Using the data provided by Fiji's ministry of health and medical services, we apply an implicit time-discrete SIR (susceptible people–infectious people–removed people) model that tracks the transmission and recovering rate at time, t to predict the trend of the coronavirus disease 2019 (COVID-19) pandemic in Fiji. The model implied time-varying transmission and recovery rates were calculated from 4 May 2021 to 9 October 2021. The estimator functions for these rates were determined, and a short-term (30 days) forecast was done. The model was validated with observed values of the active and recovered cases from 11 October 2021 to 9 December 2021. Statistical results reveal a good fit of profiles between model simulated and the reported COVID-19 data. The gradual decrease of the time-varying basic reproduction number with values below one towards the end of the study period suggest the government's success in controlling the epidemic. The mean reproduction number for the second wave of COVID-19 in Fiji was estimated as 2.7818. The results from this study can be used by researchers, the Fijian government, and the relevant health policy makers in making informed decisions should a third COVID-19 wave occur.

We investigated whether countries with higher coverage of childhood live vaccines [BCG or measles-containing-vaccine (MCV)] have reduced risk of coronavirus disease 2019 (COVID-19)-related mortality, while accounting for known systems differences between countries. In this ecological study of 140 countries using publicly available national-level data, higher vaccine coverage, representing estimated proportion of people vaccinated during the last 14 years, was associated with lower COVID-19 deaths. The associations attenuated for both vaccine variables, and MCV coverage became no longer significant once adjusted for published estimates of the Healthcare access and quality index (HAQI), a validated summary score of healthcare quality indicators. The magnitude of association between BCG coverage and COVID-19 death rate varied according to HAQI, and MCV coverage had little effect on the association between BCG and COVID-19 deaths. While there are associations between live vaccine coverage and COVID-19 outcomes, the vaccine coverage variables themselves were strongly correlated with COVID-19 testing rate, HAQI and life expectancy. This suggests that the population-level associations may be further confounded by differences in structural health systems and policies. Cluster randomised studies of booster vaccines would be ideal to evaluate the efficacy of trained immunity in preventing COVID-19 infections and mortality in vaccinated populations and on community transmission.

We combined smartphone mobility data with census track-based reports of positive case counts to study a coronavirus disease 2019 (COVID-19) outbreak at the University of Wisconsin–Madison campus, where nearly 3000 students had become infected by the end of September 2020. We identified a cluster of twenty bars located at the epicentre of the outbreak, in close proximity to campus residence halls. Smartphones originating from the two hardest-hit residence halls (Sellery-Witte), where about one in five students were infected, were 2.95 times more likely to visit the 20-bar cluster than smartphones originating in two more distant, less affected residence halls (Ogg-Smith). By contrast, smartphones from Sellery-Witte were only 1.55 times more likely than those from Ogg-Smith to visit a group of 68 restaurants in the same area [rate ratio 1.91, 95% confidence interval (CI) 1.29–2.85, P < 0.001]. We also determined the per-capita rates of visitation to the 20-bar cluster and to the 68-restaurant comparison group by smartphones originating in each of 21 census tracts in the university area. In a multivariate instrumental variables regression, the visitation rate to the bar cluster was a significant determinant of the per-capita incidence of positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests in each census tract (elasticity 0.88, 95% CI 0.08–1.68, P = 0.032), while the restaurant visitation rate showed no such relationship. The potential super-spreader effects of clusters or networks of places, rather than individual sites, require further attention.

Control of the novel COronaVIrus Disease-2019 (COVID-19) in a hospital setting is a priority. A COVID-19-infected surgeon performed surgical activities before being tested. An exposure risk classification was applied to the identified exposed subjects and high- and medium-risk contacts underwent active symptom monitoring for 14 days at home. All healthcare professionals (HCPs) were tested for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) at the end of the quarantine and serological tests were performed. Three household contacts and 20 HCPs were identified as high- or medium-risk contacts and underwent a 14-day quarantine. Fourteen HCPs and 19 patients were instead classified as low risk. All the contacts remained asymptomatic and all HCPs tested negative for SARS-CoV-2. About 25–28 days after their last exposure, HCPs underwent serological testing and two of them had positive IgM but negative confirmatory swabs. In a low COVID-19 burden area, the in-hospital transmission of SARS-CoV-2 from an infectious doctor did not occur and, despite multiple and frequent contacts, a hospital outbreak was avoided. This may be linked to the adoption of specific recommendations and to the use of standard personal protective equipment by HCPs.

The molecular epidemiology of the virus and mapping helps understand the epidemics' evolution and apply quick control measures. This study provides genomic evidence of multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) introductions into Sri Lanka and virus evolution during circulation. Whole-genome sequences of four SARS-CoV-2 strains obtained from coronavirus disease 2019 (COVID-19) positive patients reported in Sri Lanka during March 2020 were compared with sequences from Europe, Asia, Africa, Australia and North America. The phylogenetic analysis revealed that the sequence of the sample of the first local patient collected on 10 March, who contacted tourists from Italy, was clustered with SARS-CoV-2 strains collected from Italy, Germany, France and Mexico. Subsequently, the sequence of the isolate obtained on 19 March also clustered in the same group with the samples collected in March and April from Belgium, France, India and South Africa. The other two strains of SARS-CoV-2 were segregated from the main cluster, and the sample collected from 16 March clustered with England and the sample collected on 30 March showed the highest genetic divergence to the isolate of Wuhan, China. Here we report the first molecular epidemiological study conducted on circulating SARS-CoV-2 in Sri Lanka. The finding provides the robustness of molecular epidemiological tools and their application in tracing possible exposure in disease transmission during the pandemic.

This study aimed to identify an appropriate simple mathematical model to fit the number of coronavirus disease 2019 (COVID-19) cases at the national level for the early portion of the pandemic, before significant public health interventions could be enacted. The total number of cases for the COVID-19 epidemic over time in 28 countries was analysed and fit to several simple rate models. The resulting model parameters were used to extrapolate projections for more recent data. While the Gompertz growth model (mean R2 = 0.998) best fit the current data, uncertainties in the eventual case limit introduced significant model errors. However, the quadratic rate model (mean R2 = 0.992) fit the current data best for 25 (89%) countries as determined by R2 values of the remaining models. Projection to the future using the simple quadratic model accurately forecast the number of future total number of cases 50% of the time up to 10 days in advance. Extrapolation to the future with the simple exponential model significantly overpredicted the total number of future cases. These results demonstrate that accurate future predictions of the case load in a given country can be made using this very simple model.

To assess the relationship between the neutrophil-to-lymphocyte ratio (NLR) and related parameters to the severity of coronavirus disease 2019 (COVID-19) symptoms. Clinical data from 38 COVID-19 patients who were diagnosed, treated and discharged from the Qishan Hospital in Yantai over the period from January to February 2020 were analysed. NLR and procalcitonin (PCT) were determined in the first and fourth weeks after their admission, along with the clinical characteristics and laboratory test results of these patients. Based on results as obtained on the first and fourth weeks after admission, five indices consisting of NLR, white blood cells, neutrophils, lymphocytes (LY) and monocytes (MON) were selected to generate receiver operating characteristic curves, while optimal cutoff values, sensitivities and specificities were obtained according to the Yuden index. Statistically significant differences in neutrophils, LY and the NLR were present in the severe vs. moderate COVID-19 group from the first to the fourth week of their hospitalisation. The cut-off value of NLR for predicting the severity of COVID-19 was 4.425, with a sensitivity of 0.855 and a specificity of 0.979. A statistically significant positive correlation was present between PCT and NLR in the severe group as determined within the first week of admission. NLR can serve as a predictor of COVID-19 disease severity as patients' progress from the first to the fourth week of their hospitalisation. The statistically significant positive correlation between levels of NLR and PCT in severe patients indicated that increases in NLR were accompanied with gradual increases in PCT.

The current investigation was conducted with the objective to develop an epidemiological case definition of possible severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) re-infection and assess its magnitude in India. The epidemiological case definition for SARS-CoV-2 re-infection was developed from literature review of data on viral kinetics. For achieving second objective, the individuals who satisfied the developed case definition for SARS-CoV-2 re-infection were contacted telephonically. Taking available evidence into consideration, re-infection with SARS-CoV-2 in our study was defined as any individual who tested positive for SARS-CoV-2 on two separate occasions by either molecular tests or rapid antigen test at an interval of at least 102 days with one negative molecular test in between. In this archive based, telephonic survey, 58 out of 1300 individuals (4.5%) fulfilled the above-mentioned definition; 38 individuals could be contacted with healthcare workers (HCWs) accounting for 31.6% of the cases. A large proportion of participants was asymptomatic and had higher Ct value during the first episode. While SARS-CoV-2 re-infection is still a rare phenomenon, there is a need for epidemiological definition of re-infection for establishing surveillance systems and this study contributes to such a goal.

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) re-infection is an emerging concern and there is a need to define it. Therefore, working epidemiological case definition for re-infection was developed and its magnitude was explored via archive-based, telephonic survey. Re-infection with SARS-CoV-2 was defined as two positive tests at an interval of at least 102 days with one interim negative test. Thirty-eight of the 58 eligible patients could be contacted with 12 (31.6%) being HCWs. Majority of the participants were asymptomatic and had higher Ct value during their first episode. To conclude, a working epidemiological case definition of SARS-CoV-2 re-infection is important to strengthen surveillance. The present investigation contributes to this goal and records reinfection in 4.5% of SARS-CoV-2 infected individuals in India.

Health care workers (HCWs) are in a higher risk of acquiring the disease owing to their regular contact with the patients. The aim of this study is to evaluate the seroprevalence among HCWs pre- and post-vaccination. The serological assessment of anti-SARS-CoV-2 antibody was conducted in pre- and post-vaccination of first or both doses of the ChAdOx1 nCoV-19 vaccine and followed up to 8 months for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and antibody titre. The neutralising antibody was positively correlated with IgG and total antibody. IgG was significantly decreased after 4–6 months post-infection. Almost all HCWs developed IgG after 2 doses of vaccine with comparable IgG to that of the infected HCWs. A follow-up of 6 to 8 months post vaccination showed a significant drop in antibody titre, while 56% of them didn't show a detectable level of IgG, suggesting the need for a booster dose. Around 21% of the vaccinated HCWs with significantly low antibody titre were infected with the SARS-CoV-2, but a majority of them showed mild symptoms and recovered in home isolation without any O2 support. We noticed the effectiveness of the ChAdOx1 nCoV-19 vaccine as evident from the low rate of breakthrough infection with any severe symptoms.

The coronavirus disease 2019 (COVID-19) pandemic had an uneven development in different countries. In Argentina, the pandemic began in March 2020 and, during the first 3 months, the vast majority of cases were concentrated in a densely populated region that includes the city of Buenos Aires (country capital) and the Greater Buenos Aires (GBA) area that surrounds it. This work focuses on the spread of COVID-19 between June and November 2020 in GBA. Within this period of time there was no vaccine, basically only the early wild strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was present, and the official restriction and distancing measures in this region remained more or less constant. Under these particular conditions, the incidences show a sharp rise from June 2020 and begin to decrease towards the end of August until the end of November 2020. In this work we study, through mathematical modelling and available epidemiological information, the spread of COVID-19 in this region and period of time. We show that a coherent explanation of the evolution of incidences can be obtained assuming that only a minority fraction of the population got involved in the spread process, so that the incidences decreased as this group of people was becoming immune. The observed evolution of the incidences could then be a consequence at the population level of lasting immunity conferred by SARS-CoV-2.

Dromedary camels have been shown to be the main reservoir for human Middle East respiratory syndrome (MERS) infections. This systematic review aims to compile and analyse all published data on MERS-coronavirus (CoV) in the global camel population to provide an overview of current knowledge on the distribution, spread and risk factors of infections in dromedary camels. We included original research articles containing laboratory evidence of MERS-CoV infections in dromedary camels in the field from 2013 to April 2018. In general, camels only show minor clinical signs of disease after being infected with MERS-CoV. Serological evidence of MERS-CoV in camels has been found in 20 countries, with molecular evidence for virus circulation in 13 countries. The seroprevalence of MERS-CoV antibodies increases with age in camels, while the prevalence of viral shedding as determined by MERS-CoV RNA detection in nasal swabs decreases. In several studies, camels that were sampled at animal markets or quarantine facilities were seropositive more often than camels at farms as well as imported camels vs. locally bred camels. Some studies show a relatively higher seroprevalence and viral detection during the cooler winter months. Knowledge of the animal reservoir of MERS-CoV is essential to develop intervention and control measures to prevent human infections.

In this paper, we present a method to estimate the risk of reopening of schools illustrated with the case of the State of São Paulo, Brazil. The model showed that, although no death of children would result from the reopening of the schools in the three cities analysed, the risk of asymptomatic and symptomatic cases and secondary cases among teachers, school staff and relatives of the children is not negligible. Although the epidemic hit different regions with different intensities, our model shows that, for regions where the incidence profile is similar to the cities analysed, the risk of reopening of schools is still too high. This in spite of the fact that incidences in these cities were declining in the period of the time considered. Therefore, although we cannot extend the result to the entire country, the overall conclusion is valid for regions with a declining incidence and it is even more valid for regions where incidence is increasing. We assumed a very conservative level of infection transmissibility of children of just 10% as that of adults. In spite of the very low level of transmissibility is assumed, the number of secondary cases caused by infected children among teachers, school staff and relatives varied from 2 to 85. It is, therefore, too soon to have any degree of confidence that reopening of schools before the advent of a vaccine is the right decision to take. The purpose of our model and simulations is to provide a method to estimate the risk of school reopening, although we are sure it could be applied as a guide to public health strategies.

Europe is in the midst of a COVID-19 epidemic and a number of non-pharmaceutical public health and social measures have been implemented, in order to contain the transmission of severe acute respiratory syndrome coronavirus 2. These measures are fundamental elements of the public health approach to controlling transmission but have proven not to be sufficiently effective. Therefore, the European Centre for Disease Prevention and Control has conducted an assessment of research gaps that can help inform policy decisions regarding the COVID-19 response. We have identified research gaps in the area of non-pharmaceutical measures, physical distancing, contact tracing, transmission, communication, mental health, seasonality and environment/climate, surveillance and behavioural aspects of COVID-19. This prioritisation exercise is a step towards the global efforts of developing a coherent research road map in coping with the current epidemic but also developing preparedness measures for the next unexpected epidemic.

There has been no study exploring the prognostic values of neutrophil percentage-to-albumin ratio (NPAR). We hypothesised that NPAR is a novel marker of inflammation and is associated with all-cause mortality in patients with severe sepsis or septic shock. Patient data were extracted from the MIMIC-III V1.4 database. Only the data for the first intensive care unit (ICU) admission of each patient were used and baseline data were extracted within 24 h after ICU admission. The clinical endpoints were 30-, 90- and 365-day all-cause mortality in critically ill patients with severe sepsis or septic shock. Cox proportional hazards models and subgroup analyses were used to determine the relationship between NPAR and these clinical endpoints. A total of 2166 patients were eligible for this analysis. In multivariate analysis, after adjustments for age, ethnicity and gender, higher NPAR was associated with increased risk of 30-, 90- and 365-day all-cause mortality in critically ill patients with severe sepsis or septic shock. Furthermore, after adjusting for more confounding factors, higher NPAR remained a significant predictor of all-cause mortality (tertile 3 vs. tertile 1: HR, 95% CI: 1.29, 1.04–1.61; 1.41, 1.16–1.72; 1.44, 1.21–1.71). A similar trend was observed in NPAR levels stratified by quartiles. Higher NPAR was associated with increased risk of all-cause mortality in critically ill patients with severe sepsis or septic shock.

This prospective longitudinal epidemiological study was aimed at investigating the occupational SARS-CoV-2 infection risk of long distance train services in Germany. Three different employee groups (train attendants, train drivers and maintenance workers) within the workforce of the German railway carrier Deutsche Bahn Fernverkehr AG were studied based on their contact frequency with passengers and colleagues. Approximately 1100 employees were tested by PCR for acute infections and by antibody detection for past infections in June 2020, October 2020 and February 2021. Cumulative incidence (acute and past infections) after the third (final) test series in February 2021 was 8.5% (95% interval CI 6.8–10.4): 8.5% (95% CI 6.2–11.2) for train attendants, 5.5% (95% CI 2.9–9.5) for train drivers and 11.8% (95% CI 7.6–17.2) for maintenance workers. Between June 2020 and October 2020, the incidence was 1.2% (95% CI 0.6–2.3): 1.2% (95% CI 0.4–2.7) for train attendants, 1.1% (95% CI 0.1–3.9) for train drivers and 1.4% (95% CI 0.17–5.10) for maintenance workers. Between October 2020 and February 2021, it was 5.1% (95% CI 3.6–6.8): 5.2% (95% CI 3.3–7.8) for train attendants, 1.6% (95% CI 0.3–4.5) for train drivers and 8.8% (95% CI 4.9–14.3) for maintenance workers. Thus, contrary to expectation our exploratory data did not show train attendants to be at the highest risk of SARS-CoV-2 infections among the employee groups. In line with expectations, train drivers, representing the low contact group, seemed at lowest occupational risk.

An outbreak of SARS-CoV2 infection in a Barcelona prison was studied. One hundred and forty-eight inmates and 36 prison staff were evaluated by rt-PCR, and 24.1% (40 prisoners, two health workers and four non-health workers) tested positive. In all, 94.8% of cases were asymptomatic. The inmates were isolated in prison module 4, which was converted into an emergency COVID unit. There were no deaths. Generalised screening and the isolation and evaluation of the people infected were key measures. Symptom-based surveillance must be supplemented by rapid contact-based monitoring in order to avoid asymptomatic spread among prisoners and the community at large.

Using nested case–control data from the Lifelines COVID-19 cohort, we undertook a validation study of a clinical and genetic model to predict the risk of severe COVID-19 in people with confirmed COVID-19 and in people with confirmed or self-reported COVID-19. The model performed well in terms of discrimination of cases and controls for all ages (area under the receiver operating characteristic curve (AUC) = 0.680 for confirmed COVID-19 and AUC = 0.689 for confirmed and self-reported COVID-19) and in the age group in which the model was developed (50 years and older; AUC = 0.658 for confirmed COVID-19 and AUC = 0.651 for confirmed and self-reported COVID-19). There was no evidence of over- or under-dispersion of risk scores but there was evidence of overall over-estimation of risk in all analyses (all P < 0.0001). In the light of large numbers of people worldwide remaining unvaccinated and continuing uncertainty regarding vaccine efficacy over time and against variants of concern, identification of people at high risk of severe COVID-19 may encourage the uptake of vaccinations (including boosters) and the use of non-pharmaceutical inventions.

Case identification is an ongoing issue for the COVID-19 epidemic, in particular for outpatient care where physicians must decide which patients to prioritise for further testing. This paper reports tools to classify patients based on symptom profiles based on 236 severe acute respiratory syndrome coronavirus 2 positive cases and 564 controls, accounting for the time course of illness using generalised multivariate logistic regression. Significant symptoms included abdominal pain, cough, diarrhoea, fever, headache, muscle ache, runny nose, sore throat, temperature between 37.5 and 37.9 °C and temperature above 38 °C, but their importance varied by day of illness at assessment. With a high percentile threshold for specificity at 0.95, the baseline model had reasonable sensitivity at 0.67. To further evaluate accuracy of model predictions, leave-one-out cross-validation confirmed high classification accuracy with an area under the receiver operating characteristic curve of 0.92. For the baseline model, sensitivity decreased to 0.56. External validation datasets reported similar result. Our study provides a tool to discern COVID-19 patients from controls using symptoms and day from illness onset with good predictive performance. It could be considered as a framework to complement laboratory testing in order to differentiate COVID-19 from other patients presenting with acute symptoms in outpatient care.

This paper applies a scenario planning approach, to outline some current uncertainties related to COVID-19 and what they might mean for plausible futures for which we should prepare, and to identify factors that we as individual faculty members and university institutions should be considering now, when planning for the future under COVID-19. Although the contextual focus of this paper is Canada, the content is likely applicable to other places where the COVID-19 epidemic curve is in its initial rising stage, and where universities are predominantly publicly funded institutions.

The global outbreak of coronavirus disease 2019 (COVID-19) is greatly threatening the public health in the world. We reconstructed global transmissions and potential demographic expansions of severe acute respiratory syndrome coronavirus 2 based on genomic information. We found that intercontinental transmissions were rare in January and early February but drastically increased since late February. After world-wide implements of travel restrictions, the transmission frequencies decreased to a low level in April. We identified a total of 88 potential demographic expansions over the world based on the star-radiative networks and 75 of them were found in Europe and North America. The expansion numbers peaked in March and quickly dropped since April. These findings are highly concordant with epidemic reports and modelling results and highlight the significance of quarantine validity on the global spread of COVID-19. Our analyses indicate that the travel restrictions and social distancing measures are effective in containing the spread of COVID-19.