This study describes the development of a pilot sentinel school absence syndromic surveillance system. Using data from a sample of schools in England the capability of this system to monitor the impact of disease on school absences in school-aged children is shown, using the coronavirus disease 2019 (COVID-19) pandemic period as an example. Data were obtained from an online app service used by schools and parents to report their children absent, including reasons/symptoms relating to absence. For 2019 and 2020, data were aggregated into daily counts of ‘total’ and ‘cough’ absence reports. There was a large increase in the number of absence reports in March 2020 compared to March 2019, corresponding to the first wave of the COVID-19 pandemic in England. Absence numbers then fell rapidly and remained low from late March 2020 until August 2020, while lockdown was in place in England. Compared to 2019, there was a large increase in the number of absence reports in September 2020 when schools re-opened in England, although the peak number of absences was smaller than in March 2020. This information can help provide context around the absence levels in schools associated with COVID-19. Also, the system has the potential for further development to monitor the impact of other conditions on school absence, e.g. gastrointestinal infections.

Estimating the coronavirus disease-2019 (COVID-19) infection fatality rate (IFR) has proven to be particularly challenging –and rather controversial– due to the fact that both the data on deaths and the data on the number of individuals infected are subject to many different biases. We consider a Bayesian evidence synthesis approach which, while simple enough for researchers to understand and use, accounts for many important sources of uncertainty inherent in both the seroprevalence and mortality data. With the understanding that the results of one's evidence synthesis analysis may be largely driven by which studies are included and which are excluded, we conduct two separate parallel analyses based on two lists of eligible studies obtained from two different research teams. The results from both analyses are rather similar. With the first analysis, we estimate the COVID-19 IFR to be 0.31% [95% credible interval (CrI) of (0.16%, 0.53%)] for a typical community-dwelling population where 9% of the population is aged over 65 years and where the gross-domestic-product at purchasing-power-parity (GDP at PPP) per capita is $17.8k (the approximate worldwide average). With the second analysis, we obtain 0.32% [95% CrI of (0.19%, 0.47%)]. Our results suggest that, as one might expect, lower IFRs are associated with younger populations (and may also be associated with wealthier populations). For a typical community-dwelling population with the age and wealth of the United States we obtain IFR estimates of 0.43% and 0.41%; and with the age and wealth of the European Union, we obtain IFR estimates of 0.67% and 0.51%.

The World Health Organization African region recorded its first laboratory-confirmed coronavirus disease-2019 (COVID-19) cases on 25 February 2020. Two months later, all the 47 countries of the region were affected. The first anniversary of the pandemic occurred in a changed context with the emergence of new variants of concern (VOC) and growing COVID-19 fatigue. This study describes the epidemiological trajectory of COVID-19 in the region, summarises public health and social measures (PHSM) implemented and discusses their impact on the pandemic trajectory. As of 24 February 2021, the African region accounted for 2.5% of cases and 2.9% of deaths reported globally. Of the 13 countries that submitted detailed line listing of cases, the proportion of cases with at least one co-morbid condition was estimated at 3.3% of all cases. Hypertension, diabetes and human immunodeficiency virus (HIV) infection were the most common comorbid conditions, accounting for 11.1%, 7.1% and 5.0% of cases with comorbidities, respectively. Overall, the case fatality ratio (CFR) in patients with comorbid conditions was higher than in patients without comorbid conditions: 5.5% vs. 1.0% (P < 0.0001). Countries started to implement lockdown measures in early March 2020. This contributed to slow the spread of the pandemic at the early stage while the gradual ease of lockdowns from 20 April 2020 resulted in an upsurge. The second wave of the pandemic, which started in November 2020, coincided with the emergence of the new variants of concern. Only 0.08% of the population from six countries received at least one dose of the COVID-19 vaccine. It is critical to not only learn from the past 12 months to improve the effectiveness of the current response but also to start preparing the health systems for subsequent waves of the current pandemic and future pandemics.

As of 03 January 2021, the WHO African region is the least affected by the coronavirus disease-2019 (COVID-19) pandemic, accounting for only 2.4% of cases and deaths reported globally. However, concerns abound about whether the number of cases and deaths reported from the region reflect the true burden of the disease and how the monitoring of the pandemic trajectory can inform response measures.

We retrospectively estimated four key epidemiological parameters (the total number of cases, the number of missed cases, the detection rate and the cumulative incidence) using the COVID-19 prevalence calculator tool developed by Resolve to Save Lives. We used cumulative cases and deaths reported during the period 25 February to 31 December 2020 for each WHO Member State in the region as well as population data to estimate the four parameters of interest. The estimated number of confirmed cases in 42 countries out of 47 of the WHO African region included in this study was 13 947 631 [95% confidence interval (CI): 13 334 620–14 635 502] against 1 889 512 cases reported, representing 13.5% of overall detection rate (range: 4.2% in Chad, 43.9% in Guinea). The cumulative incidence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was estimated at 1.38% (95% CI: 1.31%–1.44%), with South Africa the highest [14.5% (95% CI: 13.9%–15.2%)] and Mauritius [0.1% (95% CI: 0.099%–0.11%)] the lowest. The low detection rate found in most countries of the WHO African region suggests the need to strengthen SARS-CoV-2 testing capacities and adjusting testing strategies.

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.

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.

Coronavirus disease 2019 (COVID-19) is a serious respiratory disease mediated by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The worldwide spread of COVID-19 has caused millions of confirmed cases and morbidity, and the crisis has greatly affected global economy and daily life and changed our attitudes towards life. The reproductive system, as a potential target, is at a high risk of SARS-CoV-2 infection, and females are more vulnerable to viral infection compared with males. Therefore, female fertility and associated reproductive health care in the COVID-19 era need more attention. This review summarises the mechanism of SARS-CoV-2 infection in the female reproductive system and discusses the impact of the COVID-19 crisis on female fertility. Studies have proven that COVID-19 might affect female fertility and interfere with assisted reproductive technology procedures. The side effects of vaccines against the virus on ovarian reserve and pregnancy have not yet been well investigated. In the future, the female fertility after SARS-CoV-2 infection and vaccination needs more attention because of the uncertainty of COVID-19.

This study was endeavoured to contribute in furthering our understanding of the molecular epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by sequencing and analysing the first full-length genome sequences obtained from 48 coronavirus disease-2019 (COVID-19) patients in five districts in Western Serbia in the period April 2020–July 2020. SARS-CoV-2 sequences in Western Serbia distinguished from the Wuhan sequence in 128 SNPs in total. The phylogenetic structure of local SARS-CoV-2 isolates suggested the existence of at least four distinct groups of SARS-CoV-2 strains in Western Serbia. The first group is the most similar to the strain from Italy. These isolates included two 20A sequences and 15−30 20B sequences that displayed a newly occurring set of four conjoined mutations. The second group is the most similar to the strain from France, carrying two mutations and belonged to 20A clade. The third group is the most similar to the strain from Switzerland carrying four co-occurring mutations and belonging to 20B clade. The fourth group is the most similar to another strain from France, displaying one mutation that gave rise to a single local isolate that belonged to 20A clade.

The coronavirus disease-2019 pandemic changed regular life and work around the world. Educational institutions moved to a virtual environment, in many cases without any experience and preparation. This paper explores the impact of institutional support on educators' subjective well-being during the pandemic lockdown. A quantitative study was conducted in Lithuania with 1,851 educators in April 2020. Institutional support was found to have a positive impact on work–life balance and well-being, as well as reducing work-related, client-related and personal burnout. This study begins a dialog on institutional support and its impact on employee well-being in unexpected work and life conditions.

Initial assessments of coronavirus disease 2019 (COVID-19) preparedness revealed resource shortages and variations in infection prevention policies across US hospitals. Our follow-up survey revealed improvement in resource availability, increase in testing capacity, and uniformity in infection prevention policies. Most importantly, the survey highlighted an increase in staffing shortages and use of travel nursing.

Data from all general hospitals in Israel to April 2021 show that the mean hospital rate of staff vaccination was 84.4% for the first dose and 77.1% for the second dose, which are lower than general population rate, with mean 7% who did not complete their vaccinations. Healthcare workers have an important role in influencing the wider community.

Healthcare personnel (HCP) with unprotected exposures to aerosol-generating procedures (AGPs) on patients with coronavirus disease 2019 (COVID-19) are at risk of infection with severe acute respiratory coronavirus virus 2 (SARS-CoV-2). A retrospective review at an academic medical center demonstrated an infection rate of <1% among HCP involved in AGPs without a respirator and/or eye protection.

As acute infectious pneumonia, the coronavirus disease-2019 (COVID-19) has created unique challenges for each nation and region. Both India and the United States (US) have experienced a second outbreak, resulting in a severe disease burden. The study aimed to develop optimal models to predict the daily new cases, in order to help to develop public health strategies. The autoregressive integrated moving average (ARIMA) models, generalised regression neural network (GRNN) models, ARIMA–GRNN hybrid model and exponential smoothing (ES) model were used to fit the daily new cases. The performances were evaluated by minimum mean absolute per cent error (MAPE). The predictive value with ARIMA (3, 1, 3) (1, 1, 1)14 model was closest to the actual value in India, while the ARIMA–GRNN presented a better performance in the US. According to the models, the number of daily new COVID-19 cases in India continued to decrease after 27 May 2021. In conclusion, the ARIMA model presented to be the best-fit model in forecasting daily COVID-19 new cases in India, and the ARIMA–GRNN hybrid model had the best prediction performance in the US. The appropriate model should be selected for different regions in predicting daily new cases. The results can shed light on understanding the trends of the outbreak and giving ideas of the epidemiological stage of these regions.

With increasing demand for large numbers of testing during the coronavirus disease 2019 pandemic, alternative protocols were developed with shortened turn-around time. We evaluated the performance of such a protocol wherein 1138 consecutive clinic attendees were enrolled; 584 and 554 respectively from two independent study sites in the cities of Pune and Kolkata. Paired nasopharyngeal and oropharyngeal swabs were tested by using both reference and index methods in a blinded fashion. Prior to conducting real-time polymerase chain reaction, swabs collected in viral transport medium (VTM) were processed for RNA extraction (reference method) and swabs collected in a dry tube without VTM were incubated in Tris–EDTA–proteinase K buffer for 30 min and heat-inactivated at 98 °C for 6 min (index method). Overall sensitivity and specificity of the index method were 78.9% (95% confidence interval (CI) 71–86) and 99% (95% CI 98–99.6), respectively. Agreement between the index and reference method was 96.8% (k = 0.83, s.e. = 0.03). The reference method exhibited an enhanced detection of viral genes (E, N and RNA-dependent RNA polymerase) with lower Ct values compared to the index method. The index method can be used for detecting severe acute respiratory syndrome corona virus-2 infection with an appropriately chosen primer–probe set and heat treatment approach in pressing time; low sensitivity constrains its potential wider use.