ABSTRACT
Remarkable progress has been made in developing intramuscular vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); however, they are limited with respect to eliciting local immunity in the respiratory tract, which is the primary infection site for SARS-CoV-2. To overcome the limitations of intramuscular vaccines, we constructed a nasal vaccine candidate based on an influenza vector by inserting a gene encoding the receptor-binding domain (RBD) of the spike protein of SARS-CoV-2, named CA4-dNS1-nCoV-RBD (dNS1-RBD). A preclinical study showed that in hamsters challenged 1 day and 7 days after single-dose vaccination or 6 months after booster vaccination, dNS1-RBD largely mitigated lung pathology, with no loss of body weight, caused by either the prototype-like strain or beta variant of SARS-CoV-2. Lasted data showed that the animals could be well protected against beta variant challenge 9 months after vaccination. Notably, the weight loss and lung pathological changes of hamsters could still be significantly reduced when the hamster was vaccinated 24 h after challenge. Moreover, such cellular immunity is relatively unimpaired for the most concerning SARS-CoV-2 variants. The protective immune mechanism of dNS1-RBD could be attributed to the innate immune response in the nasal epithelium, local RBD-specific T cell response in the lung, and RBD-specific IgA and IgG response. Thus, this study demonstrates that the intranasally delivered dNS1-RBD vaccine candidate may offer an important addition to fight against the ongoing COVID-19 pandemic, compensating limitations of current intramuscular vaccines, particularly at the start of an outbreak.
Subject(s)
Coronavirus Infections , Weight Loss , COVID-19ABSTRACT
Background: Since the first case of pneumonia with unknown etiology was identified in Wuhan, Hubei province in China in December 2019, the novel coronavirus pneumonia has placed a serious impact on many aspects of the world. Note that the incubation period distribution plays important roles in prevention and control efforts of COVID-19. This study aimed to investigate the conditional distribution of the incubation period of COVID-19 on the age of infected cases, and estimate its corresponding quantiles from information of 2172 confirmed cases from 29 provinces outside Hubei in China.Methods: We collected data including the infection dates, onset dates, and ages of the confirmed cases from the websites of the centres of disease control, or the daily public reports through February 16th, 2020. A maximum likelihood method was developed to account for the biased sampling issue of the data as the epidemic was still ongoing at the time of collecting data. Results: Based on the collected data, we found that the conditional quantiles of the incubation period distribution of COVID-19 varies over ages. In detail, the high conditional quantiles of people in the middle age group are shorter than those of others. We estimated that the 0.95-th quantile related to people in the age group 23∼55 is less than 15 days. Conclusions: Observing that the conditional quantiles vary over ages, we may take more precise measures for people of different ages. For example, we may consider carrying out an age-dependent quarantine duration, rather than a uniform 14-days quarantine, in practice. Remarkably, we may need to extend the current quarantine duration for people aged 0 ∼ 22 and over 55 because the related 0.95-th quantiles are much greater than 14 days.
Subject(s)
COVID-19 , Coronavirus Infections , PneumoniaABSTRACT
Background: In December 2019, a novel coronavirus-associated pneumonia, now known as coronavirus disease 2019 (COVID-19), was first detected in Wuhan, China. To prevent the rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and treat patients with mild symptoms, sports stadiums and convention centers were reconstructed into mobile hospitals. Research Question: It is unknown whether a mobile cabin hospital can provide a safe treatment site for patients with mild COVID-19 symptoms. Study Design and Methods: This study retrospectively reviewed the medical records of 421 patients with COVID-19 admitted to a mobile cabin hospital in Wuhan from February 9, 2020, to March 5, 2020. Clinical data comprised patient age, sex, clinical presentation, chest imaging, nucleic acid testing, length of hospitalization, and outcomes. Results: Of the patients who were discharged from the cabin hospital, 362 (86.0%) were categorized as recovered;14.0% developed severe symptoms and were transferred to a designated hospital. The most common presenting symptoms were fever (60.6%) and cough (52.0%);5.2% exhibited no obvious symptoms. High fever (> 39.0°C) was more common in severe cases than in recovered cases (18.6% vs 6.6%). The distribution of lung lesions was peripheral in 85.0% of patients, multifocal in 69.4%, and bilateral in 68.2%. The most common pattern was ground-glass opacity (67.7%), followed by patchy shadowing (49.2%). The incidence of patchy shadowing was higher in patients with severe disease (66.1%) than in those who recovered (31.8%, P < .0001). The median length of hospitalization was 17 days (interquartile range, 14-19 days), and the median time taken for positive real-time reverse transcriptase polymerase chain reaction results to become negative in recovered patients was 8 days (interquartile range, 6-10 days). Interpretation: Mobile cabin hospitals provide a safe treatment site for patients with mild COVID-19 symptoms and offer an effective isolation area to prevent the spread of severe acute respiratory syndrome coronavirus 2.
ABSTRACT
Background: Evidence regarding the effects of ambient air pollutants and meteorological factors on COVID-19 transmission is limited. Objectives: To explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases across 31 Chinese provinces during the outbreak period. Methods: The number of COVID-19 confirmed cases, air pollutant concentrations and meteorological factors in 31 Chinese provinces from January 25 to February 29, 2020 were extracted from authoritative electronic databases. The associations were estimated for a single-day lag (lag0-lag6) as well as moving averages lag (lag01-lag05) using generalized additive mixed models (GAMMs), adjusted for time trends, day of the week, holidays and meteorological variables. Region-specific analyses and meta-analysis were conducted in five selected regions with diverse air pollution levels and weather conditions. Nonlinear exposure-response analyses were performed. Results: We examined 77,578 COVID-19 confirmed cases across 31 Chinese provinces during the study period. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3 and CO at lag4 corresponded to 1.40 (1.37-1.43), 1.35 (1.32-1.37), 1.01 (1.00-1.02), 1.08 (1.07-1.10), 1.28 (1.27-1.29) and 1.26 (1.24-1.28) odds ratios (ORs) of daily COVID-19 confirmed new cases, respectively. For 1 oc, 1% and 1 m/s increase in temperature, relative humidity and wind velocity, the ORs were 0.97 (0.97-0.98), 0.96 (0.96-0.97), and 0.94 (0.92-0.95), respectively. The estimates of PM2.5, PM10, NO2 and all meteorological factors remained statistically significant after meta-analysis for the five selected regions. The exposure-response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily COVID-19 confirmed new cases increasing. Conclusions: Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. As summer months are arriving in the Northern Hemisphere, the environmental factors and implementation of public health control measures may play an optimistic role in controlling COVID-19 epidemic.
Subject(s)
COVID-19ABSTRACT
Background : In December 2019, some cases of pneumonia with unknown etiology were identified in Wuhan, Hubei province in China. The World Health Organization (WHO) has named this disease as COVID-19, standing for ``2019 coronavirus disease", and announced the disease have become a public health incident on December 31, 2019. This study aimed to investigate the conditional distribution of the incubation period of COVID-19 on the age of infected cases, and estimate its corresponding conditional quantiles from information on 2172 confirmed cases from 29 provinces outside Hubei in China. Methods : We collected data including the infection dates, onset dates, and ages of the confirmed cases from the websites of the centres of disease control, or the daily public reports through February 16th, 2020. A new maximum likelihood method was developed to account for the biased sampling, or right truncation, issue of the data as the epidemic is still ongoing. The estimators can be shown to be consistent asymptotically under mild conditions. Results : Based on the collected data, we found that the conditional quantiles of the incubation period distribution of COVID-19 varies over ages. In detail, the high conditional quantiles of people in the middle age group are shorter than those of others. We estimated that the 0.95-th quantile related to people in the age group 23$\sim$55 is less than 15 days. Conclusions : Observing that the conditional quantiles vary over ages, we may take more precise measures for people of different ages. For example, we may consider carrying out an age-dependent quarantine duration, rather than a uniform 14-days quarantine, in practice. Remarkably, we may need to extend the current quarantine duration for people aged $0\sim22$ and over 55 because the related 0.95-th quantiles are much greater than 14 days.