Prevalence and risk factor for long COVID in children and adolescents: A meta-analysis and systematic review

Background Millions of COVID-19 pediatric survivors are facing the risk of long COVID after recovery from acute COVID-19. The primary objective of this study was to systematically review the available literature and determine the pooled prevalence of, and risk factors for long COVID among the pediatric survivors. Methods Studies that assessed the prevalence of, or risk factors associated with long COVID among pediatric COVID-19 survivors were systematically searched in PubMed, Embase, Cochrane Library, medRxiv and bioRxiv up to December 11th, 2022. Random effects model was performed to estimate the pooled prevalence of long COVID among pediatric COVID-19 patients. Subgroup analyses and meta-regression on the estimated prevalence of long COVID were performed by stratification with follow-up duration, mean age, sex ratio, percentage of multisystem inflammatory syndrome, hospitalization rate at baseline, and percentage of severe illness. Results Based on 40 studies with 12,424 individuals, the pooled prevalence of any long COVID was 23.36% ([95% CI 15.27-32.53]). The generalized symptom (19.57%, [95% CI 9.85-31.52]) was reported most commonly, followed by respiratory (14.76%, [95% CI 7.22-24.27]), neurologic (13.51%, [95% CI 6.52-22.40]), and psychiatric (12.30%, [95% CI 5.38-21.37]). Dyspnoea (22.75%, [95% CI 9.38-39.54]), fatigue (20.22%, [95% CI 9.19-34.09]), and headache (15.88%, [95% CI 6.85-27.57]) were most widely reported specific symptoms. The prevalence of any symptom during 3-6, 6-12, and >12 months were 26.41% ([95% CI 14.33-40.59]), 20.64% ([95% CI 17.06-24.46]), and 14.89% ([95% CI 6.09-26.51]), respectively. Individuals with aged over ten years, multisystem inflammatory syndrome, or had severe clinical symptoms exhibited higher prevalence of long COVID in multi-systems. Factors such as older age, female, poor physical or mental health, or had severe infection or more symptoms were more likely to have long COVID in pediatric survivors. Conclusions Nearly one quarter of pediatric survivors suffered multisystem long COVID, even at 1 year after infection. Ongoing monitoring, comprehensive prevention and intervention is warranted for pediatric survivors, especially for individuals with high risk factors.

Prevalence and risk factor for long COVID in children and adolescents: A meta-analysis and systematic review.

BACKGROUND: Millions of COVID-19 pediatric survivors are facing the risk of long COVID after recovery from acute COVID-19. The primary objective of this study was to systematically review the available literature and determine the pooled prevalence of, and risk factors for long COVID among the pediatric survivors. METHODS: Studies that assessed the prevalence of, or risk factors associated with long COVID among pediatric COVID-19 survivors were systematically searched in PubMed, Embase, and Cochrane Library up to December 11th, 2022. Random effects model was performed to estimate the pooled prevalence of long COVID among pediatric COVID-19 patients. Subgroup analyses and meta-regression on the estimated prevalence of long COVID were performed by stratification with follow-up duration, mean age, sex ratio, percentage of multisystem inflammatory syndrome, hospitalization rate at baseline, and percentage of severe illness. RESULTS: Based on 40 studies with 12,424 individuals, the pooled prevalence of any long COVID was 23.36 % ([95 % CI 15.27-32.53]). The generalized symptom (19.57 %, [95 % CI 9.85-31.52]) was reported most commonly, followed by respiratory (14.76 %, [95 % CI 7.22-24.27]), neurologic (13.51 %, [95 % CI 6.52-22.40]), and psychiatric (12.30 %, [95% CI 5.38-21.37]). Dyspnea (22.75 %, [95% CI 9.38-39.54]), fatigue (20.22 %, [95% CI 9.19-34.09]), and headache (15.88 %, [95 % CI 6.85-27.57]) were most widely reported specific symptoms. The prevalence of any symptom during 3-6, 6-12, and> 12 months were 26.41 % ([95 % CI 14.33-40.59]), 20.64 % ([95 % CI 17.06-24.46]), and 14.89 % ([95 % CI 6.09-26.51]), respectively. Individuals with aged over ten years, multisystem inflammatory syndrome, or had severe clinical symptoms exhibited higher prevalence of long COVID in multi-systems. Factors such as older age, female, poor physical or mental health, or had severe infection or more symptoms were more likely to have long COVID in pediatric survivors. CONCLUSIONS: Nearly one quarter of pediatric survivors suffered multisystem long COVID, even at 1 year after infection. Ongoing monitoring, comprehensive prevention and intervention is warranted for pediatric survivors, especially for individuals with high risk factors.

Early Improvement of Acute Respiratory Distress Syndrome in Patients With COVID-19 in the Intensive Care Unit: Retrospective Analysis.

BACKGROUND: Since the start of the COVID-19 pandemic, there have been over 2 million deaths globally. Acute respiratory distress syndrome (ARDS) may be the main cause of death. OBJECTIVE: This study aimed to describe the clinical features, outcomes, and ARDS characteristics of patients with COVID-19 admitted to the intensive care unit (ICU) in Chongqing, China. METHODS: The epidemiology of COVID-19 from January 21, 2020, to March 15, 2020, in Chongqing, China, was analyzed retrospectively, and 75 ICU patients from two hospitals were included in this study. On day 1, 56 patients with ARDS were selected for subgroup analysis, and a modified Poisson regression was performed to identify predictors for the early improvement of ARDS (eiARDS). RESULTS: Chongqing reported a 5.3% case fatality rate for the 75 ICU patients. The median age of these patients was 57 (IQR 25-75) years, and no bias was present in the sex ratio. A total of 93% (n=70) of patients developed ARDS during ICU stay, and more than half had moderate ARDS. However, most patients (n=41, 55%) underwent high-flow nasal cannula oxygen therapy, but not mechanical ventilation. Nearly one-third of patients with ARDS improved (arterial blood oxygen partial pressure/oxygen concentration >300 mm Hg) in 1 week, which was defined as eiARDS. Patients with eiARDS had a higher survival rate and a shorter length of ICU stay than those without eiARDS. Age (<55 years) was the only variable independently associated with eiARDS, with a risk ratio of 2.67 (95% CI 1.17-6.08). CONCLUSIONS: A new subphenotype of ARDS-eiARDS-in patients with COVID-19 was identified. As clinical outcomes differ, the stratified management of patients based on eiARDS or age is highly recommended.

Decline of onset-to-diagnosis interval and its impacts on clinical outcome of COVID-19 in China: a nation-wide observational study.

BACKGROUND: To quantitatively assess the impact of the onset-to-diagnosis interval (ODI) on severity and death for coronavirus disease 2019 (COVID-19) patients. METHODS: This retrospective study was conducted based on the data on COVID-19 cases of China over the age of 40 years reported through China's National Notifiable Infectious Disease Surveillance System from February 5, 2020 to October 8, 2020. The impacts of ODI on severe rate (SR) and case fatality rate (CFR) were evaluated at individual and population levels, which was further disaggregated by sex, age and geographic origin. RESULTS: As the rapid decline of ODI from around 40 days in early January to < 3 days in early March, both CFR and SR of COVID-19 largely dropped below 5% in China. After adjusting for age, sex, and region, an effect of ODI on SR was observed with the highest OR of 2.95 (95% CI 2.37‒3.66) at Day 10-11 and attributable fraction (AF) of 29.1% (95% CI 22.2‒36.1%) at Day 8-9. However, little effect of ODI on CFR was observed. Moreover, discrepancy of effect magnitude was found, showing a greater effect from ODI on SR among patients of male sex, younger age, and those cases in Wuhan. CONCLUSION: The ODI was significantly associated with the severity of COVID-19, highlighting the importance of timely diagnosis, especially for patients who were confirmed to gain increased benefit from early diagnosis to some extent.

Ecology of Middle East respiratory syndrome coronavirus, 2012-2020: A machine learning modelling analysis.

The ongoing enzootic circulation of the Middle East respiratory syndrome coronavirus (MERS-CoV) in the Middle East and North Africa is increasingly raising the concern about the possibility of its recombination with other human-adapted coronaviruses, particularly the pandemic SARS-CoV-2. We aim to provide an updated picture about ecological niches of MERS-CoV and associated socio-environmental drivers. Based on 356 confirmed MERS cases with animal contact reported to the WHO and 63 records of animal infections collected from the literature as of 30 May 2020, we assessed ecological niches of MERS-CoV using an ensemble model integrating three machine learning algorithms. With a high predictive accuracy (area under receiver operating characteristic curve = 91.66% in test data), the ensemble model estimated that ecologically suitable areas span over the Middle East, South Asia and the whole North Africa, much wider than the range of reported locally infected MERS cases and test-positive animal samples. Ecological suitability for MERS-CoV was significantly associated with high levels of bareland coverage (relative contribution = 30.06%), population density (7.28%), average temperature (6.48%) and camel density (6.20%). Future surveillance and intervention programs should target the high-risk populations and regions informed by updated quantitative analyses.

A systematic review and meta-analysis on prevalence of and risk factors associated with depression, anxiety and insomnia in infectious diseases, including COVID-19: a call to action.

Infectious disease epidemics have become more frequent and more complex during the 21st century, posing a health threat to the general public and leading to psychological symptoms. The current study was designed to investigate the prevalence of and risk factors associated with depression, anxiety and insomnia symptoms during epidemic outbreaks, including COVID-19. We systematically searched the PubMed, Embase, Web of Science, OVID, Medline, Cochrane databases, bioRxiv and medRxiv to identify studies that reported the prevalence of depression, anxiety or insomnia during infectious disease epidemics, up to August 14th, 2020. Prevalence of mental symptoms among different populations including the general public, health workers, university students, older adults, infected patients, survivors of infection, and pregnant women across all types of epidemics was pooled. In addition, prevalence of mental symptoms during COVID-19 was estimated by time using meta-regression analysis. A total of 17,506 papers were initially retrieved, and a final of 283 studies met the inclusion criteria, representing a total of 948,882 individuals. The pooled prevalence of depression ranged from 23.1%, 95% confidential intervals (95% CI: [13.9-32.2]) in survivors to 43.3% (95% CI: [27.1-59.6]) in university students, the pooled prevalence of anxiety ranged from 25.0% (95% CI: [12.0-38.0]) in older adults to 43.3% (95% CI: [23.3-63.3]) in pregnant women, and insomnia symptoms ranged from 29.7% (95% CI: [24.4-34.9]) in the general public to 58.4% (95% CI: [28.1-88.6]) in university students. Prevalence of moderate-to-severe mental symptoms was lower but had substantial variation across different populations. The prevalence of mental problems increased over time during the COVID-19 pandemic among the general public, health workers and university students, and decreased among infected patients. Factors associated with increased prevalence for all three mental health symptoms included female sex, and having physical disorders, psychiatric disorders, COVID infection, colleagues or family members infected, experience of frontline work, close contact with infected patients, high exposure risk, quarantine experience and high concern about epidemics. Frequent exercise and good social support were associated with lower risk for these three mental symptoms. In conclusion, mental symptoms are common during epidemics with substantial variation across populations. The population-specific psychological crisis management are needed to decrease the burden of psychological problem and improve the mental wellbeing during epidemic.

Clinical characteristics and risk factors for severe scrub typhus in pediatric and elderly patients.

BACKGROUND: Scrub typhus (ST) is a life-threatening infectious disease if appropriate treatment is unavailable. Large discrepancy of clinical severity of ST patients was reported among age groups, and the underlying risk factors for severe disease are unclear. METHODS: Clinical and epidemiological data of ST patients were collected in 55 surveillance hospitals located in Guangzhou City, China, from 2012 to 2018. Severe prognosis and related factors were determined and compared between pediatric and elderly patients. RESULTS: A total of 2,074 ST patients including 209 pediatric patients and 1,865 elderly patients were included, with a comparable disease severity rate of 11.0% (95% CI 7.1%-16.1%) and 10.3% (95% CI 9.0%-11.8%). Different frequencies of clinical characteristics including lymphadenopathy, skin rash, enlarged tonsils, etc. were observed between pediatric and elderly patients. Presence of peripheral edema and decreased hemoglobin were the most important predictors of severe illness in pediatric patients with adjusted ORs by 38.99 (9.96-152.67, p<0.001) and 13.22 (1.54-113.50, p = 0.019), respectively, while presence of dyspnea and increased total bilirubin were the potential determinants of severe disease in elderly patients with adjusted ORs by 11.69 (7.33-18.64, p<0.001) and 3.17 (1.97-5.11, p<0.001), respectively. Compared with pediatric patients, elderly patients were more likely to receive doxycycline (64.8% v.s 9.9%, p<0.001), while less likely to receive azithromycin therapy (5.0% v.s 41.1%, p<0.001). CONCLUSION: The disease severity rate is comparable between pediatric and elderly ST patients, while different clinical features and laboratory indicators were associated with development of severe complications for pediatric and elderly patients, which is helpful for diagnosis and progress assessment of disease for ST patients.

Etiological and epidemiological features of acute respiratory infections in China.

Nationwide prospective surveillance of all-age patients with acute respiratory infections was conducted in China between 2009‒2019. Here we report the etiological and epidemiological features of the 231,107 eligible patients enrolled in this analysis. Children <5 years old and school-age children have the highest viral positivity rate (46.9%) and bacterial positivity rate (30.9%). Influenza virus, respiratory syncytial virus and human rhinovirus are the three leading viral pathogens with proportions of 28.5%, 16.8% and 16.7%, and Streptococcus pneumoniae, Mycoplasma pneumoniae and Klebsiella pneumoniae are the three leading bacterial pathogens (29.9%, 18.6% and 15.8%). Negative interactions between viruses and positive interactions between viral and bacterial pathogens are common. A Join-Point analysis reveals the age-specific positivity rate and how this varied for individual pathogens. These data indicate that differential priorities for diagnosis, prevention and control should be highlighted in terms of acute respiratory tract infection patients' demography, geographic locations and season of illness in China.

[Evaluation of clinical value of Xuebijing combined with human immunoglobulin in severe and critically ill patients with coronavirus disease 2019].

OBJECTIVE: To evaluate the clinical efficacy of Xuebijing combined with human immunoglobulin for the treatment of severe and critically ill patients with coronavirus disease 2019 (COVID-19). METHODS: A retrospective study was conducted. The clinical data of 65 patients with severe and critical COVID-19 admitted to Chongqing Public Health Medical Center and Chongqing Three Gorges Central Hospital from January 2020 to March 2020 during the period of supporting to combat COVID-19 by the medical team of the Second Affiliated Hospital of Chongqing Medical University and Chongqing Hospital of Traditional Chinese Medicine were analyzed. According to different treatment regimens, patients were divided into conventional treatment group (conventional antivirus, anti-infection and symptomatic support treatments), Xuebijing group (Xuebijing was applied to patients with elevated inflammatory cytokines) and combination group (Xuebijing combined with human immunoglobulin, human immunoglobulin was applied to patients with low immunity indicated by monitoring results of lymphocytes and their subsets). The improvement of blood routine examination, blood gas analysis, myocardial enzyme spectrum, liver and kidney function, lymphocytes and their subsets and cytokines as well as severity score in three groups before and after treatment were observed. Kaplan-Meier method was used to draw the 28-day survival curve of each group, and the cumulative survival rate among the groups was compared. RESULTS: Among the 65 severe and critically ill COVID-19 patients, only 20 patients received conventional treatment, 22 patients were treated with Xuebijing based on conventional treatment, and 23 patients were treated with Xuebijing combined with human immunoglobulin based on conventional treatment. Before treatment, CD4+ T cell count in combination group was higher than other two groups, and interleukin-6 (IL-6) was lower than other two groups, while other indicators showed no statistically significant differences among the three groups, suggesting that the baseline of the three groups was relatively balanced before treatment. The patients in the conventional treatment group were relieved after treatment, and it was characterized by that the acute physiology and chronic health evaluation II (APACHE II) score and lactate dehydrogenase (LDH) were significantly lower than those before treatment [APACHE II score: 5.20±2.74 vs. 6.20±1.93, LDH (µmol×s-1×L-1): 4.1±1.0 vs. 4.7±0.9, both P < 0.01], but there was still liver damage, which was manifested as higher aspartate aminotransferase (AST) than that before treatment [U/L: 30.5 (23.8, 41.5) vs. 21.0 (17.0, 34.0), P < 0.05]. In Xuebijing group, the respiratory function and immunity of patients were improved after treatment, and the improvement degree of the ratio of CD4+ T cell was more significant than that in the conventional treatment group (4.86±6.31 vs. -0.95±12.38, P < 0.05). However, the patients still lived with an "inflammatory storm" and liver damage after treatment. It was shown that IL-4 was significantly higher than that before treatment (ng/L: 2.57±1.15 vs. 1.92±1.04, P < 0.05), while albumin (ALB) decreased significantly compared with before treatment [g/L: 33.0 (30.5, 35.6) vs. 36.2 (32.1, 41.4), P < 0.01]. While the treatment of Xuebijing combined with human immunoglobulin could improve patients' respiratory function and enhance their immunity more effectively, it was shown that arterial partial pressure of oxygen (PaO2), oxygenation index (PaO2/FiO2), T lymphocyte count, ratio of CD4+ T cell, CD4+ T cell count, CD8+ T cell count and CD4+/CD8+ ratio were significantly higher than those before treatment, while ALB, IL-6, APACHE II score and sequential organ failure assessment (SOFA) score were significantly lower than those before treatment. T lymphocyte count, the ratio of CD4+ T cell and IL-6 in combination group were improved more significantly than those in conventional treatment group and Xuebijing group [T lymphocyte count (×109/L): 310.68±359.28 vs. 46.54±240.01, 81.59±256.76; ratio of CD4+ T cell: 14.53±14.49 vs. -0.95±12.38, 4.86±6.31; IL-6 (ng/L): -25.53±39.05 vs. -1.75±5.45, 12.78±44.81], PaO2/FiO2 was improved more significantly as compared with the Xuebijing group [mmHg (1 mmHg = 0.133 kPa): 146.31±109.73 vs. 59.41±87.70], and the differences were statistically different (all P < 0.05). CONCLUSIONS: The combination of Xuebijing and human immunoglobulin for the treatment of patients with COVID-19 can improve patients' respiratory function, reduce "inflammatory storm", enhance immunity, and alleviate severity of patients' condition.

Effectiveness of adjunctive corticosteroid therapy in patients with severe COVID-19: A retrospective cohort study.

BACKGROUND: The effectiveness of adjunctive corticosteroid use in patients with coronavirus disease 2019 (COVID-19) remains inconclusive. AIM: To investigate the effectiveness of adjunctive corticosteroid therapy in patients with severe COVID-19. METHODS: We conducted a retrospective analysis of the difference in several outcomes between patients with severe COVID-19 who received corticosteroid therapy (the corticosteroid group) and patients with severe COVID-19 who did not receive corticosteroid therapy (the non-corticosteroid group). RESULTS: Seventy-five patients were included in this study. Of these, 47 patients were in the corticosteroid group and 28 patients were in the non-corticosteroid group. There were no differences between the two groups in the total length of hospital stay, the length of intensive care unit stay, high-flow oxygen days, non-invasive ventilator days, invasive ventilation days, and mortality rate. Total lesion volume ratio, consolidation volume ratio and ground-glass opacity volume ratio in the corticosteroid group decreased significantly on day 14, while those in the non-corticosteroid group did not show a significant decrease. CONCLUSION: Our results show that adjunctive corticosteroid use did not significantly improve clinical outcomes in severe COVID-19 patients, but might promote the absorption of pulmonary lesions. Larger multicenter randomized controlled studies may be needed to confirm this.

Association between fatality rate of COVID-19 and selenium deficiency in China.

BACKGROUND: COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. METHODS: An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. RESULTS: Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019-13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21-12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14-4.98) for moderate-selenium-deficient cities and 3.06 (1.49-6.27) for severe-selenium-deficient cities. CONCLUSIONS: Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

Epidemiology and evolution of Middle East respiratory syndrome coronavirus, 2012-2020.

BACKGROUND: The ongoing transmission of the Middle East respiratory syndrome coronavirus (MERS-CoV) in the Middle East and its expansion to other regions are raising concerns of a potential pandemic. An in-depth analysis about both population and molecular epidemiology of this pathogen is needed. METHODS: MERS cases reported globally as of June 2020 were collected mainly from World Health Organization official reports, supplemented by other reliable sources. Determinants for case fatality and spatial diffusion of MERS were assessed with Logistic regressions and Cox proportional hazard models, respectively. Phylogenetic and phylogeographic analyses were performed to examine the evolution and migration history of MERS-CoV. RESULTS: A total of 2562 confirmed MERS cases with 150 case clusters were reported with a case fatality rate of 32.7% (95% CI: 30.9‒34.6%). Saudi Arabia accounted for 83.6% of the cases. Age of ≥ 65 years old, underlying conditions and ≥ 5 days delay in diagnosis were independent risk factors for death. However, a history of animal contact was associated with a higher risk (adjusted OR = 2.97, 95% CI: 1.10-7.98) among female cases < 65 years but with a lower risk (adjusted OR = 0.31, 95% CI: 0.18-0.51) among male cases ≥ 65 years old. Diffusion of the disease was fastest from its origin in Saudi Arabia to the east, and was primarily driven by the transportation network. The most recent sub-clade C5.1 (since 2013) was associated with non-synonymous mutations and a higher mortality rate. Phylogeographic analyses pointed to Riyadh of Saudi Arabia and Abu Dhabi of the United Arab Emirates as the hubs for both local and international spread of MERS-CoV. CONCLUSIONS: MERS-CoV remains primarily locally transmitted in the Middle East, with opportunistic exportation to other continents and a potential of causing transmission clusters of human cases. Animal contact is associated with a higher risk of death, but the association differs by age and sex. Transportation network is the leading driver for the spatial diffusion of the disease. These findings how this pathogen spread are helpful for targeting public health surveillance and interventions to control endemics and to prevent a potential pandemic.

Prevalence of posttraumatic stress disorder after infectious disease pandemics in the twenty-first century, including COVID-19: a meta-analysis and systematic review.

Pandemics have become more frequent and more complex during the twenty-first century. Posttraumatic stress disorder (PTSD) following pandemics is a significant public health concern. We sought to provide a reliable estimate of the worldwide prevalence of PTSD after large-scale pandemics as well as associated risk factors, by a systematic review and meta-analysis. We systematically searched the MedLine, Embase, PsycINFO, Web of Science, CNKI, WanFang, medRxiv, and bioRxiv databases to identify studies that were published from the inception up to August 23, 2020, and reported the prevalence of PTSD after pandemics including sudden acute respiratory syndrome (SARS), H1N1, Poliomyelitis, Ebola, Zika, Nipah, Middle Eastern respiratory syndrome coronavirus (MERS-CoV), H5N1, and coronavirus disease 2019 (COVID-19). A total of 88 studies were included in the analysis, with 77 having prevalence information and 70 having risk factors information. The overall pooled prevalence of post-pandemic PTSD across all populations was 22.6% (95% confidence interval (CI): 19.9-25.4%, I2: 99.7%). Healthcare workers had the highest prevalence of PTSD (26.9%; 95% CI: 20.3-33.6%), followed by infected cases (23.8%: 16.6-31.0%), and the general public (19.3%: 15.3-23.2%). However, the heterogeneity of study findings indicates that results should be interpreted cautiously. Risk factors including individual, family, and societal factors, pandemic-related factors, and specific factors in healthcare workers and patients for post-pandemic PTSD were summarized and discussed in this systematic review. Long-term monitoring and early interventions should be implemented to improve post-pandemic mental health and long-term recovery.

The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms.

BACKGROUND: In the context of the COVID-19 infodemic, the global profusion of monikers and hashtags for COVID-19 have found their way into daily communication and contributed to a backlash against China and the Chinese people. OBJECTIVE: This study examines public engagement in crisis communication about COVID-19 during the early epidemic stage and the practical strategy of social mobilization to mitigate the infodemic. METHODS: We retrieved the unbiased values of the top-ranked search phrases between December 30, 2019, and July 15, 2020, which normalized the anonymized, categorized, and aggregated samples from Google Search data. This study illustrates the most-searched terms, including the official COVID-19 terms, the stigmatized terms, and other controls, to measure the collective behavioral propensities to stigmatized terms and to explore the global reaction to the COVID-19 epidemic in the real world. We calculated the ratio of the cumulative number of COVID-19 cases to the regional population as the cumulative rate (R) of a specific country or territory and calculated the Gini coefficient (G) to measure the collective heterogeneity of crowd behavior. RESULTS: People around the world are using stigmatizing terms on Google Search, and these terms were used earlier than the official names. Many stigmatized monikers against China (eg, "Wuhan pneumonia," G=0.73; "Wuhan coronavirus," G=0.60; "China pneumonia," G=0.59; "China coronavirus," G=0.52; "Chinese coronavirus," G=0.50) had high collective heterogeneity of crowd behavior between December 30, 2019, and July 15, 2020, while the official terms "COVID-19" (G=0.44) and "SARS-CoV-2" (G=0.42) have not become de facto standard usages. Moreover, the pattern of high consistent usage was observed in 13 territories with low cumulative rates (R) between January 16 and July 15, 2020, out of 58 countries and territories that have reported confirmed cases of COVID-19. In the scientific literature, multifarious naming practices may have provoked unintended negative impacts by stigmatizing Chinese people. The World Health Organization; the United Nations Educational, Scientific and Cultural Organization; and the media initiated campaigns for fighting back against the COVID-19 infodemic with the same mission but in diverse voices. CONCLUSIONS: Infodemiological analysis can articulate the collective propensities to stigmatized monikers across search behaviors, which may reflect the collective sentiment of backlash against China and Chinese people in the real world. The full-fledged official terms are expected to fight back against the resilience of negative perceptual bias amid the COVID-19 epidemic. Such official naming efforts against the infodemic should be met with a fair share of identification in scientific conventions and sociocultural paradigms. As an integral component of preparedness, appropriate nomenclatures should be duly assigned to the newly identified coronavirus, and social mobilization in a uniform voice is a priority for combating the next infodemic.

Epidemiological parameters of COVID-19 and its implication for infectivity among patients in China, 1 January to 11 February 2020.

BackgroundThe natural history of disease in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remained obscure during the early pandemic.AimOur objective was to estimate epidemiological parameters of coronavirus disease (COVID-19) and assess the relative infectivity of the incubation period.MethodsWe estimated the distributions of four epidemiological parameters of SARS-CoV-2 transmission using a large database of COVID-19 cases and potential transmission pairs of cases, and assessed their heterogeneity by demographics, epidemic phase and geographical region. We further calculated the time of peak infectivity and quantified the proportion of secondary infections during the incubation period.ResultsThe median incubation period was 7.2 (95% confidence interval (CI): 6.9‒7.5) days. The median serial and generation intervals were similar, 4.7 (95% CI: 4.2‒5.3) and 4.6 (95% CI: 4.2‒5.1) days, respectively. Paediatric cases < 18 years had a longer incubation period than adult age groups (p = 0.007). The median incubation period increased from 4.4 days before 25 January to 11.5 days after 31 January (p < 0.001), whereas the median serial (generation) interval contracted from 5.9 (4.8) days before 25 January to 3.4 (3.7) days after. The median time from symptom onset to discharge was also shortened from 18.3 before 22 January to 14.1 days after. Peak infectivity occurred 1 day before symptom onset on average, and the incubation period accounted for 70% of transmission.ConclusionThe high infectivity during the incubation period led to short generation and serial intervals, necessitating aggressive control measures such as early case finding and quarantine of close contacts.

COVID-19: Challenges to GIS with Big Data

The outbreak of the 2019 novel coronavirus disease (COVID-19) has caused more than 100,000 people infected and thousands of deaths. Currently, the number of infections and deaths is still increasing rapidly. COVID-19 seriously threatens human health, production, life, social functioning and international relations. In the fight against COVID-19, Geographic Information Systems (GIS) and big data technologies have played an important role in many aspects, including the rapid aggregation of multi-source big data, rapid visualization of epidemic information, spatial tracking of confirmed cases, prediction of regional transmission, spatial segmentation of the epidemic risk and prevention level, balancing and management of the supply and demand of material resources, and social-emotional guidance and panic elimination, which provided solid spatial information support for decision-making, measures formulation, and effectiveness assessment of COVID-19 prevention and control. GIS has developed and matured relatively quickly and has a complete technological route for data preparation, platform construction, model construction, and map production. However, for the struggle against the widespread epidemic, the main challenge is finding strategies to adjust traditional technical methods and improve speed and accuracy of information provision for social management. At the data level, in the era of big data, data no longer come mainly from the government but are gathered from more diverse enterprises. As a result, the use of GIS faces difficulties in data acquisition and the integration of heterogeneous data, which requires governments, businesses, and academic institutions to jointly promote the formulation of relevant policies. At the technical level, spatial analysis methods for big data are in the ascendancy. Currently and for a long time in the future, the development of GIS should be strengthened to form a data-driven system for rapid knowledge acquisition, which signifies that GIS should be used to reinforce the social operation parameterization of models and methods, especially when providing support for social management.

[Impact of the Timing of Traditional Chinese Medicine Therapy on the Therapeutic Effect and Prognosis of Severe Coronavirus Disease 2019].

Objective To explore the optimal therapy time for the treatment of severe coronavirus disease 2019(COVID-19)by traditional Chinese medicine(TCM)and its influence on the therapeutic effect and prognosis. Methods The clinical data,laboratory findings,and outcomes of 64 patients with severe COVID-19 treated with TCM and western medicine in Chongqing from January 20,2020, to March 11,2020 were retrospectively analyzed.Patients were divided into early intervention group[TCM was initiated within 3 days (including day 3) after the first diagnosis of severe type/critical type COVID-19]and late intervention group[TCM was initiated after 7 days (including day 7) after the first diagnosis of severe type /critical type COVID-19].The changes in clinical parameters during the course of disease were compared between the two groups. Results On day 14,the oxygenation index was 292.5(252.0,351.0)mmHg in the early intervention group,which was significantly higher than that in the late intervention group [246.0(170.0,292.5)mmHg](P=0.005).The length of hospital stay [(18.56±1.11)d vs.(24.87±1.64)d,P=0.001],duration of ICU stay [(14.12±0.91)d vs.(20.00±1.53)d,P=0.000] and time to negativity [(16.77±1.04)d vs.(22.48±1.66)d,P=0.001] in the early intervention group were significantly shorter than those in the late intervention group.The intubation rate(7.3%)in the early intervention group was significantly lower than that in the late intervention group(30.4%)(P=0.028). Conclusion Early TCM therapy within three days after a diagnosis of severe COVID-19 can shorten the length of hospital stay,duration of ICU stay,and time to negativity and decrease intubation rate.

Meteorological conditions and nonpharmaceutical interventions jointly determined local transmissibility of COVID-19 in 41 Chinese cities: A retrospective observational study.

BACKGROUND: Before effective vaccines become widely available, sufficient understanding of the impacts of climate, human movement and non-pharmaceutical interventions on the transmissibility of COVID-19 is needed but still lacking. METHODS: We collected by crowdsourcing a database of 11 003 COVID-19 cases from 305 cities outside Hubei Province from December 31, 2019 to April 27, 2020. We estimated the daily effective reproduction numbers (Rt ) of COVID-19 in 41 cities where the crowdsourced case data are comparable to the official surveillance data. The impacts of meteorological variables, human movement indices and nonpharmaceutical emergency responses on Rt were evaluated with generalized estimation equation models. FINDINGS: The median Rt was 0•46 (IQR: 0•37-0•87) in the northern cities, higher than 0•20 (IQR: 0•09-0•52) in the southern cities (p=0•004). A higher local transmissibility of COVID-19 was associated with a low temperature, a relative humidity near 70-75%, and higher intracity and intercity human movement. An increase in temperature from 0℃ to 20℃ would reduce Rt by 30% (95 CI 10-46%). A further increase to 30℃ would result in another 17% (95% CI 5-27%) reduction. An increase in relative humidity from 40% to 75% would raise the transmissibility by 47% (95% CI 9-97%), but a further increase to 90% would reduce the transmissibility by 12% (95% CI 4-19%). The decrease in intracity human movement as a part of the highest-level emergency response in China reduced the transmissibility by 36% (95% CI 27-44%), compared to 5% (95% CI 1-9%) for restricting intercity transport. Other nonpharmaceutical interventions further reduced Rt by 39% (95% CI 31-47%). INTERPRETATION: Climate can affect the transmission of COVID-19 where effective interventions are implemented. Restrictions on intracity human movement may be needed in places where other nonpharmaceutical interventions are unable to mitigate local transmission. FUNDING: China Mega-Project on Infectious Disease Prevention; U.S. National Institutes of Health and National Science Foundation.