mouse tissues, conducted histological or immunofluorescence analysis in SARS-CoV-2 infected mouse tissues. We also injected intranasally AAV-hACE2 or intraperitoneally NLRP3 inflammasome inhibitor MCC950 before SARS-CoV-2 infection in mice as indicated. FINDINGS: We have provided multiple lines of evidence that the NLRP3 inflammasome plays an important role in the host immune response to SARS-CoV-2 invasion of the lungs. Inhibition of the NLRP3 inflammasome attenuated the release of COVID-19 related pro-inflammatory cytokines in cell cultures and mice. The severe pathology induced by SARS-CoV-2 in lung tissues was reduced in Nlrp3-/- mice compared to wild-type C57BL/6 mice. Finally, specific inhibition of the NLRP3 inflammasome by MCC950 alleviated excessive lung inflammation and thus COVID-19 like pathology in human ACE2 transgenic mice. INTERPRETATION: Inflammatory activation induced by SARS-CoV-2 is an important stimulator of COVID-19 related immunopathology. Targeting the NLRP3 inflammasome is a promising immune intervention against severe COVID-19 disease. FUNDING: This work was supported by grants from the Bureau of Frontier Sciences and Education, CAS (grant no. QYZDJ-SSW-SMC005 to Y.G.Y.), the key project of the CAS "Light of West China" Program (to D.Y.) and Yunnan Province (202001AS070023 to D.Y.).


Subject(s)
COVID-19 , Lung , Macrophages , NLR Family, Pyrin Domain-Containing 3 Protein/immunology , SARS-CoV-2/immunology , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/immunology , Animals , COVID-19/genetics , COVID-19/immunology , COVID-19/pathology , Disease Models, Animal , Humans , Lung/immunology , Lung/pathology , Lung/virology , Macrophages/immunology , Macrophages/pathology , Macrophages/virology , Male , Mice , Mice, Knockout , NLR Family, Pyrin Domain-Containing 3 Protein/genetics , SARS-CoV-2/genetics , THP-1 Cells
16.
Nature ; 600(7890): 695-700, 2021 12.
Article in English | MEDLINE | ID: covidwho-1562062

ABSTRACT

Surveys are a crucial tool for understanding public opinion and behaviour, and their accuracy depends on maintaining statistical representativeness of their target populations by minimizing biases from all sources. Increasing data size shrinks confidence intervals but magnifies the effect of survey bias: an instance of the Big Data Paradox1. Here we demonstrate this paradox in estimates of first-dose COVID-19 vaccine uptake in US adults from 9 January to 19 May 2021 from two large surveys: Delphi-Facebook2,3 (about 250,000 responses per week) and Census Household Pulse4 (about 75,000 every two weeks). In May 2021, Delphi-Facebook overestimated uptake by 17 percentage points (14-20 percentage points with 5% benchmark imprecision) and Census Household Pulse by 14 (11-17 percentage points with 5% benchmark imprecision), compared to a retroactively updated benchmark the Centers for Disease Control and Prevention published on 26 May 2021. Moreover, their large sample sizes led to miniscule margins of error on the incorrect estimates. By contrast, an Axios-Ipsos online panel5 with about 1,000 responses per week following survey research best practices6 provided reliable estimates and uncertainty quantification. We decompose observed error using a recent analytic framework1 to explain the inaccuracy in the three surveys. We then analyse the implications for vaccine hesitancy and willingness. We show how a survey of 250,000 respondents can produce an estimate of the population mean that is no more accurate than an estimate from a simple random sample of size 10. Our central message is that data quality matters more than data quantity, and that compensating the former with the latter is a mathematically provable losing proposition.


Subject(s)
COVID-19 Vaccines/administration & dosage , Health Care Surveys , Vaccination/statistics & numerical data , Benchmarking , Bias , Big Data , COVID-19/epidemiology , COVID-19/prevention & control , Centers for Disease Control and Prevention, U.S. , Datasets as Topic/standards , Female , Health Care Surveys/standards , Humans , Male , Research Design , Sample Size , Social Media , United States/epidemiology , /statistics & numerical data
17.
Emerg Microbes Infect ; 10(1): 2141-2150, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1532382

ABSTRACT

BACKGROUND: We studied humoral and cellular responses against SARS-CoV-2 longitudinally in a homogeneous population of healthy young/middle-aged men of South Asian ethnicity with mild COVID-19. METHODS: In total, we recruited 994 men (median age: 34 years) post-COVID-19 diagnosis. Repeated cross-sectional surveys were conducted between May 2020 and January 2021 at six time points - day 28 (n = 327), day 80 (n = 202), day 105 (n = 294), day 140 (n = 172), day 180 (n = 758), and day 280 (n = 311). Three commercial assays were used to detect anti-nucleoprotein (NP) and neutralizing antibodies. T cell response specific for Spike, Membrane and NP SARS-CoV-2 proteins was tested in 85 patients at day 105, 180, and 280. RESULTS: All serological tests displayed different kinetics of progressive antibody reduction while the frequency of T cells specific for different structural SARS-CoV-2 proteins was stable over time. Both showed a marked heterogeneity of magnitude among the studied cohort. Comparatively, cellular responses lasted longer than humoral responses and were still detectable nine months after infection in the individuals who lost antibody detection. Correlation between T cell frequencies and all antibodies was lost over time. CONCLUSION: Humoral and cellular immunity against SARS-CoV-2 is induced with differing kinetics of persistence in those with mild disease. The magnitude of T cells and antibodies is highly heterogeneous in a homogeneous study population. These observations have implications for COVID-19 surveillance, vaccination strategies, and post-pandemic planning.


Subject(s)
Antibodies, Viral/blood , COVID-19/immunology , SARS-CoV-2/immunology , T-Lymphocytes/immunology , Adult , Antibodies, Neutralizing/blood , Cross-Sectional Studies , Humans , Male , Nucleocapsid Proteins/immunology
18.
Risk Manag Healthc Policy ; 14: 4499-4510, 2021.
Article in English | MEDLINE | ID: covidwho-1515504

ABSTRACT

PURPOSE: To report the experience of health QR code application in Chengdu's anti-epidemic measures including circle-layer management, hospital triage system and healthcare plan for quarantined pregnant women and children during the summer outbreak of SARS-CoV-2 Delta strain in 2021 and to evaluate these measures. METHODS: We comprehensively summarized Chengdu's health code application in the circle-layer management (a set of stringent confinement measures of places confirmed cases and close contacts have recently been to and less strict quarantine measures of surrounding areas), hospital triage system, and healthcare plan for quarantined pregnant women and children. We also assessed the effectiveness or efficiency of these measures by analyzing the number of different cases with confirmed COVID-19 infections or epidemiological history, the attitude of quarantined pregnant women toward the summer outbreak and healthcare services, as well as the time needed for obtaining epidemiological history and accuracy of health-code-based hospital triage system. RESULTS: The circle-layer management lasted 15 days and ended with no community or nosocomial transmission happened. Approximately 70 pregnant women and 600 children below 6-year-old were quarantined. Four home visits and two patient transfers were performed. Online survey indicated that about 80% of quarantined women felt satisfactory about the healthcare service. The novel triage system identified 137/221 (61.99%) patients with epidemiological history from patients with yellow health code, and 71/4504 (1.57%) patients from patients with green health code in our hospital (p < 0.001). The health QR code markedly outperformed the traditional methods in the efficiency experiment of obtaining epidemiological history (3.52 ± 0.98 vs 78.91 ± 23.18 seconds, P < 0.001). CONCLUSION: The circle-layer management has successfully and precisely prevented the spread of the summer outbreak of COVID-19 in Chengdu. The health-code-based triage system showed great effectiveness and efficiency in triaging patients with epidemiological history. The healthcare services for quarantined pregnant women has basically met their needs.

19.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-292403

ABSTRACT

Background: This study aimed to examine the effect of convalescent plasma transfusion on patient with severe coronavirus disease ( COVID-19 ) and discussed the main nursing practices. Methods: We retrospectively analyzed the clinical data of 21 patients with severe COVID-19 who had received convalescent plasma transfusion therapy between March 1 and April 1, 2020. The observation indicators included leukocyte, lymphocyte, C-reactive protein (CRP), interleukin-6 (IL-6), and viral antibody levels;test results from pharyngeal swabs;nucleic acid test results;chest CT results;and respiratory symptoms. Further, we summarized the nursing practices related to plasma transfusion. Results: Neither death nor transfusion-related adverse reactions were observed in patients treated with convalescent plasma transfusion. Their antibody levels, especially IgG (P < 0.05), were increased to different levels, whereas the levels of inflammatory markers (CRP), white blood cells, and lymphocytes were significantly decreased (P < 0.05). Respiratory symptoms showed an improvement, and chest CT showed stable findings. Conclusions: Convalescent plasma transfusion is safe and feasible. It can increase antibody levels, reduce inflammatory factor levels, improve white blood cell and lymphocyte counts, and improve respiratory symptoms in patients with severe COVID-19. Thus, plasma transfusion can be used as a new, effective COVID-19 treatment method that requires cooperation from nursing.

20.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-291906

ABSTRACT

Surveys are a crucial tool for understanding public opinion and behavior, and their accuracy depends on maintaining statistical representativeness of their target populations by minimizing biases from all sources. Increasing data size shrinks confidence intervals but magnifies the impact of survey bias, an instance of the Big Data Paradox (Meng 2018). Here we demonstrate this paradox in estimates of first-dose COVID-19 vaccine uptake in US adults: Delphi-Facebook (about 250,000 responses per week) and Census Household Pulse (about 75,000 per week). By May 2021, Delphi-Facebook overestimated uptake by 17 percentage points and Census Household Pulse by 14, compared to a benchmark from the Centers for Disease Control and Prevention (CDC). Moreover, their large data sizes led to minuscule margins of error on the incorrect estimates. In contrast, an Axios-Ipsos online panel with about 1,000 responses following survey research best practices (AAPOR) provided reliable estimates and uncertainty. We decompose observed error using a recent analytic framework to explain the inaccuracy in the three surveys. We then analyze the implications for vaccine hesitancy and willingness. We show how a survey of 250,000 respondents can produce an estimate of the population mean that is no more accurate than an estimate from a simple random sample of size 10. Our central message is that data quality matters far more than data quantity, and compensating the former with the latter is a mathematically provable losing proposition.

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