Estimated effectiveness of symptom and risk screening to prevent the spread of COVID-19

First Long-Time Airborne Fungal Spores Study in Dublin, Ireland (1978–1980)

Ambient fungal spores within the atmosphere can contribute to a range of negative human, animal and plant health conditions and diseases. However, trends in fungal spore seasonality, species prevalence, and geographical origin have been significantly understudied in Ireland. Previously unpublished data from the late 1970s have recently been collected and analysed to establish historical fungal spore trends/characteristics for Dublin. Historical spore concentrations were largely dominated by Alternaria, Ascospores, Basidiospores, Botrytis, Cladosporium, Erysiphe and Rusts. The main fungal spore season for Dublin commenced in April with the fructification of Scopulariopsis and Ganoderma. However, the vast majority of other spore types did not reach peak spore release until late summer. The correlation between ambient spore concentration, and meteorological parameters was examined using Multivariable Regression Tree (MRT) analysis. The notable correlations found for fungal spore concentrations tended to involve temperature-based parameters. The use of a non-parametric wind regression was also employed to determine the potential geographical origin of ambient fungal spores. The impact of wind direction, and high windspeed on fungal spores was established, ultimately highlighting the importance of studying and monitoring fungal spores within Ireland, rather than attempting to rely on data from other regions, as most fungal spores collected in Dublin appeared to originate from within the island.

Airborne Fungal Spore Review, New Advances and Automatisation

Fungal spores make up a significant portion of Primary Biological Aerosol Particles (PBAPs) with large quantities of such particles noted in the air. Fungal particles are of interest because of their potential to affect the health of both plants and humans. They are omnipresent in the atmosphere year-round, with concentrations varying due to meteorological parameters and location. Equally, differences between indoor and outdoor fungal spore concentrations and dispersal play an important role in occupational health. This review attempts to summarise the different spore sampling methods, identify the most important spore types in terms of negative effects on crops and the public, the factors affecting their growth/dispersal, and different methods of predicting fungal spore concentrations currently in use.

Synergistic surface-enhanced Raman scattering effect to distinguish live SARS-CoV-2 S pseudovirus

The COVID-19 pandemic negatively affected the economy and health security on a global scale, causing a drastic change on lifestyle, calling a need to mitigate further transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Surface-enhanced Raman spectroscopy (SERS) has shown great potential in the sensitive and rapid detection of various molecules including viruses, through the identification of characteristic peaks of their outer membrane proteins. Accurate detection can be developed through the synergistic integration effect among SERS-active substrate, the appropriate laser wavelength, and the target analyte. In this study, gold nanocavities (Au NC) and Au nanoparticles upon ZrO2 nano-bowls (Au NPs/pZrO2) were tested and used as SERS-active substrates in detecting SARS-CoV-2 pseudovirus containing S protein as a surface capsid glycoprotein (SARS-CoV-2 S pseudovirus) and vesicular stomatitis virus G (VSV-G) pseudo-type lentivirus (VSV-G pseudovirus) to demonstrate their virus detection capability. The optimized Au NCs and Au NPs/pZrO2 substrates were then verified by examining the repetition of measurement, reproducibility, and detection limit. Due to the difference in geometry and composition of the substrates, the characteristic peak-positions of live SARS-CoV-2 S and VSV-G pseudoviruses in the obtained Raman spectra vary, which were also compared with those of inactivated ones. Based on the experimental results, SERS mechanism of each substrate to detect virus is proposed. The formation of hot spots brought by the synergistic integration effect among substrate, analyte, and laser induction may result differences in the obtained SERS spectra.

Sampling bias minimization in disease frequency estimates

An accurate estimate of the number of infected individuals in any disease is crucial. Current estimates are mainly based on the fraction of positive samples or the total number of positive samples. However, both methods are biased and sensitive to the sampling depth. We here propose an alternative method to use the attributes of each sample to estimate the change in the total number of positive patients in the total population. We present a Bayesian estimator assuming a combination of condition and time-dependent probability of being positive, and mixed implicit-explicit solution for the probability of a person with conditions i at time t of being positive. We use this estimate to predict the total probability of being positive at a given day t. We show that these estimate results are smooth and not sensitive to the properties of the samples. Moreover, these results are a better predictor of future mortality.

Development of a COVID-19 University-Based Clinic in Indonesia: A Pilot Project of The Gadjah Mada Electronic Nose Center

BACKGROUND: The clinic development of COVID-19 screening is essential during the pandemic. AIM: This study aimed to explore and elaborate the development process of the Gadjah Mada Electronic Nose (GeNose) Center as a pilot project for a COVID-19 university-based clinic in Indonesia. METHODS: A narrative and explorative study was conducted. Under the university platform, we initiated the GeNose center through training, simulation, and debriefing. Identification of team member recruitment, location, and apparatus development were described using the retrospective approach. RESULTS: Fifty-one team members were recruited, including person in charge, verifiers, administrative staffs, hotline team, security staffs, and janitors. Standard operating procedures, service system, and safety measures were developed to maintain the quality. Services include the application of COVID-19 protocols, registration and confirmation, education for using the air bag, collecting the air sample, and analysis of samples using the GeNose machine. CONCLUSION: The GeNose center, a model for screening test, provides services for the screening of COVID-19.

Safety Nets Work Both Ways: The Influence of Available Paid Leave on Employee Risk Taking During the COVID-19 Pandemic

BACKGROUND

During the COVID-19 pandemic, use of symptom-screening tools to limit attendance of infected workers has been widespread. However, it remains unknown how the reliability of responses to these tools may be compromised by individual and social factors. We aimed to determine whether personal concern over lost wages impacts responses to COVID-19 symptom-screening questionnaires making them less useful in limiting person-to-person transmission.

METHODS

We utilized an anonymous online questionnaire, administered through personal social media networks and those of two U.S. private colleges between September 16, 2020 and November 2, 2020 and distributed to currently or recently employed individuals 18 years of age or older. Participants considered ambiguous hypothetical scenarios involving possible COVID-19 symptoms or exposure and responded to a COVID-19 symptom screen (N = 219).

FINDINGS

In response to symptom-related scenarios (i.e., elevated temperature or slight cough), respondents lacking access to paid sick leave were 2.2 to 2.7 times more likely to attend work than those with access to paid leave (p < .05). This was not true for contact-related scenarios. Pay type and income level also significantly influenced screening responses.

CONCLUSION/APPLICATION TO PRACTICE

Risk of acute wage loss and overall financial stability appear to influence work-attendance decisions with regard to COVID-19 symptom screens. Broadened availability of paid leave and additional specificity within screening questionnaires would likely improve symptom-screen reliability.

Borderline microscopic organism and lockdown impacted across the borders-global shakers

Viruses are the potential cause of several diseases including novel corona virus-19, flu, small pox, chicken pox, acquired immunodeficiency syndrome, severe acute respiratory syndrome etc. The objectives of this review article are to summarize the reasons behind the epidemics caused by several emerging viruses and bacteria, how to control the infection and preventive strategies. We have explained the causes of epidemics along with their preventive measures, the impact of lockdown on the health of people and the economy of a country. Several reports have revealed the transmission of infection during epidemic from the contact of an infected person to the public that can be prevented by implementing the lockdown by the government of a country. Though lockdown has been considered as one of the significant parameters to control the diseases, however, it has some negative consequences on the health of people as they can be more prone to other ailments like obesity, diabetes, cardiac problems etc. and drastic decline in the economy of a country. Therefore, the transmission of diseases can be prevented by warning the people about the severity of diseases, avoiding their public transportation, keeping themselves isolated, strictly following the guidelines of lockdown and encouraging regular exercise.

Olfactory Dysfunction in COVID-19 Patients Who Do Not Report Olfactory Symptoms: A Pilot Study with Some Suggestions for Dentists

BACKGROUND

Smell and taste dysfunction are frequently reported by SARS-CoV-2 positive patients. The degree of olfactory and gustatory dysfunction varies from a very mild reduction to their complete loss. Several studies have been performed to determine their prevalence in COVID-19 patients, mostly using subjective measurement methods. The literature lacks long-term studies regarding duration and recovery.

METHODS

We assessed olfactory performance, using the Sniffin' Sticks olfactory test, in a group of patients who had not reported olfactory dysfunction, around 131 days after their COVID-19 diagnosis.

RESULTS

11 out of 20 subjects showed no olfactory reduction (65%), while 9 subjects showed reduced TDI score (45%). A total of 13 subjects (65%) scored above the cutoff point for Threshold, 16 subjects (80%) scored above the cutoff point for discrimination and 13 subjects (65%) scored above the cutoff point for identification.

CONCLUSION

Objective measurement methods of olfactory performance show a higher prevalence of olfactory reduction compared to patients' self-reported questionnaires. Olfactory dysfunction can last even months after its onset and because of its high prevalence, it could be a screening symptom for suspect COVID-19 cases.

Detection of anti-SARS-CoV-2 antibodies and its seroprevalence in Zavidovići municipality of Zenica-Doboj Canton, Bosnia and Herzegovina

OBJECTIVES

Improved serological detection of specific antibodies against SARS-CoV-2 could help estimate the true number of infections.

METHODS

A total of 443 serum samples provided by unvaccinated patients of all ages with unknown COVID-19 status that were originally submitted for routine screening or clinical management from outpatient laboratory during the March-April 2021 (third wave) were collected. Seroprevalence of IgM/IgG antibodies was determined by lateral flow immunoassay (Tigsun, Beijing, China).

RESULTS

Among 443 serum samples, 186 (42.0%) were positive (incidence of 5.2/1000) with slight predominace of females, 104 (55.9%), highest seropositivity in 25-50 and 51-64 years age groups, 61 (32.8%) and 57 (30.6%), respectively (P < 0.05); rural population was more prevalent, 101 (54.3%) (P < 0.05) and active workers, 86 (41.1%). Almost equal number of patients was with or without symptoms, 48.4% and 51.6%, respectively. For the comparison, in the same period it was registered 296 (out of 855; 34.6%) PCR SARS-CoV-19 positive persons (incidence of 8.2/1000) with the higher gender (females) and the highest age prevalence in 51-64 years age group (36.8%). In the period March 2020-June 2021, it was registered 804 (out of 3323; 24.2%) (incidence of 22.3/1000) PCR SARS-CoV-19 positive persons with no significant gender and significant age difference (25-50 and 51-64 years group, respectively).

CONCLUSION

In the regions with high prevalence/incidence of SARS-CoV-2 in the general population (Bosnia and Herzegovina is on the World top on the number of deaths) seroprevalence measuring can help tracking the spread of disease.

Limited Propagation of SARS-CoV-2 among Children in a Childcare Center, Canada, 2021

An outbreak of severe acute respiratory syndrome coronavirus 2 with no definitive source and potential exposure to variants of concern was declared at a childcare center in Ontario, Canada, in March 2021. We developed a robust outbreak management approach to detect, contain, and interrupt this outbreak and limit propagation among children.

Panel Associations Between Newly Dead, Healed, Recovered, and Confirmed Cases During COVID-19 Pandemic

Background

Currently, the knowledge of associations among newly recovered cases (NR), newly healed cases (NH), newly confirmed cases (NC), and newly dead cases (ND) can help to monitor, evaluate, predict, control, and curb the spreading of coronavirus disease 2019 (COVID-19). This study aimed to explore the panel associations of ND, NH, and NR with NC.

Methods

Data from China Data Lab in Harvard Dataverse with China (January 15, 2020 to January 14, 2021), the United States of America (the USA, January 21, 2020 to April 5, 2021), and the World (January 22, 2020 to March 20, 2021) had been analyzed. The main variables included in the present analysis were ND, NH, NR, and NC. Pooled regression, stacked within-transformed linear regression, quantile regression for panel data, random-effects negative binomial regression, and random-effects Poisson regression were conducted to reflect the associations of ND, NH, and NR with NC. Event study analyses were performed to explore how the key events influenced NC.

Results

Descriptive analyses showed that mean value of ND/NC ratio regarding China was more than those regarding the USA and the World. The results from tentative analysis reported the significant relationships among ND, NH, NR, and NC regarding China, the USA, and the World. Panel regressions confirmed associations of ND, NH, and NR with NC regarding China, the USA, and the World. Panel event study showed that key events influenced NC regarding USA and the World more greatly than that regarding China.

Conclusion

The findings in this study confirmed the panel associations of ND, NH, and NR with NC in the three datasets. The efficiencies of various control strategies of COVID-19 pandemic across the globe were compared by the regression outcomes. Future direction of research work could explore the influencing mechanisms of the panel associations.

AI-based Power Screening Solution for SARS-CoV2 Infection: A Sociodemographic Survey and COVID-19 Cough Detector

Globally, the confirmed coronavirus (SARS-CoV2) cases are being increasing day by day. Coronavirus (COVID-19) causes an acute infection in the respiratory tract that started spreading in late 2019. Huge datasets of SARS-CoV2 patients can be incorporated and analyzed by machine learning strategies for understanding the pattern of pathological spread and helps to analyze the accuracy and speed of novel therapeutic methodologies, also detect the susceptible people depends on their physiological and genetic aspects. To identify the possible cases faster and rapidly, we propose the Artificial Intelligence (AI) power screening solution for SARS- CoV2 infection that can be deployable through the mobile application. It collects the details of the travel history, symptoms, common signs, gender, age and diagnosis of the cough sound. To examine the sharpness of pathomorphological variations in respiratory tracts induced by SARS-CoV2, that compared to other respiratory illnesses to address this issue. To overcome the shortage of SARS-CoV2 datasets, we apply the transfer learning technique. Multipronged mediator for risk-averse Artificial Intelligence Architecture is induced for minimizing the false diagnosis of risk-stemming from the problem of complex dimensionality. This proposed application provides early detection and prior screening for SARS-CoV2 cases. Huge data points can be processed through AI framework that can examine the users and classify them into "Probably COVID", "Probably not COVID" and "Result indeterminate".

Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave

Considerable uncertainty surrounds the timeline of introductions and onsets of local transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) globally1-7. Although a limited number of SARS-CoV-2 introductions were reported in January and February 2020 (refs.8,9), the narrowness of the initial testing criteria, combined with a slow growth in testing capacity and porous travel screening10, left many countries vulnerable to unmitigated, cryptic transmission. Here we use a global metapopulation epidemic model to provide a mechanistic understanding of the early dispersal of infections and the temporal windows of the introduction of SARS-CoV-2 and onset of local transmission in Europe and the USA. We find that community transmission of SARS-CoV-2 was likely to have been present in several areas of Europe and the USA by January 2020, and estimate that by early March, only 1 to 4 in 100 SARS-CoV-2 infections were detected by surveillance systems. The modelling results highlight international travel as the key driver of the introduction of SARS-CoV-2, with possible introductions and transmission events as early as December 2019 to January 2020. We find a heterogeneous geographic distribution of cumulative infection attack rates by 4 July 2020, ranging from 0.78% to 15.2% across US states and 0.19% to 13.2% in European countries. Our approach complements phylogenetic analyses and other surveillance approaches and provides insights that can be used to design innovative, model-driven surveillance systems that guide enhanced testing and response strategies.

Modeling the onset of symptoms of COVID-19: Effects of SARS-CoV-2 variant

Identifying order of symptom onset of infectious diseases might aid in differentiating symptomatic infections earlier in a population thereby enabling non-pharmaceutical interventions and reducing disease spread. Previously, we developed a mathematical model predicting the order of symptoms based on data from the initial outbreak of SARS-CoV-2 in China using symptom occurrence at diagnosis and found that the order of COVID-19 symptoms differed from that of other infectious diseases including influenza. Whether this order of COVID-19 symptoms holds in the USA under changing conditions is unclear. Here, we use modeling to predict the order of symptoms using data from both the initial outbreaks in China and in the USA. Whereas patients in China were more likely to have fever before cough and then nausea/vomiting before diarrhea, patients in the USA were more likely to have cough before fever and then diarrhea before nausea/vomiting. Given that the D614G SARS-CoV-2 variant that rapidly spread from Europe to predominate in the USA during the first wave of the outbreak was not present in the initial China outbreak, we hypothesized that this mutation might affect symptom order. Supporting this notion, we found that as SARS-CoV-2 in Japan shifted from the original Wuhan reference strain to the D614G variant, symptom order shifted to the USA pattern. Google Trends analyses supported these findings, while weather, age, and comorbidities did not affect our model's predictions of symptom order. These findings indicate that symptom order can change with mutation in viral disease and raise the possibility that D614G variant is more transmissible because infected people are more likely to cough in public before being incapacitated with fever.

Exploring the Clinical Utility of Gustatory Dysfunction (GD) as a Triage Symptom Prior to Reverse Transcription Polymerase Chain Reaction (RT-PCR) in the Diagnosis of COVID-19: A Meta-Analysis and Systematic Review

BACKGROUND

The diagnosis of COVID-19 is made using reverse transcription polymerase chain reaction (RT-PCR) but its sensitivity varies from 20 to 100%. The presence of gustatory dysfunction (GD) in a patient with upper respiratory tract symptoms might increase the clinical suspicion of COVID-19.

AIMS

To perform a systematic review and meta-analysis to determine the pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-) and diagnostic odds ratio (DOR) of using GD as a triage symptom prior to RT-PCR.

METHODS

PubMed and Embase were searched up to 20 June 2021. Studies published in English were included if they compared the frequency of GD in COVID-19 adult patients (proven by RT-PCR) to COVID-19 negative controls in case control or cross-sectional studies. The Newcastle-Ottawa scale was used to assess the methodological quality of the included studies.

RESULTS

21,272 COVID-19 patients and 52,298 COVID-19 negative patients were included across 44 studies from 21 countries. All studies were of moderate to high risk of bias. Patients with GD were more likely to test positive for COVID-19: DOR 6.39 (4.86-8.40), LR+ 3.84 (3.04-4.84), LR- 0.67 (0.64-0.70), pooled sensitivity 0.37 (0.29-0.47) and pooled specificity 0.92 (0.89-0.94). While history/questionnaire-based assessments were predictive of RT-PCR positivity (DOR 6.62 (4.95-8.85)), gustatory testing was not (DOR 3.53 (0.98-12.7)). There was significant heterogeneity among the 44 studies (I2 = 92%, p < 0.01).

CONCLUSIONS

GD is useful as a symptom to determine if a patient should undergo further testing, especially in resource-poor regions where COVID-19 testing is scarce. Patients with GD may be advised to quarantine while repeated testing is performed if the initial RT-PCR is negative.

FUNDING

None.

Applications of Healthcare Robots in Combating the COVID-19 Pandemic

Due to the increasing number of COVID-19 cases, there is a remarkable demand for robots, especially in the clinical sector. SARS-CoV-2 mainly propagates due to close human interactions and contaminated surfaces, and hence, maintaining social distancing has become a mandatory preventive measure. This generates the need to treat patients with minimal doctor-patient interaction. Introducing robots in the healthcare sector protects the frontline healthcare workers from getting exposed to the coronavirus as well as decreases the need for medical personnel as robots can partially take over some medical roles. The aim of this paper is to highlight the emerging role of robotic applications in the healthcare sector and allied areas. To this end, a systematic review was conducted regarding the various robots that have been implemented worldwide during the COVID-19 pandemic to attenuate and contain the virus. The results obtained from this study reveal that the implementation of robotics into the healthcare field has a substantial effect in controlling the spread of SARS-CoV-2, as it blocks coronavirus propagation between patients and healthcare workers, along with other advantages such as disinfection or cleaning.

UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients

BACKGROUND

With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international researchers. Recently, many deep learning-based Computed Tomography (CT) image/X-ray image fast screening models for potential COVID-19 patients have been proposed. However, the existing models still have two main problems. First, most of the existing supervised models are based on pre-trained model parameters. The pre-training model needs to be constructed on a dataset with features similar to those in COVID-19 X-ray images, which limits the construction and use of the model. Second, the number of categories based on the X-ray dataset of COVID-19 and other pneumonia patients is usually imbalanced. In addition, the quality is difficult to distinguish, leading to non-ideal results with the existing model in the multi-class classification COVID-19 recognition task. Moreover, no researchers have proposed a COVID-19 X-ray image learning model based on unsupervised meta-learning.

METHODS

This paper first constructed an unsupervised meta-learning model for fast screening of COVID-19 patients (UMLF-COVID). This model does not require a pre-trained model, which solves the limitation problem of model construction, and the proposed unsupervised meta-learning framework solves the problem of sample imbalance and sample quality.

RESULTS

The UMLF-COVID model is tested on two real datasets, each of which builds a three-category and four-category model. And the experimental results show that the accuracy of the UMLF-COVID model is 3-10% higher than that of the existing models.

CONCLUSION

In summary, we believe that the UMLF-COVID model is a good complement to COVID-19 X-ray fast screening models.

CT Examinations for COVID-19: A Systematic Review of Protocols, Radiation Dose, and Numbers Needed to Diagnose and Predict

Purpose

Although chest CT has been discussed as a first-line test for coronavirus disease 2019 (COVID-19), little research has explored the implications of CT exposure in the population. To review chest CT protocols and radiation doses in COVID-19 publications and explore the number needed to diagnose (NND) and the number needed to predict (NNP) if CT is used as a first-line test.

Materials and Methods

We searched nine highly cited radiology journals to identify studies discussing the CT-based diagnosis of COVID-19 pneumonia. Study-level information on the CT protocol and radiation dose was collected, and the doses were compared with each national diagnostic reference level (DRL). The NND and NNP, which depends on the test positive rate (TPR), were calculated, given a CT sensitivity of 94% (95% confidence interval [CI]: 91%-96%) and specificity of 37% (95% CI: 26%-50%), and applied to the early outbreak in Wuhan, New York, and Italy.

Results

From 86 studies, the CT protocol and radiation dose were reported in 81 (94.2%) and 17 studies (19.8%), respectively. Low-dose chest CT was used more than twice as often as standard-dose chest CT (39.5% vs.18.6%), while the remaining studies (44.2%) did not provide relevant information. The radiation doses were lower than the national DRLs in 15 of the 17 studies (88.2%) that reported doses. The NND was 3.2 scans (95% CI: 2.2-6.0). The NNPs at TPRs of 50%, 25%, 10%, and 5% were 2.2, 3.6, 8.0, 15.5 scans, respectively. In Wuhan, 35418 (TPR, 58%; 95% CI: 27710-56755) to 44840 (TPR, 38%; 95% CI: 35161-68164) individuals were estimated to have undergone CT examinations to diagnose 17365 patients. During the early surge in New York and Italy, daily NNDs changed up to 5.4 and 10.9 times, respectively, within 10 weeks.

Conclusion

Low-dose CT protocols were described in less than half of COVID-19 publications, and radiation doses were frequently lacking. The number of populations involved in a first-line diagnostic CT test could vary dynamically according to daily TPR; therefore, caution is required in future planning.

Food Safety and Employee Health Implications of COVID-19: A Review

The COVID-19 pandemic has greatly impacted the U.S. food supply and consumer behavior. Food production and processing are being disrupted as illnesses, proactive quarantines, and government-mandated movement restrictions cause labor shortages. In this environment, the food industry has been required to adopt new, additional practices to minimize the risk of COVID-19 cases and outbreaks among its workforce. Successfully overcoming these challenges requires a comprehensive approach that addresses COVID-19 transmission both within and outside the facility. Possible interventions include strategies (i) to vaccinate employees, (ii) to assure that employees practice social distancing, (iii) to assure that employees wear face coverings, (iv) to screen employees for COVID-19, (v) to assure that employees practice frequent hand washing and avoid touching their faces, (vi) to clean frequently touched surfaces, and (vii) to assure proper ventilation. Compliance with these control strategies must be verified, and an overall COVID-19 control culture must be established to implement an effective program. Despite some public misperceptions about the health risk of severe acute respiratory syndrome coronavirus 2 on foods or food packaging, both the virus biology and epidemiological data clearly support a negligible risk of COVID-19 transmission through food and food packing. However, COVID-19 pandemic-related supply chain and workforce disruptions and the shift in resources to protect food industry employees from COVID-19 may increase the actual food safety risks. The goal of this review was to describe the COVID-19 mitigation practices adopted by the food industry and the potential impact of these practices and COVID-19-related disruptions on the industry's food safety mission. A review of these impacts is necessary to ensure that the food industry is prepared to maintain a safe and nutritious food supply in the face of future global disruptions.

Lung segmentation and automatic detection of COVID-19 using radiomic features from chest CT images

This paper aims to develop an automatic method to segment pulmonary parenchyma in chest CT images and analyze texture features from the segmented pulmonary parenchyma regions to assist radiologists in COVID-19 diagnosis. A new segmentation method, which integrates a three-dimensional (3D) V-Net with a shape deformation module implemented using a spatial transform network (STN), was proposed to segment pulmonary parenchyma in chest CT images. The 3D V-Net was adopted to perform an end-to-end lung extraction while the deformation module was utilized to refine the V-Net output according to the prior shape knowledge. The proposed segmentation method was validated against the manual annotation generated by experienced operators. The radiomic features measured from our segmentation results were further analyzed by sophisticated statistical models with high interpretability to discover significant independent features and detect COVID-19 infection. Experimental results demonstrated that compared with the manual annotation, the proposed segmentation method achieved a Dice similarity coefficient of 0.9796, a sensitivity of 0.9840, a specificity of 0.9954, and a mean surface distance error of 0.0318 mm. Furthermore, our COVID-19 classification model achieved an area under curve (AUC) of 0.9470, a sensitivity of 0.9670, and a specificity of 0.9270 when discriminating lung infection with COVID-19 from community-acquired pneumonia and healthy controls using statistically significant radiomic features. The significant features measured from our segmentation results agreed well with those from the manual annotation. Our approach has great promise for clinical use in facilitating automatic diagnosis of COVID-19 infection on chest CT images.

The environment has effects on infrared temperature screening for COVID-19 infection

Infrared temperature measurement is a common form of mass screening for febrile illnesses such as COVID-19 infection. Efficacy of infrared monitoring is debated, and external factors can affect accuracy. We determine that outside temperature, wind, and humidity can affect infrared temperature measurements and partially account for inaccurate results.

A Dispatch Screening Tool to Identify Patients at High Risk for COVID-19 in the Prehospital Setting

INTRODUCTION

Emergency medical services (EMS) dispatchers have made efforts to determine whether patients are high risk for coronavirus disease 2019 (COVID-19) so that appropriate personal protective equipment (PPE) can be donned. A screening tool is valuable as the healthcare community balances protection of medical personnel and conservation of PPE. There is little existing literature on the efficacy of prehospital COVID-19 screening tools. The objective of this study was to determine the positive and negative predictive value of an emergency infectious disease surveillance tool for detecting COVID-19 patients and the impact of positive screening on PPE usage.

METHODS

This study was a retrospective chart review of prehospital care reports and hospital electronic health records. We abstracted records for all 911 calls to an urban EMS from March 1-July 31, 2020 that had a documented positive screen for COVID-19 and/or had a positive COVID-19 test. The dispatch screen solicited information regarding travel, sick contacts, and high-risk symptoms. We reviewed charts to determine dispatch-screening results, the outcome of patients' COVID-19 testing, and documentation of crew fidelity to PPE guidelines.

RESULTS

The sample size was 263. The rate of positive COVID-19 tests for all-comers in the state of Massachusetts was 2.0%. The dispatch screen had a sensitivity of 74.9% (confidence interval [CI], 69.21-80.03) and a specificity of 67.7% (CI, 66.91-68.50). The positive predictive value was 4.5% (CI, 4.17-4.80), and the negative predictive value was 99.3% (CI, 99.09-99.40). The most common symptom that triggered a positive screen was shortness of breath (51.5% of calls). The most common high-risk population identified was skilled nursing facility patients (19.5%), but most positive tests did not belong to a high-risk population (58.1%). The EMS personnel were documented as wearing full PPE for the patient in 55.7% of encounters, not wearing PPE in 8.0% of encounters, and not documented in 27.9% of encounters.

CONCLUSION

This dispatch-screening questionnaire has a high negative predictive value but moderate sensitivity and therefore should be used with some caution to guide EMS crews in their PPE usage. Clinical judgment is still essential and may supersede screening status.

Pre-symptomatic and asymptomatic transmission of COVID-19: Implications for control measures in Qatar

Public health control measures for communicable diseases are often based on the identification of symptomatic cases. However, emerging epidemiological evidence demonstrates the role of pre-symptomatic and asymptomatic transmissions of coronavirus disease 2019 (COVID-19). Understanding high-risk settings where transmissions can occur from infected individuals without symptoms has become critical for improving the response to the pandemic. In this review, we discussed the evidence on the transmission of severe acute respiratory syndrome coronavirus-2, its effect on control strategies, and lessons that can be applied in Qatar. Although Qatar has a small population, it has a distinct setting for COVID-19 control. It has a largely young population and is mostly composed of expatriates particularly from the Middle East and Asia that reside in Qatar for work. Further key considerations for Qatar and travel include population movement during extended religious holiday periods, screening and tracing of visitors and residents at entry points into the country, and expatriates living and working in high-density settings. We also consider how its international airport serves as a major transit destination for the region, as Qatar is expected to experience a rapid expansion of visitors while preparing to host the FIFA World Cup in 2022.

COVID-19 Lung Pathogenesis in SARS-CoV-2 Autopsy Cases

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major public health issue. COVID-19 is considered an airway/multi-systemic disease, and demise has been associated with an uncontrolled immune response and a cytokine storm in response to the virus. However, the lung pathology, immune response, and tissue damage associated with COVID-19 demise are poorly described and understood due to safety concerns. Using post-mortem lung tissues from uninfected and COVID-19 deadly cases as well as an unbiased combined analysis of histology, multi-viral and host markers staining, correlative microscopy, confocal, and image analysis, we identified three distinct phenotypes of COVID-19-induced lung damage. First, a COVID-19-induced hemorrhage characterized by minimal immune infiltration and large thrombus; Second, a COVID-19-induced immune infiltration with excessive immune cell infiltration but no hemorrhagic events. The third phenotype correspond to the combination of the two previous ones. We observed the loss of alveolar wall integrity, detachment of lung tissue pieces, fibroblast proliferation, and extensive fibrosis in all three phenotypes. Although lung tissues studied were from lethal COVID-19, a strong immune response was observed in all cases analyzed with significant B cell and poor T cell infiltrations, suggesting an exhausted or compromised immune cellular response in these patients. Overall, our data show that SARS-CoV-2-induced lung damage is highly heterogeneous. These individual differences need to be considered to understand the acute and long-term COVID-19 consequences.

Is rapid scientific publication also high quality? Bibliometric analysis of highly disseminated COVID-19 research papers

The impact of COVID-19 has underlined the need for reliable information to guide clinical practice and policy. This urgency has to be balanced against disruption to journal handling capacity and the continued need to ensure scientific rigour. We examined the reporting quality of highly disseminated COVID-19 research papers using a bibliometric analysis examining reporting quality and risk of bias (RoB) amongst 250 top scoring Altmetric Attention Score (AAS) COVID-19 research papers between January and April 2020. Method-specific RoB tools were used to assess quality. After exclusions, 84 studies from 44 journals were included. Forty-three (51%) were case series/studies, and only one was an randomized controlled trial. Most authors were from institutions based in China (n = 44, 52%). The median AAS and impact factor was 2015 (interquartile range [IQR] 1,105-4,051.5) and 12.8 (IQR 5-44.2) respectively. Nine studies (11%) utilized a formal reporting framework, 62 (74%) included a funding statement, and 41 (49%) were at high RoB. This review of the most widely disseminated COVID-19 studies highlights a preponderance of low-quality case series with few research papers adhering to good standards of reporting. It emphasizes the need for cautious interpretation of research and the increasingly vital responsibility that journals have in ensuring high-quality publications.

Public health effects of travel-related policies on the COVID-19 pandemic: A mixed-methods systematic review

OBJECTIVES

To map travel policies implemented due to COVID-19 during 2020, and conduct a mixed-methods systematic review of health effects of such policies, and related contextual factors.

DESIGN

Policy mapping and systematic review. DATA SOURCES AND ELIGIBILITY CRITERIA: for the policy mapping, we searched websites of relevant government bodies and used data from the Oxford COVID-19 Government Response Tracker for a convenient sample of 31 countries across different regions. For the systematic review, we searched Medline (Ovid), PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and COVID-19 specific databases. We included randomized controlled trial, non-randomized studies, modeling studies, and qualitative studies. Two independent reviewers selected studies, abstracted data and assessed risk of bias.

RESULTS

Most countries adopted a total border closure at the start of the pandemic. For the remainder of the year, partial border closure banning arrivals from some countries or regions was the most widely adopted measure, followed by mandatory quarantine and screening of travelers. The systematic search identified 69 eligible studies, including 50 modeling studies. Both observational and modeling evidence suggest that border closure may reduce the number of COVID-19 cases, disease spread across countries and between regions, and slow the progression of the outbreak. These effects are likely to be enhanced when implemented early, and when combined with measures reducing transmission rates in the community. Quarantine of travelers may decrease the number of COVID-19 cases but its effectiveness depends on compliance and enforcement and is more effective if followed by testing, especially when less than 14 day-quarantine is considered. Screening at departure and/or arrival is unlikely to detect a large proportion of cases or to delay an outbreak. Effectiveness of screening may be improved with increased sensitivity of screening tests, awareness of travelers, asymptomatic screening, and exit screening at country source. While four studies on contextual evidence found that the majority of the public is supportive of travel restrictions, they uncovered concerns about the unintended harms of those policies.

CONCLUSION

Most countries adopted full or partial border closure in response to COVID-19 in 2020. Evidence suggests positive effects on controlling the COVID-19 pandemic for border closure (particularly when implemented early), as well as quarantine of travelers (particularly with higher levels of compliance). While these positive effects are enhanced when implemented in combination with other public health measures, they are associated with concerns by the public regarding some unintended effects.

Mathematical modeling of COVID-19 transmission dynamics between healthcare workers and community

Corona-virus disease 2019 (COVID-19) is an infectious disease that has affected different groups of humankind such as farmers, soldiers, drivers, educators, students, healthcare workers and many others. The transmission rate of the disease varies from one group to another depending on the contact rate. Healthcare workers are at a high risk of contracting the disease due to the high contact rate with patients. So far, there exists no mathematical model which combines both public control measures (as a parameter) and healthcare workers (as an independent compartment). Combining these two in a given mathematical model is very important because healthcare workers are protected through effective use of personal protective equipment, and control measures help to minimize the spread of COVID-19 in the community. This paper presents a mathematical model named SWEI s I a HR; susceptible individuals (S), healthcare workers (W), exposed (E), symptomatic infectious (I s ), asymptomatic infectious (I a ), hospitalized (H), recovered (R). The value of basic reproduction numberR 0 for all parameters in this study is 2.8540. In the absence of personal protective equipment ξ and control measure in the public θ , the value ofR 0 ≈ 4 . 6047 which implies the presence of the disease. When θ and ξ were introduced in the model, basic reproduction number is reduced to 0.4606, indicating the absence of disease in the community. Numerical solutions are simulated by using Runge-Kutta fourth-order method. Sensitivity analysis is performed to presents the most significant parameter. Furthermore, identifiability of model parameters is done using the least square method. The results indicated that protection of healthcare workers can be achieved through effective use of personal protective equipment by healthcare workers and minimization of transmission of COVID-19 in the general public by the implementation of control measures. Generally, this paper emphasizes the importance of using protective measures.

The effect of aviation responses to the control of imported COVID-19 cases

The outbreak of the COVID-19 pandemic has a lasting and unprecedented negative impact on the global aviation industry. While countries such as China have successfully curbed the domestic outbreak of the virus with various restrictive and preventive measures, the challenge of avoiding imported cases remains. More importantly, it is still unclear to what extent these implemented aviation emergency responses have effectively mitigated the transmission risk of the virus. This paper provides an empirical assessment of aviation responses to the control of imported COVID-19 cases, with a focus on the following three strategies: the "circuit breaker" policy, the "negative Nucleic Acid testing (NAT)", and the "double negative tests" requirement. Non-recursive structural equation models (SEM) with latent variables were applied to detailed international flight data and individual epidemic survey data of Guangzhou, China, between May 1 and November 30, 2020. The results show that the "double negative tests" measure has a positive effect on eliminating the number of SARS-CoV-2 carriers, while the effects of single "circuit breaker" and its co-intervention with "negative NAT" are conterproductive. This study provides important implications to civil aviation agencies in regard to medium and long-term risk control of imported cases. Specifically, although the circuit breaker mechanism was designed to target on the risk control of imported COVID-19 cases, it may be more effective to carefully maintain a timely and reliable pre-boarding screening and testing to curb the number of imported cases.

Differential clinical diagnosis and prevalence rate of allergic rhinitis, asthma and chronic obstructive pulmonary disease among COVID-19 patients

BACKGROUND

There is a great need to make a rapid differential clinical diagnosis of COVID-19 among respiratory disease patients and determining the prevalence rate of these diseases among the COVID-19 population.

METHOD

Approximately 522 patients with allergic rhinitis, asthma, COPD, and COVID-19 were analysed for demographic and clinical features. Radiological features were analysed only for COVID-19 patients.

RESULTS

COPD and asthma were more common among COVID-19 patients than allergic rhinitis. All chest CT scans of COVID-19 patients showed bilateral ground-glass opacity. Fever, dry cough, diarrhea, loss of sense of smell and taste, shortness of breath, and blue lips were significantly higher in all COVID-19 patients compared to COPD, asthma, and allergic rhinitis patients.

CONCLUSION

The presence of clinical symptoms such as fever, dry cough, diarrhea, loss of sense of smell and taste, shortness of breath, and blue lips in COVID-19 patients, can be used for differential diagnosis between COVID-19 patients and other respiratory diseases. Then, the diagnosis can be confirmed by chest CT scan for COVID-19 patients without the need for a nasopharyngeal swab or PCR test, especially in epidemic countries. Allergic rhinitis patients are the least exposed to COVID-19 infection among other respiratory disease patients.

Performance of COVID-19 associated symptoms and temperature checking as a screening tool for SARS-CoV-2 infection

INTRODUCTION

Coronavirus disease-19 (COVID-19), which started in late December, 2019, has spread to affect 216 countries and territories around the world. Globally, the number of cases of SARS-CoV-2 infection has been growing exponentially. There is pressure on countries to flatten the curves and break transmission. Most countries are practicing partial or total lockdown, vaccination, massive education on hygiene, social distancing, isolation of cases, quarantine of exposed and various screening approaches such as temperature and symptom-based screening to break the transmission. Some studies outside Africa have found the screening for fever using non-contact thermometers to lack good sensitivity for detecting SARS-CoV-2 infection. The aim of this study was to determine the usefulness of clinical symptoms in accurately predicting a final diagnosis of COVID-19 disease in the Ghanaian setting.

METHOD

The study analysed screening and test data of COVID-19 suspected, probable and contacts for the months of March to August 2020. A total of 1,986 participants presenting to Tamale Teaching hospital were included in the study. Logistic regression and receiver operator characteristics (ROC) analysis were carried out.

RESULTS

Overall SARS-CoV-2 positivity rate was 16.8%. Those with symptoms had significantly higher positivity rate (21.6%) compared with asymptomatic (17.0%) [chi-squared 15.5, p-value, <0.001]. Patients that were positive for SARS-CoV-2 were 5.9 [3.9-8.8] times more likely to have loss of sense of smell and 5.9 [3.8-9.3] times more likely to having loss of sense of taste. Using history of fever as a screening tool correctly picked up only 14.8% of all true positives of SARS-CoV-2 infection and failed to pick up 86.2% of positive cases. Using cough alone would detect 22.4% and miss 87.6%. Non-contact thermometer used alone, as a screening tool for COVID-19 at a cut-off of 37.8 would only pick 4.8% of positive SARS-CoV-2 infected patients.

CONCLUSION

The use of fever alone or other symptoms individually [or in combination] as a screening tool for SARS-CoV-2 infection is not worthwhile based on ROC analysis. Use of temperature check as a COVID-19 screening tool to allow people into public space irrespective of the temperature cut-off is of little benefit in diagnosing infected persons. We recommend the use of facemask, hand hygiene, social distancing as effective means of preventing infection.

Potential solutions for screening, triage, and severity scoring of suspected COVID-19 positive patients in low-resource settings: a scoping review

OBJECTIVES

Purposefully designed and validated screening, triage, and severity scoring tools are needed to reduce mortality of COVID-19 in low-resource settings (LRS). This review aimed to identify currently proposed and/or implemented methods of screening, triaging, and severity scoring of patients with suspected COVID-19 on initial presentation to the healthcare system and to evaluate the utility of these tools in LRS.

DESIGN

A scoping review was conducted to identify studies describing acute screening, triage, and severity scoring of patients with suspected COVID-19 published between 12 December 2019 and 1 April 2021. Extracted information included clinical features, use of laboratory and imaging studies, and relevant tool validation data.

PARTICIPANT

The initial search strategy yielded 15 232 articles; 124 met inclusion criteria.

RESULTS

Most studies were from China (n=41, 33.1%) or the United States (n=23, 18.5%). In total, 57 screening, 23 triage, and 54 severity scoring tools were described. A total of 51 tools-31 screening, 5 triage, and 15 severity scoring-were identified as feasible for use in LRS. A total of 37 studies provided validation data: 4 prospective and 33 retrospective, with none from low-income and lower middle-income countries.

CONCLUSIONS

This study identified a number of screening, triage, and severity scoring tools implemented and proposed for patients with suspected COVID-19. No tools were specifically designed and validated in LRS. Tools specific to resource limited contexts is crucial to reducing mortality in the current pandemic.

Resumption of professional football during the COVID-19 pandemic. Study findings from Iran

Due to concerns of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) transmission, professional football (soccer) was terminated almost everywhere in the world in early 2020. These are the results from a prospective cohort study conducted in Iran to analyze the resumption of professional football during the coronavirus disease 2019 (COVID-19) pandemic under assigned protocols and regulations. Sixteen teams consisting of 805 individuals formally agreed to follow the rules assigned by the ministry of health and CORONA headquarters in sport, and were subject to study monitoring. The resumption process was implemented over a 5-month period, beginning with a training phase followed by 14 match weeks of professional football. A self-declaration form was provided for the subjects to report any suspicious symptoms immediately and serial PCR testing was performed every 10 days using nasal swab samples. Those with positive tests were to be isolated until the symptoms were resolved or a negative test was returned. Of the 805 individuals included, 17.89% subjects were infected by the SARS-CoV‑2 virus (85 players and 59 staff members and officials). Only two matches were canceled in accordance with the regulations, and no severe cases were found. Case-tracing suggested that most transmissions occurred off the pitch. In conclusion, applying strict hygiene protocols and early case identification by performing repetitive PCR testing could benefit the resumption of professional football competitions.

Strategies to reduce the risk of SARS-CoV-2 importation from international travellers: modelling estimations for the United Kingdom, July 2020

BackgroundTo mitigate SARS-CoV-2 transmission risks from international air travellers, many countries implemented a combination of up to 14 days of self-quarantine upon arrival plus PCR testing in the early stages of the COVID-19 pandemic in 2020.AimTo assess the effectiveness of quarantine and testing of international travellers to reduce risk of onward SARS-CoV-2 transmission into a destination country in the pre-COVID-19 vaccination era.MethodsWe used a simulation model of air travellers arriving in the United Kingdom from the European Union or the United States, incorporating timing of infection stages while varying quarantine duration and timing and number of PCR tests.ResultsQuarantine upon arrival with a PCR test on day 7 plus a 1-day delay for results can reduce the number of infectious arriving travellers released into the community by a median 94% (95% uncertainty interval (UI): 89-98) compared with a no quarantine/no test scenario. This reduction is similar to that achieved by a 14-day quarantine period (median > 99%; 95% UI: 98-100). Even shorter quarantine periods can prevent a substantial amount of transmission; all strategies in which travellers spend at least 5 days (mean incubation period) in quarantine and have at least one negative test before release are highly effective (median reduction 89%; 95% UI: 83-95)).ConclusionThe effect of different screening strategies impacts asymptomatic and symptomatic individuals differently. The choice of an optimal quarantine and testing strategy for unvaccinated air travellers may vary based on the number of possible imported infections relative to domestic incidence.

Depression, Anxiety, and Suicidal Ideation in Chinese University Students During the COVID-19 Pandemic

Coronavirus disease-2019 (COVID-19) pandemic has seriously threatened the global public health security and caused a series of mental health problem. Current research focuses mainly on mental health status and related factors in the COVID-19 pandemic among Chinese university students. Data from 11133 participants was obtained through an online survey. The Patient Health Question-9 (PHQ-9) was used to assess depressive symptoms, the Social Support Rate Scale (SSRS) was used to assess social support. We also used 7-item Generalized Anxiety Disorder Scale (GAD-7) to assess anxiety symptoms. Totally, 37.0% of the subjects were experiencing depressive symptoms, 24.9% anxiety symptoms, 20.9% comorbid depressive and anxiety symptoms, and 7.3% suicidal ideation. Multivariable logistic regression analysis revealed an increased presence of mental health problems in female students, graduate students, and those with personal COVID-19 exposure. Awareness of COVID-19, living with family were protective factors that reduced anxiety and depression symptoms. In addition, male, personal COVID-19 exposure, depressive and anxiety symptoms were risk factors for suicidal ideation. Social support, COVID-19 preventive and control measures, prediction of COVID-19 trends, living with family and graduate students are protective factors for reducing suicidal ideation.

Analysis and Evaluation of Non-Pharmaceutical Interventions on Prevention and Control of COVID-19: A Case Study of Wuhan City

As the threat of COVID-19 increases, many countries have carried out various non-pharmaceutical interventions. Although many studies have evaluated the impact of these interventions, there is a lack of mapping between model parameters and actual geographic areas. In this study, a non-pharmaceutical intervention model of COVID-19 based on a discrete grid is proposed from the perspective of geography. This model can provide more direct and effective information for the formulation of prevention and control policies. First, a multi-level grid was introduced to divide the geographical space, and the properties of the grid boundary were used to describe the quarantine status and intensity in these different spaces; this was also combined with the model of hospital isolation and self-protection. Then, a process for the spatiotemporal evolution of the early COVID-19 spread is proposed that integrated the characteristics of residents’ daily activities. Finally, the effect of the interventions was quantitatively analyzed by the dynamic transmission model of COVID-19. The results showed that quarantining is the most effective intervention, especially for infectious diseases with a high infectivity. The introduction of a quarantine could effectively reduce the number of infected humans, advance the peak of the maximum infected number of people, and shorten the duration of the pandemic. However, quarantines only function properly when employed at sufficient intensity; hospital isolation and self-protection measures can effectively slow the spread of COVID-19, thus providing more time for the relevant departments to prepare, but an outbreak will occur again when the hospital reaches full capacity. Moreover, medical resources should be concentrated in places where there is the most urgent need under a strict quarantine measure.

A follow up survey on the impact of COVID-19 on hand therapy practice

BACKGROUND

The coronavirus-19 pandemic continues to influence on the hand therapy community. It is important to understand how therapists are currently affected and how things have changed since the onset of the pandemic.

PURPOSE

Follow-up on a previous survey and investigate the current status of hand therapy practice 10 months into the pandemic.

STUDY DESIGN

Web-based survey.

METHODS

A 38-item survey was electronically delivered to American Society of Hand Therapists members between December 9, 2020 and January 6, 2021. Stress, safety measures, changes in practice patterns and telehealth were focus areas in the survey. Spearman's Rank Correlation Coefficient was used to analyze nonparametric correlations, Chi-Square analysis examined relationships between categorical values and unpaired t-tests were utilized for the comparison of means.

RESULTS

Of the 378 respondents, 85% reported higher stress levels compared to pre-pandemic times. Younger therapists expressed more stress over childcare concerns (r_s = 0.38;P = .000) and job security (r_s = 0.21; P = .000), while older therapists expressed more stress over eldercare concerns (r_s= -.13;P = .018). Descriptively, hours spent on direct clinical care were near prepandemic levels. Telehealth is currently used by 29% of respondents and did not correlate to age or years of practice. Postoperative cases (t(423) = 4.18;P = .0001) and people age 50-64-years (t(423) = 3.01;P = .002) were most frequently seen for in person visits. Nontraumatic, nonoperative cases (t(423) = 4.52;P = .0001) as well as those 65 years and older (t(423) = 3.71; P = .0002) were more likely to be seen via telehealth.

CONCLUSIONS

Hand therapists are adapting as reflected by the return to near normal work hours and less utilization of telehealth. Respondents still report higher levels of stress compared to prior to the pandemic, and this stress appears to be multifactorial in nature. Weariness with the precautionary measures such as mask wearing, social distancing and sanitizing was expressed through open-ended responses.

New Coronavirus (SARS-CoV-2) Crossing Borders Beyond Cities, Nations, and Continents: Impact of International Travel

The third outbreak of coronavirus in the form of the COVID-19 infection started in Wuhan, China, in December 2019. The early and rapid spread of this infection across borders can be largely attributed to international air travel that has become a part of modern globalization. In this article, we analyze the spread of the novel coronavirus (SARS-CoV-2) along the routes of international travel, both by air and by sea. Pitfalls of various screening methods used at the airports and the importance of optimal aircraft ventilation are discussed. Also, we suggest measures that can be taken to reduce the risk of transmission associated with air travel.

The differential importation risks of COVID-19 from inbound travellers and the feasibility of targeted travel controls: A case study in Hong Kong

Background

Many countries/regions implemented strict border measures (e.g., 14-day quarantines) as a blanket policy to prevent COVID-19 importations, while proposed “travel bubbles” as an alternative to reduce the impact of border controls. We aim to examine the differential importation risks with departure origins and post-arrival controls.

Methods

We developed a Bayesian framework to model disease progress of COVID-19 and the effectiveness of travel measures and inferred the origin-specific disease prevalence among inbound travellers, using data on passengers arriving in Hong Kong and laboratory-confirmed imported cases. We estimated the origin-specific risks of releasing infectious travellers under different control strategies and traveller volumes. We also estimated the risk of having released infectious travellers when a resurgence occurs in departure locations with no imported cases during a certain period.

Findings

Under the then strict controls of 14-day quarantine and testing on day 12, the Philippines imposed the greatest importation risk among the studied countries/regions (95.8% of releasing at least one infectious traveller, 95% credible interval (CrI), 94.8-96.6%). This was higher than that from low prevalence countries/regions (e.g., 23.4%, 95% CrI, 21.6-25.3% for Taiwan) if controls relaxed (i.e., 7-day quarantine and test on day 5). Increased traveller volumes and resurgence in departure locations with low prevalence under relaxed controls did not impose a greater importation risk than high prevalence locations under stricter controls.

Interpretation

Moderate relaxation of control measures for travellers arriving from low prevalence locations did not impose higher risks of community outbreaks than strict controls on travellers from high prevalence locations.

Funding

Health and Medical Research Fund, Hong Kong.

Quality Improvement for Rapid Development and Scale-Up of COVID-19-Related Screening Processes

BACKGROUND

In March 2020, Ohio strongly recommended temperature and health screening for coronavirus disease 2019 symptoms in all businesses to reduce the spread of infection.

METHODS

We used multiple plan-do-study-act cycles and workplace efficiency techniques iteratively to develop 12 intervention components required to effectively screen employees and visitors across all locations. We used run and control charts to summarize our performance over time.

RESULTS

Over the course of 20 days of rapid testing, we increased from 0% to 100% of locations successfully screening. The volume of people undergoing screening peaked during employee shift change. Employee positive screen results decreased by >50% after the first 7 days of screening, whereas family positive screen results remained stable throughout the study period.

CONCLUSIONS

An empowered, multidepartmental steering team, disciplined use of rapid cycle quality improvement processes, and explicit, standardized training processes enabled rapid successful scale-up of standard screening and masking process for employees and patients during the coronavirus disease 2019 pandemic. This approach can assist hospitals in adapting screening processes to evolving evidence.

Evolution of an asymptomatic first stage of infection in a heterogeneous population

Pathogens evolve different life-history strategies, which depend in part on differences in their host populations. A central feature of hosts is their population structure (e.g. spatial). Additionally, hosts themselves can exhibit different degrees of symptoms when newly infected; this latency is a key life-history property of pathogens. With an evolutionary-epidemiological model, we examine the role of population structure on the evolutionary dynamics of latency. We focus on specific power-law-like formulations for transmission and progression from the first infectious stage as a function of latency, assuming that the across-group to within-group transmission ratio increases if hosts are less symptomatic. We find that simple population heterogeneity can lead to local evolutionarily stable strategies (ESSs) at zero and infinite latency in situations where a unique ESS exists in the corresponding homogeneous case. Furthermore, there can exist more than one interior evolutionarily singular strategy. We find that this diversity of outcomes is due to the (possibly slight) advantage of across-group transmission for pathogens that produce fewer symptoms in a first infectious stage. Thus, our work reveals that allowing individuals without symptoms to travel can have important unintended evolutionary effects and is thus fundamentally problematic in view of the evolutionary dynamics of latency.

The effect of the synchronized multi-dimensional policies on imported COVID-19 curtailment in China

As countries are lifting restrictions and resuming international travels, the rising risk of COVID-19 importation remains concerning, given that the SARS-CoV-2 virus could be transmitted unintentionally through the global transportation network. To explore and assess the effective strategies for curtailing the epidemic risk from international importation nationwide, we evaluated "the joint prevention and control" mechanism, which made up of 19 containment policies, on how it impacted the change of medical observation and detection time from border arrival to laboratory confirmation of COVID-19 in its burst in China. Based on 1,314 epidemiological-survey cases from February 29 to May 25, 2020, we found that the synchronized approach of implementing multi-dimensional interventional policies, such as a centralized quarantine and nucleic acid testing (NAT), flight service adjustment and border closure, effectively facilitate early identification of infected case. Specifically, the implementation of the international flight service reduction was found to be associated with a reduction of the mean intervals of diagnosis from arrival to lab-confirmation by 0.44 days maximally, and the border closure was associated with a reduction of the diagnosis interval of imported cases by 0.69 days, from arrival to laboratory confirmation. The study suggests that a timely and synchronized implementation of multi-dimensional policies is compelling in preventing domestic spreading from importation.

COVID-19: breaking down a global health crisis

Coronavirus disease 2019 (COVID-19) is the second pandemic of the twenty-first century, with over one-hundred million infections and over two million deaths to date. It is a novel strain from the Coronaviridae family, named Severe Acute Respiratory Distress Syndrome Coronavirus-2 (SARS-CoV-2); the 7th known member of the coronavirus family to cause disease in humans, notably following the Middle East Respiratory syndrome (MERS), and Severe Acute Respiratory Distress Syndrome (SARS). The most characteristic feature of this single-stranded RNA molecule includes the spike glycoprotein on its surface. Most patients with COVID-19, of which the elderly and immunocompromised are most at risk, complain of flu-like symptoms, including dry cough and headache. The most common complications include pneumonia, acute respiratory distress syndrome, septic shock, and cardiovascular manifestations. Transmission of SARS-CoV-2 is mainly via respiratory droplets, either directly from the air when an infected patient coughs or sneezes, or in the form of fomites on surfaces. Maintaining hand-hygiene, social distancing, and personal protective equipment (i.e., masks) remain the most effective precautions. Patient management includes supportive care and anticoagulative measures, with a focus on maintaining respiratory function. Therapy with dexamethasone, remdesivir, and tocilizumab appear to be most promising to date, with hydroxychloroquine, lopinavir, ritonavir, and interferons falling out of favour. Additionally, accelerated vaccination efforts have taken place internationally, with several promising vaccinations being mass deployed. In response to the COVID-19 pandemic, countries and stakeholders have taken varying precautions to combat and contain the spread of the virus and dampen its collateral economic damage. This review paper aims to synthesize the impact of the virus on a global, micro to macro scale.

Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study

BACKGROUND

COVID-19 outbreaks have occurred in homeless shelters across the US, highlighting an urgent need to identify the most effective infection control strategy to prevent future outbreaks.

METHODS

We developed a microsimulation model of SARS-CoV-2 transmission in a homeless shelter and calibrated it to data from cross-sectional polymerase chain reaction (PCR) surveys conducted during COVID-19 outbreaks in five homeless shelters in three US cities from March 28 to April 10, 2020. We estimated the probability of averting a COVID-19 outbreak when an exposed individual is introduced into a representative homeless shelter of 250 residents and 50 staff over 30 days under different infection control strategies, including daily symptom-based screening, twice-weekly PCR testing, and universal mask wearing.

RESULTS

The proportion of PCR-positive residents and staff at the shelters with observed outbreaks ranged from 2.6 to 51.6%, which translated to the basic reproduction number (R0) estimates of 2.9-6.2. With moderate community incidence (~ 30 confirmed cases/1,000,000 people/day), the estimated probabilities of averting an outbreak in a low-risk (R0 = 1.5), moderate-risk (R0 = 2.9), and high-risk (R0 = 6.2) shelter were respectively 0.35, 0.13, and 0.04 for daily symptom-based screening; 0.53, 0.20, and 0.09 for twice-weekly PCR testing; 0.62, 0.27, and 0.08 for universal masking; and 0.74, 0.42, and 0.19 for these strategies in combination. The probability of averting an outbreak diminished with higher transmissibility (R0) within the simulated shelter and increasing incidence in the local community.

CONCLUSIONS

In high-risk homeless shelter environments and locations with high community incidence of COVID-19, even intensive infection control strategies (incorporating daily symptom screening, frequent PCR testing, and universal mask wearing) are unlikely to prevent outbreaks, suggesting a need for non-congregate housing arrangements for people experiencing homelessness. In lower-risk environments, combined interventions should be employed to reduce outbreak risk.

Does vitamin D serum level affect prognosis of COVID-19 patients?

Background

Since the beginning of the Coronavirus disease 2019 (COVID-19) pandemic there have been contradictions and speculations about the relationship between vitamin D and COVID-19. Given that there is an association between vitamin D deficiency and some diseases – including cancer, autoimmune disease and some infectious diseases – a higher incidence and mortality rate in the vitamin-D-deficient COVID-19 population was not a surprise; conversely, some research would argue this relationship. Considering these contradictions, this study aimed to determine the relationship between prognosis and vitamin D level in cases with COVID-19.

Methods

In this cross-sectional study, 329 confirmed cases of COVID-19 – who were admitted to Kamkar-ArabNia Hospital in Qom city, Iran from March–July 2020 – were categorized into three groups according to vitamin D serum levels (ng/ml): sufficient (>30), insufficient (20–30) and deficient (<20). Prognosis was determined across the groups.

Results

There was a significant difference in hospital stay between patients with sufficient and insufficient vitamin D levels (P = 0.007). Adjusting vitamin D levels for confounding variables, linear regression underscored significant differences in the association between length of hospitalization and lower vitamin D levels, with a longer stay noted in insufficient groups (P = 0.002). However, there was no significant difference in the time interval to return to normal oxygen level (from SpO2 < 93%) or death rate between groups (P > 0.05).

Conclusion

There was a significant association between hospital stay and lower serum vitamin D levels. However, the relationship between vitamin D status and death rate or the time interval to return to normal oxygen levels was not significant.

Modelling the impact of household size distribution on the transmission dynamics of COVID-19

Under the implementation of non-pharmaceutical interventions such as social distancing and lockdowns, household transmission has been shown to be significant for COVID-19, posing challenges for reducing incidence in settings where people are asked to self-isolate at home and to spend increasing amounts of time at home due to distancing measures. Accordingly, characteristics of households in a region have been shown to relate to transmission heterogeneity of the virus. We introduce a discrete-time stochastic epidemiological model to examine the impact of the household size distribution in a region on the transmission dynamics. We choose parameters to reflect incidence in two health regions of the Greater Vancouver area in British Columbia and simulate the impact of distancing measures on transmission, with household size distribution the only different parameter between simulations for the two regions. Our result suggests that the dissimilarity in household size distribution alone can cause significant differences in incidence of the two regions, and the distributions drive distinct dynamics that match reported cases. Furthermore, our model suggests that offering individuals a place to isolate outside their household can speed the decline in cases, and does so more effectively where there are more larger households.