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Objective: To evaluate the effectiveness of SARS-CoV-2 testing on shortening the duration of quarantines for COVID-19 and to identify the most effective choices of testing schedules. Design: We performed extensive simulations to evaluate the performance of quarantine strategies when one or more SARS-CoV-2 tests were administered during the quarantine. Simulations were based on statistical models for the transmissibility and viral loads of SARS-CoV-2 infections and the sensitivities of available testing methods. Sensitivity analyses were performed to evaluate the impact of perturbations in model assumptions on the outcomes of optimal strategies. Results: We found that SARS-CoV-2 testing can effectively reduce the length of a quarantine without compromising safety. A single RT-PCR test performed before the end of quarantine can reduce quarantine duration to 10 days. Two tests can reduce the duration to 8 days, and three highly sensitive RT-PCR tests can justify a 6-day quarantine. More strategic testing schedules and longer quarantines are needed if tests are administered with less sensitive RT-PCR tests or antigen tests. Shorter quarantines can be utilized for applications that tolerate a residual post-quarantine transmission risk comparable to a 10-day quarantine. Conclusions: Testing could substantially reduce the length of isolation, reducing the physical and mental stress caused by lengthy quarantines. With increasing capacity and lowered costs of SARS-CoV-2 tests, test-assisted quarantines could be safer and more cost-effective than 14-day quarantines and warrant more widespread use. The dataset consists of PQTR (post-quarantine transmission risk) and observed test sensitivity for test-assisted quarantine strategies with different duration and test strategies, under the assumption of either mixed and simultaneous onset of infection. PQTR is calculated as the occurrence of failures (infecting others after released from quarantine) of at least 500K (mostly 1M) replicate simulations using the simulation model described in the manuscript. The dataset is in EXCEL format. Users can open it and search for interested quarantine strategies using the filter feature of EXCEL.

Postural tachycardia syndrome (POTS) is a form of autonomic dysregulation. There is increasing evidence that the etiology may be immune-mediated in a subgroup of patients. Patients with POTS often experience an exacerbation of their symptoms associated with infections and often fear the same symptom aggravation after vaccination. With this data we conducted a study to describe the tolerability of mRNA vaccines against COVID-19 and the consequences of a COVID-19 infection on POTS symptoms in our cohort of patients with neuropathic POTS.We conducted a standardized, checklist-based interview with 23 patients and recorded the acute side effects of mRNA vaccination, acute symptoms of COVID-19 infection as well as the effects of vaccination and COVID-19 infection on POTS symptoms. The following side effects were assessed in their presence (yes/no) and duration (days): fever, shivering, fatigue, headache, joint pain, muscle pain, nausea, emesis, diarrhea, and reaction at injection site (pain, swelling and cutaneous reaction). For COVID-19 infection, the following additional symptoms were queried: coughing, sore throat, rhinorrhea, breathlessness, loss of taste, loss of smell and chest pain. For each symptom, the presence (yes/no), severity (mild, moderate, severe) and duration (in days) were evaluated. Furthermore, the duration of the infection, need for hospitalization and incapacity for work were assessed. To assess possible exacerbation of POTS symptoms, the presence (yes/no), severity (mild, moderate, severe; for COVID-19 infection only) and duration of symptom exacerbation (in days) for the following symptoms were evaluated: dizziness, nausea, weakness, palpitations, lightheadedness, tremulousness, blurred vision, concentration difficulties, memory difficulties, orthostatic leg and/or arm pain, gastrointestinal symptoms, sleep disturbances, restless legs syndrome and orthostatic headache. Our observations suggest that mRNA vaccines are not associated with a higher frequency of acute side effects in patients with POTS. Symptom exacerbation as a consequence of mRNA vaccination seems to be less frequent and of shorter duration compared to patients who suffered a COVID-19 infection. This study was carried out in accordance with the recommendations of the local ethics committee (Kantonale Ethikkommission Bern, Switzerland, project-ID: 2021-02115; 02.11.2021). We conducted a standardized checklist-based interview. Data analysis was descriptive.

Datasets: DS0: Study-Level Files DS1: Round 1 Interview Info Data DS2: Round 1 Knowledge Data DS3: Round 1 Employment and Income Data DS4: Round 1 Access Food and Food Security Data DS5: Round 1 Safety Nets 1 Data DS6: Round 1 Safety Nets 2 Data DS7: Round 1 Interview Result Data DS8: Round 1 Roster Data DS9: Round 2 Interview Info Data DS10: Round 2 Access Food and Food Security Data DS11: Round 2 Access Health Data DS12: Round 2 Access to Finance Data DS13: Round 2 Access to Education Data DS14: Round 2 Education and Childcaring Data DS15: Round 2 Coping Mechanisms 1 Data DS16: Round 2 Coping Mechanisms 2 Data DS17: Round 2 Concerns Data DS18: Round 2 Interview Result Data DS19: Round 2 Roster Data DS20: Round 3 Interview Information Data DS21: Round 3 Knowledge Data DS22: Round 3 Employment and Income Data DS23: Round 3 Access Food and Food Insecurity Data DS24: Round 3 Access Health Data DS25: Round 3 Safety Net 1 Data DS26: Round 3 Safety Net 2 Data DS27: Round 3 Interview Result Data DS28: Round 3 Roster Data DS29: Round 4 Interview Information Data DS30: Round 4 Digital Transaction 1 Data DS31: Round 4 Digital Transaction 2 Data DS32: Round 4 Access to Health 1 Data DS33: Round 4 Access to Health 2 Data DS34: Round 4 Access to Education Data DS35: Round 4 Coping Mechanism 1 Data DS36: Round 4 Coping Mechanism 2 Data DS37: Round 4 Concerns Data DS38: Round 4 Interview Result Data DS39: Round 4 Roster Data DS40: Round 5 Interview Information Data DS41: Round 5 Employment and Income Data DS42: Round 5 Access Food and Food Insecurity Data DS43: Round 5 Access to Health 1 Data DS44: Round 5 Access to Health 2 Data DS45: Round 5 Subjective Welfare/Concerns Data DS46: Round 5 Safety Net 1 Data DS47: Round 5 Safety Net 2 Data DS48: Round 5 Interview Result Data DS49: Round 5 Roster Data DS50: Round 6 Interview Information Data DS51: Round 6 Employment and Income Data DS52: Round 6 Food Security Data DS53: Round 6 Access to Health 1 Data DS54: Round 6 Access to Health 2 Data DS55: Round 6 Coping Mechanism 1 Data DS56: Round 6 Coping Mechanism 2 Data DS57: Round 6 Safety-Net 1 Data DS58: Round 6 Safety-Net 2 Data DS59: Round 6 Interview Result Data DS60: Round 6 Roster Data DS61: Round 7 Interview Information Data DS62: Round 7 Employment and Income Data DS63: Round 7 Food Security Data DS64: Round 7 Access to Health 1 Data DS65: Round 7 Access to Health 2 Data DS66: Round 7 Access to Education Data DS67: Round 7 Access to Education Household Data DS68: Round 7 Interview Result Data DS69: Round 7 Roster Data DS70: PMT Results Data DS71: Rounds 1-6 Weight Data Household weights were first calculated independently by each initial survey and then combined altogether afterward. For this approach to be properly applied without potential bias, there should not be overlapped survey areas across different surveys. The household weights were calculated for both cross-section for each round and panel for all rounds of the survey. In each round of the survey, the initial sampling weight was calculated following the original sampling method of the survey from which the sampled households were drawn. A sampling weight trimming using the mean and standard deviation of the weights was then conducted to reduce weight variability. In particular, the weight trimming was applied to some outlier weights (only a small proportion of the samples), while keeping the total of the weights remaining the same. Afterwards, the weights were calibrated using a raking method to ensure the total estimates of the households with respect to designated variables were comparable with the population estimates of those variables from the National Household Survey of Socio-economic (SUSENAS) 2019. The designated variables included region (DKI Jakarta, Java Non-DKI Jakarta Urban/Rural, Outside Java Urban/Rural), gender of household's head, and level of education of household's head (junior secondary and lower, senior secondary, and tertiary). The attrition occurred when respondents were not able to be interviewed, which was mostly because their phones were unreachable or unanswered. A test for whether attrition was random showed that the dropped households were not associated with key households' characteristics, such as household head age, gender, education, region (DKI Jakarta, Java-non DKI Jakarta, and Outside Java), and wealth status. However, there was a weak association between households' participation and the area where they reside, as households in urban area were less likely to participate in the follow-up surveys than those in rural areas. The difference in participation rates between urban and rural samples was taken into account in the survey weight calculation. Therefore, for analysis requiring panel households, attrition bias is not a concern when interpreting changes between rounds. Three stages of sampling strategies were applied. For the first stage, districts (as primary sampling unit (PSU)) were selected based on probability proportional to size (PPS) systematic sampling in each stratum, with the probability of selection being proportional to the estimated number of households based on the National Household Survey of Socio-economic (SUSENAS) 2019 data. Prior to the selection, districts were sorted by provincial code. In the second stage, villages (as secondary sampling unit (SSU)) were selected systematically in each district, with probability of selection being proportional to the estimated number of households based on the Village Potential Census (PODES) 2018 data. Prior to the selection, villages were sorted by sub-district code. In the third stage, the number of households was selected systematically in each selected village. Prior to the selection, all households were sorted by implicit stratification, that is gender and education level of the head of households. If the primary selected households could not be contacted or refused to participate in the survey, these households were replaced by households from the same area where the non-response households were located and with the same gender and level of education of households' head, in order to maintain the same distribution and representativeness of sampled households as in the initial design. Response Rates: The actual sample of households in the first round was 4,338 households or 85 percent of the 5,100 target households. However, the response rates in the following rounds are higher than expected, making the sampled households successfully interviewed in Round 2 4,119 (95% of Round 1 samples), and in Rounds 3, 4, 5, and 6, 4,067 (94%), 3,953 (91%), 3,686 (85%), and 3,471 (80%) respectively. The number of balanced panel households up to Rounds 3, 4, 5, and 6 are 3,981 (92%), 3,794 (87%), 3,601 (83%), 3,320 (77%) respectively. This study covers the following topics: Knowledge and behavior (Rounds 1, 3) Employment and income loss (Rounds 1, 3, 5, 6, 7) Food security (Rounds 1, 2, 3, 4, 5, 6, 7) Access to health services (Rounds 2, 3, 4, 5, 6, 7) Digital transactions (Rounds 2, 4) Education (Rounds 2, 4, 7) Coping mechanisms (Rounds 2, 4, 6, 7) Concerns/Subjective Welfare (Rounds 2, 4, 5) Social safety-nets (Rounds 1, 3, 5, 6) Household roster (Rounds 1, 2, 3, 4, 5, 6, 7; Full updates only in R1 and R4) This study is part of an effort by the World Bank, which launched a quick-deploying high-frequency phone-monitoring survey of households to generate near real-time insights on the socio-economic impact of COVID-19 on households. The survey is part of a World Bank-supported global effort to support countries in their data collection efforts to monitor the impacts of COVID-19. computer-assisted telephone interview (CATI)For additional information on the COVID-19 High Frequency Phone Survey of Households study, please visit the World Bank website. The purpose of this study is to provide insights into the socio-economic impact of COVID-19 on households in Indonesia. Smallest Geographic Unit: district

The emergence of newer variants with the immune escape potential raises concerns about breakthroughs and re-infections resulting in future waves of infection. We examined the protective effect of prior COVID-19 disease and vaccination on infection rates among a cohort of healthcare workers (HCW) in South India during the second wave driven mainly by the delta variant. Symptomatic HCWs were routinely tested by RT-PCR as per institutional policy. Vaccination was offered to all HCWs in late January, and the details were documented. We set up a non-concurrent cohort to document infection rates and estimated protective efficacy of prior infection and vaccination between 16th Apr to 31st May 2021, using a Cox proportional hazards model with time-varying covariates adjusting for daily incidence. Between June 2020 and May 2021, 2735 (23.9%) of 11,405 HCWs were infected, with 1412, including 32 re-infections, reported during the second wave. 6863 HCWs received two doses of vaccine and 1905 one dose. The protective efficacy of prior infection against symptomatic infection was 86.0% (95% CI 76.7% - 91.6%). Vaccination combined with prior infection provided 91.1% (95% CI 84.1% - 94.9%) efficacy. In the absence of prior infection, vaccine efficacy against symptomatic infection during the second wave was 31.8% (95% CI 23.5% – 39.1%). Prior infection provided substantial protection against symptomatic re-infection and severe disease during a delta variant-driven second wave in a cohort of health care workers. This non-concurrent cohort study was conducted among the staff of a tertiary care teaching hospital in South India. The demographic, clinical and exposure variables and vaccination history were prospectively documented in an electronic database from all those presenting for COVID testing. All immunization was documented along with the date of vaccination, type of vaccine, and any adverse events. Linking the SARS-COV2 testing data set with the vaccination and administrative payroll information, we established a non-concurrent cohort that included all current employees. Every employee has a unique employment ID which was used to match across the datasets. Two investigators independently assessed the datasets to verify the accuracy of the data and linkages between the datasets. Participants were categorized into four risk groups based on their prior infection and vaccination status, namely, the unvaccinated and previously uninfected; vaccinated and previously uninfected; unvaccinated and previously infected, and vaccinated and previously infected. A sensitivity analysis that excluded participants who had received a single dose was not significantly different from the one that included those who received one dose as unvaccinated. Hence the binary classification of vaccinated and unvaccinated was based on the completion of two doses of vaccination 2 weeks after the second dose. Kaplan Meier Survival analysis was done with failure defined as the acquisition of infection during the analysis period. A Log-rank test was performed to compare the survival curves across the four risk groups. We developed a Cox-proportional hazards (PH) model with time-varying covariates adjusting for smoothed daily incidence of COVID-19 and potential confounders (S1 table). The model included participant age, type of work, sex, history of prior infection, and vaccination, as epidemiologically relevant factors. The model was tested for the proportional-hazards assumption on Schoenfeld's residuals and the PH assumption was not violated (p-value - 0.134). Efficacy of prior infection and vaccines to prevent symptomatic infection in the study period were calculated as VE= 1- hazard ratio from the Cox proportional hazard model. All data analysis was performed using Stata 15.1 (Statacorp LLC, College Station, TX).

For each round, a stratified random sample of approximately 7,500 adults ages 18 to 64 is drawn from the KnowledgePanel, a probability-based, nationally representative Internet panel maintained by Ipsos. The WBNS includes an oversample of adults with household incomes under 150 percent of the federal poverty level to improve the precision of estimates for this group. Current recruitment into the KnowledgePanel is based on an address-based sampling frame that covers nearly all residential addresses in the United States. In earlier periods, recruitment was carried out by telephone based on random-digit dialing sampling techniques. Approximately 55,000 U.S. households participate in the panel, including those with and without internet access. Web-enabled devices and internet access are provided to panel members if needed, and respondents can complete the online surveys in English or Spanish. In December 2017, the Urban Institute launched the Well-Being and Basic Needs Survey (WBNS), a nationally representative, internet-based survey of non-elderly adults designed to monitor changes in individual and family well-being during a time when policymakers are considering significant changes to federal safety net programs serving low-income families. The 2020 round of the survey collects information on a broad array of topics related to health, material hardship, and the safety net, including health insurance, housing, food security, employment, family income, program participation, family financial security, disability, school enrollment, child care, COVID-19 vaccine attitudes, the impact of the COVID-19 pandemic on family employment, and immigration issues. The WBNS weights reflect the probability of sample selection from the KnowledgePanel and post-stratification to the characteristics of nonelderly adults in the United States based on benchmarks from the Current Population Survey and American Community Survey for the following measures: age by gender; race and ethnicity; educational attainment; presence of children in the household; census region; residence in a metropolitan area; homeownership status; family income as a percentage of the federal poverty level; family composition (married or living with a partner by presence of children in the family); primary language; and internet access by age. web-based surveyUsers seeking the Noncitizen-Oversample (DS2) and Immigrant Module (DS3) datasets must enter a restricted data agreement with ICPSR to gain access to those datasets.This collection is related to the Well-Being and Basic Needs Survey, 2017 (ICPSR 37513), the Well-Being and Basic Needs Survey, 2018 (ICPSR 37653), and the Well-Being and Basic Needs Survey, 2019 (ICPSR 38044).Additional information about the survey is available at the Well-Being and Basic Needs Survey website. The Urban Institute launched the Well-Being and Basic Needs Survey (WBNS) to monitor changes in individual and family health and well-being as policymakers make changes to federal safety net programs and the labor market continues to evolve. Datasets: DS0: Study-Level Files DS1: Public-Use Data DS2: Noncitizen-Oversample Restricted-Use Data DS3: Immigrant Module Restricted-Use Data Response Rates: The WBNS response rate is roughly three to four percent each round. Household population aged 18-64. Smallest Geographic Unit: Census region

By March 2020, the COVID-19 pandemic had reached Greece, forcing the Greek government to enforce lockdown for two months. While governmental measures included banning citizens' mobility, except for a six-bullets catalogue, the church was excluded, remaining open for its believers. That resulted in an official clash, having on the one side, the state and the scientists, while on the other was the official church. After the decline in the number of COVID-19 cases during the summer period, the governmental decision of enforcing the use of masks indoors triggered the rise of anti-systemic and anti-governmental rhetoric. Having the above in mind, we aim to apply a grounded theory methodology, drawing our data from two derivations: the official announcements of the church and the Greek government during the examined period; and the scientific approach to the Church's and anti-mask supporters stand. Consequently, our main research question attempts to answer how the anti-systemic rhetoric of Greek society has been transformed during the pandemic crisis.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures. Related Article: M. Victoria Jiménez, Ana I. Ojeda-Amador, Raquel Puerta-Oteo, Joaquín Martínez-Sal, Vincenzo Passarelli, Jesús J. Pérez-Torrente|2022|Molecules|27|7666|doi:10.3390/molecules27227666