Real-time risk ranking of emerging epidemics based on optimized moving average prediction limit-taking the COVID-19 pandemic as an example.

BACKGROUND: Mathematical models to forecast the risk trend of the COVID-19 pandemic timely are of great significance to control the pandemic, but the requirement of manual operation and many parameters hinders their efficiency and value for application. This study aimed to establish a convenient and prompt one for monitoring emerging infectious diseases online and achieving risk assessment in real time. METHODS: The Optimized Moving Average Prediction Limit (Op-MAPL) algorithm model analysed real-time COVID-19 data online and was validated using the data of the Delta variant in India and the Omicron in the United States. Then, the model was utilized to determine the infection risk level of the Omicron in Shanghai and Beijing. RESULTS: The Op-MAPL model can predict the epidemic peak accurately. The daily risk ranking was stable and predictive, with an average accuracy of 87.85% within next 7 days. Early warning signals were issued for Shanghai and Beijing on February 28 and April 23, 2022, respectively. The two cities were rated as medium-high risk or above from March 27 to April 20 and from April 24 to May 5, indicating that the pandemic had entered a period of rapid increase. After April 21 and May 26, the risk level was downgraded to medium and became stable by the algorithm, indicating that the pandemic had been controlled well and mitigated gradually. CONCLUSIONS: The Op-MAPL relies on nothing but an indicator to assess the risk level of the COVID-19 pandemic with different data sources and granularities. This forward-looking method realizes real-time monitoring and early warning effectively to provide a valuable reference to prevent and control infectious diseases.

Evaluation of efficacy and safety of Qiangzhu-qinggan formula as an adjunctive therapy in adult patients with severe influenza: study protocol for a randomized parallel placebo-controlled double-blind multicenter trial.

BACKGROUND: Influenza can fall into three categories according to severity: mild influenza, severe influenza, and critical influenza. Severe influenza can result in critical illness and sometimes death particularly in patients with comorbidities, advanced age, or pregnancy. Neuraminidase inhibitors (NAIs) are the only antiviral drugs in widespread use for influenza. However, the effectiveness of NAIs against severe influenza is uncertain. New effective drugs or regimens are therefore urgently needed. Qiangzhu-qinggan (QZQG) formula has been found to be effective against influenza virus infection during long-term application in China, which lacks support of evidence-based clinical trial till now. This study is designed to assess the efficacy and safety of QZQG formula as an adjuvant therapy in adult patients with severe influenza. METHODS: This protocol is drawn up in accordance with the SPIRIT guidelines and CONSORT Extension for Chinese herbal medicine formulas. This is a randomized, placebo-controlled, double-blind, multicenter trial. Two hundred twenty-eight adults with severe influenza are randomly assigned in a 1:1 ratio to QZQG or placebo for 7 days. All participants need to receive 1 day of screening before randomization, 7 days of intervention, and 21 days of observation after randomization. The primary outcome is the proportion of clinical improvement, defined as the proportion of patients who met the criteria of 3 points or less in the seven-category ordinal scale or 2 points or less in National Early Warning Score 2 within 7 days after randomization. DISCUSSION: This is the first randomized, controlled, parallel, double-blind clinical trial to evaluate the efficacy and safety of traditional Chinese herbal formula granules as an adjuvant therapy in adult patients with severe influenza. This study aims to redefine the value of traditional Chinese herbal medicines in the treatment of virus-related respiratory infectious diseases and serves as an example of evidence-based clinical trials of other Chinese herbal medicines.

Stability of SARS-CoV-2 on inanimate surfaces: A review.

The stability of SARS-CoV-2 for varying periods on a wide range of inanimate surfaces has raised concerns about surface transmission; however, there is still no evidence to confirm this route. In the present review, three variables affecting virus stability, namely temperature, relative humidity (RH), and initial virus titer, were considered from different experimental studies. The stability of SARS-CoV-2 on the surfaces of six different contact materials, namely plastic, metal, glass, protective equipment, paper, and fabric, and the factors affecting half-life period was systematically reviewed. The results showed that the half-life of SARS-CoV-2 on different contact materials was generally 2-10 h, up to 5 d, and as short as 30 min at 22 °C, whereas the half-life of SARS-CoV-2 on non-porous surfaces was generally 5-9 h d, up to 3 d, and as short as 4 min at 22 â„ƒ. The half-life on porous surfaces was generally 1-5 h, up to 2 d, and as short as 13 min at 22 °C. Therefore, the half-life period of SARS-CoV-2 on non-porous surfaces is longer than that on porous surfaces, and thehalf-life of the virus decreases with increasing temperature, whereas RH produces a stable negative inhibitory effect only in a specific humidity range. Various disinfection precautions can be implemented in daily life depending on the stability of SARS-CoV-2 on different surfaces to interrupt virus transmission, prevent COVID-19 infections, and avoid over-disinfection. Owing to the more stringent control of conditions in laboratory studies and the lack of evidence of transmission through surfaces in the real world, it is difficult to provide strong evidence for the efficiency of transmission of the contaminant from the surface to the human body. Therefore, we suggest that future research should focus on exploring the systematic study of the entire transmission process of the virus, which will provide a theoretical basis for optimizing global outbreak prevention and control measures.

Stability of SARS-CoV-2 on Inanimate Surfaces: A Review

The stability of SARS-CoV-2 for varying periods on a wide range of inanimate surfaces has raised concerns about surface transmission;however, there is still no evidence to confirm this route. In the present review, three variables affecting virus stability, namely temperature, relative humidity (RH), and initial virus titer, were considered from different experimental studies. The stability of SARS-CoV-2 on the surfaces of six different contact materials, namely plastic, metal, glass, protective equipment, paper, and fabric, and the factors affecting half-life period was systematically reviewed. The results showed that the half-life of SARS-CoV-2 on different contact materials was generally 2–10 h, up to 5 d, and as short as 30 min at 22°C, whereas the half-life of SARS-CoV-2 on non-porous surfaces was generally 5–9 h d, up to 3 d, and as short as 4 min at 22℃. The half-life on porous surfaces was generally 1–5 h, up to 2 d, and as short as 13 min at 22°C. Therefore, the half-life period of SARS-CoV-2 on non-porous surfaces is longer than that on porous surfaces, and thehalf-life of the virus decreases with increasing temperature, whereas RH produces a stable negative inhibitory effect only in a specific humidity range. Various disinfection precautions can be implemented in daily life depending on the stability of SARS-CoV-2 on different surfaces to interrupt virus transmission, prevent COVID-19 infections, and avoid over-disinfection. Owing to the more stringent control of conditions in laboratory studies and the lack of evidence of transmission through surfaces in the real world, it is difficult to provide strong evidence for the efficiency of transmission of the contaminant from the surface to the human body. Therefore, we suggest that future research should focus on exploring the systematic study of the entire transmission process of the virus, which will provide a theoretical basis for optimizing global outbreak prevention and control measures.

Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study.

BACKGROUND: Non-pharmaceutical interventions (NPIs) have been implemented worldwide to suppress the spread of coronavirus disease 2019 (COVID-19). However, few studies have evaluated the effect of NPIs on other infectious diseases and none has assessed the avoided disease burden associated with NPIs. We aimed to assess the effect of NPIs on the incidence of infectious diseases during the COVID-19 pandemic in 2020 and evaluate the health economic benefits related to the reduction in the incidence of infectious diseases. METHODS: Data on 10 notifiable infectious diseases across China during 2010-2020 were extracted from the China Information System for Disease Control and Prevention. A two-stage controlled interrupted time-series design with a quasi-Poisson regression model was used to examine the impact of NPIs on the incidence of infectious diseases. The analysis was first performed at the provincial-level administrative divisions (PLADs) level in China, then the PLAD-specific estimates were pooled using a random-effect meta-analysis. RESULTS: A total of 61,393,737 cases of 10 infectious diseases were identified. The implementation of NPIs was associated with 5.13 million (95% confidence interval [CI] 3.45‒7.42) avoided cases and USD 1.77 billion (95% CI 1.18‒2.57) avoided hospital expenditures in 2020. There were 4.52 million (95% CI 3.00‒6.63) avoided cases for children and adolescents, corresponding to 88.2% of total avoided cases. The top leading cause of avoided burden attributable to NPIs was influenza [avoided percentage (AP): 89.3%; 95% CI 84.5‒92.6]. Socioeconomic status and population density were effect modifiers. CONCLUSIONS: NPIs for COVID-19 could effectively control the prevalence of infectious diseases, with patterns of risk varying by socioeconomic status. These findings have important implications for informing targeted strategies to prevent infectious diseases.

Efficacy and Safety of Longyizhengqi Granule in Treatment of Mild COVID-19 Patients Caused by SARS-CoV-2 Omicron Variant: A Prospective Study.

Purpose: This study aimed to evaluate the clinical efficacy of Longyizhengqi granule, a traditional Chinese medicine, in patients with mild COVID-19. Patients and Methods: We conducted a prospective study including mild COVID-19 participants conducted at Mobile Cabin Hospital in Shanghai, China. Participants were assigned to receive Longyizhengqi granule or conventional treatment. The primary outcome was the time for nucleic acid to turn negative and the secondary outcomes are hospital stay and changes in cycle threshold (Ct) values for N gene and Orf gene. Multilevel random-intercept model was performed to analyze the effects of treatment. Results: A total of 3243 patients were included in this study (Longyizhengqi granule 667 patients; conventional treatment 2576 patients). Age (43.5 vs 42.1, p<0.01) and vaccination doses (not vaccinated: 15.8% vs 21.7%, 1 dose: 3.5% vs 2.9%, 2 doses: 27.9% vs 25.6%, 3 doses: 52.8% vs 49.8%. p<0.01) show statistical difference between Conventional treatment group and LYZQ granules group. The use of Longyizhengqi granule could significantly reduce the time for nucleic acid to turn negative (14.2 days vs 10.7 days, p<0.01), shorten hospital stay (12.5 days vs 9.9 days, p<0.01), and increase the changes in Ct value for N gene (8.44 vs 10.33, p<0.01) and Orf gene (7.31 vs 8.44, p<0.01) to approximately 1.5. Moreover, the difference in the changes of Ct values on the 4th, 6th, 8th, and 10th days seem to increase between two groups. No serious adverse events were reported. Conclusion: Longyizhengqi granule might be a promising drug for the treatment of mild COVID-19, and it might be beneficial to effectively shorten the negative transition time of nucleic acid, the total days of hospitalization, and increase the changes of Ct values. Long-term randomized controlled trials with follow-up evaluations are required to confirm its long-term efficacy.

Global prevalence and trend of anxiety among graduate students: A systematic review and meta-analysis.

OBJECTIVE: To evaluate the comprehensive prevalence of anxiety among postgraduates and estimate its changes with a meta-analysis. METHOD: Systematic retrieval to SAGE, ERIC, EBSCO, Wiley, ScienceDirect, ProQuest, PubMed, EMBASE, and Web of Science database was performed for quantitative studies on the prevalence of anxiety among graduate students published before November 22, 2022. The prevalence of anxiety synthesized with random-effects model, and subgroup analysis was conducted by study characteristics (publication year, sampling method, and measurements) and subjects' characteristics (gender, region, and educational level). RESULT: Fifty studies were included in the meta-analysis, totaling 39,668 graduate students. The result revealed that 34.8% of graduates suffered from the anxiety (95% CI: 29.5%-40.5%). Specifically, 19.1% (95% CI: 15.4%-23.5%) had mild anxiety, 15.1% (95% C: 11.6%-19.6%) had moderate anxiety, and 10.3% (95% CI: 7.2%-14.6%) had severe anxiety. And this prevalence showed a upward trend since 2005. Besides, master students suffered slightly less than doctoral students (29.2% vs. 34.3%), and female had similar anxiety to male (26.4% vs. 24.9%). Due to the COVID-19, the prevalence of anxiety is higher after the pandemic than that before (any anxiety: 34.3% vs. 24.8%). Compared with other countries, students from Saudi Arabia, India, and Nepal were more vulnerable. The results of quality assessment showed that, 5 (10%) were in high quality, 21 (42%) were in moderate to high quality, 21 (42%) were in low to moderate quality, and 3 (6%) were in low quality. But, the studies with low quality tend to report a higher prevalence than that with high quality (40.3% vs. 13.0%), studies with nonrandom sampling tend to report a higher prevalence than that with random sampling (33.6% vs. 20.7%). Although we included the data collected based on the standard scales, there were higher heterogeneity among the measure (Q = 253.1, df = 12, p < .00). CONCLUSION: More than one-third postgraduates suffered from anxiety disorder, and this prevalence had a slight upward trend since 2005, school administrators, teachers and students should take joint actions to prevent mental disorder of graduates for deteriorating.

Clinical characteristics of 1139 mild cases of the SARS-CoV-2 Omicron variant infected patients in Shanghai.

In March 2022, the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surged during the Coronavirus Disease 2019 (COVID-19) pandemic in Shanghai, but over 90% of patients were mild. This study included 1139 COVID-19 patients mildly infected with the Omicron variant of SARS-CoV-2 in Shanghai from May 1 to 10, 2022, aiming to clarify the demographic characteristics and clinical symptoms of patients with mild Omicron infection. The clinical phenotypes of Omicron infection were identified by model-based cluster analysis to explore the features of different clusters. The median age of the patients was 41.0 years [IQR: 31.0-52.0 years] and 73.0% were male. The top three clinical manifestations are cough (57.5%), expectoration (48.3%), and nasal congestion and runny nose (43.4%). The prevalence of nasal congestion and runny nose varied significantly across the doses of vaccinations, with 23.1% in the unvaccinated population and 30%, 45.9%, and 44.3% in the 1-dose, 2-dose and 3-dose vaccinated populations, respectively. In addition, there were significant differences for fever (23.1%, 26.0%, 28.6%, 18.4%), head and body heaviness (15.4%, 14.0%, 26.7%, 22.4%), and loss of appetite (25.6%, 30.0%, 33.6%, 27.7%). The unvaccinated population had a lower incidence of symptoms than the vaccinated population. Cluster analysis revealed that all four clusters had multisystemic symptoms and were dominated by both general and respiratory symptoms. The more severe the degree of the symptoms was, the higher the prevalence of multisystemic symptoms will be. The Omicron variant produced a lower incidence of symptoms in mildly infected patients than previous SARS-CoV-2 variants, but the clinical symptoms caused by the Omicron variant are more complex, so that it needs to be differentiated from influenza.

Early warning signals for Omicron outbreaks in China: a retrospective study.

The Omicron variant has become the dominant COVID-19 variant worldwide due to its rapid and cryptic spread; therefore, successful early warning is of great importance to be able to control epidemics in their early phase, before developing into large outbreaks. COVID-19-related Baidu search index, which reflects human behavior to a certain degree, was used to retrospectively detect the warning signs for Omicron variant outbreaks in China in 2022. The characteristics and effects of warning signs were analyzed in detail. We detected the presence of early warning signs (both high and low thresholds) and found that these occurred 4-7 days earlier than traditional epidemiological surveillance and >20 days earlier than the implementation of the local "lockdown" policy. Compared with the "high threshold" warning, the early warning effect of the "low threshold" is also vital because it indicates a complacency about epidemic prevention and control. However, there is obvious heterogeneity in the optimal threshold for detecting early warning signs and their distribution in different cities. Multi-source and multi-point early warning systems should be established via combining internet-based big data in the future to conduct effective and early real-time warning. This would create precious time for the early control of COVID-19 outbreaks. This article is protected by copyright. All rights reserved.

Optimizing the nucleic acid screening strategy to mitigate regional outbreaks of SARS-CoV-2 Omicron variant in China: a modeling study.

BACKGROUND: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads rapidly and insidiously. Coronavirus disease 2019 (COVID-19) screening is an important means of blocking community transmission in China, but the costs associated with testing are high. Quarantine capacity and medical resources are also threatened. Therefore, we aimed to evaluate different screening strategies to balance outbreak control and consumption of resources. METHODS: A community network of 2000 people, considering the heterogeneities of household size and age structure, was generated to reflect real contact networks, and a stochastic individual-based dynamic model was used to simulate SARS-CoV-2 transmission and assess different whole-area nucleic acid screening strategies. We designed a total of 87 screening strategies with different sampling methods, frequencies of screening, and timings of screening. The performance of these strategies was comprehensively evaluated by comparing the cumulative infection rates, the number of tests, and the quarantine capacity and consumption of medical resource, which were expressed as medians (95% uncertainty intervals, 95% UIs). RESULTS: To implement COVID-19 nucleic acid testing for all people (Full Screening), if the screening frequency was four times/week, the cumulative infection rate could be reduced to 13% (95% UI: 1%, 51%), the miss rate decreased to 2% (95% UI: 0%, 22%), and the quarantine and medical resource consumption was lower than higher-frequency Full Screening or sampling screening. When the frequency of Full Screening increased from five to seven times/week (which resulted in a 2581 increase in the number of tests per positive case), the cumulative infection rate was only reduced by 2%. Screening all people weekly by splitting them equally into seven batches could reduce infection rates by 73% compared to once per week, which was similar to Full Screening four times/week. Full Screening had the highest number of tests per positive case, while the miss rate, number of tests per positive case, and hotel quarantine resource consumption in Household-based Sampling Screening scenarios were lower than Random Sampling Screening. The cumulative infection rate of Household-based Sampling Screening or Random Sampling Screening seven times/week was similar to that of Full Screening four times/week. CONCLUSIONS: If hotel quarantine, hospital and shelter hospital capacity are seriously insufficient, to stop the spread of the virus as early as possible, high-frequency Full Screening would be necessary, but intermediate testing frequency may be more cost-effective in non-extreme situations. Screening in batches is recommended if the testing capacity is low. Household-based Sampling Screening is potentially a promising strategy to implement.

Recent Advances in Lipid Nanoparticles for Delivery of mRNA.

Messenger RNA (mRNA), which is composed of ribonucleotides that carry genetic information and direct protein synthesis, is transcribed from a strand of DNA as a template. On this basis, mRNA technology can take advantage of the body's own translation system to express proteins with multiple functions for the treatment of various diseases. Due to the advancement of mRNA synthesis and purification, modification and sequence optimization technologies, and the emerging lipid nanomaterials and other delivery systems, mRNA therapeutic regimens are becoming clinically feasible and exhibit significant reliability in mRNA stability, translation efficiency, and controlled immunogenicity. Lipid nanoparticles (LNPs), currently the leading non-viral delivery vehicles, have made many exciting advances in clinical translation as part of the COVID-19 vaccines and therefore have the potential to accelerate the clinical translation of gene drugs. Additionally, due to their small size, biocompatibility, and biodegradability, LNPs can effectively deliver nucleic acids into cells, which is particularly important for the current mRNA regimens. Therefore, the cutting-edge LNP@mRNA regimens hold great promise for cancer vaccines, infectious disease prevention, protein replacement therapy, gene editing, and rare disease treatment. To shed more lights on LNP@mRNA, this paper mainly discusses the rational of choosing LNPs as the non-viral vectors to deliver mRNA, the general rules for mRNA optimization and LNP preparation, and the various parameters affecting the delivery efficiency of LNP@mRNA, and finally summarizes the current research status as well as the current challenges. The latest research progress of LNPs in the treatment of other diseases such as oncological, cardiovascular, and infectious diseases is also given. Finally, the future applications and perspectives for LNP@mRNA are generally introduced.

A bibliometric analysis of COVID-19 and physical activity.

BACKGROUND: Due to the huge impact of coronavirus disease 2019 (COVID-19) on a global scale, the level of physical activity during confinement has become a widespread concern. This study summarizes the development of performance and research trends in COVID-19 and physical activity over the last 3 years. METHODS: Research publications on COVID-19 and physical activity in the past 3 years were downloaded from the Web of Science database. CiteSpace and VOSviewer software were used to analyze the authors, published outputs, journals, cited authors, countries and institutions, co-cited journals, cited references, and keywords. Statistical and centrality analyses were used to identify the active authors, core journals, basic references, hot topics, and cutting-edge fields. RESULTS: A total of 1331 papers was retrieved. SMITH L was a prolific author in the field of exercise intervention in COVID-19 with 11 publications. International Journal of Environmental Research and Public Health was the most productive journal (179 publications) and the most cited journal (1324). The most productive countries and institutions in this field were the USA (322 publications) and Harvard Medical School (21 publications). The four hot keywords in COVID-19 and physical activity research were physical activity, exercise, health, and mental health. CONCLUSIONS: This study provides researchers with directions to intervene in changing levels of physical activity during the COVID-19 pandemic and valuable information for researchers in the field of sports medicine to identify potential collaborators, collaborating institutions, hot issues, and research frontiers.

Optimization of COVID-19 prevention and control measures during the Beijing 2022 Winter Olympics: a model-based study.

BACKGROUND: The continuous mutation of severe acute respiratory syndrome coronavirus 2 has made the coronavirus disease 2019 (COVID-19) pandemic complicated to predict and posed a severe challenge to the Beijing 2022 Winter Olympics and Winter Paralympics held in February and March 2022. METHODS: During the preparations for the Beijing 2022 Winter Olympics, we established a dynamic model with pulse detection and isolation effect to evaluate the effect of epidemic prevention and control measures such as entry policies, contact reduction, nucleic acid testing, tracking, isolation, and health monitoring in a closed-loop management environment, by simulating the transmission dynamics in assumed scenarios. We also compared the importance of each parameter in the combination of intervention measures through sensitivity analysis. RESULTS: At the assumed baseline levels, the peak of the epidemic reached on the 57th day. During the simulation period (100 days), 13,382 people infected COVID-19. The mean and peak values of hospitalized cases were 2650 and 6746, respectively. The simulation and sensitivity analysis showed that: (1) the most important measures to stop COVID-19 transmission during the event were daily nucleic acid testing, reducing contact among people, and daily health monitoring, with cumulative infections at 0.04%, 0.14%, and 14.92% of baseline levels, respectively (2) strictly implementing the entry policy and reducing the number of cases entering the closed-loop system could delay the peak of the epidemic by 9 days and provide time for medical resources to be mobilized; (3) the risk of environmental transmission was low. CONCLUSIONS: Comprehensive measures under certain scenarios such as reducing contact, nucleic acid testing, health monitoring, and timely tracking and isolation could effectively prevent virus transmission. Our research results provided an important reference for formulating prevention and control measures during the Winter Olympics, and no epidemic spread in the closed-loop during the games indirectly proved the rationality of our research results.

Preliminary discussion on hospital service areas distribution and the setting of isolation points under the COVID-19 epidemic. (Special Issue: Spatio-temporal dynamics analysis, risk assessment and emergency management for COVID-19 epidemic.) [Chinese]

Objective To explore the distributions of hospital service areas under epidemic situation and the methods of setting centralized isolation points based on service areas from the perspective of space facility layout optimization. Methods A Huff model was applied to analyze the distributions of service areas of tertiary hospitals in Shanghai. Candidate locations were set to achieve maximizing coverage, and a location-allocation model was applied to predict the optimal hospital location. Results Among the tertiary hospitals that can admit COVID-19 cases in Shanghai, the central area had a high density of hospitals. The distributions of service areas in urban and rural hospitals were obviously different, and the service areas of rural hospitals were large. It was recommended to optimize the allocation of a new hospital in the center region of Songjiang District and an appropriate number of hospitals in the central area of Pudong New District. Conclusion Considering the distribution of hospital service areas, isolation points can be set in the communities close to the affiliated hospitals, and the hospitals corresponding to each isolation point should be clearly identified when a case occurs. It is recommended to optimize the configuration to add tertiary hospitals in Songjiang District and Pudong New District.

Compartmental structures used in modeling COVID-19: a scoping review.

BACKGROUND: The coronavirus disease 2019 (COVID-19) epidemic, considered as the worst global public health event in nearly a century, has severely affected more than 200 countries and regions around the world. To effectively prevent and control the epidemic, researchers have widely employed dynamic models to predict and simulate the epidemic's development, understand the spread rule, evaluate the effects of intervention measures, inform vaccination strategies, and assist in the formulation of prevention and control measures. In this review, we aimed to sort out the compartmental structures used in COVID-19 dynamic models and provide reference for the dynamic modeling for COVID-19 and other infectious diseases in the future. MAIN TEXT: A scoping review on the compartmental structures used in modeling COVID-19 was conducted. In this scoping review, 241 research articles published before May 14, 2021 were analyzed to better understand the model types and compartmental structures used in modeling COVID-19. Three types of dynamics models were analyzed: compartment models expanded based on susceptible-exposed-infected-recovered (SEIR) model, meta-population models, and agent-based models. The expanded compartments based on SEIR model are mainly according to the COVID-19 transmission characteristics, public health interventions, and age structure. The meta-population models and the agent-based models, as a trade-off for more complex model structures, basic susceptible-exposed-infected-recovered or simply expanded compartmental structures were generally adopted. CONCLUSION: There has been a great deal of models to understand the spread of COVID-19, and to help prevention and control strategies. Researchers build compartments according to actual situation, research objectives and complexity of models used. As the COVID-19 epidemic remains uncertain and poses a major challenge to humans, researchers still need dynamic models as the main tool to predict dynamics, evaluate intervention effects, and provide scientific evidence for the development of prevention and control strategies. The compartmental structures reviewed in this study provide guidance for future modeling for COVID-19, and also offer recommendations for the dynamic modeling of other infectious diseases.

Efficacy and Safety of Chinese Medicine Lianhua Qingwen for Treating COVID-19: An Updated meta-Analysis.

The traditional Chinese medicine formula Lianhua Qingwen (LQ) combined with western medicine therapy is beneficial to coronavirus disease-19 (COVID-19), but there is still a lack of strong evidence-based. We conducted a systematic review and meta-analysis to evaluate the efficacy and safety of LQ combined with western medicine for patients with COVID-19. Seven databases (Chinese and English) were searched by two independent reviewers. Search for relevant keywords such as "Chinese medicine," "Chinese herbal medicine," and "Lianhua Qingwen" in the titles and abstracts of articles retrieved in the databases. Randomized controlled trials or case-control studies that reported sufficient data of participants before and after the intervention were included. Two researchers independently reviewed the studies and extracted the data. Fixed-or random-effect model was used to calculate the overall pooled risk estimates. Forest plots were generated to show pooled results. Seven studies involving 916 participants were included in the meta-analysis. Overall, compared with the control group, the total efficacy (OR = 2.23, 95% CI 1.56, 3.18), adverse events (OR = 0.42, 95% CI 0.18, 0.97), chest computed tomography manifestations (OR = 1.74, 95% CI 1.12, 2.72), and aggravation rate of conversion to severe cases (OR = 0.47, 95% CI 0.30, 0.75) of the intervention group were better. Moreover, the intervention group has an advantage over the control group in improving clinical symptoms (fever, cough, fatigue, chest tightness, shortness of breath, and expectoration) and shortening the fever duration (p < 0.05). Our findings indicate that LQ combined with western medicine may be more effective in treating COVID-19. However, due to the urgency of SARS-CoV-2 outbreaks leading to low methodological quality and not rigorous designs. This meta-analysis cannot draw clear conclusions. PROSPERO registration number: CRD42020190757.

Challenges in the control of COVID-19 outbreaks caused by the delta variant during periods of low humidity: an observational study in Sydney, Australia.

BACKGROUND: Since the appearance of severe acute respiratory coronavirus 2 (SARS-CoV-2) and the coronavirus disease 2019 (COVID-19) pandemic, a growing body of evidence has suggested that weather factors, particularly temperature and humidity, influence transmission. This relationship might differ for the recently emerged B.1.617.2 (delta) variant of SARS-CoV-2. Here we use data from an outbreak in Sydney, Australia that commenced in winter and time-series analysis to investigate the association between reported cases and temperature and relative humidity. METHODS: Between 16 June and 10 September 2021, the peak of the outbreak, there were 31,662 locally-acquired cases reported in five local health districts of Sydney, Australia. The associations between daily 9:00 am and 3:00 pm temperature (°C), relative humidity (%) and their difference, and a time series of reported daily cases were assessed using univariable and multivariable generalized additive models and a 14-day exponential moving average. Akaike information criterion (AIC) and the likelihood ratio statistic were used to compare different models and determine the best fitting model. A sensitivity analysis was performed by modifying the exponential moving average. RESULTS: During the 87-day time-series, relative humidity ranged widely (< 30-98%) and temperatures were mild (approximately 11-17 °C). The best-fitting (AIC: 1,119.64) generalized additive model included 14-day exponential moving averages of 9:00 am temperature (P < 0.001) and 9:00 am relative humidity (P < 0.001), and the interaction between these two weather variables (P < 0.001). Humidity was negatively associated with cases no matter whether temperature was high or low. The effect of lower relative humidity on increased cases was more pronounced below relative humidity of about 70%; below this threshold, not only were the effects of humidity pronounced but also the relationship between temperature and cases of the delta variant becomes apparent. CONCLUSIONS: We suggest that the control of COVID-19 outbreaks, specifically those due to the delta variant, is particularly challenging during periods of the year with lower relative humidity and warmer temperatures. In addition to vaccination, stronger implementation of other interventions such as mask-wearing and social distancing might need to be considered during these higher risk periods.

Impact of the coronavirus disease 2019 interventions on the incidence of hand, foot, and mouth disease in mainland China.

BACKGROUND: In early 2020, non-pharmaceutical interventions (NPIs) were implemented in China to reduce and contain the coronavirus disease 2019 (COVID-19) transmission. These NPIs might have also reduced the incidence of hand, foot, and mouth disease (HFMD). METHODS: The weekly numbers of HFMD cases and meteorological factors in 31 provincial capital cities and municipalities in mainland China were obtained from Chinese Center for Disease Control and Prevention (CCDC) and National Meteorological Information Center of China from 2016 to 2020. The NPI data were collected from local CDCs. The incidence rate ratios (IRRs) were calculated for the entire year of 2020, and for January-July 2020 and August-December 2020. The expected case numbers were estimated using seasonal autoregressive integrated moving average models. The relationships between kindergarten closures and incidence of HFMD were quantified using a generalized additive model. The estimated associations from all cities were pooled using a multivariate meta-regression model. FINDINGS: Stringent NPIs were widely implemented for COVID-19 control from January to July 2020, and the IRRs for HFMD were less than 1 in all 31 cities, and less than 0·1 for 23 cities. Overall, the proportion of HFMD cases reduced by 52·9% (95% CI: 49·3-55·5%) after the implementation of kindergarten closures in 2020, and this effect was generally consistent across subgroups. INTERPRETATION: The decrease in HFMD incidence was strongly associated with the NPIs for COVID-19. HFMD epidemic peaks were either absent or delayed, and the final epidemic size was reduced. Kindergarten closure is an intervention to prevent HFMD outbreaks. FUNDING: This research was supported by the National Natural Science Foundation of China (81973102 & 81773487), Public Health Talents Training Program of Shanghai Municipality (GWV-10.2-XD21), the Shanghai New Three-year Action Plan for Public Health (GWV-10.1-XK16), the Major Project of Scientific and Technical Winter Olympics from National Key Research and Development Program of China (2021YFF0306000), 13th Five-Year National Science and Technology Major Project for Infectious Diseases (2018ZX10725-509) and Key projects of the PLA logistics Scientific research Program (BHJ17J013).

Epidemiological features of COVID-19 patients with prolonged incubation period and its implications for controlling the epidemics in China.

BACKGROUND: COVID-19 patients with long incubation period were reported in clinical practice and tracing of close contacts, but their epidemiological or clinical features remained vague. METHODS: We analyzed 11,425 COVID-19 cases reported between January-August, 2020 in China. The accelerated failure time model, Logistic and modified Poisson regression models were used to investigate the determinants of prolonged incubation period, as well as their association with clinical severity and transmissibility, respectively. RESULT: Among local cases, 268 (10.2%) had a prolonged incubation period of > 14 days, which was more frequently seen among elderly patients, those residing in South China, with disease onset after Level I response measures administration, or being exposed in public places. Patients with prolonged incubation period had lower risk of severe illness (ORadjusted = 0.386, 95% CI: 0.203-0.677). A reduced transmissibility was observed for the primary patients with prolonged incubation period (50.4, 95% CI: 32.3-78.6%) than those with an incubation period of ≤14 days. CONCLUSIONS: The study provides evidence supporting a prolonged incubation period that exceeded 2 weeks in over 10% for COVID-19. Longer monitoring periods than 14 days for quarantine or persons potentially exposed to SARS-CoV-2 should be justified in extreme cases, especially for those elderly.