We report key learning from the public health management of the first two confirmed cases of COVID-19 identified in the UK. The first case imported, and the second associated with probable person-to-person transmission within the UK. Contact tracing was complex and fast-moving. Potential exposures for both cases were reviewed, and 52 contacts were identified. No further confirmed COVID-19 cases have been linked epidemiologically to these two cases. As steps are made to enhance contact tracing across the UK, the lessons learned from earlier contact tracing during the country's containment phase are particularly important and timely.

We recruited 1591 patients who presented to our fever clinics from 23 January 2020 to 16 February 2020. The different imaging findings between COVID-19 pneumonia and influenza A viruses, influenza B virus pneumonia were also investigated. Most patients were infected by influenza A and B viruses in the flu-season. A laboratory kit is urgently needed to test different viruses simultaneously. Computed tomography can help early screen suspected patients with COVID-19 and differentiate different virus-related pneumonia.

Episodes of bacterial superinfections have been well identified for several respiratory viruses, notably influenza. In this retrospective study, we compared the frequency of superinfections in COVID-19 patients to those found in influenza-positive patients, and to controls without viral infection. We included 42 468 patients who had been diagnosed with COVID-19 and 266 261 subjects who had tested COVID-19 negative between 26 February 2020 and 1 May 2021. In addition, 4059 patients were included who had tested positive for the influenza virus between 1 January 2017 and 31 December 2019. Bacterial infections in COVID-19 patients were more frequently healthcare-associated, and acquired in ICUs, were associated with longer ICU stays, and occurred in older and male patients when compared to controls and to influenza patients (P < 0.0001 for all). The most common pathogens proved to be less frequent in COVID-19 patients, including fewer cases of bacteraemia involving E. coli (P < 0.0001) and Klebsiella pneumoniae (P = 0.027) when compared to controls. In respiratory specimens Haemophilus influenzae (P < 0.0001) was more frequent in controls, while Streptococcus pneumoniae (P < 0.0001) was more frequent in influenza patients. Likewise, species associated with nosocomial transmission, such as Pseudomonas aeruginosa and Staphylococcus epidermidis, were more frequent among COVID-19 patients. Finally, we observed a high frequency of Enterococcus faecalis bacteraemia among COVID-19 patients, which were mainly ICU-acquired and associated with a longer timescale to acquisition.

During the coronavirus disease 2019 (COVID-19) pandemic, a new phenomenon manifesting as a multisystem inflammatory syndrome in children (MIS-C) which has a similar clinical presentation to Kawasaki disease, toxic shock syndrome and severe sepsis has emerged. Although the number of MIS-C reports is increasing, rare reports in Asia is still available. To our knowledge, this study is the largest series of published MIS-C cases in Iran. We performed a retrospective study of all patients with case definition for MIS-C admitted to the three paediatric hospitals in Iran. All of these hospitals are located within the most active COVID-19 pandemic areas (Tehran, Qom and Mazandaran) in Iran. Demographic characteristics, clinical data, laboratory findings, imaging and echocardiographic findings, treatment and outcomes were collected. Between 7 March and 23 June 2020, 45 children were included in the study. The median age of children was 7 years (range between 10 months and 17 years). Common presenting symptoms include fever (91%), abdominal pain (58%), nausea/vomiting (51%), mucocutaneous rash (53%), conjunctivitis (51%) and hands and feet oedema (40%) with median duration of symptoms prior to presentation of 5 (interquartile range (IQR) 3, 7) days. Fifty-three percent of children showed lymphopaenia. Overall, the majority of cases at admission had markedly elevated inflammatory markers erythrocyte sedimentation rate (ESR) (95.5%) and C-reactive protein (CRP) (97%). Ferritin was abnormal in 11 out of 14 tested patients (73%), and it was highly elevated (>500 ng/ml) in 47% of cases. Median fibrinogen level was 210 (IQR 165, 291) mg/dl, D-dimer was 3909 (IQR 848, 4528) ng/ml and troponin was 0.6 (IQR 0.1, 26) ng/ml, respectively. Twenty out of 31 patients (64.5%) had hypoalbuminaemia. In addition, hyponatraemia was found in 64% of cases. Twenty-five patients (56%) presented with cardiac involvement and acute renal failure was observed in 13 cases (29%). Pleural, ascitic, ileitis and pericardial effusions were found in 18%, 11%, 4% and 2% of cases, respectively. In conclusion, this is a first large case series of hospitalised children who met criteria for MIS-C in Iran. There was a wide spectrum of presenting signs and symptoms; evidence of inflammation with abnormal values of CRP, ESR, D-dimer, ferritin and albumin; and multi-organ involvement.

Estimating the case fatality ratio (CFR) for COVID-19 is an important aspect of public health. However, calculating CFR accurately is problematic early in a novel disease outbreak, due to uncertainties regarding the time course of disease and difficulties in diagnosis and reporting of cases. In this work, we present a simple method for calculating the CFR using only public case and death data over time by exploiting the correspondence between the time distributions of cases and deaths. The time-shifted distribution (TSD) analysis generates two parameters of interest: the delay time between reporting of cases and deaths and the CFR. These parameters converge reliably over time once the exponential growth phase has finished. Analysis is performed for early COVID-19 outbreaks in many countries, and we discuss corrections to CFR values using excess-death and seroprevalence data to estimate the infection fatality ratio (IFR). While CFR values range from 0.2% to 20% in different countries, estimates for IFR are mostly around 0.5–0.8% for countries that experienced moderate outbreaks and 1–3% for severe outbreaks. The simplicity and transparency of TSD analysis enhance its usefulness in characterizing a new disease as well as the state of the health and reporting systems.

This study estimates the incubation period of COVID-19 among locally transmitted cases, and its association with age to better inform public health measures in containing COVID-19. Epidemiological data of all PCR-confirmed COVID-19 cases from all restructured hospitals in Singapore were collected between 23 January 2020 and 2 April 2020. Activity mapping and detailed epidemiological investigation were conducted by trained personnel. Positive cases without clear exposure to another positive case were excluded from the analysis. One hundred and sixty-four cases (15.6% of patients) met the inclusion criteria during the defined period. The crude median incubation period was 5 days (range 1–12 days) and median age was 42 years (range 5–79 years). The median incubation period among those 70 years and older was significantly longer than those younger than 70 years (8 vis-à-vis 5 days, P = 0.040). Incubation period was negatively correlated with day of illness in both groups. These findings support current policies of 14-day quarantine periods for close contacts of confirmed cases and 28 days for monitoring infections in known clusters. An elderly person who may have a longer incubation period than a younger counterpart may benefit from earlier and proactive testing, especially after exposure to a positive case.

Coronavirus disease 2019 (COVID-19) has been described as having an overdispersed offspring distribution, i.e. high variation in the number of secondary transmissions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) per single primary COVID-19 case. Accordingly, countermeasures focused on high-risk settings and contact tracing could efficiently reduce secondary transmissions. However, as variants of concern with elevated transmissibility continue to emerge, controlling COVID-19 with such focused approaches has become difficult. It is vital to quantify temporal variations in the offspring distribution dispersibility. Here, we investigated offspring distributions for periods when the ancestral variant was still dominant (summer, 2020; wave 2) and when Alpha variant (B.1.1.7) was prevailing (spring, 2021; wave 4). The dispersion parameter (k) was estimated by analysing contact tracing data and fitting a negative binomial distribution to empirically observed offspring distributions from Nagano, Japan. The offspring distribution was less dispersed in wave 4 (k = 0.32; 95% confidence interval (CI) 0.24–0.43) than in wave 2 (k = 0.21 (95% CI 0.13–0.36)). A high proportion of household transmission was observed in wave 4, although the proportion of secondary transmissions generating more than five secondary cases did not vary over time. With this decreased variation, the effectiveness of risk group-focused interventions may be diminished.

This study aimed to analyse the survival of patients admitted to Brazilian hospitals due to the COVID-19 and estimate prognostic factors. This is a retrospective, multicentre cohort study, based on data from 46 285 hospitalisations for COVID-19 in Brazil. Survival functions were calculated using the Kaplan–Meier's method. The log-rank test compared the survival functions for each variable and from that, hazard ratios (HRs) were calculated, and the proportional hazard model was used in Cox multiple regression. The smallest survival curves were the ones for patients at the age of 68 years or more, black/mixed race, illiterate, living in the countryside, dyspnoea, respiratory distress, influenza-like outbreak, O2 saturation <95%, X-ray change, length of stay in the intensive care unit (ICU), invasive ventilatory support, previous heart disease, pneumopathy, diabetes, Down's syndrome, neurological disease and kidney disease. Better survival was observed in the influenza-like outbreak and in an asthmatic patient. The multiple model for increased risk of death when they were admitted to the ICU HR 1.28, diabetes HR 1.17, neurological disease HR 1.34, kidney disease HR 1.11, heart disease HR 1.14, black or mixed race of HR 1.50, asthma HR 0.71 and pneumopathy HR 1.12. This reinforces the importance of socio-demographic and clinical factors as a prognosis for death.

We aimed to describe the clinical features in coronavirus disease 2019 (COVID-19) cases. We studied 134 critically ill COVID-19 cases from 30 December 2019 to 20 February 2020 in an intensive care unit (ICU) at Wuhan Jinyintan Hospital. Demographics, underlying diseases, therapy strategies and test results were collected and analysed from patients on admission, admission to the ICU and 48 h before death. The non-survivors were older (65.46 (s.d. 9.74) vs. 46.45 (s.d. 11.09)) and were more likely to have underlying diseases. The blood group distribution of the COVID-19 cases differed from that of the Han population in Wuhan, with type A being 43.85%; type B, 26.92%; type AB, 10% and type O, 19.23%. Non-survivors tend to develop more severe lymphopaenia, with higher C-reactive protein, interleukin-6, procalcitonin, D-dimer levels and gradually increased with time. The clinical manifestations were non-specific. Compared with survivors, non-survivors more likely to have organ function injury, and to receive mechanical ventilation, either invasively or noninvasively. Multiple organ failure and secondary bacterial infection in the later period is worthy of attention.

India is one of the severely affected countries by the Covid-19 pandemic at present. Within the stochastic framework of the SEQIR model, we studied publicly available data of the Covid-19 patients in India and analysed possible impacts of quarantine and social distancing as controlling strategies for the pandemic. Our stochastic simulation results clearly show that proper quarantine and social distancing should be maintained right from the start of the pandemic and continued until its end for effective control. This calls for a more disciplined social lifestyle in the future. However, only social distancing and quarantine of the exposed population are found not sufficient enough to end the pandemic in India. Therefore, implementation of other stringent policies like complete lockdown as well as increased testing of susceptible populations is necessary. The demographic stochasticity, which is quite visible in the system dynamics, has a critical role in regulating and controlling the pandemic.

We report a familial cluster of 24 individuals infected with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The index case had a travel history and spent 24 days in the house before being tested and was asymptomatic. Physical overcrowding in the house provided a favourable environment for intra-cluster infection transmission. Restriction of movement of family members due to countrywide lockdown limited the spread in community. Among the infected, only four individuals developed symptoms. The complete genome sequences of SARS-CoV-2 was retrieved using next-generation sequencing from eight clinical samples which demonstrated a 99.99% similarity with reference to Wuhan strain and the phylogenetic analysis demonstrated a distinct cluster, lying in the B.6.6 pangolin lineage.

While most research focuses on the clinical treatment of COVID-19, fewer studies have investigated individuals' responses towards this novel infectious disease. This study aims to report the temporal changes in individuals' psychological wellbeing, perceived discrimination, sociopolitical perceptions and information-seeking behaviours among the general public in Hubei, China. Data were obtained from a two-wave survey of 1902 respondents aged 18–80 in Hubei province during the peak and mitigation stages of the outbreak. The results showed that the prevalence of psychological distress dropped from over 75% to around 15% throughout the study period, but perceived discrimination remained stable. Female, middle-aged, well-educated respondents and those employed in government/public institutions/state-owned enterprises tended to report more distress. While respondents' attention on COVID-19 information kept high and stable, their sources of information diversified across different sociodemographic groups. Over time, people obtained more social support from neighbourhoods than from their friends and relatives or non-government organisations. Over 80% of respondents were satisfied with the performance of the central government, which was notably higher than their ratings on the local government and neighbourhood/village committees. The findings of this research are informative for formulating effective intervention strategies to tackle various psychosocial problems during COVID-19.

Almost all hospitals are equipped with air-conditioning systems to provide a comfortable environment for patients and staff. However, the accumulation of dust and moisture within these systems increases the risk of transmission of microbes and have on occasion been associated with outbreaks of infection. Nevertheless, the impact of air-conditioning on the transmission of microorganisms leading to infection remains largely uncertain. We conducted a scoping review to screen systematically the evidence for such an association in the face of the coronavirus disease 2019 epidemic. PubMed, Embase and Web of Science databases were explored for relevant studies addressing microbial contamination of the air, their transmission and association with infectious diseases. The review process yielded 21 publications, 17 of which were cross-sectional studies, three were cohort studies and one case−control study. Our analysis showed that, compared with naturally ventilated areas, microbial loads were significantly lower in air-conditioned areas, but the incidence of infections increased if not properly managed. The use of high-efficiency particulate air (HEPA) filtration not only decreased transmission of airborne bioaerosols and various microorganisms, but also reduced the risk of infections. By contrast, contaminated air-conditioning systems in hospital rooms were associated with a higher risk of patient infection. Cleaning and maintenance of such systems to recommended standards should be performed regularly and where appropriate, the installation of HEPA filters can effectively mitigate microbial contamination in the public areas of hospitals.

The objectives of this study were to define risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in University of Cambridge (UoC) students during a period of increased incidence in October and November 2020. The study design was a survey.

Routine public health surveillance identified an increase in the numbers of UoC students with confirmed SARS-CoV-2 positivity in the 10 days after a national lockdown was announced in the UK on 5th November 2020. Cases were identified both through symptom-triggered testing and a universal asymptomatic testing programme. An online questionnaire was sent to all UoC students on 25 November to investigate risk factors for testing positive in the period after 30th October 2020. This asked about symptoms, SARS-CoV-2 test results, aspects of university life, and attendance at social events in the week prior to lockdown. Univariate and multivariable analyses were undertaken evaluating potential risk factors for SARS-CoV-2 positivity.

Among 3980 students responding to the questionnaire, 99 (2.5%) reported testing SARS-CoV-2 positive in the period studied; 28 (28%) were asymptomatic. We found strong independent associations with SARS-CoV-2 positivity and attendance at two social settings in the City of Cambridge (adjusted odds ratio favouring disease 13.0 (95% CI 6.2–26.9) and 14.2 (95% CI 2.9–70)), with weaker evidence of association with three further social settings. By contrast, we did not observe strong independent associations between disease risk and accommodation type or attendance at a range of activities associated with the university curriculum.

To conclude attendance at social settings can facilitate widespread SARS-CoV-2 transmission in university students. Constraint of transmission in higher education settings needs to emphasise risks outside university premises, as well as a COVID-safe environment within university premises.

D-dimer level on admission is a promising biomarker to predict mortality in patients with COVID-19. In this study, we reviewed the association between on-admission D-dimer levels and all-cause mortality risk in COVID-19 patients. Peer-reviewed studies and preprints reporting categorised D-dimer levels on admission and all-cause mortality until 24 May 2020 were searched for using the following keywords: ‘COVID-19’, ‘D-dimer’ and ‘Mortality’. A meta-analysis was performed to determine the pooled risk ratio (RR) for all-cause mortality. In total, 2911 COVID-19 patients from nine studies were included in this meta-analysis. Regardless of the different D-dimer cut-off values used, the pooled RR for all-cause mortality in patients with elevated vs. normal on-admission D-dimer level was 4.77 (95% confidence interval (CI) 3.02–7.54). Sensitivity analysis did not significantly affect the overall mortality risk. Analysis restricted to studies with 0.5 μg/ml as the cut-off value resulted in a pooled RR for mortality of 4.60 (95% CI 2.72–7.79). Subgroup analysis showed that the pooled all-cause mortality risk was higher in Chinese vs. non-Chinese studies (RR 5.87; 95% CI 2.67–12.89 and RR 3.35; 95% CI 1.66–6.73; P = 0.29). On-admission D-dimer levels showed a promising prognostic role in predicting all-cause mortality in COVID-19 patients, elevated D-dimer levels were associated with increased risk of mortality.

This study compared clinico-epidemiological characteristics between Japanese and non-Japanese coronavirus disease 2019 (COVID-19) patients under the pandemic in Japan. We retrospectively analysed nationwide data of hospitalised COVID-19 patients before 31 March 2021. Epidemic curves were constructed to identify the case distribution over time. A total of 28 093 patients were Japanese and 1335 patients were non-Japanese. The major racial and ethnic minorities were East Asians (n = 521), South Asians (n = 260) and Latin Americans (n = 270). Non-Japanese patients were younger and more likely to travel to COVID-19 endemic countries (7.7%), had meals with other people (17.8%), stayed in crowded places (17.9%) and worked mainly in restaurants (6.6%) and service facilities in nightlife businesses (5.2%). In the matched cohorts, we found no clear disparities in time to admission and clinical prognoses. The epidemic curve for non-Japanese patients showed a small peak in the first wave and no definite waves for the second or third waves. Racial and ethnic minorities were at less risk of severe disease but were at a greater risk of COVID-19 exposure; however, the healthcare system in Japan may provide them with equal opportunities to access inpatient care with Japanese. Further research on their social determinants of health in Japan is required.

Faeces samples from diarrhoeic and non-diarrhoeic lambs and goat kids aged 1–45 days were examined for enteric pathogens. Cryptosporidium parvum was detected in both diarrhoeic lambs (45%) and goat kids (42%) but not in non-diarrhoeic animals. F5+ (K99+) and/or F41+Escherichia coli strains were isolated from 26% and 22% of the diarrhoeic lambs and goat kids, respectively, although these strains, which did not produce enterotoxins ST I or LT I, were found with similar frequencies in non-diarrhoeic animals. A F5−F41−ST I+E. coli strain was isolated from a diarrhoeic lamb (0·6%). Verotoxigenic E. coli was isolated from both diarrhoeic and non-diarrhoeic lambs (4·1% and 8·2%, respectively) and there was no association between infection and diarrhoea. The prevalence of group A rotavirus infection in diarrhoeic lambs was very low (2·1%). Groups A and B rotaviruses were detected in three (8·1%) and five (13·5%) diarrhoeic goat kids from two single outbreaks. Group C rotaviruses were detected in four non-diarrhoeic goat kids. An association of diarrhoea and infection was demonstrated only for group B rotavirus. Clostridium perfringens was isolated from 10·8% of the diarrhoeic goat kids but not from non-diarrhoeic goat kids or lambs. Salmonella arizonae was isolated from a diarrhoeic goat kid (2·7%) and the clinical characteristics of the outbreaks where these two latter enteropathogens were found different from the rest. Picobirnaviruses were detected in a diarrhoeic lamb. No coronaviruses were detected using a bovine coronavirus ELISA. No evidence was found of synergistic effect between the agents studied. Enteric pathogens were not found in four (8·7%) and three (20%) outbreaks of diarrhoea in lambs and goat kids, respectively.

As the Middle East respiratory syndrome coronavirus (MERS-CoV) continues to occur in small outbreaks in Saudi Arabia, we aimed to assess the knowledge, attitudes and intended practices of healthcare workers (HCWs) during the early stage of the COVID-19 pandemic and compare worry levels with previous findings during the MERS-CoV outbreak in 2015. We sent an adapted version of our previously published MERS-CoV questionnaire to the same cohort of HCWs at a tertiary hospital in Saudi Arabia. About 40% of our sample had previous experience with confirmed or suspected MERS-CoV patients, and those had a significantly higher knowledge score (13.16 ± 2.02 vs. 12.58 ± 2.27, P = 0.002) and higher adherence to protective hygienic practices (2.95 ± 0.80 vs. 2.74 ± 0.92, P = 0.003). The knowledge scores on COVID-19 were higher in the current cohort than the previous MERS-CoV outbreak cohort (68% vs. 79.7%, P < 0.001). HCWs from the current cohort who felt greater anxiety from COVID-19 compared to MERS-CoV were less likely to have been exposed to MERS-CoV infected/suspected cases (odds ratio (OR) = 0.646, P = 0.042) and were less likely to have attended the hospital awareness campaign on COVID-19 (OR = 0.654, P = 0.035). We concluded that previous experience with MERS-CoV was associated with increased knowledge and adherence to protective hygienic practices, and reduction of anxiety towards COVID-19.

The Philippines confirmed local transmission of COVID-19 on 7 March 2020. We described the characteristics and epidemiological time-to-event distributions for laboratory-confirmed cases in the Philippines recorded up to 29 April 2020 and followed until 22 May 2020. The median age of 8212 cases was 46 years (IQR 32–61), with 46.2% being female and 68.8% living in the National Capital Region. Health care workers represented 24.7% of all detected infections. Mean length of hospitalisation for those who were discharged or died were 16.00 days (95% CI 15.48–16.54) and 7.27 days (95% CI 6.59–8.24). Mean duration of illness was 26.66 days (95% CI 26.06–27.28) and 12.61 days (95% CI 11.88–13.37) for those who recovered or died. Mean serial interval was 6.90 days (95% CI 5.81–8.41). Epidemic doubling time prior to the enhanced community quarantine (ECQ; 11 February and 19 March) was 4.86 days (95% CI 4.67–5.07) and the reproductive number was 2.41 (95% CI 2.33–2.48). During the ECQ (20 March to 9 April), doubling time was 12.97 days (95% CI 12.57–13.39) and the reproductive number was 0.89 (95% CI 0.78–1.02).