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3.
iScience ; JOUR
Article in English | EuropePMC | ID: covidwho-2092880

ABSTRACT

To overcome the increased risk of SARS-CoV-2 reinfection or post-vaccination infection caused by the Omicron variant, Omicron-specific vaccines were considered a potential strategy. We reported the increased magnitude and breadth of antibody response against VOCs elicited by post-vaccination Delta and Omicron infection, compared to WT infection without vaccination. Then, in mouse models, three doses of Omicron-RBD immunization elicited comparable neutralizing antibody (NAb) titers with three doses of WT-RBD immunization, but the neutralizing activity was not cross-active. By contrast, a heterologous Omicron-RBD booster following two doses of WT-RBD immunization increased the NAb titers against Omicron by 9 folds than the homologous WT-RBD booster. Moreover, it retains neutralization against both WT and current VOCs. Results suggest that Omicron-specific subunit booster shows its advantages in the immune protection from both WT and current VOCs and that SARS-CoV-2 vaccines including two or more virus lineages might improve the NAb response. Graphical

4.
Cell Host Microbe ; 2022 Oct 18.
Article in English | MEDLINE | ID: covidwho-2068781

ABSTRACT

SARS-CoV-2 spread in humans results in continuous emergence of new variants, highlighting the need for vaccines with broad-spectrum antigenic coverage. Using inter-lineage chimera and mutation-patch strategies, we engineered a recombinant monomeric spike variant (STFK1628x) that contains key regions and residues across multiple SAR-CoV-2 variants. STFK1628x demonstrated high immunogenicity and mutually complementary antigenicity to its prototypic form (STFK). In hamsters, a bivalent vaccine composed of STFK and STFK1628x elicited high titers of broad-spectrum neutralizing antibodies to 19 circulating SARS-CoV-2 variants, including Omicron sublineages BA.1, BA.1.1, BA.2, BA.2.12.1, BA.2.75, and BA.4/5. Furthermore, this vaccine conferred robust protection against intranasal challenges by either SARS-CoV-2 ancestral strain or immune-evasive Beta and Omicron BA.1. Strikingly, vaccination with the bivalent vaccine in hamsters effectively blocked within-cage virus transmission of ancestral SARS-CoV-2, Beta variant, and Omicron BA.1 to unvaccinated sentinels. Thus, our study provided insight and antigen candidates for the development of next-generation COVID-19 vaccines.

5.
Math Biosci Eng ; 19(10): 10602-10617, 2022 07 25.
Article in English | MEDLINE | ID: covidwho-2055531

ABSTRACT

The clinical data of 76 severe illness patients with novel coronavirus SARS-CoV-2 from July to August, 2020 admitted to the ICU Intensive Care Unit ward in a hospital in Urumqi were collected in the paper. By using the Laplace approximation parameter estimation method based on maximum likelihood estimation, the generalized linear mixed effect model (GLMM) was established to analyze the characteristics of clinical indicators in critical patients, and to screen the main influencing factors of COVID-19 critical patients' inability to be transferred out of the ICU in a short time: age, C-reactive protein, serum creatinine and lactate dehydrogenase.


Subject(s)
COVID-19 , Critical Illness , Hospitalization , Humans , Intensive Care Units , SARS-CoV-2
6.
Psychol Health Med ; : 1-11, 2022 Sep 27.
Article in English | MEDLINE | ID: covidwho-2042448

ABSTRACT

This study aimed to evaluate the influence of COVID-19 on the mental health of Chinese medical students at 1-year of follow-up. From 2 February 2020 to 23 February 2021, we conducted three waves of research online (T1 = during outbreak, T2 = controlling period, T3 = 1 year after outbreak). The survey collected demographic data and several self reporting questionnaires to measure the depressive, anxiety and stress symptoms. A total of 4002 participants complete the whole research phases. The study major, grade level and gender were the main factors related to psychological distress caused by the COVID-19 crisis. Importantly, medical knowledge has a protective effect on medical students' psychological distress during the COVID-19 period.

7.
Database (Oxford) ; 20222022 08 31.
Article in English | MEDLINE | ID: covidwho-2017881

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic has been severely impacting global society since December 2019. The related findings such as vaccine and drug development have been reported in biomedical literature-at a rate of about 10 000 articles on COVID-19 per month. Such rapid growth significantly challenges manual curation and interpretation. For instance, LitCovid is a literature database of COVID-19-related articles in PubMed, which has accumulated more than 200 000 articles with millions of accesses each month by users worldwide. One primary curation task is to assign up to eight topics (e.g. Diagnosis and Treatment) to the articles in LitCovid. The annotated topics have been widely used for navigating the COVID literature, rapidly locating articles of interest and other downstream studies. However, annotating the topics has been the bottleneck of manual curation. Despite the continuing advances in biomedical text-mining methods, few have been dedicated to topic annotations in COVID-19 literature. To close the gap, we organized the BioCreative LitCovid track to call for a community effort to tackle automated topic annotation for COVID-19 literature. The BioCreative LitCovid dataset-consisting of over 30 000 articles with manually reviewed topics-was created for training and testing. It is one of the largest multi-label classification datasets in biomedical scientific literature. Nineteen teams worldwide participated and made 80 submissions in total. Most teams used hybrid systems based on transformers. The highest performing submissions achieved 0.8875, 0.9181 and 0.9394 for macro-F1-score, micro-F1-score and instance-based F1-score, respectively. Notably, these scores are substantially higher (e.g. 12%, higher for macro F1-score) than the corresponding scores of the state-of-art multi-label classification method. The level of participation and results demonstrate a successful track and help close the gap between dataset curation and method development. The dataset is publicly available via https://ftp.ncbi.nlm.nih.gov/pub/lu/LitCovid/biocreative/ for benchmarking and further development. Database URL https://ftp.ncbi.nlm.nih.gov/pub/lu/LitCovid/biocreative/.


Subject(s)
COVID-19 , COVID-19/epidemiology , Data Mining/methods , Databases, Factual , Humans , PubMed , Publications
9.
PLoS One ; 17(8): e0272546, 2022.
Article in English | MEDLINE | ID: covidwho-2009688

ABSTRACT

OBJECTIVES: The coronavirus disease 2019 pandemic has affected countries around the world since 2020, and an increasing number of people are being infected. The purpose of this research was to use big data and artificial intelligence technology to find key factors associated with the coronavirus disease 2019 infection. The results can be used as a reference for disease prevention in practice. METHODS: This study obtained data from the "Imperial College London YouGov Covid-19 Behaviour Tracker Open Data Hub", covering a total of 291,780 questionnaire results from 28 countries (April 1~August 31, 2020). Data included basic characteristics, lifestyle habits, disease history, and symptoms of each subject. Four types of machine learning classification models were used, including logistic regression, random forest, support vector machine, and artificial neural network, to build prediction modules. The performance of each module is presented as the area under the receiver operating characteristics curve. Then, this study further processed important factors selected by each module to obtain an overall ranking of determinants. RESULTS: This study found that the area under the receiver operating characteristics curve of the prediction modules established by the four machine learning methods were all >0.95, and the RF had the highest performance (area under the receiver operating characteristics curve is 0.988). Top ten factors associated with the coronavirus disease 2019 infection were identified in order of importance: whether the family had been tested, having no symptoms, loss of smell, loss of taste, a history of epilepsy, acquired immune deficiency syndrome, cystic fibrosis, sleeping alone, country, and the number of times leaving home in a day. CONCLUSIONS: This study used big data from 28 countries and artificial intelligence methods to determine the predictors of the coronavirus disease 2019 infection. The findings provide important insights for the coronavirus disease 2019 infection prevention strategies.


Subject(s)
COVID-19 , Artificial Intelligence , Humans , Machine Learning , Pandemics , ROC Curve
10.
Microb Pathog ; 171: 105735, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-1996427

ABSTRACT

To improve the identification and subsequent intervention of COVID-19 patients at risk for ICU admission, we constructed COVID-19 severity prediction models using logistic regression and artificial neural network (ANN) analysis and compared them with the four existing scoring systems (PSI, CURB-65, SMARTCOP, and MuLBSTA). In this prospective multi-center study, 296 patients with COVID-19 pneumonia were enrolled and split into the General-Ward-Care group (N = 238) and the ICU-Admission group (N = 58). The PSI model (AUC = 0.861) had the best results among the existing four scoring systems, followed by SMARTCOP (AUC = 0.770), motified-MuLBSTA (AUC = 0.761), and CURB-65 (AUC = 0.712). Data from 197 patients (training set) were analyzed for modeling. The beta coefficients from logistic regression were used to develop a severity prediction model and risk score calculator. The final model (NLHA2) included five covariates (consumes alcohol, neutrophil count, lymphocyte count, hemoglobin, and AKP). The NLHA2 model (training: AUC = 0.959; testing: AUC = 0.857) had similar results to the PSI model, but with fewer variable items. ANN analysis was used to build another complex model, which had higher accuracy (training: AUC = 1.000; testing: AUC = 0.907). Discrimination and calibration were further verified through bootstrapping (2000 replicates), Hosmer-Lemeshow goodness of fit testing, and Brier score calculation. In conclusion, the PSI model is the best existing system for predicting ICU admission among COVID-19 patients, while two newly-designed models (NLHA2 and ANN) performed better than PSI, and will provide a new approach for the development of prognostic evaluation system in a novel respiratory viral epidemic.


Subject(s)
COVID-19 , Community-Acquired Infections , COVID-19/diagnosis , Community-Acquired Infections/epidemiology , Humans , Neural Networks, Computer , Prognosis , Prospective Studies , Retrospective Studies
11.
Econ Model ; 116: 105999, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-1996126

ABSTRACT

The COVID-19 pandemic adversely impacted economic activity, decreased corporate revenues, and magnified cash flow fluctuations. We study how Chinese listed firms' COVID exposure influences their cash holdings. A firm's COVID exposure is measured by its excess stock return responses to globally newly infected cases while controlling for market return. Firms increase (decrease) cash balances when their stock returns fall (increase) with COVID severity due to precautionary motives. Firms cannot predict the evolution of the pandemic, which impacts demand and supply and the cash conversion cycle. The deteriorating business condition also increases external financing costs with non-state-owned, low-growth, small, and firms without overseas businesses facing higher financial frictions. Furthermore, firms with good corporate governance tend to pre-empt operational uncertainty by increasing cash holdings. The increased cash holdings translate to more R&D expenditure but lesser capital investment. Our results remain robust to placebo tests, using excess cash and alternative COVID exposure measures.

12.
Experimental and Therapeutic Medicine ; 24(3), 2022.
Article in English | EuropePMC | ID: covidwho-1990179

ABSTRACT

In December 2019, there was an outbreak of pneumonia of unknown causes in Wuhan, China. The etiological pathogen was identified to be a novel coronavirus, named severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). The number of infected patients has markedly increased since the 2019 outbreak and COVID-19 has also proven to be highly contagious. In particular, the elderly are among the group of patients who are the most susceptible to succumbing to COVID-19 within the general population. Cross-infection in the hospital is one important route of SARS-CoV-2 transmission, where elderly patients are more susceptible to nosocomial infections due to reduced immunity. Therefore, the present study was conducted to search for ways to improve the medical management workflow in geriatric departments to ultimately reduce the risk of nosocomial infection in elderly inpatients. The present observational retrospective cohort study analysed elderly patients who were hospitalised in the Geriatric Department of the First Affiliated Hospital with Nanjing Medical University (Nanjing, China). A total of 4,066 elderly patients, who were admitted between January and March in 2019 and 2020 and then hospitalised for >48 h were selected. Among them, 3,073 (75.58%) patients hospitalised from January 2019 to March 2019 were allocated into the non-intervention group, whereas the remaining 933 (24.42%) patients hospitalised from January 2020 to March 2020 after the COVID-19 outbreak were allocated into the intervention group. Following multivariate logistic regression analysis, the risk of nosocomial infections was found to be lower in the intervention group compared with that in the non-intervention group. After age stratification and adjustment for sex, chronic disease, presence of malignant tumour and trauma, both inverse probability treatment weighting and standardised mortality ratio revealed a lower risk of nosocomial infections in the intervention group compared with that in the non-intervention group. To rule out interference caused by changes in the community floating population and social environment during this 1-year study, 93 long-stay patients in stable condition were selected as a subgroup based on 4,066 patients. The so-called floating population refers to patients who have been in hospital for <2 years. Patients aged ≥65 years were included in the geriatrics program. The incidence of nosocomial infections during the epidemic prevention and control period (24 January 2020 to 24 March 2020) and the previous period of hospitalisation (24 January 2019 to 24 March 2019) was also analysed. In the subgroup analysis, a multivariate analysis was also performed on 93 elderly patients who experienced long-term hospitalisation. The risk of nosocomial and pulmonary infections was found to be lower in the intervention group compared with that in the non-intervention group. During the pandemic, the geriatric department took active preventative measures. However, whether these measures can be normalised to reduce the risk of nosocomial infections among elderly inpatients remain unclear. In addition, the present study found that the use of an indwelling gastric tube is an independent risk factor of nosocomial pulmonary infection in elderly inpatients. However, nutritional interventions are indispensable for the long-term wellbeing of patients, especially for those with dysphagia in whom an indwelling gastric tube is the most viable method of providing enteral nutrition. To conclude, the present retrospective analysis of the selected cases showed that enacting preventative and control measures resulted in the effective control of the incidence of nosocomial infections.

13.
Exp Ther Med ; 24(3): 562, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1979466

ABSTRACT

In December 2019, there was an outbreak of pneumonia of unknown causes in Wuhan, China. The etiological pathogen was identified to be a novel coronavirus, named severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). The number of infected patients has markedly increased since the 2019 outbreak and COVID-19 has also proven to be highly contagious. In particular, the elderly are among the group of patients who are the most susceptible to succumbing to COVID-19 within the general population. Cross-infection in the hospital is one important route of SARS-CoV-2 transmission, where elderly patients are more susceptible to nosocomial infections due to reduced immunity. Therefore, the present study was conducted to search for ways to improve the medical management workflow in geriatric departments to ultimately reduce the risk of nosocomial infection in elderly inpatients. The present observational retrospective cohort study analysed elderly patients who were hospitalised in the Geriatric Department of the First Affiliated Hospital with Nanjing Medical University (Nanjing, China). A total of 4,066 elderly patients, who were admitted between January and March in 2019 and 2020 and then hospitalised for >48 h were selected. Among them, 3,073 (75.58%) patients hospitalised from January 2019 to March 2019 were allocated into the non-intervention group, whereas the remaining 933 (24.42%) patients hospitalised from January 2020 to March 2020 after the COVID-19 outbreak were allocated into the intervention group. Following multivariate logistic regression analysis, the risk of nosocomial infections was found to be lower in the intervention group compared with that in the non-intervention group. After age stratification and adjustment for sex, chronic disease, presence of malignant tumour and trauma, both inverse probability treatment weighting and standardised mortality ratio revealed a lower risk of nosocomial infections in the intervention group compared with that in the non-intervention group. To rule out interference caused by changes in the community floating population and social environment during this 1-year study, 93 long-stay patients in stable condition were selected as a subgroup based on 4,066 patients. The so-called floating population refers to patients who have been in hospital for <2 years. Patients aged ≥65 years were included in the geriatrics program. The incidence of nosocomial infections during the epidemic prevention and control period (24 January 2020 to 24 March 2020) and the previous period of hospitalisation (24 January 2019 to 24 March 2019) was also analysed. In the subgroup analysis, a multivariate analysis was also performed on 93 elderly patients who experienced long-term hospitalisation. The risk of nosocomial and pulmonary infections was found to be lower in the intervention group compared with that in the non-intervention group. During the pandemic, the geriatric department took active preventative measures. However, whether these measures can be normalised to reduce the risk of nosocomial infections among elderly inpatients remain unclear. In addition, the present study found that the use of an indwelling gastric tube is an independent risk factor of nosocomial pulmonary infection in elderly inpatients. However, nutritional interventions are indispensable for the long-term wellbeing of patients, especially for those with dysphagia in whom an indwelling gastric tube is the most viable method of providing enteral nutrition. To conclude, the present retrospective analysis of the selected cases showed that enacting preventative and control measures resulted in the effective control of the incidence of nosocomial infections.

14.
J Med Virol ; 94(12): 5691-5701, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-1966059

ABSTRACT

Immune responses elicited by viral infection or vaccination play key roles in the viral elimination and the prevention of reinfection, as well as the protection of healthy persons. As one of the most widely used Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines, there have been increasing concerns about the necessity of additional doses of inactivated vaccines, due to the waning immune response several months after vaccination. To further optimize inactivated SARS-CoV-2 vaccines, we compared immune responses to SARS-CoV-2 elicited by natural infection and immunization with inactivated vaccines in the early phase. We observed the lower antibody levels against SARS-CoV-2 spike (S) and nucleocapsid (N) proteins in the early phase of postvaccination with a slow increase, compared to the acute phase of SARS-CoV-2 natural infection. Specifically, IgA antibodies have the most significant differences. Moreover, we further analyzed cytokine expression between these two groups. A wide variety of cytokines presented high expression in the infected individuals, while a few cytokines were elicited by inactivated vaccines. The differences in antibody responses and cytokine levels between natural SARS-CoV-2 infection and vaccination with the inactivated vaccines may provide implications for the optimization of inactivated SARS-CoV-2 vaccines and the additional application of serological tests.


Subject(s)
COVID-19 , Viral Vaccines , Antibodies, Viral , Antibody Formation , COVID-19/prevention & control , COVID-19 Vaccines , Cytokines , Humans , Immunoglobulin A , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , Vaccination , Vaccines, Inactivated
15.
J Immunol ; 209(2): 280-287, 2022 Jul 15.
Article in English | MEDLINE | ID: covidwho-1964219

ABSTRACT

Hand, foot, and mouth disease (HFMD), which is mainly caused by coxsackievirus A16 (CVA16) or enterovirus A71 (EV-A71), poses a serious threat to children's health. However, the long-term dynamics of the neutralizing Ab (NAb) response and ideal paired-serum sampling time for serological diagnosis of CVA16-infected HFMD patients were unclear. In this study, 336 CVA16 and 253 EV-A71 PCR-positive HFMD inpatients were enrolled and provided 452 and 495 sera, respectively, for NAb detection. Random-intercept modeling with B-spline was conducted to characterize NAb response kinetics. The NAb titer of CVA16 infection patients was estimated to increase from negative (2.1, 95% confidence interval [CI]: 1.4-3.3) on the day of onset to a peak of 304.8 (95% CI: 233.4-398.3) on day 21 and then remained >64 until 26 mo after onset. However, the NAb response level of EV-A71-infected HFMD patients was much higher than that of CVA16-infected HFMD patients throughout. The geometric mean titer was significantly higher in severe EV-A71-infected patients than in mild patients, with a 2.0-fold (95% CI: 1.4-3.2) increase. When a 4-fold rise in titer was used as the criterion for serological diagnosis of CVA16 and EV-A71 infection, acute-phase serum needs to be collected at 0-5 d, and the corresponding convalescent serum should be respectively collected at 17.4 (95% CI: 9.6-27.4) and 24.4 d (95% CI: 15.3-38.3) after onset, respectively. In conclusion, both CVA16 and EV-A71 infection induce a persistent humoral immune response but have different NAb response levels and paired-serum sampling times for serological diagnosis. Clinical severity can affect the anti-EV-A71 NAb response.


Subject(s)
Enterovirus A, Human , Enterovirus Infections , Enterovirus , Hand, Foot and Mouth Disease , Antibodies, Neutralizing , Child , China/epidemiology , Cohort Studies , Hand, Foot and Mouth Disease/diagnosis , Humans , Infant , Longitudinal Studies
16.
Front Med (Lausanne) ; 9: 820544, 2022.
Article in English | MEDLINE | ID: covidwho-1952357

ABSTRACT

Background: Currently, promoted vaccinations against SARS-CoV-2 are being given out globally. However, the occurrence of numerous COVID-19 variants has hindered the goal of rapid mitigation of the COVID-19 pandemic by effective mass vaccinations. The real-word effectiveness of the current vaccines against COVID-19 variants has not been assessed by published reviews. Therefore, our study evaluated the overall effectiveness of current vaccines and the differences between the various vaccines and variants. Methods: PubMed, Embase, Cochrane Library, medRxiv, bioRxiv, and arXiv were searched to screen the eligible studies. The Newcastle-Ottawa scale and the Egger test were applied to estimate the quality of the literature and any publication bias, respectively. The pooled incident rates of different variants after vaccination were estimated by single-arm analysis. Meanwhile, the pooled efficacies of various vaccines against variants were evaluated by two-arm analysis using odds ratios (ORs) and vaccine effectiveness (VE). Results: A total of 6,118 studies were identified initially and 44 articles were included. We found that the overall incidence of variants post first/second vaccine were 0.07 and 0.03, respectively. The VE of the incidence of variants post first vaccine between the vaccine and the placebo or unvaccinated population was 40% and post second vaccine was 96%, respectively. The sub-single-arm analysis showed a low prevalence rate of COVID-19 variants after specific vaccination with the pooled incidence below 0.10 in most subgroups. Meanwhile, the sub-two-arm analysis indicated that most current vaccines had a good or moderate preventive effect on certain variants considering that the VE in these subgroups was between 66 and 95%, which was broadly in line with the results of the sub-single-arm analysis. Conclusion: Our meta-analysis shows that the current vaccines that are used globally could prevent COVID-19 infection and restrict the spread of variants to a great extent. We would also support maximizing vaccine uptake with two doses, as the effectiveness of which was more marked compared with one dose. Although the mRNA vaccine was the most effective against variants according to our study, specific vaccines should be taken into account based on the local dominant prevalence of variants.

17.
Frontiers in medicine ; 9, 2022.
Article in English | EuropePMC | ID: covidwho-1940340

ABSTRACT

Background We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for patients with coronavirus disease 2019 (COVID-19). Methods We evaluated patients with COVID-19 admitted to Wuhan West Union Hospital between 12 January and 25 February 2020. The data of patients were collected, and the illness severity was assessed. Results Among 1,150 enrolled patients, 296 (25.7%) patients developed into critical illness. A baseline nomogram model consists of seven variables including age [odds ratio (OR), 1.028;95% confidence interval (CI), 1.004–1.052], sequential organ failure assessment (SOFA) score (OR, 4.367;95% CI, 3.230–5.903), neutrophil-to-lymphocyte ratio (NLR;OR, 1.094;95% CI, 1.024–1.168), D-dimer (OR, 1.476;95% CI, 1.107–1.968), lactate dehydrogenase (LDH;OR, 1.004;95% CI, 1.001–1.006), international normalised ratio (INR;OR, 1.027;95% CI, 0.999–1.055), and pneumonia area interpreted from computed tomography (CT) images (medium vs. small [OR, 4.358;95% CI, 2.188–8.678], and large vs. small [OR, 9.567;95% CI, 3.982–22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an area under the curve (AUC) of 0.960 (95% CI, 0.941–0.972) in the training set and an AUC of 0.958 (95% CI, 0.936–0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2;increase per day [I/d], +0.49), NLR (value, 10.61;I/d, +2.07), C-reactive protein (CRP;value, 46.9 mg/L;I/d, +4.95), glucose (value, 7.83 mmol/L;I/d, +0.2), D-dimer (value, 6.08 μg/L;I/d, +0.28), LDH (value, 461 U/L;I/d, +13.95), and blood urea nitrogen (BUN value, 6.51 mmol/L;I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset during hospitalization. Conclusion The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for patients with COVID-19.

19.
PeerJ ; 10: e13277, 2022.
Article in English | MEDLINE | ID: covidwho-1934568

ABSTRACT

Importance: The rise of novel, more infectious SARS-CoV-2 variants has made clear the need to rapidly deploy large-scale testing for COVID-19 to protect public health. However, testing remains limited due to shortages of personal protective equipment (PPE), naso- and oropharyngeal swabs, and healthcare workers. Simple test methods are needed to enhance COVID-19 screening. Here, we describe a simple, and inexpensive spit-test for COVID-19 screening called Patient Self-Collection of Sample-CoV2 (PSCS-CoV2). Objective: To evaluate an affordable and convenient test for COVID-19. Methods: The collection method relies on deep throat sputum (DTS) self-collected by the subject without the use of swabs, and was hence termed the Self-Collection of Sample for SARS-CoV-2 (abbreviated PSCS-CoV2). We used a phenol-chloroform extraction method for the viral RNA. We then tested for SARS-CoV-2 using real-time reverse transcription polymerase chain reaction with primers against at least two coding regions of the viral nucleocapsid protein (N1 and N2 or E) of SARS-CoV-2. We evaluted the sensitivity and specificity of our protocol. In addition we assess the limit of detection, and efficacy of our Viral Inactivating Solution. We also evaluated our protocol, and pooling strategy from volunteers on a local college campus. Results: We show that the PSCS-CoV2 method accurately identified 42 confirmed COVID-19 positives, which were confirmed through the nasopharyngeal swabbing method of an FDA approved testing facility. For samples negative for COVID-19, we show that the cycle threshold for N1, N2, and RP are similar between the PSCS-CoV2 and nasopharynx swab collection method (n = 30). We found a sensitivity of 100% (95% Confidence Interval [CI], 92-100) and specifity of 100% (95% CI, 89-100) for our PSCS-CoV2 method. We determined our protocol has a limit of detection of 1/10,000 for DTS from a COVID-19 patient. In addition, we show field data of the PSCS-CoV2 method on a college campus. Ten of the twelve volunteers (N1 < 30) that we tested as positive were subsequently tested positive by an independent laboratory. Finally, we show proof of concept of a pooling strategy to test for COVID-19, and recommend pool sizes of four if the positivity rate is less than 15%. Conclusion and Relevance: We developed a DTS-based protocol for COVID-19 testing with high sensitivity and specificity. This protocol can be used by non-debilitated adults without the assistance of another adult, or by non-debilitated children with the assistance of a parent or guardian. We also discuss pooling strategies based on estimated positivity rates to help conserve resources, time, and increase throughput. The PSCS-CoV2 method can be a key component of community-wide efforts to slow the spread of COVID-19.

20.
Transbound Emerg Dis ; 69(5): e2731-e2744, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1932580

ABSTRACT

The transmission of coronavirus disease-2019 (COVID-19) epidemic is a global emergency, which is worsened by the genetic mutations of SARS-CoV-2. However, till date, few statistical studies have researched the COVID-19 spread patterns in terms of the variant cases. Hence, this paper aims to explore the associated risk factors of Delta variant, the most contagious strain of COVID-19. The study collected the state-level COVID-19 Delta variant cases in the United States during a 12-week period and included potential environmental, socioeconomic, and public prevention factors as independent variables. Instead of regarding the covariate effects as constant, this paper proposes a flexible Bayesian hierarchical model with spatio-temporally varying coefficients to account for data heterogeneity. The method enables us to cluster the states into distinctive groups based on the temporal trends of the coefficients and simultaneously identify significant risk factors for each cluster. The findings contribute novel insight into the dynamics of covariate effects on the COVID-19 Delta variant over space and time, which could help the government develop targeted prevention measures for vulnerable regions based on the selected risk factors.


Subject(s)
COVID-19 , Animals , Bayes Theorem , COVID-19/epidemiology , COVID-19/veterinary , Risk Factors , SARS-CoV-2/genetics , Spatio-Temporal Analysis , United States/epidemiology
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