The patterns and driving forces of dengue invasions in China.

BACKGROUND: Global connectivity and environmental change pose continuous threats to dengue invasions from worldwide to China. However, the intrinsic relationship on introduction and outbreak risks of dengue driven by the landscape features are still unknown. This study aimed to map the patterns on source-sink relation of dengue cases and assess the driving forces for dengue invasions in China. METHODS: We identified the local and imported cases (2006-2020) and assembled the datasets on environmental conditions. The vector auto-regression model was applied to detect the cross-relations of source-sink patterns. We selected the major environmental drivers via the Boruta algorithm to assess the driving forces in dengue outbreak dynamics by applying generalized additive models. We reconstructed the internal connections among imported cases, local cases, and external environmental drivers using the structural equation modeling. RESULTS: From 2006 to 2020, 81,652 local dengue cases and 12,701 imported dengue cases in China were reported. The hotspots of dengue introductions and outbreaks were in southeast and southwest China, originating from South and Southeast Asia. Oversea-imported dengue cases, as the Granger-cause, were the initial driver of the dengue dynamic; the suitable local bio-socioecological environment is the fundamental factor for dengue epidemics. The Bio8 [odds ratio (OR) = 2.11, 95% confidence interval (CI): 1.67-2.68], Bio9 (OR = 291.62, 95% CI: 125.63-676.89), Bio15 (OR = 4.15, 95% CI: 3.30-5.24), normalized difference vegetation index in March (OR = 1.27, 95% CI: 1.06-1.51) and July (OR = 1.04, 95% CI: 1.00-1.07), and the imported cases are the major drivers of dengue local transmissions (OR = 4.79, 95% CI: 4.34-5.28). The intermediary effect of an index on population and economic development to local cases via the path of imported cases was detected in the dengue dynamic system. CONCLUSIONS: Dengue outbreaks in China are triggered by introductions of imported cases and boosted by landscape features and connectivity. Our research will contribute to developing nature-based solutions for dengue surveillance, mitigation, and control from a socio-ecological perspective based on invasion ecology theories to control and prevent future dengue invasion and localization.

Urban spatial epidemic simulation model: A case study of the second COVID-19 outbreak in Beijing, China.

The second COVID-19 outbreak in Beijing was controlled by non-pharmaceutical interventions, which avoided a second pandemic. Until mass vaccination achieves herd immunity, cities are at risk of similar outbreaks. It is vital to quantify and simulate Beijing's non-pharmaceutical interventions to find effective intervention policies for the second outbreak. Few models have achieved accurate intra-city spatio-temporal epidemic spread simulation, and most modeling studies focused on the initial pandemic. We built a dynamic module of infected case movement within the city, and established an urban spatially epidemic simulation model (USESM), using mobile phone signaling data to create scenarios to assess the impact of interventions. We found that: (1) USESM simulated the transmission process of the epidemic within Beijing; (2) USESM showed the epidemic curve and presented the spatial distribution of epidemic spread on a map; and (3) to balance resources, interventions, and economic development, nucleic acid testing intensity could be increased and restrictions on human mobility in non-epidemic areas eased.

Impact of neutrophil extracellular traps on fluid properties, blood flow and complement activation.

Introduction: The intravascular formation of neutrophil extracellular traps (NETs) is a trigger for coagulation and blood vessel occlusion. NETs are released from neutrophils as a response to strong inflammatory signals in the course of different diseases such as COVID-19, cancer or antiphospholipid syndrome. NETs are composed of large, chromosomal DNA fibers decorated with a variety of proteins such as histones. Previous research suggested a close mechanistic crosstalk between NETs and the coagulation system involving the coagulation factor XII (FXII), von Willebrand factor (VWF) and tissue factor. However, the direct impact of NET-related DNA fibers on blood flow and blood aggregation independent of the coagulation cascade has remained elusive. Methods: In the present study, we used different microfluidic setups in combination with fluorescence microscopy to investigate the influence of neutrophil-derived extracellular DNA fibers on blood rheology, intravascular occlusion and activation of the complement system. Results: We found that extended DNA fiber networks decelerate blood flow and promote intravascular occlusion of blood vessels independent of the plasmatic coagulation. Associated with the DNA dependent occlusion of the flow channel was the strong activation of the complement system characterized by the production of complement component 5a (C5a). Vice versa, we detected that the local activation of the complement system at the vascular wall was a trigger for NET release. Discussion: In conclusion, we found that DNA fibers as the principal component of NETs are sufficient to induce blood aggregation even in the absence of the coagulation system. Moreover, we discovered that complement activation at the endothelial surface promoted NET formation. Our data envisions DNA degradation and complement inhibition as potential therapeutic strategies in NET-induced coagulopathies.

Clinical practice guidelines and expert consensus statements on rehabilitation for patients with COVID-19: protocol for a systematic review.

INTRODUCTION: COVID-19 is a highly infectious disease, characterised by respiratory, physical and psychological dysfunctions. Rehabilitation could effectively alleviate the symptoms and promote recovery of the physical and mental health of patients with COVID-19. Recently, rehabilitation medical institutions have issued clinical practice guidelines (CPGs) and expert consensus statements involving recommendations for rehabilitation assessments and rehabilitation therapies for COVID-19. This systematic review aims to assess the methodological quality and reporting quality of the guidance documents, evaluate the heterogeneity of the recommendations and summarise the recommendations with respect to rehabilitation assessments and rehabilitation therapies for COVID-19 to provide a quick reference for front-line clinicians, therapists and patients as well as reasonable suggestions for future guidelines. METHODS AND ANALYSIS: The electronic databases including PubMed, Embase, Chinese Biomedical Literature Database (CBM), Chinese Science and Technology Periodical Database (VIP), Wanfang Database and China National Knowledge Infrastructure (CNKI) and websites of governments or organisations (eg, National Guideline Clearinghouse, Guidelines International Network, National Institute for Health and Clinical Excellence, Scottish Intercollegiate Guidelines Network and WHO) will be searched for eligible CPGs and expert consensus statements from inception to August 2022. CPGs and expert consensus statements published in Chinese or English and presenting recommendations for modern functional rehabilitation techniques and/or traditional Chinese medicine rehabilitation techniques for COVID-19 will be included. Reviews, interpretations, old versions of CPGs and expert consensus statements and those for the management of other diseases during the pandemic will be excluded. Two reviewers will independently review each article, extract data, appraise the methodological quality following the Appraisal of Guidelines for Research & Evaluation II tool and assess the reporting quality with the Reporting Items for Practice Guidelines in Healthcare statement. The Measurement Scale of Rate of Agreement will be used to evaluate the heterogeneity of the recommendations in different CPGs and expert consensus statements. Agreement between reviewers will be calculated using the intraclass correlation coefficient. We will also summarise the recommendations for rehabilitation in patients with COVID-19. The results will be narratively described and presented as tables or figures. ETHICS AND DISSEMINATION: Ethics approval is not needed for this systematic review because information from published documents will be used. The findings will be submitted for publication in a peer-reviewed journal and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PROSPERO REGISTRATION NUMBER: CRD42020190761.

Propagation dynamics and control policies of COVID-19 pandemic at early stages: Implications on future resurgence response.

The spreading of novel coronavirus (SARS-CoV-2) has gravely impacted the world in the last year and a half. Understanding the spatial and temporal patterns of how it spreads at the early stage and the effectiveness of a governments' immediate response helps our society prepare for future COVID-19 waves or the next pandemic and contain it before the spreading gets out of control. In this article, a susceptible-exposed-infectious-removed model is used to model the city-to-city spreading patterns of the disease at the early stage of its emergence in China (from December 2019 to February 2020). Publicly available reported case numbers in 312 Chinese cities and between-city mobility data are leveraged to estimate key epidemiological characteristics, such as the transmission rate and the number of infectious people for each city. It is discovered that during any given time period, there are always only a few cities that are responsible for spreading the disease to other cities. We term these few cities as transmission centers. The spatial and temporal changes in transmission centers demonstrate predictable patterns. Moreover, rigorously designed experiments show that in controlling the disease spread in a city, non-pharmaceutical interventions (NPIs) implemented at transmission centers are more effective than the NPI implemented in the city itself. These findings have implications on the control of an infectious disease at the early stage of its spreading: implementing NPIs at transmission centers at early stages is effective in controlling the spread of infectious diseases.

Risk assessment and prevention and control recommendations for vectors transmitting coronavirus disease 2019

Vectors can transmit Viruses by mechanical transmission. and some species can transmit Viruses by biological means. As for whether vectors can transmit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-Z), this article assess the risk of several categories of vectors closely related to humans in transmitting SARS-CoV-Z. 50 as to provide a basis for developing more precise SARS-CoV-Z prevention and control measures. Based on the collected literature. the risk matrix method was used to evaluate the probability of vectors transmitting SARS-CoV-Z and determine the level of exposure to SARS-CoV-Z and the risk level of SARS-CnV-Z transmission for different vectors in different places. The preliminary results showed that the risk of mosquitoes in transmitting SARS-CUV-Z was Very low: rodents. cockroaches. and flies had a potential risk of mechanical transmission of SARS-COV-Z, and rodents also had a potential risk of biological transmission of SARS-CoV-Z;the three categories of vectors had different risks of the transmission of SARS-CoV-Z in different places, and the risk level of transmission was associated with the risk level of exposure to SARS-CoV-Z, as well as the distribution, density, and activity of vectors. In genera]. the risk of mosquitoes in transmitting SARS-CoV-Z could he excluded: the vectors including rodents, cockroaches, and flies have a potential but low risk of transmitting SARS-CoV-Z in specific planes and surroundings exposed to SARS-COV-Z.

Urban spatial epidemic simulation model: A case study of the second COVID‐19 outbreak in Beijing, China

The second COVID‐19 outbreak in Beijing was controlled by non‐pharmaceutical interventions, which avoided a second pandemic. Until mass vaccination achieves herd immunity, cities are at risk of similar outbreaks. It is vital to quantify and simulate Beijing's non‐pharmaceutical interventions to find effective intervention policies for the second outbreak. Few models have achieved accurate intra‐city spatio‐temporal epidemic spread simulation, and most modeling studies focused on the initial pandemic. We built a dynamic module of infected case movement within the city, and established an urban spatially epidemic simulation model (USESM), using mobile phone signaling data to create scenarios to assess the impact of interventions. We found that: (1) USESM simulated the transmission process of the epidemic within Beijing;(2) USESM showed the epidemic curve and presented the spatial distribution of epidemic spread on a map;and (3) to balance resources, interventions, and economic development, nucleic acid testing intensity could be increased and restrictions on human mobility in non‐epidemic areas eased.

Association of human mobility with road crashes for pandemic-ready safer mobility: A New York City case study.

BACKGROUND: The COVID-19 pandemic has reshaped our cities in many ways. The number of motor vehicles on the road has plummeted during lockdowns, and an increasing number of people are turning to walking and biking. From a road safety perspective, the overall question is what effects the human behavior shift brings on the crash occurrence and, more importantly, how to support decision-makers on safer mobility policies? METHOD: Based on anonymous mobile phone location and crash report data in New York City, this study attempts to provide some new insights by using survival analysis (the hazard function approach) to explore the effects of human mobility changes due to the pandemic on crashes that involve injuries and fatalities (of pedestrian, cyclist or motorist). RESULTS: (1) the increased percentage of people staying at home improves pedestrian and cyclist safety, which adds evidence for making walking and cycling more appealing; (2) the increased percentage of people staying at home raises the likelihood of injuries for motor vehicle drivers, suggesting that it will be critical to monitor the driving behavior and establish new speed limits during the future pandemic waves and in the post-pandemic era as well; (3) non-work trips (e.g., shopping, recreation, personal business, etc.) are positively associated with crash injuries for motor vehicle drivers as well as pedestrian and cyclist; (4) human mobility factors were found not related to crash fatalities; (5) control NPIs implemented increased the motor vehicle drivers' crash risk.

The impact of air pollution on COVID-19 pandemic varied within different cities in South America using different models.

There is a rising concern that air pollution plays an important role in the COVID-19 pandemic. However, the results were not consistent on the association between air pollution and the spread of COVID-19. In the study, air pollution data and the confirmed cases of COVID-19 were both gathered from five severe cities across three countries in South America. Daily real-time population regeneration (Rt) was calculated to assess the spread of COVID-19. Two frequently used models, generalized additive models (GAM) and multiple linear regression, were both used to explore the impact of environmental pollutants on the epidemic. Wide ranges of all six air pollutants were detected across the five cities. Spearman's correlation analysis confirmed the positive correlation within six pollutants. Rt value showed a gradual decline in all the five cities. Further analysis showed that the association between air pollution and COVID-19 varied across five cities. According to our research results, even for the same region, varied models gave inconsistent results. For example, in Sao Paulo, both models show SO2 and O3 are significant independent variables, however, the GAM model shows that PM10 has a nonlinear negative correlation with Rt, while PM10 has no significant correlation in the multiple linear model. Moreover, in the case of multiple regions, currently used models should be selected according to local conditions. Our results indicate that there is a significant relationship between air pollution and COVID-19 infection, which will help states, health practitioners, and policy makers in combating the COVID-19 pandemic in South America.

Ambient air pollution and low temperature associated with case fatality of COVID-19: A nationwide retrospective cohort study in China.

The evidence for the effects of environmental factors on COVID-19 case fatality remains controversial, and it is crucial to understand the role of preventable environmental factors in driving COVID-19 fatality. We thus conducted a nationwide cohort study to estimate the effects of environmental factors (temperature, particulate matter [PM2.5, PM10], sulfur dioxide [SO2], nitrogen dioxide [NO2], and ozone [O3]) on COVID-19 case fatality. A total of 71,808 confirmed COVID-19 cases were identified and followed up for their vital status through April 25, 2020. Exposures to ambient air pollution and temperature were estimated by linking the city- and county-level monitoring data to the residential community of each participant. For each participant, two windows were defined: the period from symptom onset to diagnosis (exposure window I) and the period from diagnosis date to date of death/recovery or end of the study period (exposure window II). Cox proportional hazards models were used to estimate the associations between these environmental factors and COVID-19 case fatality. COVID-19 case fatality increased in association with environmental factors for the two exposure windows. For example, each 10 µg/m3 increase in PM2.5, PM10, O3, and NO2 in window I was associated with a hazard ratio of 1.11 (95% CI 1.09, 1.13), 1.10 (95% CI 1.08, 1.13), 1.09 (95 CI 1.03, 1.14), and 1.27 (95% CI 1.19, 1.35) for COVID-19 fatality, respectively. A significant effect was also observed for low temperature, with a hazard ratio of 1.03 (95% CI 1.01, 1.04) for COVID-19 case fatality per 1°C decrease. Subgroup analysis indicated that these effects were stronger in the elderly, as well as in those with mild symptoms and living in Wuhan or Hubei. Overall, the sensitivity analyses also yielded consistent estimates. Short-term exposure to ambient air pollution and low temperature during the illness would play a nonnegligible part in causing case fatality due to COVID-19. Reduced exposures to high concentrations of PM2.5, PM10, O3, SO2, and NO2 and low temperature would help improve the prognosis and reduce public health burden.

Understanding the psychiatric symptoms of COVID-19: a meta-analysis of studies assessing psychiatric symptoms in Chinese patients with and survivors of COVID-19 and SARS by using the Symptom Checklist-90-Revised.

Understanding the psychiatric symptoms of COVID-19 could facilitate the clinical management of COVID-19 patients. However, the profile of psychiatric symptoms among COVID-19 patients has been understudied. We performed a meta-analysis of studies assessing psychiatric symptoms of COVID-19 and SARS patients and survivors by using the Symptom Checklist-90-Revised (SCL-90-R), an instrument covering a wide spectrum of psychiatric symptoms. Studies reporting SCL-90-R subscale scores among patients with and survivors of COVID-19 and SARS were retrieved from major English and Chinese literature databases. Patients' pooled SCL-90-R subscale scores were compared to the Chinese normative SCL-90-R data, and Cohen's d values were calculated to indicate the severity of psychiatric symptoms. The Joanna Briggs Institute Critical Appraisal Checklist for Studies Reporting Prevalence Data was used to assess the quality of the included studies. The search yielded 25 Chinese studies with 1675 acute COVID-19 and 964 acute SARS patients, 30 COVID-19 and 552 SARS survivors during very early recovery (up to 1 month since discharge), 291 SARS survivors during early recovery (1-6 months after discharge), and 48 SARS survivors during late recovery (12 months after discharge). None of the included studies were rated as good quality. The ten SCL-90-R-defined psychiatric symptoms, which were of medium-to-severe severity (d = 0.68-3.01), were all exhibited in acute COVID-19 patients, and the severity of these symptoms decreased to mild-to-medium during very early recovery (d = 0.17-0.73). SARS patients presented eight psychiatric symptoms with mild-to-severe severity during the acute stage (d =0.43-1.88), and thereafter, the severity of symptoms decreased over the follow-up period. However, somatization (d = 0.30) and anxiety (d = 0.28) remained at mild levels during late recovery. A wide variety of severe psychiatric symptoms have been reported by acute COVID-19 patients, and these symptoms, despite decreasing in severity, persist in very early recovery. The changing trajectory observed with SARS suggests that psychiatric symptoms of COVID-19 may persist for a long time after discharge, and therefore, periodic monitoring of psychiatric symptoms, psychosocial support, and psychiatric treatment (when necessary) may be necessary for COVID-19 patients from the acute to convalescent stages.

Meteorological impact on the COVID-19 pandemic: A study across eight severely affected regions in South America.

The role of meteorological factors in the transmission of the COVID-19 still needs to be determined. In this study, the daily new cases of the eight severely affected regions in four countries of South America and their corresponding meteorological data (average temperature, maximum temperature, minimum temperature, average wind speed, visibility, absolute humidity) were collected. Daily number of confirmed and incubative cases, as well as time-dependent reproductive number (Rt) was calculated to indicate the transmission of the diseases in the population. Spearman's correlation coefficients were assessed to show the correlation between meteorological factors and daily confirmed cases, daily incubative cases, as well as Rt. In particular, the results showed that there was a highly significant correlation between daily incubative cases and absolute humidity throughout the selected regions. Multiple linear regression model further confirmed the negative correlation between absolute humidity and incubative cases. The absolute humidity is predicted to show a decreasing trend in the coming months from the meteorological data of recent three years. Our results suggest the necessity of continuous controlling policy in these areas and some other complementary strategies to mitigate the contagious rate of the COVID-19.

Traditional Chinese herbal medicine for treating novel coronavirus (COVID-19) pneumonia: protocol for a systematic review and meta-analysis.

BACKGROUND: A new type of coronavirus, novel coronavirus (COVID-19), is causing an increasing number of cases of pneumonia and was declared a Public Health Emergency of International Concern by the World Health Organization on 30 January 2020. The virus first appeared in Wuhan, China, in late December 2019, and traditional Chinese herbal medicine is being used for its treatment. This systematic review and meta-analysis will assess studies of the effects of traditional Chinese herbal medicine in COVID-19 pneumonia. METHODS: We will search electronic databases including PubMed, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Database (VIP), and Wanfang database using keywords related to COVID-19 and traditional Chinese herbal medicine. Reference lists of relevant trials and reviews will be searched. We will manually search gray literature, such as conference proceedings and academic degree dissertations, and trial registries. Two independent reviewers will screen studies (XL and DZ), extract data (YL and LG), and evaluate risk of bias (YL and DZ). Data analysis will be conducted using the Review Manager software (version 5.3.5) and R software (version 3.6.1). Statistical heterogeneity will be assessed using a standard chi-square test with a significance level of P < 0.10. Biases associated with study size (e.g., publication bias) will be investigated using funnel plots, Egger's test and Begg's test, and Trim and Fill analysis. DISCUSSION: This study will provide a high-quality synthesis of the effects of traditional Chinese herbal medicine for COVID-19. The use of traditional Chinese herbal medicine for treatment or prevention of these novel viral infections affecting the pneumonia will be investigated. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration number: CRD42020168004.