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Zn deficiency compromises its biological functions, its effect on the immune system and its antiviral activity, increasing vulnerability to infectious diseases. This narrative review aims at presenting and discussing functional aspects and possible mechanisms involved in the potential role of Zn in the immune response and antiviral activity for coronavirus infectious disease-19 (COVID-19) prevention and control. The searches were conducted in PubMed and Science Direct databases, using clinical trials, experimental studies in animals and humans, case–control studies, case series, letters to the editor, and review articles published in English, without restrictions on year of publication. Search approach was based on using the terms: ‘zinc’, ‘COVID-19’, ‘antiviral agents’, ‘immunologic factors’ and ‘respiratory tract infections’. Literature shows the importance of Zn as an essential mineral immunomodulator with relevant antiviral activity in the body. Thus, although there is still a scarcity of studies evaluating Zn supplementation in patients with COVID-19, the results on the topic show the necessity of controlling Zn mineral deficiency, as well as maintaining its homoeostasis in the body in order to strengthen the immune system and improve the prevention of highly complex viral infections, such as that of the COVID-19.

Objective:To explore women’s perceptions of changes in specific food habits at home, specifically the food budget and shopping, and food preparation, during the COVID-19 period.Design:Non-probabilistic, exploratory study. Participants completed an online self-administered questionnaire. Perceptions of food habit changes were measured on a five-point Likert scale (strongly disagree to strongly agree). Data analysis was conducted in STATA v16.0.Setting:Chile.Participants:Adult women between 25 and 65 years old (n2047).Results:Of the participants, 72 % were responsible for cooking, 69 % for buying food and 85 % for child care. Difficulties in organising and doing food budget works were observed in groups with a lower educational level, lower income and single mothers with children. Younger participants, dependent workers, women from biparental families with children and those in mandatory quarantine perceived more changes in their food shopping and budget management tasks. Participants more educated, with higher income and non-mandatory quarantine perceived to cook and eat healthier. Older participants perceived minor changes in their food preparation tasks at home; in contrast, more educated women and women from biparental families with children perceived more changes. If women were in charge of the kids or grocery shopping, more food environment changes were noticed.Conclusions:Women perceived changes in their food environments. Some of these changes are perceived worse in the more vulnerable population. COVID-19 presents a challenge for the food system and gender perspectives. This information should be considered in the design of food-related interventions.

Objective:To assess changes in daily habits, food choices and lifestyle of adult Brazilians before and during the COVID-19 pandemic.Design:This observational study was carried out with Brazilian adults through an online questionnaire 5 months after the social distance measures implementation. The McNemar, McNemar–Bowker and Wilcoxon tests were used to investigate differences before and during the COVID pandemic period, adopting the statistical significance of P < 0·05.Setting:Brazil.Participants:Totally, 1368 volunteers aged 18+ years.Results:The volunteers reported a lower frequency of breakfast, morning and lunch snacks (P < 0·05) and a higher frequency of evening snacks and other meal categories during the pandemic period (P < 0·05). The results showed an increase in the consumption of bakery products, instant meals and fast food, while the consumption of vegetables and fruits decreased (P < 0·005). There was a significant increase in the frequency of consumption of alcoholic beverages (P < 0·001), but a reduction in the dose (P < 0·001), increased frequency of smoking (P = 0·007), an increase in sleep and screen time in hours and decrease in physical activity (P < 0·001).Conclusions:It was possible to observe an increase in screen time, hours of sleep, smoking and drinking frequency. On the other hand, there was a reduction in the dose of alcoholic beverages but also in the practice of physical activity. Eating habits also changed, reducing the performance of daytime meals and increasing the performance of nighttime meals. The frequency of consumption of instant meals and fast food has increased, while consumption of fruits and vegetables has decreased.

Objective:To assess changes in dietary patterns among youths in China after COVID-19 lockdown.Design:This study was based on the COVID-19 Impact on Lifestyle Change Survey (COINLICS), a national retrospective survey established in early May 2020. The questionnaire was distributed through social media platforms. The sociodemographic information and routine dietary patterns before and after lockdown of participants were investigated. t tests and χ2 tests were used to compare the differences in consumption patterns of twelve major food groups and beverages between sex and across educational levels before and after lockdown. Factor analysis was employed to obtain the main dietary patterns.Settings:China.Participants:A total of 10 082 youths.Results:A significant decrease was observed in the average weekly frequency of rice intake, while significant increases were observed in the frequency of intake of wheat products, other staple foods, fish, eggs, fresh vegetables, preserved vegetables, fresh fruit and dairy products (all P values < 0·01). Heterogeneities of average weekly frequency existed between sex and across educational levels to different extents. The three main dietary patterns derived were loaded most heavily on dairy products, rice and wheat products, separately; the rice pattern became more dominant than the wheat products pattern after lockdown. The frequency of sugar-sweetened beverage consumption had decreased, while the frequency of other beverages had increased.Conclusions:Our timely survey would inform policymakers and health professionals of these significant changes in youths’ dietary patterns after lockdown, with heterogeneities observed to different extents between sex and across educational levels, for better policy-making and public health practice.

Summary Telemedicine is the use of telecommunication and information technologies to support the delivery of healthcare at a distance, guaranteeing patients healthcare by facilitating access where barriers exist; the COVID-19 pandemic has attracted worldwide interest in this field. The purpose of this paper is to highlight the main pros and cons of telemedicine, which serve as the basis of the WONCA Europe Statement at the WHO Europe 70th Regional Meeting on 14 September 2020. Pros of telemedicine include virtual healthcare at home, where patients receive support in certain conditions without leaving their houses. During a pandemic, it can be adopted to limit physical human interaction. Unfortunately, it can negatively affect the quality of the doctor–patient relationship, the quality of the physical examination, and the quality of care. Telemedicine requires effective infrastructure and robust investments to be feasible and effective.

Objectives:The study aimed to determine the associated factors of household food security (HFS) and household dietary diversity (HDD) during the COVID−19 pandemic in Bangladesh.Design:Both online survey and face-to-face interviews were employed in this cross-sectional study. The Household Food Security Scale and Household Dietary Diversity Score were used to access HFS and HDD, respectively. The HDD scores were derived from a 24-h recall of food intake from 12 groups.Setting:Bangladesh.Participants:A total sample of 1876 households were recruited.Results:The overall mean scores of HFS and HDD were 31·86 (sd 2·52) and 6·22 (sd 5·49), respectively. Being a rural resident, having no formal education, occupation of household head other than government job and low monthly income were potential determinants of lower HFS and HDD. Approximately 45 % and 61 % of Bangladeshi households did not get the same quantity and same type of food, respectively, as they got before the pandemic. Over 10 % of respondents reported that they lost their job or had to close their businesses, and income reduction was reported by over 70 % of household income earners during the COVID-19 pandemic, which in turn was negatively associated with HFS and HDD.Conclusion:Household socio-economic variables and COVID-19 effects on occupation and income are potential predictors of lower HFS and HDD scores. HFS and HDD deserve more attention during this pandemic particularly with reference to low-earning households and the households whose earning persons’ occupation has been negatively impacted during the COVID-19 pandemic.

Objective:To examine how food insecurity is related to emerging adults’ food behaviours and experiences of neighbourhood safety and discrimination and to identify resources needed to support their health during the COVID-19 outbreak.Design:Rapid response online survey. Participants completed the six-item US Household Food Security Survey Module, a brief measure of food insufficiency, and measures of food behaviours, neighbourhood safety and discrimination. Open-ended questions were used to assess changes in eating behaviours during COVID-19 and needed resources.Setting:C-EAT (COVID-19 Eating and Activity over Time) study invitations were sent by email and text message to a longitudinal cohort.Participants:A total of 218 emerging adults (mean age = 24·6 (sd 2·0) years, 70·2 % female) completed a survey in April–May 2020 during a stay-at-home order in Minnesota.Results:The past year prevalence of food insecurity was 28·4 %. Among food-insecure respondents, 41·0 % reported both eating less and experiencing hunger due to lack of money in the past month. Food-insecure respondents were less likely than those who were food secure to have fruits/vegetables at home and more likely to have frequent fast-food restaurant meals, feel unsafe in their neighbourhood and experience discrimination during the stay-at-home order. Food-insecure adults reported changes including eating more food prepared at home, eating more take-out restaurant meals and purchasing more energy-dense snacks as a result of events related to COVID-19. Resources most needed to support their health included eligibility for more food assistance and relief funds.Conclusions:Food-insecure emerging adults experience many barriers to maintaining healthful eating patterns during COVID-19.

Objective:To validate the telephone modality of the Latin American and Caribbean Food Security Scale (ELCSA) included in three waves of a phone survey to estimate the monthly household food insecurity prevalence during the COVID-19 pandemic in Mexico.Design:We examined the reliability and internal validity of the ELCSA scale in three repeated waves of cross-sectional surveys with Rasch models. We estimated the monthly prevalence of food insecurity in the general population and in households with and without children and compared them with a national 2018 survey. We tested concurrent validity by testing associations of food insecurity with socio-economic status and anxiety.Setting:ENCOVID-19 is a monthly telephone cross-sectional survey collecting information on the well-being of Mexican households during the pandemic lockdown. Surveys used probabilistic samples, and we used data from April (n 833), May (n 850) and June 2020 (n 1674).Participants:Mexicans 18 years or older who had a mobile telephone.Results:ELCSA had an adequate model fit and food insecurity was associated, within each wave, with more poverty and anxiety. The COVID-19 lockdown was associated with an important reduction in food security, decreasing stepwise from 38·9 % in 2018 to 24·9 % in June 2020 in households with children.Conclusions:Telephone surveys were a feasible strategy to monitor reductions in food security during the COVID-19 lockdown.

Background Health and social care workers (HSCWs) are at risk of experiencing adverse mental health outcomes (e.g. higher levels of anxiety and depression) because of the COVID-19 pandemic. This can have a detrimental effect on quality of care, the national response to the pandemic and its aftermath. Aims A longitudinal design provided follow-up evidence on the mental health (changes in prevalence of disease over time) of NHS staff working at a remote health board in Scotland during the COVID-19 pandemic, and investigated the determinants of mental health outcomes over time. Method A two-wave longitudinal study was conducted from July to September 2020. Participants self-reported levels of depression (Patient Health Questionnaire-9), anxiety (Generalised Anxiety Disorder-7) and mental well-being (Warwick-Edinburgh Mental Well-being Scale) at baseline and 1.5 months later. Results The analytic sample of 169 participants, working in community (43%) and hospital (44%) settings, reported substantial levels of depression and anxiety, and low mental well-being at baseline (depression, 30.8%; anxiety, 20.1%; well-being, 31.9%). Although mental health remained mostly constant over time, the proportion of participants meeting the threshold for anxiety increased to 27.2% at follow-up. Multivariable modelling indicated that working with, and disruption because of, COVID-19 were associated with adverse mental health changes over time. Conclusions HSCWs working in a remote area with low COVID-19 prevalence reported substantial levels of anxiety and depression, similar to those working in areas with high COVID-19 prevalence. Efforts to support HSCW mental health must remain a priority, and should minimise the adverse effects of working with, and disruption caused by, the COVID-19 pandemic.

Given the fast spread of the novel coronavirus (COVID-19) worldwide and its classification by the World Health Organization (WHO) as being one of the worst pandemics in history, several scientific studies are carried out using various statistical and mathematical models to predict and study the likely evolution of this pandemic in the world. In the present research paper, we present a brief study aiming to predict the probability of reaching a new record number of COVID-19 cases in Lebanon, based on the record theory, giving more insights about the rate of its quick spread in Lebanon. The main advantage of the records theory resides in avoiding several statistical constraints concerning the choice of the underlying distribution and the quality of the residuals. In addition, this theory could be used, in cases where the number of available observations is somehow small. Moreover, this theory offers an alternative solution in case where machine learning techniques and long-term memory models are inapplicable because they need a considerable amount of data to be performant. The originality of this paper lies in presenting a new statistical approach allowing the early detection of unexpected phenomena such as the new pandemic COVID-19. For this purpose, we used epidemiological data from Johns Hopkins University to predict the trend of COVID-2019 in Lebanon. Our method is useful in calculating the probability of reaching a new record as well as studying the propagation of the disease. It also computes the probabilities of the waiting time to observe the future COVID-19 record. Our results obviously confirm the quick spread of the disease in Lebanon over a short time.

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.

The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is highly contagious, and the coronavirus disease 2019 (COVID-19) pandemic caused by it has forced many countries to adopt ‘lockdown’ measures to prevent the spread of the epidemic through social isolation of citizens. Some countries proposed universal mask wearing as a protection measure of public health to strengthen national prevention efforts and to limit the wider spread of the epidemic. In order to reveal the epidemic prevention efficacy of masks, this paper systematically evaluates the experimental studies of various masks and filter materials, summarises the general characteristics of the filtration efficiency of isolation masks with particle size, and reveals the actual efficacy of masks by combining the volume distribution characteristics of human exhaled droplets with different particle sizes and the SARS-CoV-2 virus load of nasopharynx and throat swabs from patients. The existing measured data show that the filtration efficiency of all kinds of masks for large particles and extra-large droplets is close to 100%. From the perspective of filtering the total number of pathogens discharged in the environment and protecting vulnerable individuals from breathing live viruses, the mask has a higher protective effect. If considering the weighted average filtration efficiency with different particle sizes, the filtration efficiencies of the N95 mask and the ordinary mask are 99.4% and 98.5%, respectively. The mask can avoid releasing active viruses to the environment from the source of infection, thus maximising the protection of vulnerable individuals by reducing the probability of inhaling a virus. Therefore, if the whole society strictly implements the policy of publicly wearing masks, the risk of large-scale spread of the epidemic can be greatly reduced. Compared with the overall cost of social isolation, limited personal freedoms and forced suspension of economic activities, the inconvenience for citizens caused by wearing masks is perfectly acceptable.

BackgroundDuring the first wave of the coronavirus disease 2019 (COVID-19) pandemic, patients with confirmed cases in New York State accounted for roughly 25% of total US cases, with psychiatric hospital in-patients at particularly high risk for COVID-19 infection.AimsThe beneficial effects of mental health medications, such as selective serotonin reuptake inhibitors (SSRIs), on the severity of COVID-19 disease outcomes have been documented. Protective effects against infection have also been suggested for these medications. We therefore tested the hypothesis that medication use modifies the risk of COVID-19 infection in a long-stay, chronic in-patient psychiatry setting, where the potential for exposure was likely uniform across the facility, and where these medications were routinely prescribed.MethodThis was a retrospective cohort study of an adult psychiatric facility operated by the New York State Office of Mental Health. Current medication information and COVID-19 status was collected from electronic medical records for 165 people who were in-patients during the period January to July 2020, and logistic regression was employed to model the main effects of medication use on COVID-19 infection.ResultsA significant protective association was observed between antidepressant use and COVID-19 infection (odds ratio (OR) = 0.33, 95% CI 0.15–0.70, adjusted P < 0.05). Analysis of individual antidepressant classes showed that SSRI, serotonin-norepinephrine reuptake inhibitor and the serotonin-2 antagonist reuptake inhibitor classes of antidepressants, drove this protective effect. Exploratory analyses of individual antidepressants demonstrated an association between lower risk of infection and fluoxetine use (P = 0.023), as well as trazodone use (P = 0.001).ConclusionsThe novel finding of reduced COVID-19 infection risk for psychiatric in-patients taking antidepressants, suggests that antidepressants may be an important weapon in the continued fight against COVID-19 disease. This finding may become particularly salient for in-patient settings if vaccine-resistant strains of the virus appear.

Coronavirus disease-2019 (COVID-19) elicits a range of different responses in patients and can manifest into mild to very severe cases in different individuals, depending on many factors. We aimed to establish a prediction model of severe risk in COVID-19 patients, to help clinicians achieve early prevention, intervention and aid them in choosing effective therapeutic strategy. We selected confirmed COVID-19 patients who were admitted to First Hospital of Changsha city between 29 January and 15 February 2020 and collected their clinical data. Multivariate logical regression was used to identify the factors associated with severe risk. These factors were incorporated into the nomogram to establish the model. The ROC curve, calibration plot and decision curve were used to assess the performance of the model. A total of 228 patients were enrolled and 33 (14.47%) patients developed severe pneumonia. Univariate and multivariate analysis showed that shortness of breath, fatigue, creatine kinase, lymphocytes and h CRP were independent factors for severe risk in COVID-19 patients. Incorporating age, chronic obstructive pulmonary disease (COPD) and these factors, the nomogram achieved good concordance indexes of 0.89 [95% confidence interval (CI) 0.832–0.949] and well-fitted calibration plot curves (Hosmer–Lemeshow test: P = 0.97). The model provided superior net benefit when clinical decision thresholds were between 15% and 85% predicted risk. Using the model, clinicians can intervene early, improve therapeutic effects and reduce the severity of COVID-19, thus ensuring more targeted and efficient use of medical resources.

Vulnerability to coronavirus disease (COVID)-19 varies due to differences in interferon gamma (IFNγ) immunity. We investigated whether a key modifiable interferon precursor, interleukin-18, was related to COVID-19, overall and by severity, using Mendelian randomisation. We used four established genome-wide significant genetic predictors of interleukin-18 applied to the most recent genome-wide association study of COVID-19 (June 2021) to obtain Mendelian randomisation inverse variance weighted estimates by severity, i.e. any (cases = 112 612, non-cases = 2 474 079), hospitalised (cases = 24 274, non-cases = 2 061 529) and very severe (cases = 8779, non-cases = 1 001 875) COVID-19. To be comprehensive, we also conducted an exploratory analysis for IFNγ and two related cytokines with less well-established genetic predictors, i.e. interleukin-12 and interleukin-23. Genetically predicted interleukin-18 was associated with lower risk of any COVID-19 (odds ratio (OR) 0.96 per standard deviation, 95% confidence interval (0.94–0.99, P-value 0.004)) and of very severe COVID-19 (OR 0.88, 95% CI 0.78–0.999, P-value 0.048). Sensitivity analysis and a more liberal genetic instrument selection gave largely similar results. Few genome-wide significant genetic predictors were available for IFNγ, interleukin-12 or interleukin-23, and no associations with COVID-19 were evident. Interleukin-18 could be a modifiable target to prevent COVID-19 and should be further explored in an experimental design.

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.

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.

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.

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.

We quantified the potential impact of different social distancing and self-isolation scenarios on the coronavirus disease 2019 (COVID-19) pandemic trajectory in Saudi Arabia and compared the modelling results to the confirmed epidemic trajectory. Using the susceptible, exposed, infected, quarantined and self-isolated, requiring hospitalisation, recovered/immune individuals, fatalities model, we assessed the impact of a non-pharmacological interventions’ subset. An unmitigated scenario (baseline), mitigation scenarios (25% reduction in social contact/twofold increase in self-isolation) and enhanced mitigation scenarios (50% reduction in social contact/twofold increase in self-isolation) were assessed and compared to the actual epidemic trajectory. For the unmitigated scenario, mitigation scenarios, enhanced mitigation scenarios and actual observed epidemic, the peak daily incidence rates (per 10 000 population) were 77.00, 16.00, 9.00 and 1.14 on days 71, 54, 35 and 136, respectively. The peak fatality rates were 35.00, 13.00, 5.00 and 0.016 on days 150, 125, 60 and 155, respectively. The R0 was 1.15, 1.14, 1.22 and 2.50, respectively. Aggressive implementation of social distancing and self-isolation contributed to the downward trend of the disease. We recommend using extensive models that comprehensively consider the natural history of COVID-19, social and behavioural patterns, age-specific data, actual network topology and population to elucidate the epidemic's magnitude and trajectory.

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 (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.

In a Nicaraguan population-based cohort, SARS-CoV-2 seroprevalence reached 28% in the first 6 months of the country's epidemic and reached 35% 6 months later. Immune waning was uncommon. Individuals with a seropositive household member were over three times as likely to be seropositive themselves, suggesting the importance of household transmission.

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.

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.

Objective:The coronavirus disease 2019 (COVID-19) pandemic has led to global shortages of N95 respirators. Reprocessing of used N95 respirators may provide a higher filtration crisis alternative, but whether effective sterilization can be achieved for a virus without impairing respirator function remains unknown. We evaluated the viricidal efficacy of Bioquell vaporized hydrogen peroxide (VHP) on contaminated N95 respirators and tested the particulate particle penetration and inhalation and exhalation resistance of respirators after multiple cycles of VHP.Methods:For this study, 3M 1870 N95 respirators were contaminated with 3 aerosolized bacteriophages: T1, T7, and Pseudomonas phage phi-6 followed by 1 cycle of VHP decontamination using a BQ-50 system. Additionally, new and unused respirators were sent to an independent laboratory for particulate filter penetration testing and inhalation and exhalation resistance after 3 and 5 cycles of VHP.Results:A single VHP cycle resulted in complete eradication of bacteriophage from respirators (limit of detection 10 PFU). Respirators showed acceptable limits for inhalation/exhalation resistance after 3 and 5 cycles of VHP. Respirators demonstrated a filtration efficiency >99 % after 3 cycles, but filtration efficiency fell below 95% after 5 cycles of HPV.Conclusion:Bioquell VHP demonstrated high viricidal activity for N95 respirators inoculated with aerosolized bacteriophages. Bioquell technology can be scaled for simultaneous decontamination of a large number of used but otherwise intact respirators. Reprocessing should be limited to 3 cycles due to concerns both about impact of clinical wear and tear on fit, and to decrement in filtration after 3 cycles.