Random forest regression on joint role of meteorological variables, demographic factors, and policy response measures in COVID-19 daily cases: global analysis in different climate zones.

Different sources of factors in environment can affect the spread of COVID-19 by influencing the diffusion of the virus transmission, but the collective influence of which has hardly been considered. This study aimed to utilize a machine learning algorithm to assess the joint effects of meteorological variables, demographic factors, and government response measures on COVID-19 daily cases globally at city level. Random forest regression models showed that population density was the most crucial determinant for COVID-19 transmission, followed by meteorological variables and response measures. Ultraviolet radiation and temperature dominated meteorological factors, but the associations with daily cases varied across different climate zones. Policy response measures have lag effect in containing the epidemic development, and the pandemic was more effectively contained with stricter response measures implemented, but the generalized measures might not be applicable to all climate conditions. This study explored the roles of demographic factors, meteorological variables, and policy response measures in the transmission of COVID-19, and provided evidence for policymakers that the design of appropriate policies for prevention and preparedness of future pandemics should be based on local climate conditions, population characteristics, and social activity characteristics. Future work should focus on discerning the interactions between numerous factors affecting COVID-19 transmission.

Association between meteorological factors and COVID-19 transmission in low- and middle-income countries: A time-stratified case-crossover study.

BACKGROUND: Evidence is limited regarding the association between meteorological factors and COVID-19 transmission in low- and middle-income countries (LMICs). OBJECTIVE: To investigate the independent and interactive effects of temperature, relative humidity (RH), and ultraviolet (UV) radiation on the spread of COVID-19 in LMICs. METHODS: We collected daily data on COVID-19 confirmed cases, meteorological factors and non-pharmaceutical interventions (NPIs) in 2143 city- and district-level sites from 6 LMICs during 2020. We applied a time-stratified case-crossover design with distributed lag nonlinear model to evaluate the independent and interactive effects of meteorological factors on COVID-19 transmission after controlling NPIs. We generated an overall estimate through pooling site-specific relative risks (RR) using a multivariate meta-regression model. RESULTS: There was a positive, non-linear, association between temperature and COVID-19 confirmed cases in all study sites, while RH and UV showed negative non-linear associations. RR of the 90th percentile temperature (28.1 °C) was 1.14 [95% confidence interval (CI): 1.02, 1.28] compared with the 50th percentile temperature (24.4 °C). RR of the10th percentile UV was 1.41 (95% CI: 1.29, 1.54). High temperature and high RH were associated with increased risks in temperate climate but decreased risks in tropical climate, while UV exhibited a consistent, negative association across climate zones. Temperature, RH, and UV interacted to affect COVID-19 transmission. Temperature and RH also showed higher risks in low NPIs sites. CONCLUSION: Temperature, RH, and UV appeared to independently and interactively affect the transmission of COVID-19 in LMICs but such associations varied with climate zones. Our results suggest that more attention should be paid to meteorological variation when the transmission of COVID-19 is still rampant in LMICs.

A systematic hybrid machine learning approach for stress prediction.

Stress is becoming an increasingly prevalent health issue, seriously affecting people and putting their health and lives at risk. Frustration, nervousness, and anxiety are the symptoms of stress and these symptoms are becoming common (40%) in younger people. It creates a negative impact on human lives and damages the performance of each individual. Early prediction of stress and the level of stress can help to reduce its impact and different serious health issues related to this mental state. For this, automated systems are required so they can accurately predict stress levels. This study proposed an approach that can detect stress accurately and efficiently using machine learning techniques. We proposed a hybrid model (HB) which is a combination of gradient boosting machine (GBM) and random forest (RF). These models are combined using soft voting criteria in which each model's prediction probability will be used for the final prediction. The proposed model is significant with 100% accuracy in comparison with the state-of-the-art approaches. To show the significance of the proposed approach we have also done 10-fold cross-validation using the proposed model and the proposed HB model outperforms with 1.00 mean accuracy and +/-0.00 standard deviation. In the end, a statistical T-test we have done to show the significance of the proposed approach in comparison with other approaches.

Outbreak investigation in a COVID-19 designated hospital: The combination of phylogenetic analysis and field epidemiology study suggesting airborne transmission.

BACKGROUND: Healthcare-associated COVID-19 infections caused by SARS-CoV-2 have increased morbidity and mortality. Hospitals and skilled nursing facilities (SNFs) have been challenged by infection control and management. METHODS: This case study presents an outbreak investigation in a COVID-19-designated hospital and a hospital-based SNF. Real-time polymerase chain reaction (PCR) and other studies were performed on samples obtained from SNF residents, hospital patients, and healthcare workers (HCWs). The results of the laboratory tests and field epidemiological data were analyzed. Genome sequencing and phylogenetic analysis of SARS-CoV-2 were performed to identify the associations between cases. The tracer gas was released and recorded by a thermal imaging camera to investigate the spatial relations within clusters. RESULTS: During the outbreak, 29 COVID-19 infections in 3 clusters were identified through hospital-wide, risk-guided, and symptom-driven PCR tests. This included 12 HCWs, 5 patients, and 12 SNF residents who had been hospitalized for at least 14 days. Serology tests did not identify any cases among the PCR-negative individuals. The phylogenetic analysis revealed that viral strains from the 3 clusters shared a common mutation of G3994T and were phylogenetically related, which suggested that this outbreak had a common source rather than multiple introductions from the community. Linked cases exhibited vertical spatial distribution, and the sulfur hexafluoride release test confirmed a potential airborne transmission. CONCLUSIONS: This report addressed the advantage of a multi-disciplinary team in outbreak investigation. Identifying an airborne transmission within an outbreak highlighted the importance of regular maintenance of ventilation systems.

Global influenza vaccination rates and factors associated with influenza vaccination.

OBJECTIVES: Influenza vaccination is an effective method for preventing influenza virus infection. Herein, we performed a meta-analysis to quantify global influenza vaccination rates (IVRs) and the factors influencing its uptake in the general population, individuals with chronic diseases, pregnant women, and healthcare workers. METHODS: Related articles were obtained from online databases and screened according to the inclusion criteria. The pooled IVRs were calculated using the random effects model. Subgroup analyses and multivariate meta-regression were performed to determine the factors associated with influenza vaccine uptake. RESULTS: e included 522 studies from 68 countries/regions. Most studies were conducted in the European region (247 studies), followed by the Western Pacific (135 studies) and American regions (100 studies). The IVRs with 95% confidence intervals (CIs) in the general population were lower (24.96%, 23.45%-26.50%) than in individuals with chronic diseases (41.65%, 40.08%-43.23%), healthcare workers (36.57%, 33.74%-39.44%), and pregnant women (25.92%, 23.18%-28.75%). The IVRs in high-income countries/regions were significantly higher than that in middle-income countries/regions. A free national or regional vaccination policy, perception of influenza vaccine efficacy and disease severity, a recommendation from healthcare workers, and having a history of influenza vaccination were positive factors for vaccine uptake (P <0.01). CONCLUSION: Overall, global IVRs were low, especially in the general population. The studies on the IVRs, especially for priority populations, should be strengthened in Eastern Mediterranean, South-East Asian, and African regions. Free vaccination policies and the dissemination of continuous awareness campaigns are effective measures to enhance vaccination uptake.

Quality improvement initiatives in the care and prevention of fragility fractures in the Asia Pacific region.

This narrative review summarises ongoing challenges and progress in the care and prevention of fragility fractures across the Asia Pacific region since mid-2019. The approaches taken could inform development of national bone health improvement Road Maps to be implemented at scale during the United Nations 'Decade of Healthy Ageing'. PURPOSE: This narrative review summarises recent studies that characterise the burden of fragility fractures, current care gaps and quality improvement initiatives intended to improve the care and prevention of fragility fractures across the Asia Pacific region. METHODS: The review focuses on published studies, reports and quality improvement initiatives undertaken during the period July 2019 to May 2022. RESULTS: Epidemiological studies conducted in countries and regions throughout Asia Pacific highlight the current and projected increasing burden of fragility fractures. Recent studies and reports document a persistent and pervasive post-fracture care gap among people who have sustained fragility fractures. Global initiatives developed by the Fragility Fracture Network and International Osteoporosis Foundation have gained significant momentum in the Asia Pacific region, despite the disruption caused by the COVID-pandemic. The Asia Pacific Fragility Fracture Alliance has developed educational resources including a Hip Fracture Registry Toolbox and a Primary Care Physician Education Toolkit. The Asia Pacific Osteoporosis and Fragility Fractures Society-a new section of the Asia Pacific Orthopaedic Association-is working to engage orthopaedic surgeons across the region in the care and prevention of fragility fractures. The Asia Pacific Consortium on Osteoporosis developed a framework to support national clinical guidelines development groups. Considerable activity at the national level is evident in many countries across the region. CONCLUSION: Development and implementation of national Road Maps informed by the findings of this review are urgently required to respond to the epidemiological emergency posed by fragility fractures during the United Nations 'Decade of Healthy Ageing'.

Independent and Interactive Effects of Environmental Conditions on Aerosolized Surrogate SARS-CoV-2 - Beijing, China, June to September 2020.

What is already known about this topic?: Environmental factors such as temperature and humidity play important roles in the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via droplets/aerosols. What is added by this report?: Higher relative humidity (61%-80%), longer spreading time (120 min), and greater dispersal distance (1 m) significantly reduced SARS-CoV-2 pseudovirus loads. There was an interaction effect between relative humidity and spreading time. What are the implications for public health practice?: The findings contribute to our understanding of the impact of environmental factors on the transmission of SARS-CoV-2 via airborne droplets/aerosols.

Wearing time and respiratory volume affect the filtration efficiency of masks against aerosols at different sizes.

Face masks are critical in preventing the spread of respiratory infections including coronavirus disease 2019 (COVID-19). Different types of masks have distinct filtration efficiencies (FEs) with differential costs and supplies. Here we reported the impact of breathing volume and wearing time on the inward and outward FEs of four different mask types (N95, surgical, single-use, and cloth masks) against various sizes of aerosols. Specifically, 1) Mask type was an important factor affecting the FEs. The FEs of N95 and surgical mask were better than those of single-use mask and cloth mask; 2) As particle size decreased, the FEs tended to reduce. The trend was significantly observed in FEs of aerosols with particle size < 1 µ m ; 3) After wearing N95 and surgical masks for 0, 2, 4, and 8 h, their FEs (%) maintained from 95.75 ± 0.09 to 100 ± 0 range. While a significant decrease in FEs were noticed for single-use masks worn for 8 h and cloth masks worn >2 h under deep breathing (30 L/min); 4) Both inward and outward FEs of N95 and surgical masks were similar, while the outward FEs of single-use and cloth masks were higher than their inward FEs; 5) The FEs under deep breathing was significantly lower than normal breathing with aerosol particle size <1 µ m. In conclusion, our results revealed that masks have a critical role in preventing the spread of aerosol particles by filtering inhalation, and FEs significantly decreased with the increasing of respiratory volume and wearing time. Deep breathing may cause increasing humidity and hence decrease FEs by increasing the airflow pressure. With the increase of wearing time, the adsorption capacity of the filter material tends to be saturated, which may reduce FEs. Findings may be used to provide information for policies regarding the proper use of masks for general public in current and future pandemics.

Characteristics of Viral Shedding Time in SARS-CoV-2 Infections: A Systematic Review and Meta-Analysis.

Background: The viral shedding time (VST) of SARS-CoV-2 mainly determines its transmission and duration of infectiousness. However, it was heterogeneous in the existing studies. Here, we performed a meta-analysis to comprehensively summarize the VST of SARS-CoV-2. Methods: We searched PubMed, Web of Science, MedRxiv, BioRxiv, CNKI, CSTJ, and Wanfang up to October 25, 2020, for studies that reported VSTs of SARS-CoV-2. Pooled estimates and 95% CIs for the VSTs were calculated using log-transformed data. The VSTs in SARS-CoV-2 infections based on different demographic and clinical characteristics, treatments and specimens were stratified by subgroup analysis. Results: A total of 35 studies involving 3,385 participants met the inclusion criteria. The pooled mean VST was 16.8 days (95% CI: 14.8-19.4, I2 = 99.56%) in SARS-CoV-2 infections. The VST was significantly longer in symptomatic infections (19.7 days, 95% CI: 17.2-22.7, I2 = 99.34%) than in asymptomatic infections (10.9 days, 95% CI: 8.3-14.3, I2 = 98.89%) (P < 0.05). The VST was 23.2 days (95% CI: 19.0-28.4, I2 = 99.24%) in adults, which was significantly longer than that in children (9.9 days, 95% CI: 8.1-12.2, I2 = 85.74%) (P < 0.05). The VST was significantly longer in persons with chronic diseases (24.2 days, 95% CI: 19.2-30.2, I2 = 84.07%) than in those without chronic diseases (11.5 days, 95% CI: 5.3-25.0, I2 = 82.11%) (P < 0.05). Persons receiving corticosteroid treatment (28.3 days, 95% CI: 25.6-31.2, I2 = 0.00%) had a longer VST than those without corticosteroid treatment (16.2 days, 95% CI: 11.5-22.5, I2 = 92.27%) (P = 0.06). The VST was significantly longer in stool specimens (30.3 days, 95% CI: 23.1-39.2, I2 = 92.09%) than in respiratory tract specimens (17.5 days, 95% CI: 14.9-20.6, I2 = 99.67%) (P < 0.05). Conclusions: A longer VST was found in symptomatic infections, infected adults, persons with chronic diseases, and stool specimens.

One-year follow-up of chest CT findings in patients after SARS-CoV-2 infection.

BACKGROUND: Knowledge about the 1-year outcome of COVID-19 is limited. The aim of this study was to follow-up and evaluate lung abnormalities on serial computed tomography (CT) scans in patients with COVID-19 after hospital discharge. METHODS: A prospective cohort study of patients with COVID-19 from the First Affiliated Hospital, Zhejiang University School of Medicine was conducted, with assessments of chest CT during hospitalization and at 2 weeks, 1 month, 3 months, 6 months, and 1 year after hospital discharge. Risk factors of residual CT opacities and the influence of residual CT abnormalities on pulmonary functions at 1 year were also evaluated. RESULTS: A total of 41 patients were followed in this study. Gradual recovery after hospital discharge was confirmed by the serial CT scores. Around 47% of the patients showed residual aberration on pulmonary CT with a median CT score of 0 (interquartile range (IQR) of 0-2) at 1 year after discharge, with ground-glass opacity (GGO) with reticular pattern as the major radiologic pattern. Patients with residual radiological abnormalities were older (p = 0.01), with higher rate in current smokers (p = 0.04), higher rate in hypertensives (p = 0.05), lower SaO2 (p = 0.004), and higher prevalence of secondary bacterial infections during acute phase (p = 0.02). Multiple logistic regression analyses indicated that age was a risk factor associated with residual radiological abnormalities (OR 1.08, 95% CI 1.01-1.15, p = 0.02). Pulmonary functions of total lung capacity (p = 0.008) and residual volume (p < 0.001) were reduced in patients with residual CT abnormalities and were negatively correlated with CT scores. CONCLUSION: During 1-year follow-up after discharge, COVID-19 survivors showed continuous improvement on chest CT. However, residual lesions could still be observed and correlated with lung volume parameters. The risk of developing residual CT opacities increases with age.

Risk factors and on-site simulation of environmental transmission of SARS-CoV-2 in the largest wholesale market of Beijing, China.

From June 11, 2020, a surge in new cases of coronavirus disease 2019 (COVID-19) in the largest wholesale market of Beijing, the Xinfadi Market, leading to a second wave of COVID-19 in Beijing, China. Understanding the transmission modes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the personal behaviors and environmental factors contributing to viral transmission is of utmost important to curb COVID-19 rise. However, currently these are largely unknown in food markets. To this end, we completed field investigations and on-site simulations in areas with relatively high infection rates of COVID-19 at Xinfadi Market. We found that if goods were tainted or personnel in market was infected, normal transaction behaviors between sellers and customers, daily physiological activities, and marketing activities could lead to viral contamination and spread to the surroundings via fomite, droplet or aerosol routes. Environmental factors such as low temperature and high humidity, poor ventilation, and insufficient hygiene facilities and disinfection practices may contribute to viral transmission in Xinfadi Market. In addition, precautionary control strategies were also proposed to effectively reduce the clustering cases of COVID-19 in large-scale wholesale markets.

The value of infectious disease modeling and trend assessment: a public health perspective.

INTRODUCTION: Disease outbreaks of acquired immunodeficiency syndrome, severe acute respiratory syndrome, pandemic H1N1, H7N9, H5N1, Ebola, Zika, Middle East respiratory syndrome, and recently COVID-19 have raised the attention of the public over the past half-century. Revealing the characteristics and epidemic trends are important parts of disease control. The biological scenarios including transmission characteristics can be constructed and translated into mathematical models, which can help to predict and gain a deeper understanding of diseases. AREAS COVERED: This review discusses the models for infectious diseases and highlights their values in the field of public health. This information will be of interest to mathematicians and clinicians, and make a significant contribution toward the development of more specific and effective models. Literature searches were performed using the online database of PubMed (inception to August 2020). EXPERT OPINION: Modeling could contribute to infectious disease control by means of predicting the scales of disease epidemics, indicating the characteristics of disease transmission, evaluating the effectiveness of interventions or policies, and warning or forecasting during the pre-outbreak of diseases. With the development of theories and the ability of calculations, infectious disease modeling would play a much more important role in disease prevention and control of public health.

The epidemiological and radiographical characteristics of asymptomatic infections with the novel coronavirus (COVID-19): A systematic review and meta-analysis.

OBJECTIVES: The role of asymptomatic infections in the transmission of COVID-19 have drawn considerable attention. Here, we performed a meta-analysis to summarize the epidemiological and radiographical characteristics of asymptomatic infections associated with COVID-19. METHODS: Data on the epidemiological and radiographical characteristics of asymptomatic infections were extracted from the existing literature. Pooled proportions with 95% confidence intervals were then calculated using a random effects model. RESULTS: A total of 104 studies involving 20,152 cases were included. The proportion of asymptomatic individuals among those with COVID-19 was 13.34% (10.86%-16.29%), among which presymptomatic and covert infections accounted for 7.64% (4.02%-14.04%) and 8.44% (5.12%-13.62%), respectively. The proportions of asymptomatic infections among infected children and healthcare workers were 32.24% (23.08%-42.13%) and 36.96% (18.51%-60.21%), respectively. The proportion of asymptomatic infections was significantly higher after 2020/02/29 than before (33.53% vs 10.19%) and in non-Asian regions than in Asia (28.76% vs 11.54%). The median viral shedding duration of asymptomatic infections was 14.14 days (11.25-17.04). A total of 47.62% (31.13%-72.87%) of asymptomatic infections showed lung abnormalities, especially ground-glass opacity (41.11% 19.7%-85.79%). CONCLUSIONS: Asymptomatic infections were more commonly found in infected children and healthcare workers and increased after 2020/02/29 and in non-Asian regions. Chest radiographical imaging could be conducive to the early identification of asymptomatic infections.

Risk factors and clinical features of deterioration in COVID-19 patients in Zhejiang, China: a single-centre, retrospective study.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection swept through Wuhan and spread across China and overseas beginning in December 2019. To identify predictors associated with disease progression, we evaluated clinical risk factors for exacerbation of SARS-CoV-2 infection. METHODS: A retrospective analysis was used for PCR-confirmed COVID-19 (coronavirus disease 2019)-diagnosed hospitalized cases between January 19, 2020, and February 19, 2020, in Zhejiang, China. We systematically analysed the clinical characteristics of the patients and predictors of clinical deterioration. RESULTS: One hundred patients with COVID-19, with a median age of 54 years, were included. Among them, 49 patients (49%) had severe and critical disease. Age ([36-58] vs [51-70], P = 0.0001); sex (49% vs 77.6%, P = 0.0031); Body Mass Index (BMI) ([21.53-25.51] vs [23.28-27.01], P = 0.0339); hypertension (17.6% vs 57.1%, P < 0.0001); IL-6 ([6.42-30.46] vs [16.2-81.71], P = 0.0001); IL-10 ([2.16-5.82] vs [4.35-9.63], P < 0.0001); T lymphocyte count ([305-1178] vs [167.5-440], P = 0.0001); B lymphocyte count ([91-213] vs [54.5-163.5], P = 0.0001); white blood cell count ([3.9-7.6] vs [5.5-13.6], P = 0.0002); D2 dimer ([172-836] vs [408-953], P = 0.005), PCT ([0.03-0.07] vs [0.04-0.15], P = 0.0039); CRP ([3.8-27.9] vs [17.3-58.9], P < 0.0001); AST ([16, 29] vs [18, 42], P = 0.0484); artificial liver therapy (2% vs 16.3%, P = 0.0148); and glucocorticoid therapy (64.7% vs 98%, P < 0.0001) were associated with the severity of the disease. Age and weight were independent risk factors for disease severity. CONCLUSION: Deterioration among COVID-19-infected patients occurred rapidly after hospital admission. In our cohort, we found that multiple factors were associated with the severity of COVID19. Early detection and monitoring of these indicators may reduce the progression of the disease. Removing these factors may halt the progression of the disease. In addition, Oxygen support, early treatment with low doses of glucocorticoids and artificial liver therapy, when necessary, may help reduce mortality in critically ill patients.

Factors Associated With Prolonged Viral RNA Shedding in Patients with Coronavirus Disease 2019 (COVID-19).

BACKGROUND: An outbreak of coronavirus disease 2019 (COVID-19) is becoming a public health emergency. Data are limited on the duration and host factors related to viral shedding. METHODS: In this retrospective study, risk factors associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA shedding were evaluated in a cohort of 113 symptomatic patients from 2 hospitals outside Wuhan. RESULTS: The median (interquartile range) duration of SARS-CoV-2 RNA detection was 17 (13-22) days as measured from illness onset. When comparing patients with early (<15 days) and late (≥15 days after illness onset) viral RNA clearance, prolonged SARS-CoV-2 RNA shedding was associated with male sex (P = .009), old age (P = .033), concomitant hypertension (P = .009), delayed admission to hospital after illness onset (P = .001), severe illness at admission (P = .049), invasive mechanical ventilation (P = .006), and corticosteroid treatment (P = .025). Patients with longer SARS-CoV-2 RNA shedding duration had slower recovery of body temperature (P < .001) and focal absorption on radiograph images (P < .001) than patients with early SARS-CoV-2 RNA clearance. Male sex (OR, 3.24; 95% CI, 1.31-8.02), delayed hospital admission (OR, 1.30; 95% CI, 1.10-1.54), and invasive mechanical ventilation (OR, 9.88; 95% CI, 1.11-88.02) were independent risk factors for prolonged SARS-CoV-2 RNA shedding. CONCLUSIONS: Male sex, delayed admission to hospital after illness onset, and invasive mechanical ventilation were associated with prolonged SARS-CoV-2 RNA shedding. Hospital admission and general treatments should be started as soon as possible in symptomatic COVID-19 patients, especially male patients.

Effect of Corticosteroid Therapy on the Duration of SARS-CoV-2 Clearance in Patients with Mild COVID-19: A Retrospective Cohort Study.

INTRODUCTION: In December, 2019, an outbreak of the coronavirus disease 2019 (COVID-19), which was caused by a novel coronavirus, started in Wuhan, China. So far, there is limited clinical evidence on the effect of corticosteroid therapy for this disease. This study aims to investigate the association between corticosteroid therapy and the duration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) clearance among patients with mild COVID-19. METHODS: Patients with mild COVID-19 were enrolled from two medical centers in China between January 13, 2020 and February 29, 2020. Baseline characteristics and durations of RNA clearance were compared between the corticosteroid and non-corticosteroid therapy groups. The independent effects of corticosteroid therapy on the duration of RNA clearance were estimated by generalized linear models. RESULTS: Of 82 patients with a mild infection, 40 patients were male (48.8%), with a median age of 49 years (interquartile range, IQR 36-61). Among those patients, 36 patients (43.9%) received corticosteroid therapy. The adjusted multivariate models showed that the effects of corticosteroids were non-significant on the durations of onset to first RNA clearance [ß 2.48, 95% CI (95% confidence interval) - 0.42 to 5.38, P = 0.0926] and to persistent RNA clearance (ß 1.54, 95% CI - 1.41 to 4.48, P = 0.3016), and durations of therapy to first RNA clearance (ß 2.16, 95% CI - 0.56 to 4.89, P = 0.1184) and to persistent RNA clearance (ß 1.22, 95% CI - 1.52 to 3.95, P = 0.3787). CONCLUSIONS: Corticosteroid therapy in patients with mild COVID-19 was not associated with the duration of SARS-CoV-2 clearance, suggesting that the use of corticosteroids may not be beneficial for patients with mild COVID-19 and should be prudently recommended in clinical practice. However, further studies are needed to verify the findings.

Serotype distribution and clinical characteristics associated with streptococcus pneumoniae among Chinese children and adults with invasive pneumococcal disease: a multicenter observational study.

Few studies in China focused on serotypes of Streptococcus pneumoniae in patients with invasive pneumococcal disease (IPD). We aimed at investigating the serotype distribution for IPD-causing S. pneumoniae and vaccine coverage among Chinese children and adults. This was a multicenter, observational study to collect S. pneumoniae isolates from normal sterile sites and IPD-related clinical information among children and adults. Serotyping was performed by a Capsule-Quellung reaction test using type-specific antisera. The study collected a total of 300 eligible isolates (pediatric = 148, adult = 152) were serotyped in a central laboratory. The most prevalent serotypes were 19A (20.9%) and 23 F (20.3%) in the pediatric group; 3 (21.7%) and 19 F (11.8%) in the adult group. PCV10 had low-to-moderate serotype coverage rates for children (60.8%) and adults (34.2%). PCV13 and PPV23 had high coverage rates for children (89.9%, 93.2%) and adults (70.4%, 82.9%), respectively, Investigational PCVs including PCV15 and PCV20 had high estimated coverage rates in children (89.9%, 93.9%). The study identified 269 subjects with IPD reported as the primary diagnosis in the medical records. Sepsis (48/136, 35.3%) and pneumonia (48/133, 36.1%) had the highest occurrence in the pediatric and adult groups, respectively. Study findings showed that non-PCV7 S. pneumoniae 19A and 3 were the most prevalent serotypes in Chinese children and adults, respectively. High-valent vaccines had similar coverage rates and may have a greater potential in preventing IPD.