bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of testing and infection prevention and control strategies on within-hospital transmission dynamics of COVID-19 in English hospitals
Authors: Evans Stephanie , Agnew Emily , Vynnycky Emilia , Stimson James , Bhattacharya Alex , Rooney Christopher , Warne Ben , Robotham Julie 
Published: May 2021

Nosocomial transmission of SARS-CoV-2 is a key concern, and evaluating the effect of testing and infection prevention and control strategies is essential for guiding policy in this area. Using a within-hospital SEIR transition model of SARS-CoV-2 in a typical English hospital, we estimate that between 9 March 2020 and 17 July 2020 approximately 20% of infections in inpatients, and 73% of infections in healthcare workers (HCWs) were due to nosocomial transmission. Model results suggest that placing suspected COVID-19 patients in single rooms or bays has the potential to reduce hospital-acquired infections in patients by up to 35%. Periodic testing of HCWs has a smaller effect on the number of hospital-acquired COVID-19 cases in patients, but reduces infection in HCWs by as much as 37% and results in only a small proportion of staff absences (approx. 0.3% per day). This is considerably less than the 20–25% of staff that have been reported to be absent from work owing to suspected COVID-19 and self-isolation. Model-based evaluations of interventions, informed by data collected so far, can help to inform policy as the pandemic progresses and help prevent transmission in the vulnerable hospital population.
This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.
The population attributable fraction of cases due to gatherings and groups with relevance to COVID-19 mitigation strategies
Authors: Brooks-Pollock Ellen , Read Jonathan M. , House Thomas , Medley Graham F. , Keeling Matt J. , Danon Leon 
Published: May 2021

Many countries have banned groups and gatherings as part of their response to the pandemic caused by the coronavirus, SARS-CoV-2. Although there are outbreak reports involving mass gatherings, the contribution to overall transmission is unknown. We used data from a survey of social contact behaviour that specifically asked about contact with groups to estimate the population attributable fraction (PAF) due to groups as the relative change in the basic reproduction number when groups are prevented. Groups of 50+ individuals accounted for 0.5% of reported contact events, and we estimate that the PAF due to groups of 50+ people is 5.4% (95% confidence interval 1.4%, 11.5%). The PAF due to groups of 20+ people is 18.9% (12.7%, 25.7%) and the PAF due to groups of 10+ is 25.2% (19.4%, 31.4%). Under normal circumstances with pre-COVID-19 contact patterns, large groups of individuals have a relatively small epidemiological impact; small- and medium-sized groups between 10 and 50 people have a larger impact on an epidemic.
This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.
Segmentation and shielding of the most vulnerable members of the population as elements of an exit strategy from COVID-19 lockdown
Authors: van Bunnik Bram A. D. , Morgan Alex L. K. , Bessell Paul R. , Calder-Gerver Giles , Zhang Feifei , Haynes Samuel , Ashworth Jordan , Zhao Shengyuan , Cave Roo Nicola Rose , Perry Meghan R. , Lepper Hannah C. , Lu Lu , Kellam Paul , Sheikh Aziz , Medley Graham F. , Woolhouse Mark E. J. 
Published: May 2021

This study demonstrates that an adoption of a segmenting and shielding strategy could increase the scope to partially exit COVID-19 lockdown while limiting the risk of an overwhelming second wave of infection. We illustrate this using a mathematical model that segments the vulnerable population and their closest contacts, the ‘shielders’. Effects of extending the duration of lockdown and faster or slower transition to post-lockdown conditions and, most importantly, the trade-off between increased protection of the vulnerable segment and fewer restrictions on the general population are explored. Our study shows that the most important determinants of outcome are: (i) post-lockdown transmission rates within the general and between the general and vulnerable segments; (ii) fractions of the population in the vulnerable and shielder segments; (iii) adherence to protective measures; and (iv) build-up of population immunity. Additionally, we found that effective measures in the shielder segment, e.g. intensive routine screening, allow further relaxations in the general population. We find that the outcome of any future policy is strongly influenced by the contact matrix between segments and the relationships between physical distancing measures and transmission rates. This strategy has potential applications for any infectious disease for which there are defined proportions of the population who cannot be treated or who are at risk of severe outcomes.
This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.
Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave
Authors: Birrell Paul , Blake Joshua , van Leeuwen Edwin , Gent Nick , De Angelis Daniela 
Published: May 2021

England has been heavily affected by the SARS-CoV-2 pandemic, with severe ‘lockdown’ mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management throughout the first wave. Estimates on the 10 May showed lockdown had reduced transmission by 75%, the reproduction number falling from 2.6 to 0.61. This regionally varying impact was largest in London with a reduction of 81% (95% credible interval: 77–84%). Reproduction numbers have since then slowly increased, and on 19 June the probability of the epidemic growing was greater than 5% in two regions, South West and London. By this date, an estimated 8% of the population had been infected, with a higher proportion in London (17%). The infection-to-fatality ratio is 1.1% (0.9–1.4%) overall but 17% (14–22%) among the over-75s. This ongoing work continues to be key to quantifying any widespread resurgence, should accrued immunity and effective contact tracing be insufficient to preclude a second wave.This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.
Use of medicinal plants for COVID-19 prevention and respiratory symptom treatment during the pandemic in Cusco, Peru: A cross-sectional survey
Authors: Villena-Tejada Magaly , Vera-Ferchau Ingrid , Cardona-Rivero Anahí , Zamalloa-Cornejo Rina , Quispe-Florez Maritza , Frisancho-Triveño Zany , Abarca-Melendez Rosario C. , Alvarez-Sucari Susan G. , Mejia Christian R. , Yañez Jaime A. 
Published: May 2021

ABSTRACTBackgroundThe burden of the COVID-19 pandemic in Peru has led to people seeking alternative treatments as preventives and treatment options such as medicinal plants. This study aimed to assess factors associated with the use of medicinal plants as preventive or treatment of respiratory symptom related to COVID-19 during the pandemic in Cusco, Peru.MethodA web-based cross-sectional study was conducted on general public (20- to 70-year-old) from August 31 to September 20, 2020. Data were collected using a structured questionnaire via Google Forms, it consisted of an 11-item questionnaire that was developed and validated by expert judgment using Aiken’s V (Aiken’s V > 0.9). Both descriptive statistics and bivariate followed by multivariable logistic regression analyses were conducted to assess factors associated with the use of medicinal plants for COVID-19 prevention and respiratory symptom treatment during the pandemic. Prevalence ratios (PR) with 95% Confidence Interval (CI), and a P-value of 0.05 was used to determine statistical significance.ResultsA total of 1,747 respondents participated in the study, 80.2% reported that they used medicinal plants as preventives, while 71% reported that they used them to treat respiratory symptoms. At least, 24% of respondents used medicinal plants when presenting with two or more respiratory symptoms, while at least 11% used plants for malaise. For treatment or prevention, the multivariate analysis showed that most respondents used eucalyptus (p < 0.001 for both), ginger (p < 0.022 for both), spiked pepper (p < 0.003 for both), garlic (p = 0.023 for prevention), and chamomile (p = 0.011 for treatment). The respondents with COVID-19 (p < 0.001), at older ages (p = 0.046), and with a family member or friend who had COVID-19 (p < 0.001) used more plants for prevention. However, the respondents with technical or higher education used less plants for treatment (p < 0.001).ConclusionThere was a significant use of medicinal plants for both prevention and treatment, which was associated with several population characteristics and whether respondents had COVID-19.
Medical brain drain from Western Balkan and Croatia to Germany and Austria – an approach to the digital demography
Authors: Jurić Tado 
Published: May 2021

ABSTRACTBackgroundIn this paper, we show that the tools of digital demography, such as the Google Trends (GT) can be very useful for determining, estimating, and predicting the migration of healthcare workers as well as for further predictions of the general interest in emigration.ObjectiveThis paper analyses recent trends in the mobility of health workers in Europe and focuses specifically on the patterns of mobility among medical doctors and nurses from Western Balkans and Croatia to Germany and Austria. It identifies the drivers of this mobility and shows how to predict further migration of this stuff. In the last 10 years, every fourth nurse has emigrated from the Croatian health system -to Germany, while according to projections Croatia will lose as much as 1/3 of all doctors in the next five years.MethodsA special problem in the analysis of the emigration of healthcare workers from the Western Balkans and Croatia is the fact that there is no system for monitoring this process. Official data up to three years late, and exist only for persons who have deregistered from the state system. The basic methodological concept of our approach is to monitor the digital trace of language searches with the Google Trends analytical tool (trends.google.com). Initially, keywords were chosen by brainstorming possible words that we believed to be predictive, specific, and common enough for use in the forecasting of migration of healthcare professionals. To standardize the data, we requested the data for the period from Dec. 2015 to Dec. 2020 and divided the keyword frequency for each word giving us a search frequency index. Then we have compared searches with official statistics to prove the significations of results and correlations.ResultsIn Croatia search activities using GT for terms such as ‘‘Bewerbung” (job application), “Arbeit” (work), “Krankenschwester, Bewerbung” (nurses, job application) correlate strongly with officially Germans data for emigrants from Croatia. The data collected by this method correlate with official data, which allows reliable forecasts for the future. Austria will soon become one of the most desirable emigration destinations for Croats, especially for healthcare workers. Simultaneously, the emigration of Croatian citizens to Germany will continue.ConclusionUnderstanding why health care personnel emigrate from Western Balkans and Croatia and which are the consequences of this process are key to enable state agencies and government to develop optimal intervention strategies to retain medical staff. The benefit of this method is reliable estimates that can enable state agencies and the government to prepare and better respond to a possible shortage of healthcare workers and to protect the functioning of the health system.
Estimating the SARS-CoV-2 infected population fraction and the infection-to-fatality ratio: A data-driven case study based on Swedish time series data
Authors: Wacker Andreas , Jöud Anna , Bernhardsson Bo , Gerlee Philip , Gustafsson Fredrik , Soltesz Kristian 
Published: May 2021

AbstractAimTo estimate the COVID-19 infection-to-fatality ratio (IFR), infection-to-case ratio (ICR), and infection-to-ICU admission ratio (IIAR) in Sweden; to suggest methods for time series reconstruction and prediction.MethodsWe optimize a set of simple finite impulse response (FIR) models comprising of a scaling factor and time-delay between officially reported cases, ICU admissions and deaths time series using the least squares method. Combined with randomized PCR study results, we utilize this simple model to estimate the total number of infections in Sweden, and the corresponding IFR.ResultsThe model class provides a good fit between ICU admissions and deaths throughout 2020. Cases fit consistently from July 2020, by when PCR tests had become broadly available. We observe a diminished IFR in late summer as well as a strong decline during 2021, following the launch of a nation-wide vaccination program. The total number of infections during 2020 is estimated to 1.3 million.ConclusionsA FIR model with a delta filter function describes the evolution of epidemiological data in Sweden well. The fact that we found IFR, ICR and IIAR constant over large parts of 2020 is in contrast with claims of healthcare adaptation or mutated virus variants importantly affecting these ratios. The model allows us to retrospectively estimate the COVID-19 epidemiological trajectory, and conclude that Sweden was far from herd immunity by the end of 2020.
COVID-19 vaccine uptake in United States counties: geospatial vaccination patterns and trajectories towards herd immunity
Authors: Chernyavskiy Pavel , Richardson Jeanita W. , Ratcliffe Sarah J. 
Published: May 2021

AbstractFollowing the COVID-19 pandemic, safe and effective vaccines were developed and authorized for use in the general population. Studying factors that encourage community acceptance of these vaccines is needed to prevent proliferation of SARS-CoV-2 variants, to safely relax local restrictions, and to return to pre-pandemic living conditions. To our knowledge, United States (US) county-level disparities in vaccination are yet to be investigated. Our data span February - May 2021 across 3138 US counties. We consider percentage of residents with at least one dose of an authorized COVID vaccine as the outcome. Spatio-temporal models were used to determine associations of vaccination rates with time-fixed and time-varying covariates. Spatial variability was modelled via Conditional Auto-regressive models; county trajectories over time were specified using random slopes. Greater vaccination rates occur in counties with older residents, high educational attainment, and high proportion of minority residents. Vaccination rates change with COVID risk metrics, suggesting continued slowing of vaccine uptake due to decreasing incidence and infection rates. County effects reveal strong regional patterns in average vaccination rates and trajectories. Although local herd immunity can be expected in August 2021 for counties with typical uptake rates, these counties are clustered in relatively few areas of the country.
Pan[dem]ic! Rational Risk Avoidance During a Health Pandemic
Authors: Okeke Edward N. 
Published: May 2021

AbstractDuring a health pandemic health workers have to balance two competing objectives: their own welfare vs. that of their patients. Intuitively, attending to sick patients during a pandemic poses risks to health workers because some of these patients could be infected. One way to reduce risk is by reducing contact with patients. These changes could be on the extensive margin, e.g., seeing fewer patients; or, more insidiously, on the intensive margin, by reducing the duration/intensity of contact. This paper studies risk avoidance behavior during the Covid-19 pandemic and examines implications for patient welfare. Using primary data on thousands of patient-provider interactions between January 2019 and October 2020 in Nigeria, I present evidence of risk compensation by health workers along the intensive margin. For example, the probability that a patient receives a physical examination has dropped by about a third. I find suggestive evidence of negative effects on health outcomes.
UV-A and UV-B Can Neutralize SARS-CoV-2 Infectivity
Authors: Biasin Mara , Strizzi Sergio , Bianco Andrea , Macchi Alberto , Utyro Olga , Pareschi Giovanni , Loffreda Alessia , Cavalleri Adalberto , Lualdi Manuela , Trabattoni Daria , Tacchetti Carlo , Mazza Davide , Clerici Mario 
Published: May 2021

ABSTRACTWe performed an in-depth analysis of the virucidal effect of discrete wavelengths: UV-C (278 nm), UV-B (308 nm), UV-A (366 nm) and violet (405 nm) on SARS-CoV-2. By using a highly infectious titer of SARS-CoV-2 we observed that the violet light-dose resulting in a 2-log viral inactivation is only 10−4 times less efficient than UV-C light. Moreover, by qPCR and fluorescence in situ hybridization (FISH) approach we verified that the viral titer typically found in the sputum of COVID-19 patients can be completely inactivated by the long UV-wavelengths corresponding to UV-A and UV-B solar irradiation. The comparison of the UV action spectrum on SARS-CoV-2 to previous results obtained on other pathogens suggests that RNA viruses might be particularly sensitive to long UV wavelengths. Our data extend previous results showing that SARS-CoV-2 is highly susceptible to UV light and offer an explanation to the reduced incidence of SARS-CoV-2 infection seen in the summer season.SYNOPSISUV-A, UV-B and violet wavelengths kill SARS-CoV-2, supporting the sterilizing effects of the solar pump on human pathogens and the explanation of the seasonality of the COVID-19 pandemic.
The UGT2A1/UGT2A2 locus is associated with COVID-19-related anosmia
Authors: Shelton Janie F. , Shastri Anjali J. ,   The 23andMe COVID-19 Team, Aslibekyan Stella , Auton Adam 
Published: May 2021

AbstractLoss of sense of smell is a characteristic symptom of infection with SARS-CoV-2. However, specific mechanisms linking infection with loss of smell are poorly understood. Using self-reported symptom data from the 23andMe COVID-19 study, we describe the demographic patterns associated with COVID-19 related anosmia, and find the symptom is more often reported in women and younger respondents, and less often by those of East Asian and African American ancestry compared to those of European ancestry. We ran a trans-ethnic genome-wide association study (GWAS) comparing loss of smell or taste (n=47,298) with no loss of smell or taste (n=22,543) among those with a positive SARS-CoV-2 test result. We identified an association (rs7688383) in the vicinity of the UGT2A1 and UGT2A2 genes (OR=1.115, p-value=4×10−15), which have been linked to olfactory function. These results may shed light on the biological mechanisms underlying COVID-19 related anosmia.
Observational Study on 255 Mechanically Ventilated Covid Patients at the Beginning of the USA Pandemic
Authors: Smith Leon G. , Mendoza Nicolas , Dobesh David , Smith Stephen M. 
Published: May 2021

AbstractIntroductionThis observational study looked at 255 COVID19 patients who required invasive mechanical ventilation (IMV) during the first two months of the US pandemic. Through comprehensive, longitudinal evaluation and new consideration of all the data, we were able to better describe and understand factors affecting outcome after intubation.MethodsAll vital signs, laboratory values, and medication administrations (time, date, dose, and route) were collected and organized. Further, each patient’s prior medical records, including PBM data and available ECG, were reviewed by a physician. These data were incorporated into time-series database for statistical analysis.ResultsBy discharge or Day 90, 78.2% of the cohort expired. The most common pre-existing conditions were hypertension, (63.5%), diabetes (59.2%) and obesity (50.4%). Age correlated with death. Comorbidities and clinical status on presentation were not predictive of outcome. Admission markers of inflammation were universally elevated (>96%). The cohort’s weight range was nearly 7-fold. Causal modeling establishes that weight-adjusted HCQ and AZM therapy improves survival by over 100%. QTc prolongation did not correlate with cumulative HCQ dose or HCQ serum levels.DiscussionThis detailed approach gives us better understanding of risk factors, prognostic indicators, and outcomes of Covid patients needing IMV. Few variables were related to outcome. By considering more factors and using new methods, we found that when increased doses of co-administered HCQ and AZM were associated with >100% increase in survival. Comparison of absolute with weight-adjusted cumulative doses proves administration ≥80 mg/kg of HCQ with > 1 gm AZM increases survival in IMV-requiring Covid patients by over 100%. According to our data, HCQ is not associated with prolongation. Studies, which reported QTc prolongation secondary to HCQ, need to be re-evaluated more stringently and with controls.The weight ranges of Covid patient cohorts are substantially greater than those of most antibiotic RCTs. Future clinical trials need to consider the weight variance of hospitalized Covid patients and need to study therapeutics more thoughtfully.
f-statistics estimation and admixture graph construction with Pool-Seq or allele count data using the R package poolfstat
Authors: Gautier Mathieu , Vitalis Renaud , Flori Laurence , Estoup Arnaud 
Published: May 2021

AbstractBy capturing various patterns of the structuring of genetic variation across populations, f -statistics have proved highly effective for the inference of demographic history. Such statistics are defined as covariance of SNP allele frequency differences among sets of populations without requiring haplotype information and are hence particularly relevant for the analysis of pooled sequencing (Pool-Seq) data. We here propose a reinterpretation of the F (and D) parameters in terms of probability of gene identity and derive from this unified definition unbiased estimators for both Pool-Seq and standard allele count data obtained from individual genotypes. We implemented these estimators in a new version of the R package poolfstat, which now includes a wide range of inference methods: (i) three-population test of admixture; (ii) four-population test of treeness; (iii) F4-ratio estimation of admixture rates; and (iv) fitting, visualization and (semi-automatic) construction of admixture graphs. A comprehensive evaluation of the methods implemented in poolfstat on both simulated Pool-Seq (with various sequencing coverages and error rates) and allele count data confirmed the accuracy of these approaches, even for the most cost-effective Pool-Seq design involving low sequencing coverages. We further analyzed a real Pool-Seq data made of 14 populations of the invasive species Drosophila suzukii which allowed refining both the demographic history of native populations and the invasion routes followed by this emblematic pest. Our new package poolfstat provides the community with a user-friendly and efficient all-in-one tool to unravel complex population genetic histories from large-size Pool-Seq or allele count SNP data.