Conflicting results have been obtained through meta-analyses for the role of obesity as a risk factor for adverse outcomes in patients with coronavirus disease-2019 (COVID-19), possibly due to the inclusion of predominantly multimorbid patients with severe COVID-19. Here, we aimed to study obesity alone or in combination with other comorbidities as a risk factor for short-term all-cause mortality and other adverse outcomes in Mexican patients evaluated for suspected COVID-19 in ambulatory units and hospitals in Mexico. We performed a retrospective observational analysis in a national cohort of 71 103 patients from all 32 states of Mexico from the National COVID-19 Epidemiological Surveillance Study. Two statistical models were applied through Cox regression to create survival models and logistic regression models to determine risk of death, hospitalisation, invasive mechanical ventilation, pneumonia and admission to an intensive care unit, conferred by obesity and other comorbidities (diabetes mellitus (DM), chronic obstructive pulmonary disease, asthma, immunosuppression, hypertension, cardiovascular disease and chronic kidney disease). Models were adjusted for other risk factors. From 24 February to 26 April 2020, 71 103 patients were evaluated for suspected COVID-19; 15 529 (21.8%) had a positive test for SARS-CoV-2; 46 960 (66.1%), negative and 8614 (12.1%), pending results. Obesity alone increased adjusted mortality risk in positive patients (hazard ratio (HR) = 2.7, 95% confidence interval (CI) 2.04–2.98), but not in negative and pending-result patients. Obesity combined with other comorbidities further increased risk of death (DM: HR = 2.79, 95% CI 2.04–3.80; immunosuppression: HR = 5.06, 95% CI 2.26–11.41; hypertension: HR = 2.30, 95% CI 1.77–3.01) and other adverse outcomes. In conclusion, obesity is a strong risk factor for short-term mortality and critical illness in Mexican patients with COVID-19; risk increases when obesity is present with other comorbidities.

Although vaccines have become available, emergence and rapid transmission of new variants have added new paradigm in the coronavirus disease-2019 (COVID-19) pandemic. Weather, population and host immunity have been detected as the regulatory elements of COVID-19. This study aims to investigate the effects of weather, population and host factors on the outcome of COVID-19 and mutation frequency in Japan. Data were collected during January 2020 to February 2021. About 92% isolates were form GR clades. Variants 501Y.V1 (53%) and 452R.V1 (24%) were most prevalent in Japan. The strongest correlation was detected between fatalities and population density (rs = 0.81) followed by total population (rs = 0.72). Relative humidity had the highest correlation (rs = −0.71) with the case fatality rate. Cluster mutations namely N501Y (45%), E484K (30%), N439K (16%), K417N (6%) and T478I (3%) at spike protein have increased during January to February 2021. Above 90% fatality was detected in patients aged >60 years. The ratio of male to female patients of COVID-19 was 1.35:1. This study will help to understand the seasonality of COVID-19 and impact of weather on the outcome which will add knowledge to reduce the health burden of COVID-19 by the international organisations and policy makers.

Hospital healthcare workers (HCWs) are at increased risk of contracting COVID-19 infection. We aimed to determine the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in HCWs in Ireland. Two tertiary referral hospitals in Irish cities with diverging community incidence and seroprevalence were identified; COVID-19 had been diagnosed in 10.2% and 1.8% of staff respectively by the time of the study (October 2020). All staff of both hospitals (N = 9038) were invited to participate in an online questionnaire and blood sampling for SARS-CoV-2 antibody testing. Frequencies and percentages for positive SARS-CoV-2 antibody were calculated and adjusted relative risks (aRR) for participant characteristics were calculated using multivariable regression analysis. In total, 5788 HCWs participated (64% response rate). Seroprevalence of antibodies to SARS-CoV-2 was 15% and 4.1% in hospitals 1 and 2, respectively. Thirty-nine percent of infections were previously undiagnosed. Risk for seropositivity was higher for healthcare assistants (aRR 2.0, 95% confidence interval (CI) 1.4–3.0), nurses (aRR: 1.6, 95% CI 1.1–2.2), daily exposure to patients with COVID-19 (aRR: 1.6, 95% CI 1.2–2.1), age 18–29 years (aRR: 1.4, 95% CI 1.1–1.9), living with other HCWs (aRR: 1.3, 95% CI 1.1–1.5), Asian background (aRR: 1.3, 95% CI 1.0–1.6) and male sex (aRR: 1.2, 95% CI 1.0–1.4). The HCW seroprevalence was six times higher than community seroprevalence. Risk was higher for those with close patient contact. The proportion of undiagnosed infections call for robust infection control guidance, easy access to testing and consideration of screening in asymptomatic HCWs. With emerging evidence of reduction in transmission from vaccinated individuals, the authors strongly endorse rapid vaccination of all HCWs.

Estimating the lengths-of-stay (LoS) of hospitalised COVID-19 patients is key for predicting the hospital beds’ demand and planning mitigation strategies, as overwhelming the healthcare systems has critical consequences for disease mortality. However, accurately mapping the time-to-event of hospital outcomes, such as the LoS in the intensive care unit (ICU), requires understanding patient trajectories while adjusting for covariates and observation bias, such as incomplete data. Standard methods, such as the Kaplan-Meier estimator, require prior assumptions that are untenable given current knowledge. Using real-time surveillance data from the first weeks of the COVID-19 epidemic in Galicia (Spain), we aimed to model the time-to-event and event probabilities of patients’ hospitalised, without parametric priors and adjusting for individual covariates. We applied a non-parametric mixture cure model and compared its performance in estimating hospital ward (HW)/ICU LoS to the performances of commonly used methods to estimate survival. We showed that the proposed model outperformed standard approaches, providing more accurate ICU and HW LoS estimates. Finally, we applied our model estimates to simulate COVID-19 hospital demand using a Monte Carlo algorithm. We provided evidence that adjusting for sex, generally overlooked in prediction models, together with age is key for accurately forecasting HW and ICU occupancy, as well as discharge or death outcomes.

The study aims to estimate and compare the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence, the fraction of asymptomatic or subclinical infections in the population, determine the demographic risk factors and analyse the antibody development at different time points among adults in Bhubaneswar city, India. This was a serial three-round cross-sectional, community-based study where participants were selected from the residents of Bhubaneswar city using multi-stage random sampling. Blood samples were collected during household visits along with demographic and clinical data from every participant. Total anti-SARS-CoV-2 antibody present in serum was assessed using the electro-chemiluminescence immunoassay platform. Temporal comparisons of the community seroprevalence were performed against the detected number of cumulative cases, active cases, recoveries and deaths. A total of 3693 participants were enrolled in this study with a cumulative non-response rate of 18.33% in all the three rounds. The gender-weighted seroprevalence for the city in the first round was 1.55% (95% confidence interval (CI) 0.84–2.58), second round was 5.27% (95% CI 4.13–6.59) and in the third round was 49.04% (95% CI 46.39–51.68). In the first round, the seroprevalence was found to be highest in the elderly population, whereas the seroprevalence for the second and third phases was highest in the age group of 30–39 years. Seroprevalence showed an increasing trend over the three time periods, with the highest seropositivity rates among individuals sampled between 16 and 18 September 2020. By the third round, 93.93% of those who had previously been tested positive by real-time reverse transcription polymerase chain reaction had seroconversion and 46.57% of those who had been tested negative also showed seroconversion. Infection to case ratio during first round was 27.05, for second round and third round it was 5.62 and 17.91, respectively.

The explosive outbreak of COVID-19 led to a shortage of medical resources, including isolation rooms in hospitals, healthcare workers (HCWs) and personal protective equipment. Here, we constructed a new model, non-contact community treatment centres to monitor and quarantine asymptomatic and mildly symptomatic COVID-19 patients who recorded their own vital signs using a smartphone application. This new model in Korea is useful to overcome shortages of medical resources and to minimise the risk of infection transmission to HCWs.

When humanity has either suppressed coronavirus disease 2019 or learned to come to terms with its continued existence, governments and corporations probably return to their prepandemic stances. Solutions to the world’s problems are sought from technology and business innovations, not from considerations of equality and well-being for all. This is in stark contrast with the pandemic-time situation. Many governments, at least initially, listened to the recommendations of expert advisers, most notably public health authorities, who proceeded from considerations of equality and common good. I suggest that we should continue on this path when the immediate threat of the disease is over. Other crises are already ongoing—poverty, conflicts, climate change, financial bubbles, and so on—and it would be good to use expert knowledge rather than interests and ideologies in dealing with them. To assist in this, I outline the characteristics of a new kind of counsellor, impartial adviser, who is normatively motivated by a sense of copathy and who takes into account all views, nice and not-so-nice alike. I illustrate the nature and ideological orientation of copathic impartial advisers by placing them on a map of justice and examining their relationships with the main political moralities of our time.

During COVID-19, health provision and information resources have been increasingly provided via digital means (e.g. websites, apps) and this will become a standard practice beyond the pandemic. People with severe mental illness face profound health inequalities (e.g. a >20-year mortality gap). Digital exclusion puts this population at risk of heightened or compounded inequalities. This has been referred to as the ‘digital divide’. For any new digital means introduced in clinical practice to augment healthcare service provision, issues of accessibility, acceptability and usability should be addressed by researchers and developers early in the design phase, and prior to full implementation, to prevent digital exclusion.

Brazil ranks second in the number of confirmed cases of COVID-19 worldwide. In spite of this, coping measures differ throughout the national territory, as does the disease's impact on the population. This cross-sectional observational study, with 59 695 cases of COVID-19 registered in the state of Alagoas between March and August 2020, analysed clinical-epidemiological variables, incidence rate, mortality rate, case fatality rate (CFR) and the social indicators municipal human development index (MHDI) and social vulnerability index (SVI). Moran statistics and regression models were applied. Logistic regression analysis was applied to determine the predictors of death. The incidence rate was 1788.7/100 000 inhabitants; mortality rate was 48.0/100 000 and CFR was 2.7%. The highest incidence rates were observed in municipalities with better human development (overall MHDI (I = 0.1668; p = 0.002), education MHDI (I = 0.1649; p = 0.002) and income MHDI (I = 0.1880; p = 0.005)) and higher social vulnerability (overall SVI (I = 0.0599; p = 0.033)). CFR was associated with higher social vulnerability (SVI human capital (I = 0.0858; p = 0.004) and SVI urban infrastructure (I = 0.0985; p = 0.040)). Of the analysed cases, 55.4% were female; 2/3 were Black or Brown and the median age was 41 years. Among deaths, most were male (919; 57.4%) and elderly (1171; 73.1%). The predictors of death were male sex, advanced age and the presence of comorbidities. In Alagoas, Brazil, the disease has undergone a process of interiorisation and caused more deaths in poorer municipalities. The presence of comorbidities and advanced age were predictors of death.

The study aimed to investigate behavioural intentions to receive free and self-paid COVID-19 vaccinations (BICV-F and BICV-SP) among Chinese university students if the vaccine was 80% effective with rare mild side effects, to examine their associations with social media exposures and peer discussions regarding COVID-19 vaccination, and to explore the mediational role of perceived information sufficiency about COVID-19 vaccination. An online anonymous survey (N = 6922) was conducted in November 2020 in five Chinese provinces. Logistic regression and path analysis were adopted. The prevalence of BICV-F and BICV-SP were 78.1% and 57.7%. BICV-F was positively associated with the frequencies of passive social media exposure (adjusted odds ratio (AOR) = 1.32, P < 0.001), active social media interaction (AOR = 1.13, P < 0.001) and peer discussions (AOR = 1.17, P < 0.001). Indirect effects of the three factors on BICV-F via perceived information sufficiency were all significant (P < 0.001). The direct effect of active social media interaction on BICV-F was significantly negative (P < 0.001). Similar associations/mediations were observed for BICV-SP. The COVID-19 vaccination intention of Chinese university students needs improvement. Boosting social media exposures and peer discussions may raise students' perceived information sufficiency and subsequently increase their vaccination intention. Considering the potential negative effect of active social media interaction, caution is needed when using social media to promote COVID-19 vaccination.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emerged as an unprecedented global crisis challenging health systems. This paper aims to assess and characterise SARS-CoV-2 outbreaks in the state of Baden-Wuerttemberg to identify groups at greatest risk, to establish early measures to curb transmission. We analysed all mandatory notified (i.e. laboratory-confirmed) coronavirus disease (COVID-19) outbreaks with more than two cases in Baden-Wuerttemberg from calendar weeks 18–49 (from 27 April to 6 December 2020). We used the following classification for settings: asylum and refugee accommodation, care homes, care facilities, day care child centres, hobby-related, hospitality, hospitals, households, other, residence halls, schools, supported housing, training schools, transportation, treatment facilities and workplace (occupational). We used R program version 3.6.3 for analysis. In our analysis, 3219 outbreaks with 22 238 individuals were included. About 48% were in household and hobby-related settings. Care homes accounted for 9.5% of outbreaks and 21.6% of cases. The median age across all settings was 43 (interquartile range (IQR) 24–63). The median age of cases in care homes was 81 (IQR 56–88). Of all reported cases in care homes, 72.1% were women. Over 30% (466/1511) of hospitalisations were among cases in care homes compared to 17.7% (268/1511) in households. Overall, 70% (500/715) of all deceased persons in outbreaks in the study period were in care homes compared to 4.2% in household settings (30/715). We observed an exponential increase in the number of notified outbreaks starting around the 41st week with N = 291 outbreaks reported in week 49. The median number of cases in outbreaks in care homes and care facilities after the 40th week was 14 (IQR 5–29) and 11 (IQR 5–20), respectively, compared to 3 (IQR 3–5) in households. We observed an increase in hospitalisations, and mortality associated with COVID-19 outbreaks in care homes after the 40th week. We found the care home demographic to be at greatest risk after the 40th week, based on the exponential increase in outbreaks, the number of cases, hospitalisations and mortality trends. Our analysis highlights the necessity of targeted, setting-specific approaches to control transmission in this vulnerable population. Regular screening of staff members and visitors' using rapid antigen point-of-care-tests could be a game-changer in curbing transmission in this setting.