MERS, SARS, and Ebola: The Role of Super-Spreaders in Infectious Disease

Sudan virus disease super-spreading, Uganda, 2022

BACKGROUND

On 20 September 2022, Uganda declared its fifth Sudan virus disease (SVD) outbreak, culminating in 142 confirmed and 22 probable cases. The reproductive rate (R) of this outbreak was 1.25. We described persons who were exposed to the virus, became infected, and they led to the infection of an unusually high number of cases during the outbreak.

METHODS

In this descriptive cross-sectional study, we defined a super-spreader person (SSP) as any person with real-time polymerase chain reaction (RT-PCR) confirmed SVD linked to the infection of ≥ 13 other persons (10-fold the outbreak R). We reviewed illness narratives for SSPs collected through interviews. Whole-genome sequencing was used to support epidemiologic linkages between cases.

RESULTS

Two SSPs (Patient A, a 33-year-old male, and Patient B, a 26-year-old male) were identified, and linked to the infection of one probable and 50 confirmed secondary cases. Both SSPs lived in the same parish and were likely infected by a single ill healthcare worker in early October while receiving healthcare. Both sought treatment at multiple health facilities, but neither was ever isolated at an Ebola Treatment Unit (ETU). In total, 18 secondary cases (17 confirmed, one probable), including three deaths (17%), were linked to Patient A; 33 secondary cases (all confirmed), including 14 (42%) deaths, were linked to Patient B. Secondary cases linked to Patient A included family members, neighbours, and contacts at health facilities, including healthcare workers. Those linked to Patient B included healthcare workers, friends, and family members who interacted with him throughout his illness, prayed over him while he was nearing death, or exhumed his body. Intensive community engagement and awareness-building were initiated based on narratives collected about patients A and B; 49 (96%) of the secondary cases were isolated in an ETU, a median of three days after onset. Only nine tertiary cases were linked to the 51 secondary cases. Sequencing suggested plausible direct transmission from the SSPs to 37 of 39 secondary cases with sequence data.

CONCLUSION

Extended time in the community while ill, social interactions, cross-district travel for treatment, and religious practices contributed to SVD super-spreading. Intensive community engagement and awareness may have reduced the number of tertiary infections. Intensive follow-up of contacts of case-patients may help reduce the impact of super-spreading events.

Discovery of First-in-Class PROTAC Degraders of SARS-CoV-2 Main Protease

We have witnessed three coronavirus (CoV) outbreaks in the past two decades, including the COVID-19 pandemic caused by SARS-CoV-2. Main protease (MPro), a highly conserved protease among various CoVs, is essential for viral replication and pathogenesis, making it a prime target for antiviral drug development. Here, we leverage proteolysis targeting chimera (PROTAC) technology to develop a new class of small-molecule antivirals that induce the degradation of SARS-CoV-2 MPro. Among them, MPD2 was demonstrated to effectively reduce MPro protein levels in 293T cells, relying on a time-dependent, CRBN-mediated, and proteasome-driven mechanism. Furthermore, MPD2 exhibited remarkable efficacy in diminishing MPro protein levels in SARS-CoV-2-infected A549-ACE2 cells. MPD2 also displayed potent antiviral activity against various SARS-CoV-2 strains and exhibited enhanced potency against nirmatrelvir-resistant viruses. Overall, this proof-of-concept study highlights the potential of targeted protein degradation of MPro as an innovative approach for developing antivirals that could fight against drug-resistant viral variants.

Ubiquitination and deubiquitination in the regulation of N6-methyladenosine functional molecules

N6 methyladenosine (m6A) is the most prevalent RNA epigenetic modification, regulated by methyltransferases and demethyltransferases and recognized by methylation-related reading proteins to impact mRNA splicing, translocation, stability, and translation efficiency. It significantly affects a variety of activities, including stem cell maintenance and differentiation, tumor formation, immune regulation, and metabolic disorders. Ubiquitination refers to the specific modification of target proteins by ubiquitin molecule in response to a series of enzymes. E3 ligases connect ubiquitin to target proteins and usually lead to protein degradation. On the contrary, deubiquitination induced by deubiquitinating enzymes (DUBs) can separate ubiquitin and regulate the stability of protein. Recent studies have emphasized the potential importance of ubiquitination and deubiquitination in controlling the function of m6A modification. In this review, we discuss the impact of ubiquitination and deubiquitination on m6A functional molecules in diseases, such as metabolism, cellular stress, and tumor growth.

Disease resistance and infectivity of virus susceptible and resistant common carp strains

Infectious diseases challenge health and welfare of humans and animals. Unlike for humans, breeding of genetically resistant animals is a sustainable solution, also providing unique research opportunities. Chances to survive a disease are improved by disease resistance, but depend also on chances to get infected and infect others. Considerable knowledge exists on chances of susceptible and resistant animals to survive a disease, yet, almost none on their infectivity and if and how resistance and infectivity correlate. Common carp (Cyprinus carpio) is widely produced in aquaculture, suffering significantly from a disease caused by cyprinid herpes virus type 3 (CyHV-3). Here, the infectivity of disease-resistant and susceptible fish types was tested by playing roles of shedders (infecting) and cohabitants (infected) in all four type-role combinations. Resistant shedders restricted spleen viral load and survived more than susceptible ones. However, mortality of susceptible cohabitants infected by resistant shedders was lower than that of resistant cohabitants infected by susceptible shedders. Virus levels in water were lower in tanks with resistant shedders leading to lower spleen viral loads in cohabitants. Thus, we empirically demonstrated that disease resistant fish survive better and infect less, with implications to epidemiology in general and to the benefit of aquaculture production.

Reduction of acute respiratory infections in day-care by non-pharmaceutical interventions: a narrative review

Objective

Children who start in day-care have 2-4 times as many respiratory infections compared to children who are cared for at home, and day-care staff are among the employees with the highest absenteeism. The extensive new knowledge that has been generated in the COVID-19 era should be used in the prevention measures we prioritize. The purpose of this narrative review is to answer the questions: Which respiratory viruses are the most significant in day-care centers and similar indoor environments? What do we know about the transmission route of these viruses? What evidence is there for the effectiveness of different non-pharmaceutical prevention measures?

Design

Literature searches with different terms related to respiratory infections in humans, mitigation strategies, viral transmission mechanisms, and with special focus on day-care, kindergarten or child nurseries, were conducted in PubMed database and Web of Science. Searches with each of the main viruses in combination with transmission, infectivity, and infectious spread were conducted separately supplemented through the references of articles that were retrieved.

Results

Five viruses were found to be responsible for ≈95% of respiratory infections: rhinovirus, (RV), influenza virus (IV), respiratory syncytial virus (RSV), coronavirus (CoV), and adenovirus (AdV). Novel research, emerged during the COVID-19 pandemic, suggests that most respiratory viruses are primarily transmitted in an airborne manner carried by aerosols (microdroplets).

Conclusion

Since airborne transmission is dominant for the most common respiratory viruses, the most important preventive measures consist of better indoor air quality that reduces viral concentrations and viability by appropriate ventilation strategies. Furthermore, control of the relative humidity and temperature, which ensures optimal respiratory functionality and, together with low resident density (or mask use) and increased time outdoors, can reduce the occurrence of respiratory infections.

Model for Interpreting Discordant SARS-CoV-2 Diagnostic Test Results

We devised a model to interpret discordant SARS-CoV-2 test results. We estimate that, during March 2020-May 2022, a patient in the United States who received a positive rapid antigen test result followed by a negative nucleic acid test result had only a 15.4% (95% CI 0.6%-56.7%) chance of being infected.

Unravelling the effect of New Year's Eve celebrations on SARS-CoV-2 transmission

Public holidays have been associated with SARS-CoV-2 incidence surges, although a firm link remains to be established. This association is sometimes attributed to events where transmissions occur at a disproportionately high rate, known as superspreading events. Here, we describe a sudden surge in new cases with the Omicron BA.1 strain amongst higher education students in Belgium. Contact tracers classed most of these cases as likely or possibly infected on New Year's Eve, indicating a direct trigger by New Year celebrations. Using a combination of contact tracing and phylogenetic data, we show the limited role of superspreading events in this surge. Finally, the numerous simultaneous transmissions allowed a unique opportunity to determine the distribution of incubation periods of the Omicron strain. Overall, our results indicate that, even under social restrictions, a surge in transmissibility of SARS-CoV-2 can occur when holiday celebrations result in small social gatherings attended simultaneously and communitywide.

Addressing the Knowledge Deficit in Hospital Bed Planning and Defining an Optimum Region for the Number of Different Types of Hospital Beds in an Effective Health Care System

Based upon 30-years of research by the author, a new approach to hospital bed planning and international benchmarking is proposed. The number of hospital beds per 1000 people is commonly used to compare international bed numbers. This method is flawed because it does not consider population age structure or the effect of nearness-to-death on hospital utilization. Deaths are also serving as a proxy for wider bed demand arising from undetected outbreaks of 3000 species of human pathogens. To remedy this problem, a new approach to bed modeling has been developed that plots beds per 1000 deaths against deaths per 1000 population. Lines of equivalence can be drawn on the plot to delineate countries with a higher or lower bed supply. This method is extended to attempt to define the optimum region for bed supply in an effective health care system. England is used as an example of a health system descending into operational chaos due to too few beds and manpower. The former Soviet bloc countries represent a health system overly dependent on hospital beds. Several countries also show evidence of overutilization of hospital beds. The new method is used to define a potential range for bed supply and manpower where the most effective health systems currently reside. The method is applied to total curative beds, medical beds, psychiatric beds, critical care, geriatric care, etc., and can also be used to compare different types of healthcare staff, i.e., nurses, physicians, and surgeons. Issues surrounding the optimum hospital size and the optimum average occupancy will also be discussed. The role of poor policy in the English NHS is used to show how the NHS has been led into a bed crisis. The method is also extended beyond international benchmarking to illustrate how it can be applied at a local or regional level in the process of long-term bed planning. Issues regarding the volatility in hospital admissions are also addressed to explain the need for surge capacity and why an adequate average bed occupancy margin is required for an optimally functioning hospital.

Discovery of First-in-Class PROTAC Degraders of SARS-CoV-2 Main Protease

We have witnessed three coronavirus (CoV) outbreaks in the past two decades, including the COVID-19 pandemic caused by SARS-CoV-2. Main protease (M Pro ) is a highly conserved and essential protease that plays key roles in viral replication and pathogenesis among various CoVs, representing one of the most attractive drug targets for antiviral drug development. Traditional antiviral drug development strategies focus on the pursuit of high-affinity binding inhibitors against M Pro . However, this approach often suffers from issues such as toxicity, drug resistance, and a lack of broad-spectrum efficacy. Targeted protein degradation represents a promising strategy for developing next-generation antiviral drugs to combat infectious diseases. Here we leverage the proteolysis targeting chimera (PROTAC) technology to develop a new class of small-molecule antivirals that induce the degradation of SARS-CoV-2 M Pro . Our previously developed M Pro inhibitors MPI8 and MPI29 were used as M Pro ligands to conjugate a CRBN E3 ligand, leading to compounds that can both inhibit and degrade SARS-CoV-2 M Pro . Among them, MDP2 was demonstrated to effectively reduce M Pro protein levels in 293T cells (DC 50 = 296 nM), relying on a time-dependent, CRBN-mediated, and proteasome-driven mechanism. Furthermore, MPD2 exhibited remarkable efficacy in diminishing M Pro protein levels in SARS-CoV-2-infected A549-ACE2 cells, concurrently demonstrating potent anti-SARS-CoV-2 activity (EC 50 = 492 nM). This proof-of-concept study highlights the potential of PROTAC-mediated targeted protein degradation of M Pro as an innovative and promising approach for COVID-19 drug discovery.

Replicating superspreader dynamics with compartmental models

Infectious disease outbreaks often exhibit superspreader dynamics, where most infected people generate no, or few secondary cases, and only a small fraction of individuals are responsible for a large proportion of transmission. Although capturing this heterogeneity is critical for estimating outbreak risk and the effectiveness of group-specific interventions, it is typically neglected in compartmental models of infectious disease transmission-which constitute the most common transmission dynamic modeling framework. In this study we propose different classes of compartmental epidemic models that incorporate transmission heterogeneity, fit them to a number of real outbreak datasets, and benchmark their performance against the canonical superspreader model (i.e., the negative binomial branching process model). We find that properly constructed compartmental models can capably reproduce observed superspreader dynamics and we provide the pathogen-specific parameter settings required to do so. As a consequence, we also show that compartmental models parameterized according to a binary clinical classification have limited support.

Positive feedback loops exacerbate the influence of superspreaders in disease transmission

Superspreaders are recognized as being important drivers of disease spread. However, models to date have assumed random occurrence of superspreaders, irrespective of whom they were infected by. Evidence suggests though that those individuals infected by superspreaders may be more likely to become superspreaders themselves. Here, we begin to explore, theoretically, the effects of such a positive feedback loop on (1) the final epidemic size, (2) the herd immunity threshold, (3) the basic reproduction number, R₀, and (4) the peak prevalence of superspreaders, using a generic model for a hypothetical acute viral infection and illustrative parameter values. We show that positive feedback loops can have a profound effect on our chosen epidemic outcomes, even when the transmission advantage of superspreaders is moderate, and despite peak prevalence of superspreaders remaining low. We argue that positive superspreader feedback loops in different infectious diseases, including SARS-CoV-2, should be investigated further, both theoretically and empirically.

The effect of variation of individual infectiousness on SARS-CoV-2 transmission in households

Quantifying variation of individual infectiousness is critical to inform disease control. Previous studies reported substantial heterogeneity in transmission of many infectious diseases including SARS-CoV-2. However, those results are difficult to interpret since the number of contacts is rarely considered in such approaches. Here, we analyze data from 17 SARS-CoV-2 household transmission studies conducted in periods dominated by ancestral strains, in which the number of contacts was known. By fitting individual-based household transmission models to these data, accounting for number of contacts and baseline transmission probabilities, the pooled estimate suggests that the 20% most infectious cases have 3.1-fold (95% confidence interval: 2.2- to 4.2-fold) higher infectiousness than average cases, which is consistent with the observed heterogeneity in viral shedding. Household data can inform the estimation of transmission heterogeneity, which is important for epidemic management.

Host–Pathogen Interactions Influencing Zoonotic Spillover Potential and Transmission in Humans

Emerging infectious diseases of zoonotic origin are an ever-increasing public health risk and economic burden. The factors that determine if and when an animal virus is able to spill over into the human population with sufficient success to achieve ongoing transmission in humans are complex and dynamic. We are currently unable to fully predict which pathogens may appear in humans, where and with what impact. In this review, we highlight current knowledge of the key host–pathogen interactions known to influence zoonotic spillover potential and transmission in humans, with a particular focus on two important human viruses of zoonotic origin, the Nipah virus and the Ebola virus. Namely, key factors determining spillover potential include cellular and tissue tropism, as well as the virulence and pathogenic characteristics of the pathogen and the capacity of the pathogen to adapt and evolve within a novel host environment. We also detail our emerging understanding of the importance of steric hindrance of host cell factors by viral proteins using a “flytrap”-type mechanism of protein amyloidogenesis that could be crucial in developing future antiviral therapies against emerging pathogens. Finally, we discuss strategies to prepare for and to reduce the frequency of zoonotic spillover occurrences in order to minimize the risk of new outbreaks.

Animal Models, Zoonotic Reservoirs, and Cross-Species Transmission of Emerging Human-Infecting Coronaviruses

Over the past three decades, coronavirus (CoV) diseases have impacted humans more than any other emerging infectious disease. The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19 (coronavirus disease 2019), has resulted in huge economic disruptions and loss of human lives. The SARS-CoV-2 genome was found to mutate more rapidly due to sustained transmission in humans and potentially animals, resulting in variants of concern (VOCs) that threaten global human health. However, the primary difficulties are filling in the current knowledge gaps in terms of the origin and modalities of emergence for these viruses. Because many CoVs threatening human health are suspected to have a zoonotic origin, identifying the animal hosts implicated in the spillover or spillback events would be beneficial for current pandemic management and to prevent future outbreaks. In this review, wesummarize the animal models, zoonotic reservoirs, and cross-species transmission of the emerging human CoVs. Finally, we comment on potential sources of SARS-CoV-2 Omicron VOCs and the new SARS-CoV-2 recombinants currently under investigation.

The COVID-19 pandemic in sub-Saharan Africa: The significance of presumed immune sufficiency

A novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in China in 2019 and later ignited a global pandemic. Contrary to expectations, the effect of the pandemic was not as devastating to Africa and its young population compared to the rest of the world. To provide insight into the possible reasons for the presumed immune sufficiency to coronavirus disease 2019 (COVID-19) in Africa, this review critically examines literature published from 2020 onwards on the dynamics of COVID-19 infection and immunity and how other prevalent infectious diseases in Africa might have influenced the outcome of COVID-19. Studies characterising the immune response in patients with COVID-19 show that the correlates of protection in infected individuals are T-cell responses against the SARS-CoV-2 spike protein and neutralising titres of immunoglobin G and immunoglobin A antibodies. In some other studies, substantial pre-existing T-cell reactivity to SARS-CoV-2 was detected in many people from diverse geographical locations without a history of exposure. Certain studies also suggest that innate immune memory, which offers protection against reinfection with the same or another pathogen, might influence the severity of COVID-19. In addition, an initial analysis of epidemiological data showed that COVID‑19 cases were not severe in some countries that implemented universal Bacillus Calmette-Guerin (BCG) vaccination policies, thus supporting the potential of BCG vaccination to boost innate immunity. The high burden of infectious diseases and the extensive vaccination campaigns previously conducted in Africa could have induced specific and non-specific protective immunity to infectious pathogens in Africans.

Multiple pathways of SARS-CoV-2 nosocomial transmission uncovered by integrated genomic and epidemiological analyses during the second wave of the COVID-19 pandemic in the UK

Introduction

Throughout the global COVID-19 pandemic, nosocomial transmission has represented a major concern for healthcare settings and has accounted for many infections diagnosed within hospitals. As restrictions ease and novel variants continue to spread, it is important to uncover the specific pathways by which nosocomial outbreaks occur to understand the most suitable transmission control strategies for the future.

Methods

In this investigation, SARS-CoV-2 genome sequences obtained from 694 healthcare workers and 1,181 patients were analyzed at a large acute NHS hospital in the UK between September 2020 and May 2021. These viral genomic data were combined with epidemiological data to uncover transmission routes within the hospital. We also investigated the effects of the introduction of the highly transmissible variant of concern (VOC), Alpha, over this period, as well as the effects of the national vaccination program on SARS-CoV-2 infection in the hospital.

Results

Our results show that infections of all variants within the hospital increased as community prevalence of Alpha increased, resulting in several outbreaks and super-spreader events. Nosocomial infections were enriched amongst older and more vulnerable patients more likely to be in hospital for longer periods but had no impact on disease severity. Infections appeared to be transmitted most regularly from patient to patient and from patients to HCWs. In contrast, infections from HCWs to patients appeared rare, highlighting the benefits of PPE in infection control. The introduction of the vaccine at this time also reduced infections amongst HCWs by over four-times.

Discussion

These analyses have highlighted the importance of control measures such as regular testing, rapid lateral flow testing alongside polymerase chain reaction (PCR) testing, isolation of positive patients in the emergency department (where possible), and physical distancing of patient beds on hospital wards to minimize nosocomial transmission of infectious diseases such as COVID-19.

A new One Health Framework in Qatar for future emerging and re-emerging zoonotic diseases preparedness and response

One Health is increasingly recognized as an optimal approach to address the global risk of health threats originating at the human, animal, and ecosystem interface, and their impact. Qatar has successfully practiced One Health approach for investigation and surveillance of zoonotic diseases such as MERS-CoV, and other health threats. However, the current gaps at institution and policy level hinder the sustainment of One Health. In this paper, we have assessed the potential for implementation of One Health Framework to reinforce and sustain One Health capacities in Qatar for 2022-2027. To implement One Health Framework in the country, Qatar Joint External Evaluation (JEE) report, lessons learnt during One Health experiences on zoonotic, vector-borne, and food borne diseases were used to present an outline for multisectoral coordination. In addition, technical capacities of One Health and factors that are required to operationalize it in the country were also assessed in series of meetings and workshops held at Ministry of Public Health on March 2022. Present health care infrastructure and resources were found to be conducive for effective management and response to shared health threats as evident during MERS-CoV, despite being more event based. Regardless, the need for more sustainable capacity development was unanimously emphasized. The consensus between all relevant stakeholders and partners was that there is a need for better communication channels, policies and protocols for data sharing, and the need to invest more resources for better sustainability. The proposed framework is expected to strengthen and facilitate multilateral coordination, enhanced laboratory capacity and network, improve active surveillance and response, risk communication, community engagement, maximize applied research, and build One Health technical work force. This would enable advancement and sustainment of One Health activities to prevent and control health threats shared between humans-animals-ecosystem interface.

Quantifying Mycobacterium tuberculosis Transmission Dynamics Across Global Settings: A Systematic Analysis

The degree to which individual heterogeneity in the production of secondary cases ("superspreading") affects tuberculosis (TB) transmission has not been systematically studied. We searched for population-based or surveillance studies in which whole genome sequencing was used to estimate TB transmission and in which the size distributions of putative TB transmission clusters were enumerated. We fitted cluster-size-distribution data to a negative binomial branching process model to jointly infer the transmission parameters $R$ (the reproduction number) and the dispersion parameter, $k$, which quantifies the propensity of superspreading in a population (generally, lower values of $k$ ($<1.0$) suggest increased heterogeneity). Of 4,796 citations identified in our initial search, 9 studies from 8 global settings met the inclusion criteria (n = 5 studies of all TB; n = 4 studies of drug-resistant TB). Estimated $R$ values (range, 0.10-0.73) were below 1.0, consistent with declining epidemics in the included settings; estimated $k$ values were well below 1.0 (range, 0.02-0.48), indicating the presence of substantial individual-level heterogeneity in transmission across all settings. We estimated that a minority of cases (range, 2%-31%) drive the majority (80%) of ongoing TB transmission at the population level. Identifying sources of heterogeneity and accounting for them in TB control may have a considerable impact on mitigating TB transmission.

Interleukin 6: A biomarker for COVID-19 progression

COVID-19 was discovered in China for the first time in December 2019 and was declared a pandemic by the World Health Organization on March 11, 2020. Due to its rapid geographic expansion over the last three years, it has now become a global health issue. The infection is caused by SARS-CoV-2, which is obtained from a zoonotic source and transmitted directly or through contact. Following exposure, the immune system becomes hyperactive resulting in the production of pro-inflammatory cytokines, particularly interleukin-6 (IL-6), a naturally occurring pleiotropic cytokine that plays a significant role in respiratory failure and multi-organ dysfunction. This massive inflammatory phenomenon is reminiscent of cytokine release syndrome (CRS) or "cytokine storm", which may be at the root of many severe complications. In fact, serum IL-6 levels are significantly high in patients with severe Covid-19 disease. The goal of treatment is to change the cytokine's concentration or activity. Interleukin-6 production could be inhibited, reducing inflammation and so serving as a therapeutic target. anti-interleukin-6 receptor monoclonal antibodies have been proven to reduce the severity of COVID-19 in clinical trials aimed at clarifying the function of immunoregulation. As a result, the Il-6 assay is a reliable predictor of morbidity and mortality at the time of infection diagnosis. The aim of our study is to highlight the role of interleukin 6 as biomarker of the COVID- 19 progression.

Unraveling the Complex Interactions between the Fat Mass and Obesity-Associated (FTO) Gene, Lifestyle, and Cancer

Carcinogenesis is a complicated process and originates from genetic, epigenetic, and environmental factors. Recent studies have reported a potential critical role for the fat mass and obesity-associated (FTO) gene in carcinogenesis through different signaling pathways such as mRNA N6-methyladenosine (m6A) demethylation. The most common internal modification in mammalian mRNA is the m6A RNA methylation that has significant biological functioning through regulation of cancer-related cellular processes. Some environmental factors, like physical activity and dietary intake, may influence signaling pathways engaged in carcinogenesis, through regulating FTO gene expression. In addition, people with FTO gene polymorphisms may be differently influenced by cancer risk factors, for example, FTO risk allele carriers may need a higher intake of nutrients to prevent cancer than others. In order to obtain a deeper viewpoint of the FTO, lifestyle, and cancer-related pathway interactions, this review aims to discuss upstream and downstream pathways associated with the FTO gene and cancer. The present study discusses the possible mechanisms of interaction of the FTO gene with various cancers and provides a comprehensive picture of the lifestyle factors affecting the FTO gene as well as the possible downstream pathways that lead to the effect of the FTO gene on cancer.

COVID-19 pandemic and air transportation: Summary of Recent Research, Policy Consideration and Future Research Directions

The COVID-19 pandemic can be considered an unparalleled disruption to the aviation industry in the last century. Starting with an at-that-time inconceivable reduction in the number of flights from March 2020 to May 2020, the aviation industry has been trying to navigate through and out of the crisis. This process is accompanied with a significant number of scientific studies, reporting on the direct and indirect impact of the COVID-19 pandemic on aviation and vice versa. This paper reviews the impacts in context of the recent literature. We have collected nearly 200 well-published papers on the subject in the years 2021/2022 and dissected them into a framework of eight categories, built around: airlines, airports, passengers, workforce, markets, contagion, sustainability, and economics. We highlight the essence of findings in the literature and derive a set of future research directions and policy considerations which we deem important on the way towards pandemic-resilient aviation.

A topology-based evaluation of resilience on urban road networks against epidemic spread: Implications for COVID-19 responses

Road closure is an effective measure to reduce mobility and prevent the spread of an epidemic in severe public health crises. For instance, during the peak waves of the global COVID-19 pandemic, many countries implemented road closure policies, such as the traffic-calming strategy in the UK. However, it is still not clear how such road closures, if used as a response to different modes of epidemic spreading, affect the resilient performance of large-scale road networks in terms of their efficiency and overall accessibility. In this paper, we propose a simulation-based approach to theoretically investigate two types of spreading mechanisms and evaluate the effectiveness of both static and dynamic response scenarios, including the sporadic epidemic spreading based on network topologies and trajectory-based spreading caused by superspreaders in megacities. The results showed that (1) the road network demonstrates comparatively worse resilient behavior under the trajectory-based spreading mode; (2) the road density and centrality order, as well as the network's regional geographical characteristics, can substantially alter the level of impacts and introduce heterogeneity into the recovery processes; and (3) the resilience lost under static recovery and dynamic recovery scenarios is 8.6 and 6.9%, respectively, which demonstrates the necessity of a dynamic response and the importance of making a systematic and strategic recovery plan. Policy and managerial implications are also discussed. This paper provides new insights for better managing the resilience of urban road networks against public health crises in the post-COVID era.

Effet protecteur des alpha-bloquants dans la Covid-19

Introduction

Patients et méthodes

Résultats

Conclusion

Characterizing superspreading potential of infectious disease: Decomposition of individual transmissibility

In the context of infectious disease transmission, high heterogeneity in individual infectiousness indicates that a few index cases can generate large numbers of secondary cases, a phenomenon commonly known as superspreading. The potential of disease superspreading can be characterized by describing the distribution of secondary cases (of each seed case) as a negative binomial (NB) distribution with the dispersion parameter, k. Based on the feature of NB distribution, there must be a proportion of individuals with individual reproduction number of almost 0, which appears restricted and unrealistic. To overcome this limitation, we generalized the compound structure of a Poisson rate and included an additional parameter, and divided the reproduction number into independent and additive fixed and variable components. Then, the secondary cases followed a Delaporte distribution. We demonstrated that the Delaporte distribution was important for understanding the characteristics of disease transmission, which generated new insights distinct from the NB model. By using real-world dataset, the Delaporte distribution provides improvements in describing the distributions of COVID-19 and SARS cases compared to the NB distribution. The model selection yielded increasing statistical power with larger sample sizes as well as conservative type I error in detecting the improvement in fitting with the likelihood ratio (LR) test. Numerical simulation revealed that the control strategy-making process may benefit from monitoring the transmission characteristics under the Delaporte framework. Our findings highlighted that for the COVID-19 pandemic, population-wide interventions may control disease transmission on a general scale before recommending the high-risk-specific control strategies.

Superspreading is one of the key transmission features of many infectious diseases and is considered a consequence of the heterogeneity in infectiousness of individual cases. To characterize the superspreading potential, we divided individual infectiousness into two independent and additive components, including a fixed baseline and a variable part. Such decomposition produced an improvement in the fit of the model explaining the distribution of real-world datasets of COVID-19 and SARS that can be captured by the classic statistical tests. Disease control strategies may be developed by monitoring the characteristics of superspreading. For the COVID-19 pandemic, population-wide interventions are suggested first to limit the transmission at a scale of general population, and then high-risk-specific control strategies are recommended subsequently to lower the risk of superspreading.

Structural, genomic information and computational analysis of emerging coronavirus (SARS-CoV-2)

Background

The emerging viral pandemic worldwide is associated with a novel coronavirus, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). This virus is said to emerge from its epidemic center in Wuhan, China, in 2019. Coronaviruses (CoVs) are single-stranded, giant, enveloped RNA viruses that come under the family of coronaviridae and order Nidovirales which are the crucial pathogens for humans and other vertebrates.

Main body

Coronaviruses are divided into several subfamilies and genera based on the genomic structure and phylogenetic relationship. The name corona is raised due to the presence of spike protein on the envelope of the virus. The structural and genomic study revealed that the total genome size of SARS-CoV-2 is from 29.8 kb to 29.9 kb. The spike protein (S) is a glycoprotein that attaches to the receptor of host cells for entry into the host cell, followed by the attachment of virus RNA to the host ribosome for translation. The phylogenetic analysis of SARS-CoV-2 revealed the similarity (75-88%) with bat SARS-like coronavirus.

Conclusion

The sign and symptoms of novel severe acute respiratory syndrome coronavirus 2 are also discussed in this paper. The worldwide outbreak and prevention from severe acute respiratory syndrome coronavirus 2 are overviewed in the present article. The latest variant of coronavirus and the status of vaccines are also overviewed in the present article.

Epidemiological characterization of COVID-19 in displaced populations of South Sudan

Introduction

South Sudan is facing a protracted humanitarian crisis with increasing population vulnerability. The study aimed to describe the epidemiology of COVID-19 in displaced populations in South Sudan.

Methods

the study involved the internally displaced populations (IDP) in Bentiu IDP camp, South Sudan. This was a descriptive cross-sectional study involving individuals that met the COVID-19 probable and confirmed case definitions from May 2020 to November 2021. Case data were managed using Microsoft Excel databases.

Results

the initial COVID-19 case in Bentiu IDP camp was reported on 2 May 2020. The overall cumulative attack rate (cases per million) was 3,230 for Bentiu IDP and 1,038 at the national level. The COVID-19 Case Fatality Ratio (CFR) among the IDPs was 19.08% among confirmed and 1.06% at the national level. There was one wave of COVID-19 transmission in the IDPs that coincided with the second COVID-19 wave in South Sudan for the period May 2020 to November 2021. Adult males aged 20-49 years were the most affected and constituted 47.1% of COVID-19 cases. Most severe cases were reported among adults 60-69 years (53%) and ≥ 70 years (80%). The risk of COVID-19 death (deaths per 10,000) increased with age and was highest in patients aged ≥ 60 years at 64.1. The commonest underlying illnesses among COVID-19 deaths was HIV-related illness, heart disease, and tuberculosis.

Conclusion

COVID-19 constitutes a significant impact on internally displaced populations of South Sudan. The COVID-19 response in displaced populations and the high-risk groups therein should be optimized.

The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia

The ongoing COVID-19 pandemic has posed a global threat to human health. In order to prevent the spread of this virus, many countries have imposed travel restrictions. This difficult situation has dramatically affected the airline industry by reducing the passenger volume, number of flights, airline flow patterns, and even has changed the entire airport network, especially in Northeast Asia (because it includes the original disease seed). However, although most scholars have used conventional statistical analysis to describe the changes in passenger volume before and during the COVID-19 outbreak, very few of them have applied statistical assessment or time series analysis, and have not even examined how the impact may be different from place to place. Therefore, the purpose of this study was to identify the impact of COVID-19 on the airline industry and affected areas (including the origin-destination flow and the airport network). First, a Clustering Large Applications (CLARA) algorithm was used to group numerous origin-destination (O-D) flow patterns based on their characteristics and to determine if these characteristics have changed the severity of the impact of each cluster during the COVID-19 outbreak. Second, two statistical tests (the paired t-test and the Wilcoxon signed-rank test) were utilized to determine if the entire airport network and the top 30 hub airports changed during COVID-19. Four centrality measurement indices (degree, closeness, eigenvector, and betweenness centrality) of the airports were used to assess the entire network and ranking of individual hub airports. The study data, provided by The Official Aviation Guide (OAG) from December 2019 to April 2020, indicated that during the COVID-19 outbreak, there was a decrease in passenger volume (60%-98.4%) as well as the number of flights (1.5%-82.6%). However, there were no such significant changes regarding the popularity ranking of most airports during the outbreak. Before this occurred (December 2019), most hub airports were in China (April 2020), and this trend remain similar during the COVID-19 outbreak. However, the values of the centrality measurement decreased significantly for most hub airports due to travel restrictions issued by the government.

Global pandemics, conflict and networks - the dynamics of international instability, infodemics and health care in the 21st century

Background

The COVID-19 global pandemic is a harbinger of a future destabilised world driven by climate change, rapid mass migration, food insecurity, state failures and epidemics. A significant feature fuelling this destabilised world is networked misinformation and disinformation (referred to as an infodemic), particularly in the area of health.

Aims

To describe the interactive dynamic of climate change; mass population movement; famine; state failure and epidemic disease, analyse developments over the year 2020–2021 and discuss their relationship to an infodemic about disease and public health responses and how this should be addressed in the future.

Methods

Using the concept of ‘the Five Horsemen’ of epochal change and network theory to guide a narrative review.

Results

Concepts of epidemiology are reflected in how misinformation is spread around the world. Health care services and personnel face threats as a result that make it more difficult to manage pan global health risks effectively.

Conclusions

Heath care professionals at an individual and organisational level need to counter infodemic networks. Health care professionals who consistently spread misinformation should have their licence to practice withdrawn.

A COVID-19 Vaccine for Dogs Prevents Reverse Zoonosis

COVID-19 is caused by severe acute respiratory syndrome virus type 2 (SARS-CoV-2), which can infect both humans and animals. SARS-CoV-2 originated from bats and can affect various species capable of crossing the species barrier due to active mutation. Although reports on reverse zoonosis (human-to-animal transmission) of SARS-CoV-2 remain limited, reverse zoonosis has been reported in many species such as cats, tigers, minks, etc. Therefore, transmission to more animals cannot be ruled out. Moreover, the wide distribution of SARS-CoV-2 in the human population could result in an increased risk of reverse zoonosis. To counteract reverse zoonosis, we developed the first COVID-19 subunit vaccines for dogs, which are representative companion animals, and the vaccine includes the SARS-CoV-2 recombinant protein of whole S1 protein and the receptor-binding domain (RBD). A subunit vaccine is a vaccine developed by purifying only the protein region that induces an immune response instead of the whole pathogen. This type of vaccine is safer than the whole virus vaccine because there is no risk of infection and proliferation through back-mutation of the virus. Vaccines were administered to beagles twice at an interval of 3 weeks subcutaneously and antibody formation rates were assessed in serum. We identified a titer, comparable to that of vaccinated people, shown to be sufficient to protect against SARS-CoV-2. Therefore, the vaccination of companion animals, such as dogs, may prevent reverse zoonosis by protecting animals from SARS-CoV-2; thus, reverse zoonosis of COVID-19 is preventable.

Applications of blockchain for vaccine passport and challenges

Purpose

The purpose of this study is to investigate the applications of blockchain in vaccine passport solution. The world is facing an unprecedented situation because of the COVID-19 pandemic. Many countries have witnessed sporadic lockdown and travel restrictions and it has marred trade and tourism. As the mass vaccination has started the life is slowly and steadily returning to true normal. Various countries are issuing vaccination passports to manage the immunization information and validate it. To realize vaccine-passport’s true potential, security and privacy concerns should be being taken care of. There is a need for studies to evaluate the emerging technology for the vaccine passport.

Design/methodology/approach

This study uses a mix of qualitative and quantitative methods to achieve its objective. This study uses a systematic literature review to analyze the potential of blockchain for vaccine passports. The case study of three different types of organizations implementing blockchain for vaccine passports was analyzed and results were presented. Last but not least, focus group discussion and search of secondary literature was to done to identify scientific, ethical and legal challenges associated with the use of vaccine passports. The method used for calculating the importance score of these challenges was analytical hierarchy process.

Findings

This study concludes that blockchain-based solutions are very suitable for vaccine passports and addresses the concern related to interoperability, privacy and security. The case study approach was used to elaborate the use of blockchain in three different options available for the vaccine. Last but not least, this study identifies the challenges faced by vaccine passport programs and suggests measures to overcome them. This study concludes that the ethical challenges associated with vaccine passports are more important and should be preferentially treated.

Research limitations/implications

This study is timely and will be he lpful for policymakers in designing the vaccine passport programs. It gives valuable insight to decision-makers evaluating technologies for the development of vaccine passport programs. This study identifies nine challenges to be tackled to making a vaccine passport program successful.

Originality/value

To the best of the author’s knowledge, this study is not able to find out a review on the use of blockchain technology for vaccine passports, and this study attempts to fill this gap. This study further discusses the cases of organizations that have implemented blockchain technology for vaccine passport programs.

The Covid-19 pandemic, an Environmental Neurology perspective

Neurologists have a particular interest in SARS-CoV-2 because the nervous system is a major participant in COVID-19, both in its acute phase and in its persistent post-COVID phase. The global spread of SARS-CoV-2 infection has revealed most of the challenges and risk factors that humanity will face in the future. We review from an environmental neurology perspective some characteristics that have underpinned the pandemic. We consider the agent, SARS-CoV-2, the spread of SARS-CoV-2 as influenced by environmental factors, its impact on the brain and some containment measures on brain health. Several questions remain, including the differential clinical impact of variants, the impact of SARS-CoV-2 on sleep and wakefulness, and the neurological components of Long-COVID syndrome. We touch on the role of national leaders and public health policies that have underpinned management of the COVID-19 pandemic. Increased awareness, anticipation and preparedness are needed to address comparable future challenges.

A Cluster-based Method to Quantify Individual Heterogeneity in Tuberculosis Transmission

BACKGROUND

Recent evidence suggests transmission of Mycobacterium tuberculosis (Mtb) may be characterized by extreme individual heterogeneity in secondary cases (i.e., few cases account for the majority of transmission). Such heterogeneity implies outbreaks are rarer but more extensive and has profound implications in infectious disease control. However, discrete person-to-person transmission events in tuberculosis (TB) are often unobserved, precluding our ability to directly quantify individual heterogeneity in TB epidemiology.

METHODS

We used a modified negative binomial branching process model to quantify the extent of individual heterogeneity using only observed transmission cluster size distribution data (i.e., the simple sum of all cases in a transmission chain) without knowledge of individual-level transmission events. The negative binomial parameter k quantifies the extent of individual heterogeneity (generally, indicates extensive heterogeneity, and as transmission becomes more homogenous). We validated the robustness of the inference procedure considering common limitations affecting cluster size data. Finally, we demonstrate the epidemiologic utility of this method by applying it to aggregate US molecular surveillance data from the US Centers for Disease Control and Prevention.

RESULTS

The cluster-based method reliably inferred k using TB transmission cluster data despite a high degree of bias introduced into the model. We found that the TB transmission in the United States was characterized by a high propensity for extensive outbreaks (; 95% confidence interval = 0.09, 0.10).

CONCLUSIONS

The proposed method can accurately quantify critical parameters that govern TB transmission using simple, more easily obtainable cluster data to improve our understanding of TB epidemiology.

Prioritizing high-contact occupations raises effectiveness of vaccination campaigns

A twenty-year-old idea from network science is that vaccination campaigns would be more effective if high-contact individuals were preferentially targeted. Implementation is impeded by the ethical and practical problem of differentiating vaccine access based on a personal characteristic that is hard-to-measure and private. Here, we propose the use of occupational category as a proxy for connectedness in a contact network. Using survey data on occupation-specific contact frequencies, we calibrate a model of disease propagation in populations undergoing varying vaccination campaigns. We find that vaccination campaigns that prioritize high-contact occupational groups achieve similar infection levels with half the number of vaccines, while also reducing and delaying peaks. The paper thus identifies a concrete, operational strategy for dramatically improving vaccination efficiency in ongoing pandemics.

Travel Bubbles in Air Transportation: Myth or Reality?

Aviation has been hit hard by COVID-19, with passengers stranded in remote destinations, airlines filing for bankruptcy, and uncertain demand scenarios for the future. Travel bubbles are discussed as one possible solution, meaning countries which have successfully constrained the spread of COVID-19 gradually increase their mutual international flights, returning to a degree of normality. This study aims to answer the question of whether travel bubbles are indeed observable in flight data for the year 2020. We take the year 2019 as reference and then search for anomalies in countries’ flight bans and recoveries, which could possibly be explained by having successfully implemented a travel bubble. To the best of our knowledge, this study is the first to try to address the identification of COVID-19 travel bubbles in real data. Our methodology and findings lead to several important insights regarding policy making, problems associated with the concept of travel bubbles, and raise interesting avenues for future research.

Secondary transmission of SARS-CoV-2 during the first two waves in Japan: Demographic characteristics and overdispersion

Objectives

Super-spreading events caused by overdispersed secondary transmission are crucial in the transmission of COVID-19. However, the exact level of overdispersion, demographics, and other factors associated with secondary transmission remain elusive. In this study, we aimed to elucidate the frequency and patterns of secondary transmission of SARS-CoV-2 in Japan.

Methods

We analyzed 16,471 cases between January 2020 and August 2020. We generated the number of secondary cases distribution and estimated the dispersion parameter (k) by fitting the negative binomial distribution in each phase. The frequencies of the secondary transmission were compared by demographic and clinical characteristics, calculating the odds ratio using logistic regression models.

Results

We observed that 76.7% of the primary cases did not generate secondary cases with an estimated dispersion parameter k of 0.23. The demographic patterns of primary-secondary cases differed between phases, with 20–69 years being the predominant age group. There were higher proportions of secondary transmissions among older individuals, symptomatic patients, and patients with 2 days or more between onset and confirmation.

Conclusions

The study showed the estimation of the frequency of secondary transmission of SARS-CoV-2 and the characteristics of people who generated the secondary transmission.

A Review of SARS-CoV2: Compared With SARS-CoV and MERS-CoV

The outbreak of coronavirus disease 2019 (COVID-19) has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic. Studies found that severe COVID-19 is characterized by pneumonia, lymphopenia, exhausted lymphocytes and a cytokine storm. Studies have showen that SARS-CoV2 has significant genomic similarity to the severe acute respiratory syndrome (SARS-CoV), which was a pandemic in 2002. More importantly, some diligent measures were used to limit its spread according to the evidence of hospital spread. Therefore, the Public Health Emergency of International Concern (PHEIC) has been established by the World Health Organization (WHO) with strategic objectives for public health to curtail its impact on global health and economy. The purpose of this paper is to review the transmission patterns of the three pneumonia: SARS-CoV2, SARS-CoV, and MERS-CoV. We compare the new characteristics of COVID-19 with those of SARS-CoV and MERS-CoV.

Changes in the pattern of suicide attempters visiting the emergency room after COVID-19 pandemic: an observational cross sectional study

BACKGROUND

This study aimed to find out the change in the rate and pattern of suicide attempts during severe acute respiratory syndrome COVID-19 pandemic period.

METHODS

This study was a retrospective analysis of data collected as a part of an emergency room-based post-suicide management program. The data were collected through interviews and from medical records of suicide attempts, maintained in the emergency room, from January 19 to October 31, 2020, during the "COVID-19 period," and those who attempted suicide from January 19 to October 31, 2019 "pre-COVID-19 period." We extracted educational background, marital status, occupation, presence of domestic partner, history of mental illness, alcohol consumption, history of previous suicide attempts; suicide attempt method and location (i.e., at home or a place other than home) at the time of attempt, and whether the attempt was a mass suicide. In addition, we compared patient severity between "COVID-19 period" and "pre-COVID-19 period" using the initial KTAS (South Korean triage and acuity scale) level, consciousness level, and systolic blood pressure. In 2012, KTAS was developed through the Ministry of Health and Welfare's research project to establish triage system in South Korea.

RESULTS

The analysis of the number of suicide attempts during "pre-COVID-19 period" and " COVID-19 period" showed that the number of suicide attempts during "COVID-19 period" (n = 440) increased compared to the "pre-COVID-19 period" (n = 400). Moreover, the method of suicide attempts during "COVID-19 period" included overdose of drugs such as hypnotics, antipsychotics, and pesticides that were already possessed by the patient increased compared to the "pre-COVID-19 period" (P < 0.05). At the time of the visit to the emergency room, high KTAS level, low level of consciousness, and low systolic blood pressure, were observed, which were significantly different between "COVID-19 period" and "pre-COVID-19 period" (P < 0.05).

CONCLUSION

With the worldwide COVID-19 virus spread, suicide rate and suicide attempts at home have significantly increased. In addition, patient severity was higher in the "COVID-19 period" than that in the "pre-COVID-19 period." The increasing suicide attempt rate should be controlled by cooperation between the emergency room and regional organizations.

Sector-by-sector analysis of dependence dynamics between global large-cap companies and infectious diseases: A time-varying copula approach in EBOV and COVID-19 episodes

Infectious diseases and widespread outbreaks influence different sectors of the economy, including the stock market. In this article, we investigate the effect of EBOV and COVID-19 outbreaks on stock market indices. We employ time-varying and constant bivariate copula methods to measure the dependence structure between the infectious disease equity market volatility index (IEMV) and the stock market indices of several sectors. The results show that the financial and communication services sectors have the highest and the lowest negative dependency on IEMV during the Ebola virus (EBOV) pandemic, respectively. However, the health care and energy sectors have the highest and lowest negative dependency on IEMV during the COVID-19 outbreak, respectively. Therefore, the results confirm the heterogeneous time-varying dependency between infectious diseases and the stock market indices. The finding of our study contributes to the ongoing literature on the impact of disease outbreaks, especially the novel coronavirus outbreak on global large-cap companies in the stock market.

Role of key infectivity parameters in the transmission of Ebola virus Makona in macaques

Many characteristics associated with Ebola virus disease remain to be fully understood. It is known that direct contact with infected bodily fluids is an associated risk factor, but few studies have investigated parameters associated with transmission between individuals, such as the dose of virus required to facilitate spread and route of infection. Therefore, we sought to characterize the impact by route of infection, viremia, and viral shedding through various mucosae, with regards to intraspecies transmission of Ebola virus in a nonhuman primate model. Here, challenge via the esophagus or aerosol to the face did not result in clinical disease, although seroconversion of both challenged and contact animals was observed in the latter. Subsequent intramuscular or intratracheal challenges suggest that viral loads determine transmission likelihood to naive animals in an intramuscular-challenge model, which is greatly facilitated in an intratracheal-challenge model where transmission from challenged to direct contact animal was observed consistently.

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.

[Impact of SARS-CoV-2 on fertility, gametes' quality and Assisted Reproduction Technology]

Le contexte actuel de pandémie conduit à s’interroger sur les conséquences de la COVID-19 en Assistance médicale à la procréation (AMP). En effet, suite aux premières recommandations de l’Agence de la biomédecine en mars 2020, les centres d’AMP ont suspendu leurs activités. La reprise progressive des tentatives en mai 2020 s’est accompagnée de nombreux questionnements, concernant les effets directs et indirects du SARS-CoV-2 sur la qualité des gamètes, la gamétogenèse, la fertilité, la grossesse et la santé néonatale. L’objectif de cette revue de la littérature est de synthétiser les données disponibles, pour informer les patient(e)s pris(es) en charge et adapter les pratiques d’AMP en cette période de la COVID-19. La plupart des études récentes se basent sur l’évaluation des effets du syndrome infectieux, sur l’analyse des facteurs hormonaux, et sur l’expression des protéines d’entrée virale (ACE2 et TMPRSS2) au niveau des cellules impliquées dans la gamétogenèse pour évaluer les répercussions de la COVID-19. La transmission materno-fœtale du SARS-CoV-2 n’a pas pu être démontrée à ce jour, mais l’infection néonatale reste possible. Néanmoins, les hommes seraient plus à risque d’être infectés par le SARS-CoV-2, d’être symptomatiques et la spermatogenèse est vraisemblablement affectée. La présence du virus dans le sperme est un évènement rare, mais l’ensemble de ces paramètres sont à prendre en compte dans la prise en charge des couples en AMP. Cependant, aucune conséquence sur la qualité des gamètes féminins n’a été mise en évidence jusqu’à présent.

Superspreading in the emergence of COVID-19 variants

Superspreading and variants of concern (VOC) of the human pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are the main catalyzers of the coronavirus disease 2019 (COVID-19) pandemic. However, measuring their individual impact is challenging. By examining the largest database of SARS-CoV-2 genomes The Global Initiative on Sharing Avian Influenza Data [GISAID; n >1.2 million high-quality (HQ) sequences], we present evidence suggesting that superspreading has had a key role in the epidemiological predominance of VOC. There are clear signatures in the database compatible with large superspreading events (SSEs) coinciding chronologically with the worst epidemiological scenarios triggered by VOC. The data suggest that, without the randomness effect of the genetic drift facilitated by superspreading, new VOC of SARS-CoV-2 would have had more limited chance of success.

Social distancing as risk reduction strategy during COVID-19 pandemic: A study of Delhi-NCT, India

COVID-19 pandemic impacted countries all over the world calling as urgent need to enhance the capacity of individuals and communities to respond in such disease outbreaks. Public health interventions, such as social distancing could help to protect many vulnerable people and reduce secondary transmissions within the community. This research was undertaken as a longitudinal study to identify and comprehend the preferences given to different preventive measures adopted by individuals to ensure protection against the spread of coronavirus. An online survey was conducted with a representative sample of 176 stakeholders to identify practices and behaviour adopted by the key stakeholders working in the domains of water, health and disaster risk reduction to curb the spread of COVID-19 in Delhi-National Capital Territory of India (Delhi-NCT). Findings of this study shown preferred willingness to adopt sanitisation measures, often by cleaning their hands with soap and water, and restricting any movement inside and outside of the house. Three-fourth of the respondents considered washing their hands after returning from outside an important measure to limit the spread of the disease. Moreover, two-third of the people stopped ordering food from outside as a prevention strategy. Furthermore, only about 36% of the respondents showed interest in stocking up on grocery items as their most preferred choice, reflecting that this was considered to be the least important of all choices. Research outcomes of this study will help policymakers to better understand mitigation options that are used in the early and later stages of the lockdown to improve resilience from such viruses. Further, it will assist decision-makers to understand the range of individual-level practices adopted by stakeholders to mitigate disease transmission at the community level and inform the government's planning efforts in the future.

Model-informed drug repurposing: Viral kinetic modelling to prioritize rational drug combinations for COVID-19

AIM

We hypothesized that viral kinetic modelling could be helpful to prioritize rational drug combinations for COVID-19. The aim of this research was to use a viral cell cycle model of SARS-CoV-2 to explore the potential impact drugs, or combinations of drugs, that act at different stages in the viral life cycle might have on various metrics of infection outcome relevant in the early stages of COVID-19 disease.

METHODS

Using a target-cell limited model structure that has been used to characterize viral load dynamics from COVID-19 patients, we performed simulations to inform on the combinations of therapeutics targeting specific rate constants. The endpoints and metrics included viral load area under the curve (AUC), duration of viral shedding and epithelial cells infected. Based on the known kinetics of the SARS-CoV-2 life cycle, we rank ordered potential targeted approaches involving repurposed, low-potency agents.

RESULTS

Our simulations suggest that targeting multiple points central to viral replication within infected host cells or release from those cells is a viable strategy for reducing both viral load and host cell infection. In addition, we observed that the time-window opportunity for a therapeutic intervention to effect duration of viral shedding exceeds the effect on sparing epithelial cells from infection or impact on viral load AUC. Furthermore, the impact on reduction on duration of shedding may extend further in patients who exhibit a prolonged shedder phenotype.

CONCLUSIONS

Our work highlights the use of model-informed drug repurposing approaches to better rationalize effective treatments for COVID-19.

Nanotechnology based solutions to combat zoonotic viruses with special attention to SARS, MERS, and COVID 19: Detection, protection and medication

Zoonotic viruses originate from birds or animal sources and responsible for disease transmission from animals to people through zoonotic spill over and presents a significant global health concern due to lack of rapid diagnostics and therapeutics. The Corona viruses (CoV) were known to be transmitted in mammals. Early this year, SARS-CoV-2, a novel strain of corona virus, was identified as the causative pathogen of an outbreak of viral pneumonia in Wuhan, China. The disease later named corona virus disease 2019 (COVID-19), subsequently spread across the globe rapidly. Nano-particles and viruses are comparable in size, which serves to be a major advantage of using nano-material in clinical strategy to combat viruses. Nanotechnology provides novel solutions against zoonotic viruses by providing cheap and efficient detection methods, novel, and new effective rapid diagnostics and therapeutics. The prospective of nanotechnology in COVID 19 is exceptionally high due to their small size, large surface-to-volume ratio, susceptibility to modification, intrinsic viricidal activity. The nano-based strategies address the COVID 19 by extending their role in i) designing nano-materials for drug/vaccine delivery, ii) developing nano-based diagnostic approaches like nano-sensors iii) novel nano-based personal protection equipment to be used in prevention strategies.This review aims to bring attention to the significant contribution of nanotechnology to mitigate against zoonotic viral pandemics by prevention, faster diagnosis and medication point of view.

Public Awareness, Attitudes, and Adherence to COVID-19 Quarantine and Isolation in Saudi Arabia

BACKGROUND

This study aims to assess the general population's awareness, attitude, and adherence regarding COVID-19 and quarantine in Saudi Arabia.

METHODS

A descriptive cross-sectional design with a consecutive sampling method was used in this study. All accessible Saudi population during the study period were invited to participate in the survey from 1st April to 25th April 2020. The study questionnaire was constructed by the researchers based on experts' consultation.

RESULTS

A total sample of 1998 respondents with complete data was included in the survey. A total of 1936 participants reported that they were aware of regarding COVID-19 outbreak (96.9%). The most identified symptom was fever (92.3%; 1843), followed by respiratory distress (90.8%; 1813). About 81% of the participants reported that quarantine should be applied with travel or contact with infected persons. Also, 98.3% of the participants reported that the quarantine period should be a minimum of 14 days. In total, more than three-quarters of the participants had good awareness levels regarding COVID-19 and quarantine.

CONCLUSION

This study showed that the Saudi population had very high levels of awareness, adherence regarding COVID-19 quarantine and isolation measures.