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Ongoing social restrictions, including social distancing and lockdown, adopted by many countries to inhibit spread of the the COVID-19 epidemic, must attempt to find a trade-off between induced economic damage, healthcare system collapse, and the costs in terms of human lives. Applying and removing restrictions on a system with a given latency as represented by an epidemic outbreak (and formally comparable with mechanical inertia), may create critical instabilities, overshoots, and strong oscillations in the number of infected people around the desirable set-point, defined in a practical way as the maximum number of hospitalizations acceptable by a given healthcare system. A good understanding of the system reaction to any change of the input control variable can be reasonably achieved using a proportional-integral-derivative controller (PID), which is a widely used technique in various physics and technological applications. In this paper, this control theory to is proposed to be applied epidemiology, to understand the reaction of COVID-19 propagation to social restrictions and to reduce epidemic damages through the correct tuning of the containment policy. Regarding the synthesis of this interdisciplinary approach, the extended to the susceptible-infectious-recovered (SIR) model name "SIR-PID" is suggested. [ABSTRACT FROM AUTHOR]

To mitigate the spread of the Novel Coronavirus (COVID-19), governments around the world have imposed social distancing policies ranging from minor social activity suspensions to full curfews. These social distancing policies have altered electricity consumption behaviors in numerous countries. Many governments imposed strict social distancing policies during a temperature transition season where the impacts of temperature variations are particularly important for the operation of the electric grid. This paper studies how strict social distancing policies affect the relationship between electricity demand and ambient temperature. We first review the expected short- and long-term impacts of social distancing on the electricity demand. We then present a case study on the electricity demand of the Kingdom of Saudi Arabia during strict social distancing policies. The results of this case study suggest that strict social distancing policies result in a stronger correlation between temperature and electricity demand compared to previous years. Additionally, we observe a reduction in the time required for the electricity demand to respond to temperature changes. Power system regulators can use the results in this paper to better design energy policies. The results can also be used by power system operators to more accurately forecast electricity demands and avoid inefficient and insecure operation of the electric grid. [ABSTRACT FROM AUTHOR]

The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health authorities attempt to fight against the virus while maintaining economic activity. In the face of the uncertainty derived from the virus, all the countries have adopted non-pharmaceutical interventions for limiting the mobility and maintaining social distancing. In order to support these interventions, some health authorities and governments have opted for sharing very fine-grained data related with the impact of the virus in their territories. Geographical science is playing a major role in terms of understanding how the virus spreads across regions. Location of cases allows identifying the spatial patterns traced by the virus. Understanding these patterns makes controlling the virus spread feasible, minimizes its impact in vulnerable regions, anticipates potential outbreaks, or elaborates predictive risk maps. The application of geospatial analysis to fine-grained data must be urgently adopted for optimal decision making in real and near-real time. However, some aspects related to process and map sensitive health data in emergency cases have not yet been sufficiently explored. Among them include concerns about how these datasets with sensitive information must be shown depending on aspects related to data aggregation, scaling, privacy issues, or the need to know in advance the particularities of the study area. In this paper, we introduce our experience in mapping fine-grained data related to the incidence of the COVID-19 during the first wave in the region of Galicia (NW Spain), and after that we discuss the mentioned aspects. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease (COVID-19) pandemic has impacted every facet of society. One of the non-pharmacological measures to contain the COVID-19 infection is social distancing. Federal, state, and local governments have placed multiple executive orders for human mobility reduction to slow down the spread of COVID-19. This paper uses geotagged tweets data to reveal the spatiotemporal human mobility patterns during this COVID-19 pandemic in New York City. With New York City open data, human mobility pattern changes were detected by different categories of land use, including residential, parks, transportation facilities, and workplaces. This study further compares human mobility patterns by land use types based on an open social media platform (Twitter) and the human mobility patterns revealed by Google Community Mobility Report cell phone location, indicating that in some applications, open-access social media data can generate similar results to private data. The results of this study can be further used for human mobility analysis and the battle against COVID-19. [ABSTRACT FROM AUTHOR]

The risk of COVID-19 infection from virulent aerosols is particularly high indoors. This is especially true for classrooms, which often do not have pre-installed ventilation and are occupied by a large number of students at the same time. It has been found that precautionary measures, such as the use of air purifiers (AP), physical distancing, and the wearing of masks, can reduce the risk of infection. To quantify the actual effect of precautions, it is not possible in experimental studies to expose subjects to virulent aerosols. Therefore, in this study, we develop a computational fluid dynamics (CFD) model to evaluate the impact of applying the aforementioned precautions in classrooms on reducing aerosol concentration and potential exposure in the presence of index or infected patients. A CFD-coupled Wells–Riley model is used to quantify the infection probability (IP) in the presence of index patients. Different cases are simulated by varying the occupancy of the room (half/full), the volumetric flow rate of the AP, two different locations of the AP, and the effect of wearing masks. The results suggest that using an AP reduces the spread of virulent aerosols and thereby reduces the risk of infection. However, the risk of the person sitting adjacent to the index patient is only marginally reduced and can be avoided with the half capacity of the class (physical distancing method) or by wearing face masks of high efficiencies. [ABSTRACT FROM AUTHOR]

Simple Summary: Dogs are considered man's best friend, with many owners sharing a close relationship with their dogs. This affection increased during the COVID-19 pandemic, as owners spent more time with their canines during the lockdowns and quarantines. During this time, owners noted how their dogs helped reduce their stress and anxiety. Yet, of concern is the known natural infection/transmission of SARS-CoV-2 reported in numerous animals (e.g., cats, minks, deer), necessitating the need to determine if dogs can contract or spread SARS-CoV-2. In this review, we focused on the human–canine interface of COVID-19 and the positives and negatives of this interface. We found that dogs can get COVID-19 from their owners but are asymptomatic when infected—it is unclear if it affects the health of dogs. Research is inconclusive on if dogs can transmit SARS-CoV-2 to their owners. Although dogs could be hosts, they are beneficial beyond just stress relief. Sniffer dogs can rapidly detect COVID-19-positive individuals in crowds, with almost 80% success in distinguishing between positive and negative people. Overall, we emphasize that more research is needed to understand the role of dogs in the interspecies spread and even contraction of SARS-CoV-2. COVID-19 is one of the deadliest epidemics. This pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but the role of dogs in spreading the disease in human society is poorly understood. This review sheds light on the limited susceptibility of dogs to COVID-19 infections which is likely attributed to the relatively low levels of angiotensin-converting enzyme 2 (ACE2) in the respiratory tract and the phylogenetic distance of ACE2 in dogs from the human ACE2 receptor. The low levels of ACE2 affect the binding affinity between spike and ACE2 proteins resulting in it being uncommon for dogs to spread the disease. To demonstrate the role of dogs in spreading COVID-19, we reviewed the epidemiological studies and prevalence of SARS-CoV-2 in dogs. Additionally, we discussed the use of detection dogs as a rapid and reliable method for effectively discriminating between SARS-CoV-2 infected and non-infected individuals using different types of samples (secretions, saliva, and sweat). We considered the available information on COVID-19 in the human–dog interfaces involving the possibility of transmission of COVID-19 to dogs by infected individuals and vice versa, the human–dog behavior changes, and the importance of preventive measures because the risk of transmission by domestic dogs remains a concern. [ABSTRACT FROM AUTHOR]

The novel coronavirus (SARS-CoV-2) has imposed the need for a series of social distancing restrictions worldwide to mitigate the scourge of the COVID-19 pandemic. This applies to many domains, including airplane boarding and seat assignments. As airlines are considering their passengers' safety during the pandemic, boarding methods should be evaluated both in terms of social distancing norms and the resulting efficiency for the airlines. The present paper analyzes the impact of a series of restrictions that have been imposed or mooted worldwide on the boarding methods used by the airlines, featuring the use of jet-bridges and one-door boarding. To compare the efficacy of classical airplane boarding methods with respect to new social distancing norms, five metrics were used to evaluate their performance. One metric is the time to complete the boarding of the airplane. The other four metrics concern passenger health and reflect the potential exposure to the virus from other passengers through the air and surfaces (e.g., headrests and luggage) touched by passengers. We use the simulation platform in NetLogo to test six common boarding methods under various conditions. The back-to-front by row boarding method results in the longest time to complete boarding but has the advantage of providing the lowest health risk for two metrics. Those two metrics are based on passengers potentially infecting those passengers previously seated in the rows they traverse. Interestingly, those two risks are reduced for most boarding methods when the social distance between adjacent passengers advancing down the aisle is increased, thus indicating an unanticipated benefit stemming from this form of social distancing. The modified reverse pyramid by half zone method provides the shortest time to the completing boarding of the airplane and—along with the WilMA boarding method—provides the lowest health risk stemming from potential infection resulting from seat interferences. Airlines have the difficult task of making tradeoffs between economic productivity and the resulting impact on various health risks. [ABSTRACT FROM AUTHOR]

The continuing crisis caused by the novel coronavirus (COVID-19) outbreak has raised significant challenges for the higher education community globally. In South Africa, the government-forced lockdown measures and social distancing containment policy changed working arrangements across sectors and organisations. As a result, academics were forced to work from home (WFH), a task for which they were hardly prepared. Several researchers have engaged the WFH situation of academics to understand the relationship between WFH and productivity. As far as we know, very few studies have tried to describe academics' WFH experiences in relation to the challenges, including determining possible ways of improving their satisfaction with working from home. We examine in this article the experiences of academics working from home across selected universities in South Africa. Using a qualitative approach and applying Atlas.ti for data analysis, our findings show that working from home in academia is a daunting task requiring extensive organisational, personal, and social adjustments. The population comprised all academics irrespective of any demographic or personality characteristic within the management faculty of the participating universities to secure the anonymity of the respondents. Five themes—inability to adapt, lack of a home office, loneliness and isolation, inability to balance family and work, and improving satisfaction with work from home—were identified as significant variables from the participants' responses. Our analysis suggests that organisations need to customise approaches to engage with the experiences of academics who work from home during COVID-19 and to develop fit-for-purpose support for these academics. The study contributes to the growing research exploring the relationship between COVID-19 lockdown and work in higher education. [ABSTRACT FROM AUTHOR]

The strict lockdowns imposed to contain the COVID-19 pandemic brought an increase in levels of stress, anxiety, and depression in the general population. However, in a previous study, our group found that individuals with High-Functioning Autism Spectrum Disorders (HF-ASD) reported an increase in their psychological wellbeing and a decrease in their daily tiredness, in relation to the social distancing measures imposed during the first Italian lockdown (between March and May 2020). In this follow-up study, conducted during the "second wave" of COVID-19, we included the same group of individuals with HF-ASD and evaluated their levels of stress, anxiety, depression, PTSD-related symptoms, tiredness, and perceived wellbeing; moreover, we compared our results to the ones we obtained during the first lockdown on the same population. We found that individuals with HF-ASD experienced higher levels of the aforementioned psychiatric symptoms during the second lockdown, with respect to the first one. These levels positively correlated with their scores at the Autism Quotient subscale Attention Switching: hence, we speculated that these symptoms might be due not only to the prolonging of the social distancing measures, but also to the uncertainty that HF-ASD participants started experiencing at the end of the first lockdown. [ABSTRACT FROM AUTHOR]

The global pandemic caused by the new coronavirus has largely changed established business practices. The aim of this study is to present the results of eighteen months of intensive research into the effects of the pandemic on e-consumer behavior. In one of the most active e-commerce markets in Europe, the Czech Republic, we analyzed a sample of more than one and a half million Facebook users in terms of their C2B interactions on the B2C activities of the five major e-commerce market players. The measurements were carried out in three periods, which corresponded to the onset of the first wave, the peak, and the fading of the second wave of the pandemic. This enabled us to monitor the effect of seasonality and the stabilization of patterns of consumer behavior during the coronavirus crisis. The results suggest that a specific panic pattern of e-consumer behavior was developed at the time of the onset of the pandemic. However, as the pandemic progressed, the market adapted to a new normal, which, as evidenced by the change in trends, appears to be a combination of the pre-pandemic and pandemic behavioral patterns. Using a statistical analysis, it was possible to identify the delta of changes within the patterns of consumer behavior, thus fulfilling the final condition for creating an empirical model of the impacts of the COVID-19 pandemic on e-consumer behavior presented in this study. [ABSTRACT FROM AUTHOR]

The social distancing imposed by the novel coronavirus, SARS-CoV-2, has affected people's everyday lives and has resulted in companies changing the way they conduct business. The airline industry has been continually adapting since the novel coronavirus appeared. A series of airlines have changed their airplane boarding and passenger seat allocation process to increase their passengers' safety. Many suggest a minimum social distance among passengers in the aisle while boarding. Some airlines have reduced their airplanes' capacities by keeping the middle seats empty. Recent literature indicates that the Reverse Pyramid boarding method provides favorable values for boarding time and passenger health metrics when compared to other boarding methods. This paper analyses the extent to which aisle social distancing, the quantity of carry-on luggage, and an airline's relative preferences for different performance metrics influence the optimal number of passengers to board the airplane in each of three boarding groups when the Reverse Pyramid method is used and the middle seats are empty. We also investigate the resulting impact on the average boarding time and health risks to boarding passengers. We use an agent-based model and stochastic simulation approach to evaluate various levels of aisle social distancing among passengers and the quantity of luggage carried aboard the airplane. When minimizing boarding time is the primary objective of an airline, for a given value of aisle social distance, decreasing the carry-on luggage volumes increases the optimal number of boarding group 1 passengers and decreases the optimal number of group 2 passengers with aisle seats; for a given volume of luggage, an increase in aisle social distance is associated with more passengers in group 1 and more aisle seat passengers in group 2. When minimizing the health risk to aisle seat passengers or to window seat passengers, the optimal solution results from assigning an equal number of window seat passengers to groups 1 and 2 and an equal number of aisle seat passengers to groups 2 and 3. This solution is robust to changes in luggage volume and the magnitude of aisle social distance. Furthermore, across all luggage and aisle social distancing scenarios, the solution reduces the health risk to aisle seat passengers between 22.76% and 35.31% while increasing average boarding time by less than 3% in each scenario. [ABSTRACT FROM AUTHOR]

The newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as COVID-19, has been recognized as a pandemic by the World Health Organization (WHO) on 11th March 2020. There are many unknowns about this virus to date and no vaccine or conclusive treatment due to the lack of understanding of its pathogenesis and proliferation pathways which are unknown and cannot be traced. The prime objective is to stop its spread worldwide. This article aims to provide predictions of its spread using a stochastic Lotka–Volterra model coupled with an extended Kalman Filter (EKF) algorithm to model the COVID-19 dynamics. Our results show the feasibility of utilizing this model for predicting the spread of the virus and the ability of different control measures (e.g., social distancing) on reducing the number of affected people. [ABSTRACT FROM AUTHOR]

There is no doubt about the importance of diagnostic testing in an emergency; specifically, which range of tests is available, where and when they are dispensed, and who might be tested using laboratory-developed tests, or other diagnostic tests including experimental tests. This includes testing for the SARS-CoV-2 virus that causes the COVID-19 disease. Testing is essential to "flatten the curve" of the number of confirmed positive cases of the disease, in addition to handwashing, isolation, and social distancing, among other essential measures. Is one diagnostic test enough to obtain the correct decision about a confirmed positive outcome?. [ABSTRACT FROM AUTHOR]

Simple Summary: During the COVID-19 pandemic, many veterinary practices have been required to move to a low or no-contact consultation model to minimise the risk of SARS-CoV-2. Utilising data from a global survey, we explored the experiences of veterinary team members performing low and no-contact euthanasia during the early months of the COVID-19 pandemic. We found that low and no-contact euthanasia were encountered as common and/or stressful ethical challenges in the pandemic. In order to minimise the potential negative impacts of low and no-contact euthanasia on veterinary team members, clients and animal patients, there is a need for a toolkit of protocols to assist veterinary team members in provision of low-contact euthanasia, and avoidance of no-contact euthanasia wherever possible. Background: During the ongoing COVID-19 pandemic, many veterinary practices around the world have shifted to a low or no-contact consultation model to ensure the safety of their team members and clients, and comply with public health orders, while continuing to provide veterinary care. Methods: We performed reflexive thematic analysis on a subset of data collected using a mixed-methods survey of veterinary team members globally. Results: There were 540 valid responses available for analysis. Low and no-contact euthanasia we raised as a common and/or stressful ethical challenge for 22.8% of respondents. We identified five key themes: no-contact euthanasia as a unique ethical challenge; balancing veterinary team safety with the emotional needs of clients; low and no-contact protocols may cause or exacerbate fear, anxiety and distress in veterinary patients; physical distancing was more challenging during euthanasia consultations; and biosecurity measures complicated communication around euthanasia and end-of-life decision making. Recommendations: In light of concerns highlighted by respondents, we recommend the development of a toolkit of protocols that will assist veterinary team members in performing low-contact euthanasia in a range of circumstances, in alignment with their values and professional ethical codes. Professional bodies may be involved in developing, updating and disseminating this information, and ensuring a continuous supply chain of PPE. [ABSTRACT FROM AUTHOR]

Introduction: Healthcare workers experience a significant risk of exposure to and infection from SARS-CoV-2, COVID-19. Nonetheless, little research has focused on physicians' use of personal protective equipment (PPE), their concerns about becoming infected and their social distancing maneuvers. Methods: All staff physicians at Advocate Lutheran General Hospital were invited to participate. Their COVID-19 IgG antibody level was measured and an online questionnaire was completed. The questionnaire assessed the risk of COVID-19 exposure, PPE usage, concern for contracting COVID-19, the performance of high-risk procedures, work in high-risk settings, and social distancing practices. Testing was performed in September (T0), and December 2020 (T1) at the height of the global pandemic. Results: A total of 481 (26.7%) of 1800 AGLH physicians were enrolled at T0 and 458 (95% of the original group) at T1. A total of 21 (4.3%) and 39 (8.5%) participants had antibodies at T0 and T1. A total of 63 (13.8%) worked in high-risk settings and 111 (24.2%) performed high-risk procedures. Participants working in high-risk settings had increased exposure to COVID-19 infected patients (OR = 4.464 CI = 2.522–8.459, p < 0.001). Participants were highly adherent to the use of PPE and social distancing practices including mask-wearing in public (86%, 82.1%), avoiding crowds (85.1%, 85.6%), six feet distancing (83.8%, 83.4%), and avoiding public transportation (78%, 83.8%). A total of 251 (55.4%) participants expressed moderate to extreme concern about becoming infected with COVID-19. Conclusions and Relevance: Among a group of community physicians, consistent PPE use and social distancing practices were common. These practices were associated with a low level of initial acquisition of COVID-19 infections and a relatively low longitudinal risk of infection. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic challenges healthcare services. Concomitantly, this pandemic had a stimulating effect on technological expansions related to telehealth and telemedicine. We sought to elucidate the principal patients' reasons for using telemedicine during the COVID-19 pandemic and the propensity to use it thereafter. Our primary objective was to identify the reasons of the survey participants' disparate attitudes toward the use of telemedicine. We performed an online, multilingual 30-question survey for 14 days during March–April 2021, focusing on the perception and usage of telemedicine and their intent to use it after the pandemic. We analyzed the data to identify the attributes influencing the intent to use telemedicine and built decision trees to highlight the most important related variables. We examined 473 answers: 272 from Israel, 87 from Uruguay, and 114 worldwide. Most participants were women (64.6%), married (63.8%) with 1–2 children (52.9%), and living in urban areas (84.6%). Only a third of the participants intended to continue using telemedicine after the COVID-19 pandemic. Our main findings are that an expected substitution effect, technical proficiency, reduced queueing times, and peer experience are the four major factors in the overall adoption of telemedicine. Specifically, (1) for most participants, the major factor influencing their telemedicine usage is the implicit expectation that such a visit will be a full substitute for an in-person appointment; (2) another factor affecting telemedicine usage by patients is their overall technical proficiency and comfort level in the use of common web-based tools, such as social media, while seeking relevant medical information; (3) time saving as telemedicine can allow for asynchronous communications, thereby reducing physical travel and queuing times at the clinic; and finally (4) some participants have also indicated that telemedicine seems more attractive to them after watching family and friends (peer experience) use it successfully. [ABSTRACT FROM AUTHOR]

Four months into the SARS-CoV-2 vaccination campaign, only 10.7% of the Lebanese population have received at least one dose, raising serious concerns over the speed of vaccine roll-out and its impact in the event of a future surge. Using mathematical modeling, we assessed the short-term impact of various vaccine roll-out scenarios on SARS-CoV-2 epidemic course in Lebanon. At current population immunity levels, estimated by the model at 40% on 15 April 2021, a large epidemic wave is predicted if all social distancing restrictions are gradually eased and variants of concern are introduced. Reaching 80% vaccine coverage by the end of 2021 will flatten the epidemic curve and will result in a 37% and 34% decrease in the peak daily numbers of severe/critical disease cases and deaths, respectively; while reaching intermediate coverage of 40% will result in only a 10–11% decrease in each. Reaching 80% vaccine coverage by August would prevent twice as many severe/critical disease cases and deaths than if it were reached by December. Easing restrictions over a longer duration resulted in more favorable vaccination impact. In conclusion, for vaccination to have impact in the short-term, scale-up has to be rapid and reach high coverage (at least 70%), while sustaining social distancing measures during roll-out. At current vaccination pace, this is unlikely to be achieved. Concerted efforts need to be made to overcome local challenges and substantially scale up vaccination to avoid a surge that the country, with its multiple crises and limited health-care capacity, is largely unprepared for. [ABSTRACT FROM AUTHOR]

Despite collaborative efforts from all countries, coronavirus disease 2019 (COVID-19) pandemic has been continuing to spread globally, forcing the world into social distancing period, making a special challenge for public healthcare system. Before vaccine widely available, the best approach to manage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is to achieve highest diagnostic accuracy by improving biosensor efficacy. For SARS-CoV-2 diagnostics, intensive attempts have been made by many scientists to ameliorate the drawback of current biosensors of SARS-CoV-2 in clinical diagnosis to offer benefits related to platform proposal, systematic analytical methods, system combination, and miniaturization. This review assesses ongoing research efforts aimed at developing integrated diagnostic tools to detect RNA viruses and their biomarkers for clinical diagnostics of SARS-CoV-2 infection and further highlights promising technology for SARS-CoV-2 specific diagnosis. The comparisons of SARS-CoV-2 biomarkers as well as their applicable biosensors in the field of clinical diagnosis were summarized to give scientists an advantage to develop superior diagnostic platforms. Furthermore, this review describes the prospects for this rapidly growing field of diagnostic research, raising further interest in analytical technology and strategic plan for future pandemics. [ABSTRACT FROM AUTHOR]

The service industry provides distributive services, producer services, personal services, and social services. These services largely breakdowns due to restrictions on border movements, confined travel and transportation services, a decline in international tourists' visitation, nationwide lockdowns, and maintaining social distancing in the population. Although these measures are highly needed to contain coronavirus, it decreases economic and financial activities in a country, which requires smart solutions to globally subsidize the services sector. The study used different COVID-19 measures, and its resulting impact on the services industry by using world aggregated data from 1975 through 2020. The study benefited from the Keynesian theory of aggregate demand that remains provided a solution to minimize economic shocks through stringent or liberalizing economic policies. The COVID-19 pandemic is more severe than the financial shocks of 2018 that affected almost all sectors of the globalized world, particularly the services sector, which has been severally affected by COVID-19; it is a high time to revisit economic policies to control pandemic recession. The study used quantiles regression and innovation accounting matrix to obtain ex-ante and ex-post analysis. The quantile regression estimates show that causes of death by communicable diseases, including COVID-19, mainly decline the share of services value added to the global GDP at different quantiles distribution. In contrast, word-of-mouth helps to prevent it from the transmission channel of coronavirus plague through information sharing among the general masses. The control of food prices and managing physical distancing reduces suspected coronavirus cases; however, it negatively affects the services sector's value share. The smart lockdown and sound economic activities do not decrease coronavirus cases, while they support increasing the percentage of the services sector to the global GDP. The innovation accounting matrix suggested that smart lockdown, managing physical distancing, effective price control, and sound financial activities will help to reduce coronavirus cases that will further translate into increased services value-added for the next ten years. The social distancing will exert a more considerable variance error shock to the services industry, which indicates the viability of these measures to contained novel coronavirus over a time horizon. The study used the number of proxies to the COVID-19 measures on the service sector that can be continued with real-time variables to obtain more inferences. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) is a novel disease pandemic that emerged in late 2019 in China, and later spread to other parts of the world, including Nigeria. This review analyzes the preparedness of Nigeria to the COVID-19 pandemic and recommends strategies that could be useful in controlling the disease. Published articles on COVID-19 worldwide, socioeconomic and disease status and preparedness to COVID-19 in Africa and Nigeria, were retrieved from databases such as Pubmed, MEDLINE, Scopus, Web of Knowledge and Google search engine. Nigeria is the most populous black nation in the world, and is one of the largest crude oil producers in the world. However, its healthcare system is dilapidated and weak, due to years of neglect and widespread corruption. As a result, Nigeria is vulnerable to COVID-19, as evidenced by the current geographical distribution of the disease in its population. Many socioeconomic factors could potentially facilitate the spread of COVID-19 in Nigeria. This could lead to a high caseload in the country, which could overwhelm the health care system. The application of social distancing, personal hygiene, especially hand hygiene and mask-wearing, as practiced in many countries, has proven to be effective to reduce the spread of COVID-19. In Nigeria, social distancing, in many instances, may be impracticable, given its large population, and a high density of people living in crowded conditions like slums and camps. Moreover, there is a sizeable population of internally displaced people, due to the attack by Boko Haram fighters in Northern Nigeria, and herdsmen in Southern Nigeria. The implementation of these measures is likely to be a great challenge. Nigeria has announced a complete lockdown for the containment of COVD-19, but its implementation and efficacy are doubtful, due to the same reasons previously mentioned. [ABSTRACT FROM AUTHOR]

The onset of the novel coronavirus SARS-CoV2 has changed many aspects of people's economic and social activities. For many airlines, social distancing has reduced airplane capacity by one third as a result of keeping the middle seats empty. Additionally, social distancing between passengers traversing the aisle slows the boarding process. Recent literature has suggested that the reverse pyramid boarding method provides favorable values for boarding time and passenger health metrics when compared to other boarding methods with social distancing. Assuming reverse pyramid boarding with the middle seats unoccupied, we determined the number of passengers to include in each of three boarding groups. We assumed that passengers use a jet-bridge that connects the airport terminal to the airplane's front door. We used agent-based modeling and a stochastic simulation to evaluate solutions. A full grid search found an initial good solution, and then local search optimization determined the best solution based upon the airline's relative preference for minimizing average boarding time and minimizing risks to previously seated passengers from later-boarding, potentially contagious passengers breathing near them. The resulting solution contained the number of passengers to place into each of the three boarding groups. If an airline is most concerned about the health risk to seated passengers from later boarding passengers walking near them, the best three-group reverse pyramid method adapted for social distancing will first board passengers with window seats in the rear half of the airplane, then will board passengers with window seats in the front half of the airplane and those with aisle seats in the rear half of the airplane, and finally will board the passengers with aisle seats in the front half of the airplane. The resulting solution takes about 2% longer to board than the three-group solution that minimizes boarding time while providing a 25% decrease in health risk to aisle seat passengers from later boarding passengers. [ABSTRACT FROM AUTHOR]

The unwavering spread of COVID-19 has taken the world by storm. Preventive measures like social distancing and mask usage have been taken all around the globe but still, as of September 2020, the number of cases continues to rise in many countries. Evidently, these measures are insufficient. Although decreases in population density and surges in the public's usage of personal protective equipment can mitigate direct transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), indirect transmission of the virus is still probable. By summarizing the current state of knowledge on the stability of coronaviruses on dry materials, this review uncovers the high potential for SARS-CoV-2 transmission through contaminated surfaces (i.e., fomites) and prompts future research. Fully contextualized data on coronavirus persistence are presented. The methods and limitations to testing the stability of coronaviruses are explored, and the SARS-CoV-2 representativeness of different coronaviruses is analyzed. The factors which dictate the persistence of coronaviruses on surfaces (media, environmental conditions, and material-type) are investigated, and the review is concluded by encouraging material innovation to combat the current pandemic. To summarize, SARS-CoV-2 remains viable on the timescale of days on hard surfaces under ambient indoor conditions. Similarly, the virus is stable on human skin, signifying the necessity of hand hygiene amidst the current pandemic. There is an inverse relationship between SARS-CoV-2 surface persistence and temperature/humidity, and the virus is well suited to air-conditioned environments (room temperature, ~ 40% relative humidity). Sunlight may rapidly inactivate the virus, suggesting that indirect transmission predominantly occurs indoors. The development of antiviral materials and surface coatings would be an extremely effective method to mitigate the spread of COVID-19. To obtain applicable data on the persistence of coronaviruses and the efficiency of virucidal materials, future researchers should understand the common experimental limitations outlined in this review and plan their studies accordingly. [ABSTRACT FROM AUTHOR]

Simple Summary: There is a large variety of data available about the coronavirus pandemic, but we still lack data about some important factors. Who is likely to infect whom and under what conditions and how long after becoming infected? These factors are the essence of transmission dynamics. Two groups using identical complex models can be expected to make different predictions simply because they make different choices for such transmission parameters in the model. A policy setter has no way to choose between their predictions. Simple models are not good for assessing contact tracing and detecting asymptomatic carriers, and do not replace agent-based models. However, we explain how simple models can be used to answer complex questions by adding what we call satellite equations, addressing questions involving age groups, death rates, and likelihood of transmission to nursing homes and to uninfected, isolated populations. Simple models are ideal for showing policy setters who are not mathematically sophisticated the kinds of interventions that are needed to achieve public goals. As the coronavirus pandemic spreads across the globe, people are debating policies to mitigate its severity. Many complex, highly detailed models have been developed to help policy setters make better decisions. However, the basis of these models is unlikely to be understood by non-experts. We describe the advantages of simple models for COVID-19. We say a model is "simple" if its only parameter is the rate of contact between people in the population. This contact rate can vary over time, depending on choices by policy setters. Such models can be understood by a broad audience, and thus can be helpful in explaining the policy decisions to the public. They can be used to evaluate the outcomes of different policies. However, simple models have a disadvantage when dealing with inhomogeneous populations. To augment the power of a simple model to evaluate complicated situations, we add what we call "satellite" equations that do not change the original model. For example, with the help of a satellite equation, one could know what his/her chance is of remaining uninfected through the end of an epidemic. Satellite equations can model the effects of the epidemic on high-risk individuals, death rates, and nursing homes and other isolated populations. To compare simple models with complex models, we introduce our "slightly complex" Model J. We find the conclusions of simple and complex models can be quite similar. However, for each added complexity, a modeler may have to choose additional parameter values describing who will infect whom under what conditions, choices for which there is often little rationale but that can have big impacts on predictions. Our simulations suggest that the added complexity offers little predictive advantage. [ABSTRACT FROM AUTHOR]

The rapid spread of the novel coronavirus disease, COVID-19, and its resulting situation has garnered much effort to contain the virus through scientific research. The tragedy has not yet fully run its course, but it is already clear that the crisis is thoroughly global, and science is at the forefront in the fight against the virus. This includes medical professionals trying to cure the sick at risk to their own health; public health management tracking the virus and guardedly calling on such measures as social distancing to curb its spread; and researchers now engaged in the development of diagnostics, monitoring methods, treatments and vaccines. Recent advances in non-contact sensing to improve health care is the motivation of this study in order to contribute to the containment of the COVID-19 outbreak. The objective of this study is to articulate an innovative solution for early diagnosis of COVID-19 symptoms such as abnormal breathing rate, coughing and other vital health problems. To obtain an effective and feasible solution from existing platforms, this study identifies the existing methods used for human activity and health monitoring in a non-contact manner. This systematic review presents the data collection technology, data preprocessing, data preparation, features extraction, classification algorithms and performance achieved by the various non-contact sensing platforms. This study proposes a non-contact sensing platform for the early diagnosis of COVID-19 symptoms and monitoring of the human activities and health during the isolation or quarantine period. Finally, we highlight challenges in developing non-contact sensing platforms to effectively control the COVID-19 situation. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease (COVID-19) poses a severe threat to public health officials all around the world. The early COVID-19 outbreak in South Korea displayed significant spatial heterogeneity. The number of confirmed cases increased rapidly in the Daegu and Gyeongbuk (epicenter), whereas the spread was much slower in the rest of Korea. A two-patch mathematical model with a mobility matrix is developed to capture this significant spatial heterogeneity of COVID-19 outbreaks from 18 February to 24 March 2020. The mobility matrix is taken from the movement data provided by the Korea Transport Institute (KOTI). Some of the essential patch-specific parameters are estimated through cumulative confirmed cases, including the transmission rates and the basic reproduction numbers (local and global). Our simulations show that travel restrictions between the epicenter and the rest of Korea effectively prevented massive outbreaks in the rest of Korea. Furthermore, we explore the effectiveness of several additional strategies for the mitigation and suppression of Covid-19 spread in Korea, such as implementing social distancing and early diagnostic interventions. [ABSTRACT FROM AUTHOR]

Dental fear and anxiety is a significant issue that affects pediatric patients and creates challenges in oral health management. Considering that the coronavirus disease 2019 (COVID-19) pandemic, along with its associated sanitary regime, social distancing measures and nationwide quarantines, could itself induce public fears, including in children, it is of great interest to explore whether this situation and the necessity of reorganizing dental care could potentially affect the emotional state of pediatric patients facing a need for urgent dental intervention. The present study assessed the emotional state of children ≤ seven years old (n = 25) requiring dental healthcare during a nationwide quarantine in Poland, as well as the anxiety levels of their caregivers. The Faces Anxiety Scale was adopted, and the evaluation was independently performed by the dentist, caregivers and children themselves. The level of anxiety in caregivers was also measured. As demonstrated, children requiring dental intervention during the nationwide quarantine did not reveal a significantly higher anxiety level as compared to the age- and indication-matched pre-pandemic control group (n = 20), regardless of whether their emotional state was evaluated by the dentist, caregivers, or by themselves. However, the share of children scoring the lowest anxiety level in all assessments was smaller in the pandemic group. Boys in the pandemic group had a higher anxiety level, as indicated by a caregiver assessment, and displayed a negative correlation with age in all three types of evaluation. Moreover, caregiver anxiety levels were higher in the pandemic group as compared to the pre-pandemic subset and revealed stronger correlations with the dental anxiety in children. The results suggest that the reorganization of oral healthcare under the pandemic scenario did not have a profound effect on children's dental anxiety. Nevertheless, findings in young boys highlight that they may be more vulnerable and require special care to mitigate their anxiety and decrease the risk of dentophobia in the future—these observations must be, however, treated with caution due to the small sample size and require further confirmation. Moreover, it is important to reassure caregivers of the safety of the dental visit during the pandemic to minimize the effect of their own anxiety on dental fears in children. [ABSTRACT FROM AUTHOR]

Since the World Health Organization declared the novel coronavirus outbreak a global health emergency, Italy's lockdown was declared on 9 March 2020. Elective orthopedic surgery was forced to stop to allow the healthcare system to face the emergency. However, many orthopedic oncology cases could not be postponed. The aim of this study was to report the experience in managing sarcoma patients and the reorganization of a cancer center in an attempt to maintain it free from COVID-19. A Coronavirus Crisis Unit was established by the health directorate coordination in order to adopt specific procedures. General rules of screening and social distancing were applied in different health settings (entrance check point, hospital inward, outpatient clinic, operative room). Regarding oncologic orthopedics, priority was given to bone and soft tissue sarcomas, metastases and aggressive benign tumors at risk of impending or pathologic fracture. Precise indications were followed to manage first outpatient visits, patients undergoing surgery and follow-up. Meticulous adherence to rules among patients and personnel and collaboration between leadership and medical staff in order to continue to perform multidisciplinary treatment protocols, maintain the availability of infrastructural spaces and source protective equipment, swabs and screening samples have been successful in the aim towards a safe cure for cancer patients. [ABSTRACT FROM AUTHOR]