Due to the outbreak of the deadly coronavirus disease in 2019 (COVID-19), Wuhan was on lockdown for more than 60 days by the state government. This study investigated the perceptions and attitudes of the public on quarantine as a practical approach to halting the spread of COVID-19. An online survey was conducted via WeChat between 10 January 2020 and 10 March 2020 on the general population in Hubei province at the height of the COVID-19 outbreak. In total, 549 respondents participated in the survey. Results revealed that the public displayed significantly strong support towards quarantine throughout the outbreak period, apart from locking people up and using imprisonment legal sanctions against those who failed to comply with the stringent regulations. The support exerted by the public stemmed from the execution of authorised officers to protect the public interest and provision of psychosocial support for those affected. In situations where quarantine could not be imposed, public health policy-makers and government officials should implement an extensive system of psychosocial support to safeguard, instruct and inform frontline public health workers. The public should also be enlisted in an open conversation concerning the ethical utility of restrictive values during the COVID-19 outbreak.

Several studies have reported evidence of interference between respiratory viruses: respiratory viruses rarely reach their epidemic peak concurrently and there appears to be a negative association between infection with one respiratory virus and co-infection with another. We used results spanning 16 years (2002–2017) of a routine diagnostic multiplex panel that tests for nine respiratory viruses to further investigate these interactions in Victoria, Australia. Time series analyses were used to plot the proportion positive for each virus. The seasonality of all viruses included was compared with respiratory syncytial virus (RSV) and influenza A virus using cross-correlations. Logistic regression was used to explore the likelihood of co-infection with one virus given infection with another. Seasonal peaks were observed each year for influenza A and RSV and less frequently for influenza B, coronavirus and parainfluenza virus. RSV circulated an average of 6 weeks before influenza A. Co-infection with another respiratory virus was less common with picornavirus, RSV or influenza A infection. Our findings provide further evidence of a temporal relationship in the circulation of respiratory viruses. A greater understanding of the interaction between respiratory viruses may enable better prediction of the timing and magnitude of respiratory virus epidemics.

The main objective of this paper is to address the following question: are the containment measures imposed by most of the world governments effective and sufficient to stop the epidemic of COVID-19 beyond the lock-down period? In this paper, we propose a mathematical model which allows us to investigate and analyse this problem. We show by means of the reproductive number, ${\cal R}_0$ that the containment measures appear to have slowed the growth of the outbreak. Nevertheless, these measures remain only effective as long as a very large fraction of population, p, greater than the critical value $1-1/{\cal R}_0$ remains confined. Using French current data, we give some simulation experiments with five scenarios including: (i) the validation of model with p estimated to 93%, (ii) the study of the effectiveness of containment measures, (iii) the study of the effectiveness of the large-scale testing, (iv) the study of the social distancing and wearing masks measures and (v) the study taking into account the combination of the large-scale test of detection of infected individuals and the social distancing with linear progressive easing of restrictions. The latter scenario was shown to be effective at overcoming the outbreak if the transmission rate decreases to 75% and the number of tests of detection is multiplied by three. We also noticed that if the measures studied in our five scenarios are taken separately then the second wave might occur at least as far as the parameter values remain unchanged.

Nearly 1 year into the coronavirus disease 2019 pandemic, the first severe acute respiratory syndrome coronavirus 2 vaccines received emergency use authorisation and vaccination campaigns began. A number of factors can reduce the averted burden of cases and deaths due to vaccination. Here, we use a dynamic model, parametrised with Bayesian inference methods, to assess the effects of non-pharmaceutical interventions (NPIs) (such as social distancing, mask mandates, school and workplace closure), and vaccine administration and uptake rates on infections and deaths averted in the United States. We show that scenarios depicting higher compliance with NPIs avert more than 60% of infections and 70% of deaths during the period of vaccine administration, and that increasing the vaccination rate from 5 to 11 million people per week could increase the averted burden by more than one-third. These findings underscore the importance of maintaining NPIs and increasing vaccine administration rates.

This study presents the main motivation to investigate the COVID-19 pandemic, a major threat to the whole world from the day when it first emerged in China city of Wuhan. Predictions on the number of cases of COVID-19 are crucial in order to prevent and control the outbreak. In this research study, an artificial neural network with rectifying linear unit-based technique is implemented to predict the number of deaths, recovered and confirmed cases of COVID-19 in Pakistan by using previous data of 137 days of COVID-19 cases from the day 25 February 2020 when the first two cases were confirmed, until 10 July 2020. The collected data were divided into training and test data which were used to test the efficiency of the proposed technique. Furthermore, future predictions have been made by the proposed technique for the next 7 days while training the model on whole available data.

The coronavirus disease (COVID-19), while mild in most cases, has nevertheless caused significant mortality. The measures adopted in most countries to contain it have led to colossal social and economic disruptions, which will impact the medium- and long-term health outcomes for many communities. In this paper, we deliberate on the reality and facts surrounding the disease. For comparison, we present data from past pandemics, some of which claimed more lives than COVID-19. Mortality data on road traffic crashes and other non-communicable diseases, which cause more deaths each year than COVID-19 has so far, is also provided. The indirect, serious health and social effects are briefly discussed. We also deliberate on how misinformation, confusion stemming from contrasting expert statements, and lack of international coordination may have influenced the public perception of the illness and increased fear and uncertainty. With pandemics and similar problems likely to re-occur, we call for evidence-based decisions, the restoration of responsible journalism and communication built on a solid scientific foundation.

Effectiveness of corona virus disease-19 (COVID-19) vaccines used in India is unexplored and need to be substantiated. The present case-control study was planned to elicit the effectiveness of COVID-19 vaccines in preventing infection and disease severity in the general population of Bihar, India. This case-control study was conducted among people aged ≥45 years during April to June 2021. The cases were the COVID-19 patients admitted or visited All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India, and were contacted directly. The controls were the individuals tested negative for severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) at the Virology laboratory, AIIMS-Patna and contacted telephonically for collection of relevant information. The vaccine effectiveness (VE) was calculated by using the formula (VE = 1 – odds ratio). The adjusted VE for partial and full vaccination were estimated to be 52.0% (95% confidence interval (CI) 39.0–63.0%) and 83.0% (95% CI 73.0–89.0%) respectively for preventing SARS CoV-2 infection. The sub-group analyses of the cases have shown that the length of hospital stays (LOS) (partially vaccinated: 9 days vs. unvaccinated: 12 days; P = 0.028) and the severity of the disease (fully vaccinated: 30.3% vs. partially vaccinated: 51.3% and unvaccinated: 54.1%; P = 0.035) were significantly low among vaccinated compared to unvaccinated individuals. To conclude, four out of every five fully vaccinated individuals are estimated to be protected from contracting SARS CoV-2 infection. Vaccination lowered LOS and chances of development of severe disease.

Vaccine hesitancy remains a serious global threat to achieve herd immunity, and this study aimed to assess the magnitude and associated factors of coronavirus disease-19 (COVID-19) vaccine hesitancy among healthcare workers (HCWs) in Amhara regional referral hospitals. A web-based anonymised survey was conducted among 440 HCWs in the Amhara region referral hospitals. The questionnaire was designed using Google Forms and distributed using telegram and e-mail from 15 May to 10 June 2021 to the randomly selected participants in each hospital. The data were analysed with Stata 14.0 and described using frequency tables. A multivariable binary logistic regression model was fitted and model fitness was checked with the Hosmer–Lemeshow goodness of fit test. Out of 440 participants, 418 were willing to participate in the study and the mean age was about 30 years. Overall, 45.9% (n = 192) of participants reported vaccine hesitancy. After applying multivariate analysis, age ≤25 years (adjusted odds ratio (aOR) = 5.6); do not wear a mask (aOR = 2.4); not compliance with physical distancing (aOR = 3.6); unclear information by public health authorities (aOR = 2.5); low risk of getting COVID-19 infection (aOR = 2.8); and not sure about the tolerability of the vaccine (aOR = 3.76) were associated with COVID-19 vaccine hesitancy. A considerable proportion of HCWs were hesitant towards COVID-19 vaccine, and this can be tackled with the provision of clear information about the vaccine.

Data on the possibility of transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) during the provision of chronic haemodialysis, which often entails many person-to-person contacts, are lacking. We report a follow-up of the in-centre contacts of three positive chronic haemodialysis patients. Under strict preventive measures, only one patient out of 21 patient-contacts and 29 personnel-contacts tested positive within 2 weeks after the last contact. This patient, case #3, most likely became infected during unprotected, organised group transportation to the dialysis centre.

The pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has emerged as a serious global public health issue. Since the start of the outbreak, the importance of hand-hygiene and respiratory protection to prevent the spread of the virus has been the prime focus for infection control. Health regulatory organisations have produced guidelines for the formulation of hand sanitisers to the manufacturing industries. This review summarises the studies on alcohol-based hand sanitisers and their disinfectant activity against SARS-CoV-2 and related viruses. The literature shows that the type and concentration of alcohol, formulation and nature of product, presence of excipients, applied volume, contact time and viral contamination load are critical factors that determine the effectiveness of hand sanitisers.

We conducted a retrospective observational study in patients with laboratory-confirmed coronavirus disease (COVID-19) who received medical care in 688 COVID-19 ambulatory units and hospitals in Mexico City between 24 February 2020 and 24 December 2020, to study if the elderly seek medical care later than younger patients and their severity of symptoms at initial medical evaluation. Patients were categorised into eight groups (<20, 20–29, 30–39, 40–49, 50–59, 60–69, 70–79 and ≥80 years). Symptoms at initial evaluation were classified according to a previously validated classification into respiratory and non-respiratory symptoms. Comparisons between time from symptom onset to medical care for every age category were performed through variance analyses. Logistic regression models were applied to determine the risk of presenting symptoms of severity according to age, and mortality risk according to delays in medical care. In total, 286 020 patients were included (mean age: 42.8, s.d.: 16.8 years; 50.4% were women). Mean time from symptom onset to medical care was 4.04 (s.d.: 3.6) days and increased with older age categories (P < 0.0001). Mortality risk increased by 6.4% for each day of delay in medical care from symptom onset. The risk of presenting with the symptoms of severity was greater with increasing age categories. In conclusion, COVID-19 patients with increasing ages tend to seek medical care later, with higher rates of symptoms of severity at initial presentation in both ambulatory units and hospitals.

We used social network analysis (SNA) to study the novel coronavirus (COVID-19) outbreak in Karnataka, India, and to assess the potential of SNA as a tool for outbreak monitoring and control. We analysed contact tracing data of 1147 COVID-19 positive cases (mean age 34.91 years, 61.99% aged 11–40, 742 males), anonymised and made public by the Karnataka government. Software tools, Cytoscape and Gephi, were used to create SNA graphics and determine network attributes of nodes (cases) and edges (directed links from source to target patients). Outdegree was 1–47 for 199 (17.35%) nodes, and betweenness, 0.5–87 for 89 (7.76%) nodes. Men had higher mean outdegree and women, higher mean betweenness. Delhi was the exogenous source of 17.44% cases. Bangalore city had the highest caseload in the state (229, 20%), but comparatively low cluster formation. Thirty-four (2.96%) ‘super-spreaders’ (outdegree ⩾ 5) caused 60% of the transmissions. Real-time social network visualisation can allow healthcare administrators to flag evolving hotspots and pinpoint key actors in transmission. Prioritising these areas and individuals for rigorous containment could help minimise resource outlay and potentially achieve a significant reduction in COVID-19 transmission.

It has been speculated that some drugs can be used against SARS-CoV-2. As for antiretrovirals, the follow-up of pre-exposure prophylaxis (PrEP) users during the coronavirus disease 2019 (COVID-19) outbreak may help to understand the potential protective effect of PrEP against SARS-CoV-2. We aimed to identify associations between oral PrEP use and COVID-19-related symptoms self-reporting. Phone call interviews or digital investigation (through WhatsApp® or e-mail) about oral PrEP regular use, social distancing, exposure to suspected or confirmed cases of SARS-CoV-2 infection and COVID-19-related symptoms. Among 108 individuals, the majority were cisgender, white and gay men. Although most of the individuals engaged in social distancing (68.52%), they kept on taking PrEP (75.93%). Few people have had contact with suspected or confirmed cases of COVID-19 (12.04%), but some had COVID-19-related symptoms the month before the interview (27.78%) including rhinorrheoa (56.67%), cough (53.33%), asthaenia (50.00%) and headache (43.33%). Also, oral PrEP was associated with lower self-reporting COVID-19-symptoms (OR 0.26, 95% CI 0.07–0.96, P = 0.04; h = 0.92) even after controlling confounders as social distancing, age, body-mass index and morbidities . In our sample, the regular use of oral PrEP was associated with lower self-reporting of COVID-19-related symptoms during the outbreak in São Paulo, Brazil.

In Spain, the epidemic curve caused by COVID-19 has reached its peak in the last days of March. The implementation of the blockade derived from the declaration of the state of alarm on 14th March has raised a discussion on how and when to deal with the unblocking. In this paper, we intend to add information that may help by using epidemic simulation techniques with stochastic individual contact models and several extensions.

School lockdowns have been widely used to control the COVID-19 pandemic. However, these lockdowns may have a significant negative impact on the lives of young people. In this study, we have evaluated the impact of closing lower secondary schools for COVID-19 incidence in 13–15-year-olds in Finland, in a situation where restrictions and recommendation of social distancing were implemented uniformly in the entire country. COVID-19 case numbers were obtained from the National Infectious Disease Registry (NIDR) of the Finnish Institute for Health and Welfare, in which clinical microbiology laboratories report all positive SARS-CoV-2 tests with unique identifiers in a timely manner. The NIDR is linked to population data registry, enabling calculation of incidences. We estimated the differences in trends between areas with both restaurant and lower secondary school closures and areas with only restaurant closures in different age groups by using joinpoint regression. We also estimated the differences in trends between age groups. Based on our analysis, closing lower secondary schools had no impact on COVID-19 incidence among 13–15-year-olds. No significant changes on COVID-19 incidence were observed in other age groups either.

Poultry contact is a risk factor for zoonotic transmission of non-typhoidal Salmonella spp. Salmonella illness outbreaks in the United States are identified by PulseNet, the national laboratory network for enteric disease surveillance. During 2020, PulseNet observed a 25% decline in the number of Salmonella clinical isolates uploaded by state and local health departments. However, 1722 outbreak-associated Salmonella illnesses resulting from 12 Salmonella serotypes were linked to contact with privately owned poultry, an increase from all previous years. This report highlights the need for continued efforts to prevent backyard poultry-associated outbreaks of Salmonella as ownership increases in the United States.

Six coronaviruses isolated in the U.S.A. have been inoculated into volunteers and all produced colds. Between 10 and 20 % of infected volunteers developed heterologous antibody responses after these and other experimental infections with coronaviruses. The haemagglutination-inhibition test with the OC43 virus strain was found to detect antibody rises after infection with a variety of strains.

Studies on normal adult sera taken between 1965 and 1970 revealed a high frequency of neutralizing antibody to one strain (229E) and a frequency of HI antibody to strain OC43 which fluctuated from year to year. Complement-fixing antibodies to these two viruses were also found, revealing an apparent increase in the activity of coronaviruses in the general population of the U.K., during the winter of 1968–9.

Forecasting the epidemics of the diseases is very valuable in planning and supplying resources effectively. This study aims to estimate the epidemiological trends of the coronavirus disease 2019 (COVID-19) prevalence and mortality using the advanced α-Sutte Indicator, and its prediction accuracy level was compared with the most frequently adopted autoregressive integrated moving average (ARIMA) method. Time-series analysis was performed based on the total confirmed cases and deaths of COVID-19 in the world, Brazil, Peru, Canada and Chile between 27 February 2020 and 30 June 2020. By comparing the prediction reliability indices, including the root mean square error, mean absolute error, mean error rate, mean absolute percentage error and root mean square percentage error, the α-Sutte Indicator was found to produce lower forecasting error rates than the ARIMA model in all data apart from the prevalence testing set globally. The α-Sutte Indicator can be recommended as a useful tool to nowcast and forecast the COVID-19 prevalence and mortality of these regions except for the prevalence around the globe in the near future, which will help policymakers to plan and prepare health resources effectively. Also, the findings of our study may have managerial implications for the outbreak in other countries.

The SARS-CoV-2 virus is rapidly evolving via mutagenesis, lengthening the pandemic, and threatening the public health. Until August 2021, 12 variants of SARS-CoV-2 named as variants of concern (VOC; Alpha to Delta) or variants of interest (VOI; Epsilon to Mu), with significant impact on transmissibility, morbidity, possible reinfection and mortality, have been identified. The VOC Delta (B.1.617.2) of Indian origin is now the dominant and the most contagious variant worldwide as it provokes a strong binding to the human ACE2 receptor, increases transmissibility and manifests considerable immune escape strategies after natural infection or vaccination. Although the development and administration of SARS-CoV-2 vaccines, based on different technologies (mRNA, adenovirus carrier, recombinant protein, etc.), are very promising for the control of the pandemic, their effectiveness and neutralizing activity against VOCs varies significantly. In this review, we describe the most significant circulating variants of SARS-CoV-2, and the known effectiveness of currently available vaccines against them.

The effectiveness of screening travellers during times of international disease outbreak is contentious, especially as the reduction in the risk of disease importation can be very small. Border screening typically consists of travellers being thermally scanned for signs of fever and/or completing a survey declaring any possible symptoms prior to admission to their destination country; while more thorough testing typically exists, these would generally prove more disruptive to deploy. In this paper, we describe a simple Monte Carlo based model that incorporates the epidemiology of coronavirus disease-2019 (COVID-19) to investigate the potential decrease in risk of disease importation that might be achieved by requiring travellers to undergo screening upon arrival during the current pandemic. This is a purely theoretical study to investigate the maximum impact that might be attained by deploying a test or testing programme simply at the point of entry, through which we may assess such action in the real world as a method of decreasing the risk of importation. We, therefore, assume ideal conditions such as 100% compliance among travellers and the use of a ‘perfect’ test. In addition to COVID-19, we also apply the presented model to simulated outbreaks of influenza, severe acute respiratory syndrome (SARS) and Ebola for comparison. Our model only considers screening implemented at airports, being the predominant method of international travel. Primary results showed that in the best-case scenario, screening at the point of entry may detect a maximum of 8.8% of travellers infected with COVID-19, compared to 34.8.%, 9.7% and 3.0% for travellers infected with influenza, SARS and Ebola respectively. While results appear to indicate that screening is more effective at preventing disease ingress when the disease in question has a shorter average incubation period, our results suggest that screening at the point of entry alone does not represent a sufficient method to adequately protect a nation from the importation of COVID-19 cases.