A self-controlled case series study to measure the risk of SARS-CoV-2 infection associated with attendance at sporting and cultural events: the UK Events Research Programme events

BACKGROUND

In 2021, whilst societies were emerging from major social restrictions during the SARS-CoV-2 pandemic, the UK government instigated an Events Research Programme to examine the risk of COVID-19 transmission from attendance at cultural events and explore ways to enable people to attend a range of events whilst minimising risk of transmission. We aimed to measure any impact on risk of COVID-19 transmission from attendance at events held at or close to commercially viable capacity using routinely collected data.

METHODS

Data were obtained on attendees at Phase 3 Events Research Programme events, for which some infection risk mitigation measures were in place (i.e. evidence of vaccination or a negative lateral flow test). Attendance data were linked with COVID-19 test result data from the UK Test and Trace system. Using a self-controlled case series design, we measured the within person incidence rate ratio for testing positive for COVID-19, comparing the rate in days 3 to 9 following event attendance (high risk period) with days 1 and 2 and 10-16 (baseline period). Rate ratios were adjusted for estimates of underlying regional COVID-19 prevalence to account for population level fluctuations in infection risk, and events were grouped into broadly similar types.

RESULTS

From attendance data available for 188,851 attendees, 3357 people tested positive for COVID-19 during the observation period. After accounting for total testing trends over the period, incidence rate ratios and 95% confidence intervals for positive tests were 1.16 (0.53-2.57) for indoor seated events, 1.12 (0.95-1.30) for mainly outdoor seated events, 0.65 (0.51-0.83) for mainly outdoor partially seated events, and 1.70 (1.52-1.89) for mainly outdoor unseated multi-day events.

CONCLUSIONS

For the majority of event types studied in the third phase of the UK Events Research Programme, we found no evidence of an increased risk of COVID-19 transmission associated with event attendance. However, we found a 70% increased risk of infection associated with attendance at mainly outdoor unseated multi-day events. We have also demonstrated a novel use for self-controlled case series methodology in monitoring infection risk associated with event attendance.

Leveraging School Infection Data to Address Community COVID-19 Data Gaps

BACKGROUND

At-home COVID-19 tests became available in the USA in April 2021 with widespread use by January 2022; however, the lack of infrastructure to report test results to public health agencies created a gap in public health data. Kindergarten through grade 12 (K-12) schools often tracked COVID-19 cases among students and staff; leveraging school data may have helped bridge data gaps.

METHODS

We examined infection rates reported by school districts to ABC Science Collaborative with corresponding community rates from March 15, 2021 to June 3, 2022. We computed weekly ratios of community-to-district-reported rates (reporting ratios) across 3 study periods (spring 2021, fall 2021, and spring 2022) and estimated the difference and 95% confidence intervals (CIs) in the average reporting ratio between study periods.

RESULTS

In spring 2021, before approval or widespread use of at-home testing, the community-reported infection rate was higher than the school-reported infection rate (reporting ratio: 1.40). In fall 2021 and spring 2022, as at-home testing rapidly increased, school-reported rates were higher than community-reported rates (reporting ratios: 0.82 and 0.66). Average reporting ratios decreased between spring 2021 and fall 2021 (-0.58, 95% CI -0.84, -0.32) and spring 2021 and spring 2022 (-0.73, 95% CI -0.96, -0.48); there was no significant change between fall 2021 and spring 2022 (-0.15, 95% CI -0.36, 0.06).

CONCLUSIONS

At-home COVID-19 testing resulted in significant data gaps; K-12 data could have supplemented community data. In future public health emergencies, reporting of school data could minimize data gaps, but requires additional resources including funding to track infections and standardized data reporting methods.

A prospective study of extraesophageal reflux and potential microaspiration in patients hospitalized with COVID-19 in Jordan

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lung infection has represented a global challenge. Intriguingly, it has been shown that the alveolar lung epithelium expresses little Angiotensin Converting Enzyme receptor protein (ACE2), the entry receptor for SARS-CoV-2. Upper airway establishment of infection and translocation to the lung is well documented but other anatomical niches may be relevant to potentially serious lung infection. ACE2 is heavily expressed in the gastrointestinal tract and gastrointestinal symptoms support a clinical diagnosis of Coronavirus disease 2019 (COVID-19). This suggests a research question and the need to gather patient data exploring potential aerodigestive links in SARS-CoV-2 tranlocation and infection which may be relevant in the peripheral lung. This recognizes anatomical proximity and concepts of bi-directional movement between the Gastrointestinal and lung systems in normal physiology and disease. We have therefore explored the potential for gastro oesophageal reflux disease (GORD) micro aspiration and aeorodigestive pathophysiology in a novel prospective investigation of patients hospitalized with COVID-19.

METHODS

This is a prospective descriptive cohort study of 210 patients who were hospitalized with a confirmed diagnosis of COVID-19. The cohort was divided into three groups of patients based on symptom severity and radiological results. The Reflux Symptom Index (RSI) was used to evaluate the presence and severity of GOR. An RSI greater than 13 is considered to be abnormal. Patients' saliva samples were tested using enzyme-linked immunosorbent assay (ELISA) to determine the level of salivary pepsin among the cohort of patients.

RESULTS

A total of 210 patients with COVID-19 were enrolled in the study with 55.2% (116/210) classified as mildly ill, 31.9% (67/210) moderately ill and 12.9% (27/210) as severely ill. 34% (72/210) of the patients had an RSI score of over 13 and a median salivary pepsin value of 54 ± 29 ng/ml which suggested an incidence of extraesophageal reflux (EOR) in around a third of patients. The presence of respiratory comorbid conditions, an RSI score of over 13 and a salivary pepsin level of > 76ng/ml increased the risk of developing a more severe COVID-19 infection.

CONCLUSION

The study showed a high prevalence of EOR among the study cohort and provide the first prospective evidence suggesting the potential for aerodigestive pathophysiology including microaspiration in COVID-19 disease. We believe that the results of our study support the need for more extensive research.

Physics-Informed Neural Networks Integrating Compartmental Model for Analyzing COVID-19 Transmission Dynamics

Modelling and predicting the behaviour of infectious diseases is essential for early warning and evaluating the most effective interventions to prevent significant harm. Compartmental models produce a system of ordinary differential equations (ODEs) that are renowned for simulating the transmission dynamics of infectious diseases. However, the parameters in compartmental models are often unknown, and they can even change over time in the real world, making them difficult to determine. This study proposes an advanced artificial intelligence approach based on physics-informed neural networks (PINNs) to estimate time-varying parameters from given data for the compartmental model. Our proposed PINNs method captures the complex dynamics of COVID-19 by integrating a modified Susceptible-Exposed-Infectious-Recovered-Death (SEIRD) compartmental model with deep neural networks. Specifically, we modelled the system of ODEs as one network and the time-varying parameters as another network to address significant unknown parameters and limited data. Such structure of the PINNs method is in line with the prior epidemiological correlations and comprises the mismatch between available data and network output and the residual of ODEs. The experimental findings on real-world reported data data have demonstrated that our method robustly and accurately learns the dynamics and forecasts future states. Moreover, as more data becomes available, our proposed PINNs method can be successfully extended to other regions and infectious diseases.

An agricultural community's perspectives on COVID-19 testing to support safe school reopening

Introduction

School-based COVID-19 testing may be an effective strategy for reducing transmission in schools and keeping schools open. The study objective was to examine community perspectives on school-based COVID-19 testing as a mitigation strategy to support safe school reopening.

Methods

We conducted a qualitative study in Yakima County, an agricultural region of Washington state, where over half of residents are Hispanic/Latino. From June to July 2021, we interviewed 18 students (13 years old, on average) and 19 school employees, and conducted four focus groups (2 in Spanish, 2 in English) with 26 parents. We audio-recorded the semi-structured interviews and focus group discussions which were then transcribed. We used an inductive, constant comparison approach to code the transcripts and conducted a thematic analysis to generate themes.

Results

We identified four main themes. Students, parents, and school employees desired a return to in-person learning (Theme 1). Schools implemented numerous COVID-19 mitigation strategies (e.g., masking) to facilitate a safe return to school but felt that adding testing would not be feasible due to a lack of resources and overworked staff (Theme 2). Parents and school employees' familiarity with COVID-19 testing procedures influenced their support for testing (Theme 3). Parents and school employees felt there were inadequate resources for individuals who test positive for COVID-19 (Theme 4).

Discussion

Schools require adequate resources and medical personnel to implement COVID-19 testing. Individuals also need resources after testing positive, including physical space to isolate, financial resources for those without paid time off, and delivery of food and other necessities to households in rural communities.

Prevalence of gastro-intestinal symptoms among COVID-19 patients and the association with disease clinical outcomes

Aim

This study examined the various manifestations of COVID-19 in people's gastro-intestinal system and how gastro-intestinal involvement relates to the progression and outcome of the disease.

Methodology

A questionnaire survey was used to collect data from 561 COVID-19 patients between February 6 and 6 April 2022. Laboratory data and clinical outcomes were obtained from the patients' medical records.

Results

39.9% of patients presented gastro-intestinal symptoms, mainly loss of appetite, nausea, vomiting and diarrhea. Gastro-intestinal symptoms were not linked to poorer outcomes such as mortality, ICU admission or length of hospital stays.

Conclusion

gastro-intestinal symptoms were common among patients and may manifest with respiratory symptoms. We recommended clinicians to watch out for gastro-intestinal symptoms as related to COVID-19 infection.

Geo-epidemiological approach of the COVID-19 pandemic in France and in Europe for public health policies

The spread of the COVID-19 pandemic has shown great heterogeneity between countries that merits investigation. There is a need to better highlight the variability in the pandemic trajectories in different geographic areas. By using openly available data from 'GitHub' COVID-19 dataset for Europe and from the official dataset of France for the period 2020 to 2021, I present the three COVID-19 waves in France and Europe in maps. The epidemic trends across areas display different evolutions for different time periods. National and European public health authorities will be able to improve allocation of resources for more effective public health measures based on geo-epidemiological analyses.

Transmission potential of vaccinated and unvaccinated persons infected with the SARS-CoV-2 Delta variant in a federal prison, July-August 2021

BACKGROUND

The extent to which vaccinated persons who become infected with SARS-CoV-2 contribute to transmission is unclear. During a SARS-CoV-2 Delta variant outbreak among incarcerated persons with high vaccination rates in a federal prison, we assessed markers of viral shedding in vaccinated and unvaccinated persons.

METHODS

Consenting incarcerated persons with confirmed SARS-CoV-2 infection provided mid-turbinate nasal specimens daily for 10 consecutive days and reported symptom data via questionnaire. Real-time reverse transcription-polymerase chain reaction (RT-PCR), viral whole genome sequencing, and viral culture was performed on these nasal specimens. Duration of RT-PCR positivity and viral culture positivity was assessed using survival analysis.

RESULTS

A total of 957 specimens were provided by 93 participants, of whom 78 (84 %) were vaccinated and 17 (16 %) were unvaccinated. No significant differences were detected in duration of RT-PCR positivity among vaccinated participants (median: 13 days) versus those unvaccinated (median: 13 days; p = 0.50), or in duration of culture positivity (medians: 5 days and 5 days; p = 0.29). Among vaccinated participants, overall duration of culture positivity was shorter among Moderna vaccine recipients versus Pfizer (p = 0.048) or Janssen (p = 0.003) vaccine recipients. In post-hoc analyses, Moderna vaccine recipients demonstrated significantly shorter duration of culture positivity compared to unvaccinated participants (p = 0.02). When restricted to participants without reported prior infection, the difference between Moderna vaccine recipients and unvaccinated participants was more pronounced (medians: 3 days and 6 days, p = 0.002).

CONCLUSIONS

Infectious periods for vaccinated and unvaccinated persons who become infected with SARS-CoV-2 are similar and can be highly variable, though some vaccinated persons are likely infectious for shorter durations. These findings are critically important, especially in congregate settings where viral transmission can lead to large outbreaks. In such settings, clinicians and public health practitioners should consider vaccinated, infected persons to be no less infectious than unvaccinated, infected persons.

Clinical, Virologic, and Immunologic Evaluation of Symptomatic Coronavirus Disease 2019 Rebound Following Nirmatrelvir/Ritonavir Treatment

BACKGROUND

Nirmatrelvir/ritonavir, the first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protease inhibitor, reduces the risk of hospitalization and death by coronavirus disease 2019 (COVID-19) but has been associated with symptomatic rebound after therapy completion.

METHODS

Six individuals with relapse of COVID-19 symptoms after treatment with nirmatrelvir/ritonavir, 2 individuals with rebound symptoms without prior antiviral therapy and 7 patients with acute Omicron infection (controls) were studied. Soluble biomarkers and serum SARS-CoV-2 nucleocapsid protein were measured. Nasal swabs positive for SARS-CoV-2 underwent viral isolation and targeted viral sequencing. SARS-CoV-2 anti-spike, anti-receptor-binding domain, and anti-nucleocapsid antibodies were measured. Surrogate viral neutralization tests against wild-type and Omicron spike protein, as well as T-cell stimulation assays, were performed.

RESULTS

High levels of SARS-CoV-2 anti-spike immunoglobulin G (IgG) antibodies were found in all participants. Anti-nucleocapsid IgG and Omicron-specific neutralizing antibodies increased in patients with rebound. Robust SARS-CoV-2-specific T-cell responses were observed, higher in rebound compared with early acute COVID-19 patients. Inflammatory markers mostly decreased during rebound. Two patients sampled longitudinally demonstrated an increase in activated cytokine-producing CD4+ T cells against viral proteins. No characteristic resistance mutations were identified. SARS-CoV-2 was isolated by culture from 1 of 8 rebound patients; Polybrene addition increased this to 5 of 8.

CONCLUSIONS

Nirmatrelvir/ritonavir treatment does not impede adaptive immune responses to SARS-CoV-2. Clinical rebound corresponds to development of a robust antibody and T-cell immune response, arguing against a high risk of disease progression. The presence of infectious virus supports the need for isolation and assessment of longer treatment courses.

CLINICAL TRIALS REGISTRATION

NCT04401436.

Assessment of SARS-CoV-2 entry in gingival epithelial cells expressing CD147

SARS-CoV-2, the causative agent of the debilitating COVID-19, is mainly transmitted by first infecting nose and lung epithelial cells. The mouth is also believed to be a viral portal site since certain types of oral epithelial cells were shown to express ACE2 receptor. However, it is unclear whether oral epithelial cells are directly infected by SARS-CoV-2. In this study, we addressed whether epithelial cells of the oral gingiva were susceptible to infection. Interestingly, we found that KRT5+ and KRT18+ gingival epithelial cells do not express ACE2 but highly express TMPRSS2 and Furin as well as CD147, which was proposed to be an alternative receptor for SARS-CoV-2. However, using SARS-CoV-2 pseudoviruses containing the spike protein, we observed that gingival epithelial cells were not susceptible to infection due to the lack of ACE2 expression and the inability of CD147 to mediate viral entry. These results strongly suggest that epithelial cells from the gingiva are not susceptible to SARS-CoV-2 and CD147 is not a receptor for the SARS-CoV-2 virus. The susceptibility of oral cells from other oral structures under healthy and pathological conditions still needs to be confirmed to better understand the role of the oral cavity in COVID-19 infection and transmission.

To open or not to open: the moderating effects of human mobility on the relationship between vaccination and COVID-19 transmission

COVID-19 vaccination is being used to control SARS-CoV-2 transmission globally, and many countries have relaxed some non-pharmaceutical interventions. It is unclear whether relaxing human mobility restrictions is proper and increases transmission risk. To fill this knowledge gap, we aim to examine if human mobility impairs the role of vaccination on COVID-19 transmission. We apply dynamic panel data models with three lag levels (i.e. 0 day, 7 days, and 14 days) to investigate the relationship between vaccination and COVID-19 transmission and the moderating effects of different kinds of human mobility. Our results show a negative relationship between the percentage of the vaccinated population and daily new COVID-19 cases after controlling for human mobility. We also observe that when people are only vaccinated with one dose, increased human mobility in retail and recreation, grocery and pharmacy, parks, transit stations, and workplaces could impair the role of vaccination on COVID-19 transmission, although their moderating effects appear at different lag levels. However, there are no moderating effects of human mobility in transit stations and workplaces at all lag levels when people are fully vaccinated. This finding does not mean that governments may relax restrictions in these two areas since mobility in transit stations and workplaces could affect COVID-19 transmission by themselves directly. Therefore, we recommend that governments still insist on implementing human mobility control measures from the perspective of transmission risk.

Longitudinal Participatory Surveillance Highlights Association Between Mask-Wearing and Lower COVID-19 Risk - United States, 2020

What is already known about this topic?

Numerous ecological and laboratory studies suggest face masks are an effective non-pharmaceutical intervention for reducing the spread of coronavirus disease 2019 (COVID-19), but cannot otherwise assess individual-level effects.

What is added by this report?

Using a prospective cohort of individuals enrolled in a participatory, syndromic surveillance tool prior to the first case of COVID-19 in the United States, we present a novel longitudinal assessment of the effectiveness of face masks.

What are the public health implications for public health practice?

Our analysis demonstrates an association between self-reported mask-wearing behavior and lower individual risk of syndromic COVID-19-like illness while adjusting for confounders at the individual level. Our results also highlight the dual utility of participatory syndromic surveillance systems as both disease trend monitors and tools that can aid in understanding the effectiveness of personal protective measures.

Paramedics' knowledge, attitudes, and practices regarding the use of personal protective equipment against COVID-19

The risk of novel coronavirus disease (COVID-19) transmission in the confined mobile ambulance compartment is increased during aerosol-generating procedures and close proximity. Paramedics are encouraged to increase body-surface-isolation by donning additional personal protective equipment (PPE) during patient encounters. This study aimed to better understand paramedics’ knowledge, attitudes, and practices related to PPE use during the COVID-19 pandemic in the prehospital setting with a focus on mitigating risks associated with infection control.

This prospective quantitative study collected descriptive data using a specifically designed data collection tool. The survey data was then cleaned and analyzed with Microsoft Excel® and the latest version of the Statistical Package for Social Sciences.

One thousand frontline paramedics employed by the Hamad Medical Corporation Ambulance Service (HMCAS) were invited via email to participate in the study. A total of 282 (28.2% of frontline paramedics) paramedics completed the online survey, of which 80.1% completed the mandatory HMCAS online infection control training program within the last year, and 17.0% between one to two years ago. Approximately 83% of the participants had completed an N95 mask fit test at HMCAS within the past five years, and 91.5% completed the hand hygiene training.

The study found that 98.2% of the paramedics were knowledgeable about COVID-19 and its transmission, while 96.1% agreed that aerosol-generating procedures increased airborne transmission. The paramedics’ attitudes were mainly positive toward the use of PPE to prevent the spread of the virus, which was synchronous with their practice. The sample population demonstrated a strong knowledge of COVID-19 and its transmission. Their overall positive attitudes and good infection control practices were demonstrative of efforts to mitigate risks associated with the spread of the virus.

COVID-19 transmission in cities

Do cities accelerate COVID-19 transmission? Increased transmission arising from population density prompts spatial policies for financial support and containment, and poorer prospects for recovery. Using daily case counts from over 3,000 counties in the U.S. from February to September 2020, I estimate a compartmental transmission equation. Rational sheltering behavior plausibly varies by location, so I propose two instruments that exploit unanticipated variation in exposure to potential infection. In the first month of local infections, an additional log point of population density raises the expected transmission parameter estimate by around 3%. After the first month, the relation vanishes: density effects occur only in the outbreaks. Public transport, work-from-home jobs and income explain additional variation in transmission but do not account for the density effects. Consistent with location-varying optimal sheltering behavior, I document stronger mobility declines in denser areas, but only after the first month of infections. These results suggest that differences in transmission between cities and other places do not motivate spatial policies for recovery or containment, or poorer prospects after the pandemic.

Modeling COVID-19 Transmission Dynamics: A Bibliometric Review

A good amount of research has evolved just in three years in COVID-19 transmission, mortality, vaccination, and some socioeconomic studies. A few bibliometric reviews have already been performed in the literature, especially on the broad theme of COVID-19, without any particular area such as transmission, mortality, or vaccination. This paper fills this gap by conducting a bibliometric review on COVID-19 transmission as the first of its kind. The main aim of this study is to conduct a bibliometric review of the literature in the area of COVID-19 transmission dynamics. We have conducted bibliometric analysis using descriptive and network analysis methods to review the literature in this area using RStudio, Openrefine, VOSviewer, and Tableau. We reviewed 1103 articles published in 2020-2022. The result identified the top authors, top disciplines, research patterns, and hotspots and gave us clear directions for classifying research topics in this area. New research areas are rapidly emerging in this area, which needs constant observation by researchers to combat this global epidemic.

Deep learning modelling of public's sentiments towards temporal evolution of COVID-19 transmission

Public sentiments towards global pandemics are important for public health assessment and disease control. This study develops a modularized deep learning framework to quantify public sentiments towards COVID-19, followed by leveraging the predicted sentiments to model and forecast the daily growth rate of confirmed COVID-19 cases globally, via a proposed G parameter. In the proposed framework, public sentiments are first modeled via a valence dimensional indicator, instead of discrete schemas, and are classified into 4 primary emotional categories: (a) neutral; (b) negative; (c) positive; (d) ambivalent, by using multiple word embedding models and classifiers for text sentiments analyses and classification. The trained model is subsequently applied to analyze large volumes (millions in quantity) of daily Tweets pertaining to COVID-19, ranging from 22 Jan 2020 to 10 May 2020. The results demonstrate that the global community gradually evokes both positive and negative sentiments towards COVID-19 over time compared to the dominant neural emotion at its inception. The predicted time-series sentiments are then leveraged to train a deep neural network (DNN) to model and forecast the G parameter by achieving the lowest possible mean absolute percentage error (MAPE) score of around 17.0% during the model's testing step with the optimal model configuration.

The effect of air purifiers and curtains on aerosol dispersion and removal in multi-patient hospital rooms

Airborne transmission of disease is of concern in many indoor spaces. Here, aerosol dispersion and removal in an unoccupied 4-bed hospital room were characterized using a transient aerosol tracer experiment for 38 experiments covering 4 configurations of air purifiers and 3 configurations of curtains. NaCl particle (mass mean aerodynamic diameter ~3 μm) concentrations were measured around the room following an aerosol release. Particle transport across the room was 1.5-4 min which overlaps with the characteristic times for significant viral deactivation and gravitational settling of larger particles. Concentrations were close to spatially uniform except very near the source. Curtains resulted in a modest increase in delay and decay times, less so when combined with purifiers. The aerosol decay rate was in most cases higher than expected from the clean air delivery rate, but the reduction in steady-state concentrations resulting from air purifiers was less than suggested by the decay rates. Apparently, a substantial (and configuration-dependent) fraction of the aerosol is removed immediately, and this effect is not captured by the decay rate. Overall, the combination of curtains and purifiers is likely to reduce disease transmission in multi-patient hospital rooms.

In-person learning low risk for COVID-19 acquisition: Findings from a population-based analysis of the 2020-2021 school year in Saskatchewan, Canada

Background

The coronavirus disease 2019 (COVID-19) pandemic has caused substantial disruption to in-person learning, often interfering with the social and educational experience of children and youth across North America, and frequently impacting the greater community by limiting the ability of parents and caregivers to work outside the home. Real-world evidence related to the risk of COVID-19 transmission in school settings can help inform decisions around initiating, continuing, or suspending in-person learning.

Methods

We analyzed routinely collected case-based surveillance data from Saskatchewan's electronic integrated public health system, Panorama, from the 2020-2021 school year, spanning various phases of the pandemic (including the Alpha variant wave), to better understand the risk of in-school transmission of COVID-19 in Saskatchewan schools.

Results

The majority (over 80%) of school-associated COVID-19 infections were acquired outside the school setting. This finding suggests that the non-pharmaceutical measures in place (including masking, distancing, enhanced hygiene, and cohorting) worked to limit viral spread in schools.

Conclusion

Implementation of such control measures may play an essential role in allowing children and youth to safely maintain in-person learning during the pandemic.

Estimation of the risk of COVID-19 transmission through aerosol-generating procedures

BACKGROUND

The outbreak of the coronavirus disease 2019 (COVID-19) pandemic was associated with the provision of multiple guidelines for the dental profession. All elective procedures were restricted, and only emergency procedures were performed. There was fear and anxiety among dentists while performing aerosol-generating procedures (AGPs), as they were considered to pose a high risk of COVID-19 transmission.

OBJECTIVES

The aim of this study was to assess the risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during AGPs, and to examine the association between risk severity and the number of AGPs performed per day. The efficacy of personal protective equipment (PPE) was also assessed.

MATERIAL AND METHODS

This cross-sectional cohort study was based on an online questionnaire form completed by 629 general and specialized dentists between January 1 and February 28, 2021. The collected data referred to the sources of COVID-19 infection, the type of PPE used and the number of AGPs performed each day by dental healthcare professionals (DHCPs). For each question, the absolute numbers of responses as well as percentages were calculated.

RESULTS

Among the 629 DHCPs, 113 (17.97%) contracted COVID-19. The risk of contracting COVID-19 during AGPs was the same as in the case of non-AGPs, and the infection risk was not associated with the number of AGPs performed per day. The efficacy of a surgical mask with a face shield/eye goggles was higher in comparison with all other types of PPE. Differences in the infection risk across the different types of PPE used were statistically significant (p < 0.001).

CONCLUSIONS

The risk of COVID-19 transmission during AGPs is the same as in the case of non-AGPs. Thus, restrictions on the performance of elective AGPs should be lifted. On the other hand, the best protection during AGPs is provided by a surgical mask with a face shield/eye goggles.

COVID-19 pandemic over 2020 (withlockdowns) and 2021 (with vaccinations): similar effects for seasonality and environmental factors

How is the dynamics of Coronavirus Disease 2019 (COVID-19) in 2020 with an health policy of full lockdowns and in 2021 with a vast campaign of vaccinations? The present study confronts this question here by developing a comparative analysis of the effects of COVID-19 pandemic between April-September 2020 (based upon strong control measures) and April-September 2021 (focused on health policy of vaccinations) in Italy, which was one of the first European countries to experience in 2020 high numbers of COVID-19 related infected individuals and deaths and in 2021 Italy has a high share of people fully vaccinated against COVID-19 (>89% of population aged over 12 years in January 2022). Results suggest that over the period under study, the arithmetic mean of confirmed cases, hospitalizations of people and admissions to Intensive Care Units (ICUs) in 2020 and 2021 is significantly equal (p-value<0.01), except fatality rate. Results suggest in December 2021 lower hospitalizations, admissions to ICUs, and fatality rate of COVID-19 than December 2020, though confirmed cases and mortality rates are in 2021 higher than 2020, and likely converging trends in the first quarter of 2022. These findings reveal that COVID-19 pandemic is driven by seasonality and environmental factors that reduce the negative effects in summer period, regardless control measures and/or vaccination campaigns. These findings here can be of benefit to design health policy responses of crisis management considering the growth of COVID-19 pandemic in winter months having reduced temperatures and low solar radiations ( COVID-19 has a behaviour of influenza-like illness). Hence, findings here suggest that strategies of prevention and control of infectious diseases similar to COVID-19 should be set up in summer months and fully implemented during low-solar-irradiation periods (autumn and winter period).

High-flow nasal oxygen as first-line therapy for COVID-19-associated hypoxemic respiratory failure: a single-centre historical cohort study

PURPOSE

The optimal noninvasive modality for oxygenation support in COVID-19-associated hypoxemic respiratory failure and its association with healthcare worker infection remain uncertain. We report here our experience using high-flow nasal oxygen (HFNO) as the primary support mode for patients with COVID-19 in our institution.

METHODS

We conducted a single-centre historical cohort study of all COVID-19 patients treated with HFNO for at least two hours in our university-affiliated and intensivist-staffed intensive care unit (Jewish General Hospital, Montreal, QC, Canada) between 27 August 2020 and 30 April 2021. We report their clinical characteristics and outcomes. Healthcare workers in our unit cared for these patients in single negative pressure rooms wearing KN95 or fit-tested N95 masks; they underwent mandatory symptomatic screening for COVID-19 infection, as well as a period of asymptomatic screening.

RESULTS

One hundred and forty-two patients were analysed, with a median [interquartile range (IQR)] age of 66 [59-73] yr; 71% were male. Patients had a median [IQR] Sequential Organ Failure Assessment Score of 3 [2-3], median [IQR] oxygen saturation by pulse oximetry/fraction of inspired oxygen ratio of 120 [94-164], and a median [IQR] 4C score (a COVID-19-specific mortality score) of 12 [10-14]. Endotracheal intubation occurred in 48/142 (34%) patients, and overall hospital mortality was 16%. Barotrauma occurred in 21/142 (15%) patients. Among 27 symptomatic and 139 asymptomatic screening tests, there were no cases of HFNO-related COVID-19 transmission to healthcare workers.

CONCLUSION

Our experience indicates that HFNO is an effective first-line therapy for hypoxemic respiratory failure in COVID-19 patients, and can be safely used without significant discernable infection risk to healthcare workers.

Climatic influence on the magnitude of COVID-19 outbreak: a stochastic model-based global analysis

We investigate the climatic influence on COVID-19 transmission risks in 228 cities globally across three climatic zones. The results, based on the application of a Boosted Regression Tree algorithm method, show that average temperature and average relative humidity explain significant variations in COVID-19 transmission across temperate and subtropical regions, whereas in the tropical region, the average diurnal temperature range and temperature seasonality significantly predict the infection outbreak. The number of positive cases showed a decrease sharply above an average temperature of 10°C in the cities of France, Turkey, the US, the UK, and Germany. Among the tropical countries, COVID-19 in Indian cities is most affected by mean diurnal temperature, and those in Brazil by temperature seasonality. The findings have implications on public health interventions, and contribute to the ongoing scientific and policy discourse on the complex interplay of climatic factors determining the risks of COVID-19 transmission.

Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data

The outbreak of the COVID-19 has become a worldwide public health challenge for contemporary cities during the background of globalization and planetary urbanization. However, spatial factors affecting the transmission of the disease in urban spaces remain unclear. Based on geotagged COVID-19 cases from social media data in the early stage of the pandemic, this study explored the correlation between different infectious outcomes of COVID-19 transmission and various factors of the urban environment in the main urban area of Wuhan, utilizing the multiple regression model. The result shows that most spatial factors were strongly correlated to case aggregation areas of COVID-19 in terms of population density, human mobility and environmental quality, which provides urban planners and administrators valuable insights for building healthy and safe cities in an uncertain future.

Cold Chain Food and COVID-19 Transmission Risk: From the Perspective of Consumption and Trade

Since the outbreak of the coronavirus disease 2019 (COVID-19), political and academic circles have focused significant attention on stopping the chain of COVID-19 transmission. In particular outbreaks related to cold chain food (CCF) have been reported, and there remains a possibility that CCF can be a carrier. Based on CCF consumption and trade matrix data, here, the "source" of COVID-19 transmission through CCF was analyzed using a complex network analysis method, informing the construction of a risk assessment model reflecting internal and external transmission dynamics. The model included the COVID-19 risk index, CCF consumption level, urbanization level, CCF trade quantity, and others. The risk level of COVID-19 transmission by CCF and the dominant risk types were analyzed at national and global scales as well as at the community level. The results were as follows. (1) The global CCF trade network is typically dominated by six core countries in six main communities, such as Indonesia, Argentina, Ukraine, Netherlands, and the USA. These locations are one of the highest sources of risk for COVID-19 transmission. (2) The risk of COVID-19 transmission by CCF in specific trade communities is higher than the global average, with the Netherlands-Germany community being at the highest level. There are eight European countries (i.e., Netherlands, Germany, Belgium, France, Spain, Britain, Italy, and Poland) and three American countries (namely the USA, Mexico, and Brazil) facing a very high level of COVID-19 transmission risk by CCF. (3) Of the countries, 62% are dominated by internal diffusion and 23% by external input risk. The countries with high comprehensive transmission risk mainly experience risks from external inputs. This study provides methods for tracing the source of virus transmission and provides a policy reference for preventing the chain of COVID-19 transmission by CCF and maintaining the security of the global food supply chain.

Interpretation of Discrepancies between Cities in the Transmission of COVID-19: Evidence from China in the First Weeks of the Pandemic: Interpreting the Discrepancies of COVID-19 Transmission

OBJECTIVES

This study aims to examine and explain the differences at city level in cumulative Covid-19 cases and time from first to last infection, during the first six weeks of the epidemic in China.

METHODS

A quantitative study is conducted in China based on the multi-source spatial data of 315 Chinese cities. Firstly, the spatial discrepancy of COVID-19 transmission was examined based on spatial autocorrelation analysis and hot pot analysis. Next, a comprehensive indicator framework was established by including a wide range of factors such as human mobility, geographical features, public health measures and residents' awareness. Finally, multivariate regression models employing the variables were constructed to identify the determinants of Covid-19 transmission.

RESULTS

Significant spatial discrepancy of transmission was proved and ten determinants were identified.

CONCLUSIONS

The transmission consequence (measured by number of cumulative cases) was mostly correlated with the migration scale from Wuhan, followed by socio-economic factors. Transmission duration (measured by the time from the first to last case within the city) was mostly determined by total migration scale and lockdown speed, which suggests that timely implementation of public health measures facilitated fast control of transmission. Residents' attention to COVID-19 was proved to be not only helpful for reducing confirmed cases, but also in favor of rapid transmission control. Altitude produced slightly but significant effect on transmission duration. Those conclusions are expected to provide decision support for the local governments of China and other jurisdictions.

The risk of COVID-19 transmission upon return to sport: a systematic review

OBJECTIVES

To evaluate COVID-19 transmission rates in athletes upon return to sport (RTS), as well as the effectiveness of preventive and surveillance measures associated with RTS.

METHODS

In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, the PubMed, Embase, and Cochrane Library databases were searched to identify all articles reporting on RTS during COVID-19. Articles were excluded on the basis of the following criteria: (1) non-English text, (2) only abstract available, (3) population not athlete-specific, (4) outcome not RTS-specific, (5) COVID-19 transmission data not quantified, (6) editorial, or (7) review article or meta-analysis. Study characteristics; athlete demographics; COVID-19 preventive, surveillance, and diagnostic measures; COVID-19 transmission outcomes; and RTS recommendations were collected from each included article and analyzed.

RESULTS

10 studies were included in the final analysis, comprising over 97,000 athletes across a wide variety of sports, levels of play, and RTS settings. Of the 10 studies, eight identified low transmission rates and considered RTS to be safe/low risk. Overall, COVID-19 transmission rates were higher in athletes than in contacts, and more prevalent in the greater community than in athletes specifically. The risk of COVID-19 did not appear to be necessarily higher for athletes who played high-contact team sports, shared common facilities, or lived in communities impacted by high transmission rates, provided that rigorous COVID-19 safety and testing protocols were implemented and followed. Mask wearing and physical distancing during active play presented the greatest challenge to athletes.

CONCLUSION

Rigorous preventive and surveillance measures can mitigate the risk of COVID-19 transmission in athletes upon RTS. However, the heterogeneity of RTS playing conditions, availability of COVID-19 resources, rise of unforeseen novel variants, and undetermined long-term impact of vaccination on athletes remain a challenge to safe and effective RTS in the era of COVID-19.

Modeling the dynamics of COVID-19 using fractal-fractional operator with a case study

This research study consists of a newly proposed Atangana-Baleanu derivative for transmission dynamics of the coronavirus (COVID-19) epidemic. Taking the advantage of non-local Atangana-Baleanu fractional-derivative approach, the dynamics of the well-known COVID-19 have been examined and analyzed with the induction of various infection phases and multiple routes of transmissions. For this purpose, an attempt is made to present a novel approach that initially formulates the proposed model using classical integer-order differential equations, followed by application of the fractal fractional derivative for obtaining the fractional COVID-19 model having arbitrary order Ψ and the fractal dimension Ξ . With this motive, some basic properties of the model that include equilibria and reproduction number are presented as well. Then, the stability of the equilibrium points is examined. Furthermore, a novel numerical method is introduced based on Adams-Bashforth fractal-fractional approach for the derivation of an iterative scheme of the fractal-fractional ABC model. This in turns, has helped us to obtained detailed graphical representation for several values of fractional and fractal orders Ψ and Ξ , respectively. In the end, graphical results and numerical simulation are presented for comprehending the impacts of the different model parameters and fractional order on the disease dynamics and the control. The outcomes of this research would provide strong theoretical insights for understanding mechanism of the infectious diseases and help the worldwide practitioners in adopting controlling strategies.

Public health impact of mass sporting and cultural events in a rising COVID-19 prevalence in England

A subset of events within the UK Government Events Research Programme (ERP), developed to examine the risk of transmission of COVID-19 from attendance at events, was examined to explore the public health impact of holding mass sporting events. We used contact tracing data routinely collected through telephone interviews and online questionnaires, to describe the potential public health impact of the large sporting and cultural events on potential transmission and incidence of COVID-19. Data from the EURO 2020 matches hosted at Wembley identified very high numbers of individuals who tested positive for COVID-19 and were traced through NHS Test & Trace. This included both individuals who were potentially infectious (3036) and those who acquired their infection during the time of the Final (6376). This is in contrast with the All England Lawn Tennis Championships at Wimbledon, where there were similar number of spectators and venue capacity but there were lower total numbers of potentially infectious cases (299) and potentially acquired cases (582). While the infections associated with the EURO 2020 event may be attributed to a set of socio-cultural circumstances which are unlikely to be replicated for the forthcoming sporting season, other aspects may be important to consider including mitigations for spectators to consider such as face coverings when travelling to and from events, minimising crowding in poorly ventilated indoor spaces such as bars and pubs where people may congregate to watch events, and reducing the risk of aerosol exposure through requesting that individuals avoid shouting and chanting in large groups in enclosed spaces.

Heterogeneity of the COVID-19 Pandemic in the United States of America: A Geo-Epidemiological Perspective

The spread of the COVID-19 pandemic has shown great heterogeneity between regions of countries, e. g., in the United States of America (USA). With the growing of the worldwide COVID-19 pandemic, there is a need to better highlight the variability in the trajectory of this disease in different worldwide geographic areas. Indeed, the epidemic trends across areas can display completely different evolution at a given time. Geo-epidemiological analyses using data, that are publicly available, could be a major topic to help governments and public administrations to implement health policies. Geo-epidemiological analyses could provide a basis for the implementation of relevant public health policies. With the COVID-19 pandemic, geo-epidemiological analyses can be readily utilized by policy interventions and USA public health authorities to highlight geographic areas of particular concern and enhance the allocation of resources.

The impact of weather condition and social activity on COVID-19 transmission in the United States

The coronavirus disease 2019 (COVID-19) has been first reported in December 2019 and rapidly spread worldwide. As other severe acute respiratory syndromes, it is a widely discussed topic whether seasonality affects the COVID-19 infection spreading. This study presents two different approaches to analyse the impact of social activity factors and weather variables on daily COVID-19 cases at county level over the Continental U.S. (CONUS). The first one is a traditional statistical method, i.e., Pearson correlation coefficient, whereas the second one is a machine learning algorithm, i.e., random forest regression model. The Pearson correlation is analysed to roughly test the relationship between COVID-19 cases and the weather variables or the social activity factor (i.e. social distance index). The random forest regression model investigates the feasibility of estimating the number of county-level daily confirmed COVID-19 cases by using different combinations of eight factors (county population, county population density, county social distance index, air temperature, specific humidity, shortwave radiation, precipitation, and wind speed). Results show that the number of daily confirmed COVID-19 cases is weakly correlated with the social distance index, air temperature and specific humidity through the Pearson correlation method. The random forest model shows that the estimation of COVID-19 cases is more accurate with adding weather variables as input data. Specifically, the most important factors for estimating daily COVID-19 cases are the population and population density, followed by the social distance index and the five weather variables, with temperature and specific humidity being more critical than shortwave radiation, wind speed, and precipitation. The validation process shows that the general values of correlation coefficients between the daily COVID-19 cases estimated by the random forest model and the observed ones are around 0.85.

Exploring the effects of PM2.5 and temperature on COVID-19 transmission in Seoul, South Korea

With a recent surge of the new severe acute respiratory syndrome-coronavirus 2 (SARS-Cov-2, COVID-19) in South Korea, this study attempts to investigate the effects of environmental conditions such as air pollutants (PM_2.5) and meteorological covariate (Temperature) on COVID-19 transmission in Seoul. To account for unobserved heterogeneity in the daily confirmed cases of COVID-19 across 25 contiguous districts within Seoul, we adopt a full Bayesian hierarchical approach for the generalized linear mixed models. A formal statistical analysis suggests that there exists a positive correlation between a 7-day lagged effect of PM_2.5 concentration and the number of confirmed COVID-19 cases, which implies an elevated risk of the infectious disease. Conversely, temperature has shown a negative correlation with the number of COVID-19 cases, leading to reduction in relative risks. In addition, we clarify that the random fluctuation in the relative risks of COVID-19 mainly originates from temporal aspects, whereas no significant evidence of variability in relative risks is observed in terms of spatial alignment of the 25 districts. Nevertheless, this study provides empirical evidence using model-based formal assessments regarding COVID-19 infection risks in 25 districts of Seoul from a different perspective.

Exosomes and COVID-19: challenges and opportunities

Coronavirus disease 2019 or COVID-19, starting from Wuhan, China, in December 2019, is a pandemic situation affecting millions worldwide and has exerted a huge burden on healthcare infrastructure. Therefore, there is an urgent need to understand the molecular mechanisms underlying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and design novel effective therapeutic strategies for combating this pandemic. In this regard, special attention has been paid to the exosomes. These nanoparticles are extracellular vesicles with critical function in the pathogenesis of several diseases including viral sepsis. Therefore, they may be involved in the pathogenesis of COVID-19 infection and also may be a way for transferring viral components and infecting other neighbor cells. Exosomes also can be considered as a therapeutic strategy for treating COVID-19 patients or used as a carrier for delivering effective therapeutic agents. Therefore, in this review, we discussed the biogenesis and contents of exosomes, their function in viral infection, and their potential as a therapeutic candidate in treating COVID-19.

The nexus between in-car aerosol concentrations, ventilation and the risk of respiratory infection

We examined the trade-offs between in-car aerosol concentrations, ventilation and respiratory infection transmission under three ventilation settings: windows open (WO); windows closed with air-conditioning on ambient air mode (WC-AA); and windows closed with air-conditioning on recirculation (WC-RC). Forty-five runs, covering a total of 324 km distance on a 7.2-km looped route, were carried out three times a day (morning, afternoon, evening) to monitor aerosols (PM_2.5; particulate matter < 2.5 μm and PNC; particle number concentration), CO₂ and environmental conditions (temperature and relative humidity). Ideally, higher ventilation rates would give lower in-car pollutant concentrations due to dilution from outdoor air. However, in-car aerosol concentrations increased with ventilation (WO > WC-AA > WC-RC) due to the ingress of polluted outdoor air on urban routes. A clear trade-off, therefore, exists for the in-car air quality (icAQ) versus ventilation; for example, WC-RC showed the least aerosol concentrations (i.e. four-times lower compared with WO), but corresponded to elevated CO₂ levels (i.e. five-times higher compared with WO) in 20 mins. We considered COVID-19 as an example of respiratory infection transmission. The probability of its transmission from an infected occupant in a five-seater car was estimated during different quanta generation rates (2-60.5 quanta hr^-1) using the Wells-Riley model. In WO, the probability with 50%-efficient and without facemasks under normal speaking (9.4 quanta hr^-1) varied only by upto 0.5%. It increased by 2-fold in WC-AA (<1.1%) and 10-fold in WC-RC (<5.2%) during a 20 mins trip. Therefore, a wise selection of ventilation settings is needed to balance in-car exposure in urban areas affected by outdoor air pollution and that by COVID-19 transmission. We also successfully developed and assessed the feasibility of using sensor units in static and dynamic environments to monitor icAQ and potentially infer COVID-19 transmission. Further research is required to develop automatic-alarm systems to help reduce both pollutant exposure and infection from respiratory COVID-19 transmission.

Avoidance of COVID-19 for Children and Adolescents and Isolation Precautions

Limiting exposure to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus has been the major principle guiding public health measures. Masking, social distancing, as well as frequent hand hygiene have been the chief nonpharmaceutical interventions as preventive strategies for all age groups. Advancement in vaccine development and vaccination of large populations offer a glimmer of hope for containing and ending this pandemic. However, until immunization is widespread in the community, masking, social distancing, and frequent handwashing, as well as early detection and isolation of infected persons, should be continued to curb the spread of illness.

Are surgical and non-operating room intervention safe in the COVID-19 pandemic? A retrospective study

Little is known about the impact of COVID-19 on the outcomes of patients undergoing surgery and intervention. This study was conducted between 20 March and 20 May 2020 in six hospitals in Istanbul, and aimed to investigate the effects of surgery and intervention on COVID-19 disease progression, intensive care (ICU) need, mortality and virus transmission to patients and healthcare workers. Patients were examined in three groups: group I underwent emergency surgery, group II had an emergency non-operating room intervention, and group III received inpatient COVID-19 treatment but did not have surgery or undergo intervention. Mortality rates, mechanical ventilation needs and rates of admission to the ICU were compared between the three groups. During this period, patient and healthcare worker transmissions were recorded. In total, 1273 surgical, 476 non-operating room intervention patients and 1884 COVID-19 inpatients were examined. The rate of ICU requirement among patients who had surgery was nearly twice that for inpatients and intervention patients, but there was no difference in mortality between the groups. The overall mortality rates were 2.3% in surgical patients, 3.3% in intervention patients and 3% in inpatients. COVID-19 polymerase chain reaction positivity among hospital workers was 2.4%. Only 3.3% of infected frontline healthcare workers were anaesthesiologists. No deaths occurred among infected healthcare workers. We conclude that emergency surgery and non-operating room interventions during the pandemic period do not increase postoperative mortality and can be performed with low transmission rates.

Environmental risk assessment and comprehensive index model of disaster loss for COVID-19 transmission

This paper focuses on the study of environmental risk assessment and comprehensive index model of disaster loss for COVID-19 transmission. Considering the five environmental vectors of carrier vulnerability, environmental instability of pregnancy and disaster, intensity of disaster-causing factors, disaster prevention and mitigation capacity and emergency prevention and control capacity and its 38 indicators, the correlation coefficient matrix and principal component expressions of each vector are established by principal component analysis, respectively, and the index model of each vector is established on the basis. Then, considering the index models of these five vectors, we established the disaster loss composite index model, which was used to conduct environmental risk assessment and disaster loss composite index analysis of the transmission of COVID-19 in Hubei Province during the period of January 21, 2020 to March 18, 2020. The empirical study showed that: (1) the risk index peaked from January 21 to January 23; (2) the risk index was at a low but volatile level from January 24 to March 14; (3) the risk index rose again slightly from March 15 and rose to another peak on March 16. These fluctuating, smooth and fluctuating processes of the comprehensive index of disaster losses of COVID-19 in Hubei Province are basically stable and consistent with the actual situation of the virus outbreak in the early stage, isolation and prevention and control in the middle stage, and resumption of work and production in the late stage. The study in this paper provides a scientific decision-making reference for the prevention and control of COVID-19 as well as emergency prevention and control measures.

Presentation of a participatory approach to develop preventive measures to reduce COVID-19 transmission in child care

Background

It can be suspected that work in child care facilities is associated with an elevated exposure risk towards SARS-CoV-2 infections. It is still unclear under which conditions employees in those facilities can safely pursue their work. Preventive workplace-related measures to reduce transmission dynamics in this work environment need to be developed. These measures need to build on a solid scientific foundation and be ready for practical use at the same time. Therefore, the aim of the study is to present a participatory approach to identify, minimize, and eliminate workplace-specific COVID-19 transmission within child care. The approach presented combines quantitative as well as qualitative elements and includes a screening of critical workplace conditions and the development of preventive measures to foster a safe workplace design.

Methods

First, 428 employees of different child care facilities in a large German city reported their subjective risk of infection, fear of infection, and support received by the employer. Second, the participants commented in detail about high risk conditions during work. Third, employees provided suggestions for preventive measures. We conducted a qualitative analysis of free text answers to evaluate which aspects are perceived as critical from an employee perspective.

Results

Participants provided valuable and practicable ideas on how to design and improve preventive measures to reduce COVID-19 transmission in child care dealing with structural conditions, the interaction with the parents, the implementation of preventive measures and recommendations for policy makers.

Conclusions

These new insights help to organize pandemic risk management in order to align theoretical based measures with the practical realization. We encourage researchers to adapt the approach presented to other work areas in order to foster participation of employees in work design to reduce COVID-19 transmission.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12995-021-00316-0.

Transmission frequency of COVID-19 through pre-symptomatic and asymptomatic patients in AJK: a report of 201 cases

BACKGROUND

The COVID-19 pandemic is a catastrophic global phenomenon, affecting human life in a way unseen since the 1918 influenza pandemic. Effective management of this threat requires halting transmission, a strategy requiring accurate knowledge of SARS-CoV-2 transmission patterns.

METHODS

This was a retrospective contact study aiming to estimate the transmission rate of COVID-19 by tracing contacts in symptomatic, pre-symptomatic, and asymptomatic patients. History of patients' contacts during 24 h before appearance of symptoms or infection confirmation was traced for disease transmission.

RESULTS

Overall, a total of 201 COVID-19 patients had contact with 7168 people in 24 h with an average of 35.66 contacts per patient, ranging from a minimum of 4 to maximum of 87 contacts (meetings). Out of 7168 persons met, infection was detected in 64 (0.89%). For the 155 symptomatic patients, a total of 5611 contacted persons were traced before appearance of symptoms (pre-symptomatic) in last 24 h with an average of 36.20 meetings per patient. The infection was transmitted in 63 (1.12%) people with 5548 (98.88%) remaining uninfected. Out of the 63 transmissions, 62 (98.4%) were traced within 6 h before symptom onset, while only 1 was identified in the 6-12 h timeframe before symptoms. A total of 1557 persons were traced having meeting/contacts with asymptomatic cases in last 24 h before infection confirmation. Out of these 1557 persons, only 1 was found to be infected and the infection rate was calculated to be 0.06%. Statistically, the transmission rate by pre-symptomatic patients was found to be significantly higher than the transmission rate by asymptomatic individuals (P < 0.05).

CONCLUSION

In the studied population, the risk of pre-symptomatic and asymptomatic transmission of COVID-19 was low, with transmission risks of 1.12% and 0.06% respectively. Pre-symptomatic infection becomes very rare in contacts made longer than 6 h before onset of symptoms. The infection transmission is traced as long as about 9 h before the appearance of clear symptoms in the patients, but the incidence rate was as low as about 0.02% of the total contacts in that period.

Network analysis of population flow among major cities and its influence on COVID-19 transmission in China

Large-scale and diffuse population flow amplifies the localized COVID-19 outbreak into a widespread pandemic. Network analysis provides a new methodology to uncover the topology and evolution of the population flow and understand its influence on the early dynamics of COVID-19 transmission. In this paper, we simulated 42 transmission scenarios to show the distribution of the COVID-19 outbreak across China. We predicted some original (Guangzhou, Shanghai, Shenzhen) had higher total aggregate population outflows than Wuhan, indicating larger spread scopes and faster growth rates of COVID-19 outbreak. We built an importation risk model to identify some major cities (Dongguan and Foshan) with the highest total importation risk values and the highest standard deviations, indicating the core transmission chains (Dongguan-Shenzhen, Foshan-Guangzhou). We built the population flow networks to analyze their Spatio-temporal characteristics and identify the influential sub-groups and spreaders. By removing different influential spreaders, we identified Guangzhou can most influence the network's topological characteristics, and some major cities' degree centrality was significantly decreased. Our findings quantified the effectiveness of travel restrictions on delaying the epidemic growth and limiting the spread scope of COVID-19 in China, which helped better derive the geographical COVID-19 transmission related to population flow networks' structural features.

Identifying novel factors associated with COVID-19 transmission and fatality using the machine learning approach

The COVID-19 virus has infected more than 38 million people and resulted in more than one million deaths worldwide as of October 14, 2020. By using the logistic regression model, we identified novel critical factors associated with COVID19 cases, death, and case fatality rates in 154 countries and in the 50 U.S. states. Among numerous factors associated with COVID-19 risk, economic inequality enhanced the risk of COVID-19 transmission. The per capita hospital beds correlated negatively with COVID-19 deaths. Blood types B and AB were protective factors for COVID-19 risk, while blood type A was a risk factor. The prevalence of HIV and influenza and pneumonia was associated with reduced COVID-19 risk. Increased intake of vegetables, edible oil, protein, vitamin D, and vitamin K was associated with reduced COVID-19 risk, while increased intake of alcohol was associated with increased COVID-19 risk. Other factors included age, sex, temperature, humidity, social distancing, smoking, health investment, urbanization level, and race. High temperature is a more compelling factor mitigating COVID-19 transmission than low temperature. Our comprehensive identification of the factors affecting COVID-19 transmission and fatality may provide new insights into the COVID-19 pandemic and advise effective strategies for preventing and migrating COVID-19 spread.

Coronavirus 2019 Infectious Disease Epidemic: Where We Are, What Can Be Done and Hope For

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads mainly by means of aerosols (microdroplets) in enclosed environments, especially those in which temperature and humidity are regulated by means of air-conditioning. About 30% of individuals infected with SARS-CoV-2 develop coronavirus disease 2019 (COVID-19) disease. Among them, approximately 25% require hospitalization. In medicine, cases are identified as those who become ill. During this pandemic, cases have been identified as those with a positive SARS-CoV-2 polymerase chain reaction test, including approximately 70% who were asymptomatic-this has caused unnecessary anxiety. Individuals more than 65 years old, those affected by obesity, diabetes, asthma, or are immune-depressed owing to cancer and other conditions, are at a higher risk of hospitalization and of dying of COVID-19. Healthy individuals younger than 40 years very rarely die of COVID-19. Estimates of the COVID-19 mortality rate vary because the definition of COVID-19-related deaths varies. Belgium has the highest death rate at 154.9 per 100,000 persons, because it includes anyone who died with symptoms compatible with COVID-19, even those never tested for SARS-CoV-2. The United States includes all patients who died with a positive test, whether they died because of, or with, SARS-CoV-2. Countries that include only patients in which COVID-19 was the main cause of death, rather than a cofactor, have lower death rates. Numerous therapies are being developed, and rapid improvements are anticipated. Because of disinformation, only approximately 50% of the U.S. population plans to receive a COVID-19 vaccine. By sharing accurate information, physicians, health professionals, and scientists play a key role in addressing myths and anxiety, help public health officials enact measures to decrease infections, and provide the best care for those who become sick. In this article, we discuss these issues.

Inhaled aerosols: Their role in COVID-19 transmission, including biophysical interactions in the lungs

The high rate of spreading of COVID-19 is attributed to airborne particles exhaled by infected but often asymptomatic individuals. In this review, the role of aerosols in SARS-CoV-2 coronavirus transmission is discussed from the biophysical perspective. The essential properties of the coronavirus virus transported inside aerosol droplets, their successive inhalation, and size-dependent deposition in the respiratory system are highlighted. The importance of face covers (respirators and masks) in the reduction of aerosol spreading is analyzed. Finally, the discussion of the physicochemical phenomena of the coronavirus entering the surface of lung liquids (bronchial mucus and pulmonary surfactant) is presented with a focus on a possible role of interfacial phenomena in pulmonary alveoli. Information given in this review should be important in understanding the essential biophysical conditions of COVID-19 infection via aerosol route as a prerequisite for effective strategies of respiratory tract protection, and possibly, indications for future treatments of the disease.

Early Transmission Dynamics, Spread, and Genomic Characterization of SARS-CoV-2 in Panama

We report an epidemiologic analysis of 4,210 cases of infection with severe acute respiratory syndrome coronavirus 2 and genetic analysis of 313 new near-complete virus genomes in Panama during March 9-April 16, 2020. Although containment measures reduced R0 and Rt, they did not interrupt virus spread in the country.

How Does Railway Respond to the Spread of COVID-19? Countermeasure Analysis and Evaluation Around the World

The global COVID-19 pandemic is having a significant impact on the development of many aspects all over the world. As an important part of public services, rail transit requires effective response countermeasures to control the spread of COVID-19. Considering the current development of the epidemic situation, this article discusses the characteristics of COVID-19 transmission and identifies vulnerable areas to target in order to prevent and control the spread of the epidemic in the rail transit system. Countermeasures adopted to prevent the spread of COVID-19 are analyzed in terms of external and internal categories, which were classified into six groups: passenger service, case care, information, staff, equipment and operation management. An evaluation architecture was also constructed, which was established from the perspective of effectiveness, economic efficiency, acceptability, privacy and so on. The effect of implementing the measures was evaluated by a social survey, and their advantages and shortcomings were analyzed, which can be used to guide future epidemic prevention and control for rail transit systems around the world. It is important to formulate a reasonable work schedule according to local conditions, providing a reference for rapid response to future public health emergencies of international concern.

Modeling the transmission of COVID-19 in the US - A case study

We propose a mathematical model to investigate the transmission dynamics of COVID-19. The model incorporates both human-to-human and environment-to-human transmission pathways, and employs different transmission rates to represent the epidemiological characteristics at different time periods. Using this model and publicly reported data, we perform a case study for Hamilton County, the fourth-most populous county in the state of Tennessee and a region that could represent the typical situation of COVID-19 in the United States (US). Our data fitting and simulation results show that the environment may play an important role in the transmission and spread of the coronavirus. In addition, we numerically simulate a range of epidemic scenarios and make near-term forecasts on the development and trend of COVID-19 in Hamilton County.

Does Temperature Affect COVID-19 Transmission?

This study utilizes the non-linear least squares method to estimate the impact of temperature on COVID-19 cases per million in forty-three countries, divided into three groups as follows: the first group is composed of thirteen countries that announced the first COVID-19 cases in January 2020, while the second and third groups contain thirteen and seventeen countries, respectively, that witnessed the pandemic for the first time in February and March of the same year. This relationship was measured after four time periods from the date of reporting the first case until April 1, April 15, May 15, and July 8, 2020. The results show an inverse relationship between COVID-19 cases per million and the temperature in the studies of the four-time periods for the three-country groups. These results were only significant statistically (p < 0.1) after 110.8, 164.8 days on average from the beginning of the pandemic in the case of "January" countries.

COVID-19 in Bangladesh: A Deeper Outlook into The Forecast with Prediction of Upcoming Per Day Cases Using Time Series

A global pandemic on March 11th of 2020, which was initially renowned by the World Health Organization (WHO) revealed the coronavirus (the COVID-19 epidemic). Coronavirus was flown in -December 2019 in Wuhan, Hubei region in China. Currently, the situation is enlarged by the infection in more than 200 countries all over the world. In this situation it was rising into huge forms in Bangladesh too. Modulated with a public dataset delivered by the IEDCR health authority, we have produced a sustainable prognostic method of COVID-19 outbreak in Bangladesh using a deep learning model. Throughout the research, we forecasted up to 30 days in which per day actual prediction was confirmed, death and recoveries number of people. Furthermore, we illustrated that long short-term memory (LSTM) demands the actual output trends among time series data analysis with a controversial study that exceeds random forest (RF) regression and support vector regression (SVR), which both are machine learning (ML) models. The current COVID-19 outbreak in Bangladesh has been considered in this paper. Here, a well-known recurrent neural network (RNN) model in order to referred by the LSTM network that has forecasted COVID-19 cases on per day infected scenario of Bangladesh from May 15th of 2020 till June 15th of 2020. Added with a comparative study that drives into the LSTM, SVR, RF regression which is processed by the RMSE transmission rate. In all respects, in Bangladesh the gravity of COVID-19 has become excessive nowadays so that depending on this situation public health sectors and common people need to be aware of this situation and also be able to get knowledge of how long self-lockdown will be maintained. So far, to the best of our knowledge LSTM based time series analysis forecasting infectious diseases is a well-done formula.

Planning of surgical activity in the COVID-19 era: A proposal for a step toward a possible healthcare organization

Health-care systems worldwide are experiencing a decline in elective surgical activity during the current COVID-19 pandemics. The progression of morbid conditions-especially of cancer-and the uncontained increase of waiting list for scheduled interventions are the major drawbacks. We propose a possible organization of a COVID-19 free hospital or hub, that include both patients' and workforce's preparation before entering the facility. The addition of a planned pathway for the whole workforce (physicians, nurses, cleaning and transporting crews, etc.) represents the basis of the program, and involves COVID-19 testing and subsequent self-isolation before entering the hospital, avoidance of work in non-COVID free areas, a strategic fractioning with a multilayer coverage system of care, periodic re-testing. Based on these suggestions, the realization of a COVID-19 free hospital could be achieved, allowing the continuation of a safe surgical activity in view of a possible restoration of non-urgent activity.

COVID-19 and its Modes of Transmission

The World Health Organization recognized SARS-CoV-2 as a public health concern and declared it as a pandemic on March 11, 2020. Over 12 million people have been affected across several countries since it was first recognized. SARS-CoV-2 is thought to commonly spread via respiratory droplets formed while talking, coughing, and sneezing of an infected patient. As several cases, with an absence of travel history to the majorly affected areas were identified, a strong possibility of community transmission could have been possible. Broadly, two modes of transmission of COVID-19 exist—direct and indirect. The direct mode includes (1) transmission via aerosols formed via surgical and dental procedures and/or in the form of respiratory droplet nuclei; (2) other body fluids and secretions, for example, feces, saliva, urine, semen, and tears; and (3) mother-to-child. Indirect transmission may occur via (1) fomites or surfaces (e.g., furniture and fixtures) present within the immediate environment of an infected patient and (2) objects used on the infected person (e.g., stethoscope or thermometer). As many of these modes may be underestimated, it is necessary to emphasize and illustrate them. The goal of this paper is to briefly review how SARS-CoV-2 is shown to transmit via various modes and propose measures to reduce the risk of spread within the population and operating personnel.

Surface Alterations to Impart Antiviral Properties to Combat COVID-19 Transmission

A global epidemic caused by highly transmittable COVID-19 is causing severe loss of human life. In this study, two aspects of reducing transmission of COVID-19 virus, due to surface contact, are discussed: first refers to the effect of nanocarbon fullerene C60 coating on surface, that causes lipid peroxidation on the phospholipid layer present in the outer envelope of COVID-19; the second aspect refers to creating hydrophobic surfaces by texturing them, so that the contact area between virus and surface is minimized due to the presence of entrapped air between the topographies. These can be similar to micro-/nano-multiscale textured surfaces that have anti-biofouling properties. Fullerene-coated surfaces can be seen as a possible solution to decrease the adhesion of virus on the surface, as they will be hydrophobic as well as toxic to the envelope.