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1.
Clin Infect Dis ; 72(12): 2248-2249, 2021 06 15.
Article in English | MEDLINE | ID: covidwho-1821697
2.
Frontiers in cellular and infection microbiology ; 12, 2022.
Article in English | EuropePMC | ID: covidwho-1813117

ABSTRACT

Background SARS-CoV-2 is highly contagious and poses a great threat to epidemic control and prevention. The possibility of fecal-oral transmission has attracted increasing concern. However, viral shedding in feces has not been completely investigated. Methods This study retrospectively reviewed 97 confirmed coronavirus disease 2019 (COVID-19) patients hospitalized at the First Affiliated Hospital, School of Medicine, Zhejiang University, from January 19 to February 17, 2020. SARS-CoV-2 RNA in samples of sputum, nasopharyngeal or throat swabs, bronchoalveolar lavage and feces was detected by real-time reverse transcription polymerase chain reaction (RT–PCR). Clinical characteristics and parameters were compared between groups to determine whether fecal RNA was positive. Results Thirty-four (35.1%) of the patients showed detectable SARS-CoV-2 RNA in feces, and 63 (64.9%) had negative detection results. The median time of viral shedding in feces was approximately 25 days, with the maximum time reaching 33 days. Prolonged fecal-shedding patients showed longer hospital stays. Those patients for whom fecal viral positivity persisted longer than 3 weeks also had lower plasma B-cell counts than those patients in the non-prolonged group [70.5 (47.3-121.5) per μL vs. 186.5 (129.3-376.0) per μL, P = 0.023]. Correlation analysis found that the duration of fecal shedding was positively related to the duration of respiratory viral shedding (R = 0.70, P < 0.001) and negatively related to peripheral B-cell counts (R = -0.44, P < 0.05). Conclusions COVID-19 patients who shed SARS-CoV-2 RNA in feces presented similar clinical characteristics and outcomes as those who did not shed SARS-CoV-2 RNA in feces. The prolonged presence of SARS-CoV-2 nucleic acids in feces was highly correlated with the prolonged shedding of SARS-CoV-2 RNA in the respiratory tract and with lower plasma B-cell counts.

3.
Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences ; 49(2):147-157, 2020.
Article in Chinese | EuropePMC | ID: covidwho-1772475

ABSTRACT

当前2019冠状病毒病(COVID-19)疫情仍处于胶着状态。浙江大学医学院附属第一医院是国家感染性疾病临床医学中心,浙江省COVID-19患者救治中心。疫情一线的专家集智攻关,以国家卫生健康委员会和国家中医药管理局发布的COVID-19诊治指南为依据,以抗病毒、抗休克、抗低氧血症、抗继发感染、维持水电解质和酸碱平衡、维持微生态平衡的“四抗二平衡”救治策略为核心,总结完善诊治方案,聚焦临床实践的一些具体问题,为COVID-19患者临床诊治提供借鉴。推荐以多学科协作诊治个性化治疗提高COVID-19患者救治质量。建议病原学检测、炎症指标监测和肺部影像学动态观察指导临床诊治。痰液的病毒核酸检测阳性率最高,约10%的急性期患者血液中检测到病毒核酸,50%的患者粪便中检测到病毒核酸,粪便中可分离出活病毒,须警惕粪便是否具有传染性;开展细胞因子等炎症指标监测有助于发现是否出现细胞因子风暴,判断是否需要人工肝血液净化治疗。通过以“四抗二平衡”为核心的综合治疗提高治愈率、降低病死率;早期抗病毒治疗能减少重症、危重症发生,前期使用阿比多尔联合洛匹那韦/利托那韦抗病毒显示出一定效果。休克和低氧血症多为细胞因子风暴所致,人工肝血液净化治疗能迅速清除炎症介质,阻断细胞因子风暴,对维持水电解质酸碱平衡也有很好的作用,可以提高危重型患者的疗效。重型病例疾病早期可适量、短程应用糖皮质激素。氧疗过程中,患者氧合指数小于200 mmHg时应及时转入重症医学科治疗;采用保守氧疗策略,不推荐常规进行无创通气;机械通气患者应严格执行集束化呼吸机相关性肺炎预防管理策略;氧合指数大于150 mmHg时,及早减、停镇静剂并撤机拔管。不推荐预防性使用抗菌药物,对于病程长,体温反复升高和血降钙素原水平升高的患者可酌情使用抗菌药物;要关注COVID-19患者继发真菌感染的诊治。COVID-19患者有肠道微生态紊乱,肠道乳酸杆菌、双歧杆菌等有益菌减少,推荐对所有患者进行营养和胃肠道功能评估,以营养支持和补充大剂量肠道微生态调节剂,纠正肠道微生态失衡,减少细菌移位和继发感染。COVID-19患者普遍存在焦虑和恐惧心理,应建立动态心理危机干预和处理。提倡中西医结合辨证施治;优化重型患者护理促进康复。严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染后病毒清除规律仍不明了,出院后仍须居家隔离2周,并定期随访。以上经验和建议在本中心实行,取得较好效果,但COVID-19是一种新的疾病,其诊治方案及策略仍有待进一步探索与完善。

4.
Lancet Microbe ; 3(3): e193-e202, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1721237

ABSTRACT

Background: Safe and effective vaccines are urgently needed to end the COVID-19 pandemic caused by SARS-CoV-2 infection. We aimed to assess the preliminary safety, tolerability, and immunogenicity of an mRNA vaccine ARCoV, which encodes the SARS-CoV-2 spike protein receptor-binding domain (RBD). Methods: This single centre, double-blind, randomised, placebo-controlled, dose-escalation, phase 1 trial of ARCoV was conducted at Shulan (Hangzhou) hospital in Hangzhou, Zhejiang province, China. Healthy adults aged 18-59 years negative for SARS-CoV-2 infection were enrolled and randomly assigned using block randomisation to receive an intramuscular injection of vaccine or placebo. Vaccine doses were 5 µg, 10 µg, 15 µg, 20 µg, and 25 µg. The first six participants in each block were sentinels and along with the remaining 18 participants, were randomly assigned to groups (5:1). In block 1 sentinels were given the lowest vaccine dose and after a 4-day observation with confirmed safety analyses, the remaining 18 participants in the same dose group proceeded and sentinels in block 2 were given their first administration on a two-dose schedule, 28 days apart. All participants, investigators, and staff doing laboratory analyses were masked to treatment allocation. Humoral responses were assessed by measuring anti-SARS-CoV-2 RBD IgG using a standardised ELISA and neutralising antibodies using pseudovirus-based and live SARS-CoV-2 neutralisation assays. SARS-CoV-2 RBD-specific T-cell responses, including IFN-γ and IL-2 production, were assessed using an enzyme-linked immunospot (ELISpot) assay. The primary outcome for safety was incidence of adverse events or adverse reactions within 60 min, and at days 7, 14, and 28 after each vaccine dose. The secondary safety outcome was abnormal changes detected by laboratory tests at days 1, 4, 7, and 28 after each vaccine dose. For immunogenicity, the secondary outcome was humoral immune responses: titres of neutralising antibodies to live SARS-CoV-2, neutralising antibodies to pseudovirus, and RBD-specific IgG at baseline and 28 days after first vaccination and at days 7, 15, and 28 after second vaccination. The exploratory outcome was SARS-CoV-2-specific T-cell responses at 7 days after the first vaccination and at days 7 and 15 after the second vaccination. This trial is registered with www.chictr.org.cn (ChiCTR2000039212). Findings: Between Oct 30 and Dec 2, 2020, 230 individuals were screened and 120 eligible participants were randomly assigned to receive five-dose levels of ARCoV or a placebo (20 per group). All participants received the first vaccination and 118 received the second dose. No serious adverse events were reported within 56 days after vaccination and the majority of adverse events were mild or moderate. Fever was the most common systemic adverse reaction (one [5%] of 20 in the 5 µg group, 13 [65%] of 20 in the 10 µg group, 17 [85%] of 20 in the 15 µg group, 19 [95%] of 20 in the 20 µg group, 16 [100%] of 16 in the 25 µg group; p<0·0001). The incidence of grade 3 systemic adverse events were none (0%) of 20 in the 5 µg group, three (15%) of 20 in the 10 µg group, six (30%) of 20 in the 15 µg group, seven (35%) of 20 in the 20 µg group, five (31%) of 16 in the 25 µg group, and none (0%) of 20 in the placebo group (p=0·0013). As expected, the majority of fever resolved in the first 2 days after vaccination for all groups. The incidence of solicited systemic adverse events was similar after administration of ARCoV as a first or second vaccination. Humoral immune responses including anti-RBD IgG and neutralising antibodies increased significantly 7 days after the second dose and peaked between 14 and 28 days thereafter. Specific T-cell response peaked between 7 and 14 days after full vaccination. 15 µg induced the highest titre of neutralising antibodies, which was about twofold more than the antibody titre of convalescent patients with COVID-19. Interpretation: ARCoV was safe and well tolerated at all five doses. The acceptable safety profile, together with the induction of strong humoral and cellular immune responses, support further clinical testing of ARCoV at a large scale. Funding: National Key Research and Development Project of China, Academy of Medical Sciences China, National Natural Science Foundation China, and Chinese Academy of Medical Sciences.

5.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325413

ABSTRACT

Background: The global outbreak of coronavirus disease 2019 (COVID-19) has been ongoing in Southeast Asia since 13 January 2020. We conducted an observational study to investigate underlying disease patterns of COVID-19 in Southeast Asia, and consequently to guide intervention strategies against the pandemic. Methods: : In this population-level observational study set in Southeast Asia, we compiled a list of patients with COVID-19 (n = 925) and daily country-level case counts (n = 1346) from 13 January 2020 through 16 March 2020. All epidemiological data were extracted from official websites of the WHO and health authorities of each Southeast Asian country. Relevant spatiotemporal distributions, demographic characteristics, and short-term trends were assessed. Results: : A total of 1,346 confirmed cases of COVID-19, with 217 (16.1%) recoveries and 18 (1.3%) deaths, were reported in Southeast Asia as of 16 March 2020. Early transmission dynamics were examined with an exponential regression model: y=0.30e 0.13x (p<0·01, adjusted R 2 = 0.96). Using this model, we predicted that the cumulative number of reported COVID-19 cases in Southeast Asia would exceed 10,000 by early April 2020. A total of 74 cities across eight countries in Southeast Asia were affected by COVID-19. Most of the confirmed cases were located in five international metropolitan areas. Demographic analyses of the 925 confirmed cases indicated a median age of 44 years and a sex ratio of 1.25. The median age of the local patient population was significantly higher than that of the corresponding country’s general population (p<0·01), whereas the sex ratio did not significantly differ. Conclusions: : The COVID-19 situation in Southeast Asia is unevenly geographically distributed and pessimistic in the short term. Age may play a significant role in both the susceptibility to and outcome of infection. Real-time active surveillance and targeted intervention strategies are urgently needed to contain the pandemic.

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324643

ABSTRACT

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

7.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324151

ABSTRACT

Contact tracing APPs have been recently advocated by many countries (e.g., the United Kingdom, Australia, etc.) as part of control measures on COVID-19. Controversies have been raised about their effectiveness in practice as it still remains unclear how they can be fully utilized to fuel the fight against COVID-19. In this article, we show that an abundance of information can be extracted from contact tracing for COVID-19 prevention and control, providing the first data-driven evidence that supports the wide implementation of such APPs. Specifically, we construct a temporal contact graph that quantifies the daily contacts between infectious and susceptible individuals by exploiting a large volume of location related data contributed by 10,527,737 smartphone users in Wuhan, China. Five time-varying indicators we introduce can accurately capture actual contact trends at individual and population levels, demonstrating that travel restriction in Wuhan played an important role in containing COVID-19. We reveal a strong correlation (Pearson coefficient 0.929) between daily confirmed cases and daily total contacts, which can be utilized as a new and efficient way to evaluate and predict the evolving epidemic situation of COVID-19. Further, we find that there is a prominent distinction of contact behaviors between the infected and uninfected contacted individuals, and design an infection risk evaluation framework to identify infected ones. This can help narrow down the search of high risk contacted individuals for quarantine. Our results indicate that user involvement has an explicit impact on individual-level contact trend estimation while minor impact on situation evaluation, offering guidelines for governments to implement contact tracing APPs.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315976

ABSTRACT

The relationship between gut microbes and COVID-19 or H1N1 flu is not fully understood. Here, we compared gut mycobiota of 67 COVID-19 patients, 35 H1N1 patients and 48 healthy controls (HCs) using internal transcribed spacer (ITS) 3-ITS4 sequencing. Fungal richness decreased in COVID-19 and H1N1 patients compared to HCs, but fungal diversity decreased in only H1N1 patients. Fungal mycobiota dysbiosis in both COVID-19 and H1N1 patients was mainly characterized by depletions of fungi such as Aspergillus , Penicillium , but several fungi, such as Candida parapsilosis , and Malassezia yamatoensis , were enriched in H1N1 patients. The altered fungal taxa were strongly associated with clinical features such as the incidence of diarrhoea, albumin. Gut mycobiota between COVID-19 patients with mild and severity symptoms are not different, as well as between COVID-19 patients in and out hospital. Therefore, gut mycobiota dysbiosis occur in covid-19 or H1N1 patients and do not improve until discharge.

9.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315365

ABSTRACT

Objective: The novel coronavirus pneumonia (COVID-19) has spread rapidly across the globe with the movement of people. How to diagnose COVID-19 quickly and accurately is a concern for all. We retrospectively assessed the clinical characteristics of patients with COVID-19 detected by outpatient screening in areas outside Wuhan, China, to guide early screening outside the epidemic area, to isolate and treat COVID-19-positive patients, and to control the spread of this virus in the region. Results: : Among the 213 patients treated in the fever clinic of our hospital, 41 tested positive for novel coronavirus (2019-nCoV) and 172 were negative. Among the positive patients, 13 (31.7%) of the patients had been to Wuhan, while 28 (68.3%) had not been to Wuhan. There were 4 cases of clustering occurrence. The main symptoms exhibited by COVID-19-positive patients were fever (87.8%), cough (68.3%), and expectoration (34.1%). The C-reactive protein (CRP) levels were increased in 35 (85.3%) positive patients;the hydroxybutyrate dehydrogenase in the myocardial zymogram was increased in 22 positive patients (53.6%) and 38 negative patients (22.1%);computed tomography (CT) findings revealed lung lesions in all 41 positive patients (100%). Conclusion: We classified the patient population and analyzed the data to understand the early clinical performance of COVID-19. Our research illustrate that screening for COVID-19 outside Wuhan should focus on early symptoms such as fever and cough, in combination with lung CT findings, epidemiological history, and sputum pathogen detection to determine whether patients need further isolation.

10.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-309031

ABSTRACT

Novel coronavirus pneumonia (NCP) has been widely spread in China and several other countries. Early finding of this pneumonia from huge numbers of suspects gives clinicians a big challenge. The aim of the study was to develop a rapid screening model for early predicting NCP in a Zhejiang population, as well as its utility in other areas. A total of 880 participants who were initially suspected of NCP from Jan 17 to Feb 19 were included. Potential predictors were selected via stepwise logistic regression analysis. The model was established based on epidemiological features, clinical manifestations, white blood cell count, and pulmonary imaging changes, with the area under receiver operating characteristic (AUROC) curve of 0.920 (95% confidence interval : 0.902-0.938;AUROC=0.915, and its standard deviation of 0.028, as evaluated in 5-fold cross-validation). At a value of whether the predicted score >4.0, the model could detect NCP with a specificity of 98.3%;at a cut-off value of < -0.5, the model could rule out NCP with a sensitivity of 97.9%. The study demonstrated that the rapid screening model was a helpful and cost-effective tool for early predicting NCP and had great clinical significance given the high activity of NCP.

11.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308288

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) causing a cluster of respiratory infections in Wuhan, China, is identified in December 2019. The main symptoms are defined as fever, cough, shortness of breath, with early symptom of sputum, acute respiratory distress syndrome (ARDS), and the final lung injury and pulmonary fibrosis. Currently, there is no effective method to cure it. Mesenchymal stem cell (MSC) therapy is an immediate need for treating COVID-19 especially severe patients at present. Methods: : We describe the two confirmed case of COVID-19 severe patients in Hangzhou, China to explore the role of menstrual blood-derived MSC in the treatment of SARS-CoV-2 infection. Furthermore, we mimic disease model of pulmonary fibrosis in mice to assess the role of MSC. Then, a co-culture system to investigate the underlying mechanism between MSC and pulmonary-associated cells by a series of Physiological, biochemical, bioinformatics analysis. Results: : MSC transplantation increases the immune indicators (including lymphocytes) and decreases inflammatory indicators (such as IL-6, IL-10, TNF, and IFN). More importantly, the two patients alleviated symptom and discharged after 3 weeks’ treatment with MSC. Additionally, MSCs exhibit an anti-inflammatory role through suppressing some inflammatory factors (RANTES, GM-CSF, MIG-1g, MCP-5, Eotaxin), which is anastomotic to current clinical study using MSC to treat COVID-19. Conclusions: : This is the first report using menstrual blood-derived MSC in treating COVID-19 patients. From our clinical results, we hold one idea that MSCs reduced inflammatory effect to defend cytokine storm. The underlying mechanism is probably that MSCs inhibit epithelia cell apoptosis and reduce the secretion of inflammatory factors to prevent myofibroblasts activity. MSC provides an alternative method for treating COVID-19 particularly some patients with ARDS or subsequent pulmonary fibrosis. Trial registration: This clinical trial was submitted to and approved by the Ethics Committee of the First Affiliated Hospital, Collage of Medicine, Zhejiang University. MSC administration in patient with COVID-19 was conducted in a single center and open-label clinical trial (ChiCTR2000029606).

12.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308161

ABSTRACT

Background: The COVID-19 infection has caused 111652 deaths worldwide as of 13 April 2020. Risk factors for fatal outcomes of COVID-19 have varied across studies due to limited samples and have lacked effective qualitative and quantitative measurements. We performed a meta-analysis to evaluate risk factors for fatal outcomes of COVID-19. Methods: : Data on demographic, clinic, laboratory findings and complications were extracted. Quantitative and qualitative synthesis was conducted for weighted-mean-difference (WMD) and odds-ratio (OR) . Results: : A total of 30 studies involving 5741 survivors and 1670 deaths were included. The death cases were significantly older than survivors (WMD=15.36, 95% CI: 12.90-17.82), male and smoking history showed higher risk to develop fatal outcome (OR=3.37, 95% CI: 2.27-5.01;OR=1.37, 95% CI: 1.02-1.83, respectively). The clinical symptoms including dyspnea (OR=4.63, 95% CI: 2.85-7.54), hemoptysis (OR=3.11, 95% CI: 1.26-7.56), malaise (OR=2.44, 95% CI: 1.49-3.97). comorbidities with coronary heart disease (OR=4.36, 95% CI: 1.91-9.97), COPD (OR=3.70, 95% CI: 2.03-6.73) and cardiovascular disease (OR=3.45, 95% CI: 2.54-4.70). Compared to survivors, many laboratory indexes increased in deaths group, including serum ferritin (WMD=741.47, 95% CI: 566.77-916.16), lactate dehydrogenase (WMD=226.86, 95% CI: 177.08-276.64) and myoglobin (WMD=102.58, 95% CI: 65.12-140.04), and the decreased indexes included PaO2/FiO2 (WMD=-71.61, 95% CI: -134.11 to -9.11), platelets (WMD=-41.09, 95% CI: -47.33 to -34.85) and PaO2 (WMD=-26.09, 95% CI: -38.9 to -13.29). Main complications contributed to the fatal outcome included sepsis (OR=184.61, 95% CI: 33.43-1019.42), shock (OR=133.76, 95% CI: 36.86-485.34) and respiratory failure (OR=47.37, 95% CI: 20.65-108.66). Conclusion: The main risk factors associated with fatal outcome of COVID-19 involved male, older age, smoking history, chronic medical conditions including coronary heart disease, COPD and cardiovascular disease, clinical symptoms including dyspnea, hemoptysis and malaise, the increased laboratory indexes including serum ferritin, lactate dehydrogenase and myoglobin, the decreased indexes including PaO2/FiO2, platelets and PaO2, main complications including sepsis, shock and respiratory failure. These factors could be considered in triaging patients and allocating medical resources when such medical resources are scarce, devising improved protocols for patient diagnosis and management, and developing new drugs and other therapies to treat COVID-19 patients.

14.
Front Public Health ; 9: 773130, 2021.
Article in English | MEDLINE | ID: covidwho-1593754

ABSTRACT

Background: Although coinfection with influenza in COVID-19 patients has drawn considerable attention, it is still not completely understood whether simultaneously infected with these two viruses influences disease severity. We therefore aimed to estimate the impact of coinfected with SARS-CoV-2 and influenza on the disease outcomes compared with the single infection of SARS-CoV-2. Materials and Methods: We searched the PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure Database (CNKI) to identify relevant articles up to July 9, 2021. Studies that assessed the effect of SARS-CoV-2 and influenza coinfection on disease outcomes or those with sufficient data to calculate risk factors were included. Risk effects were pooled using fixed or random effects model. Results: We ultimately identified 12 studies with 9,498 patients to evaluate the risk effects of SARS-CoV-2 and influenza coinfection on disease severity. Results indicated that coinfection was not significantly associated with mortality (OR = 0.85, 95%CI: 0.51, 1.43; p = 0.55, I 2 = 76.00%). However, mortality was found significantly decreased in the studies from China (OR = 0.51, 95%CI: 0.39, 0.68; I 2 = 26.50%), while significantly increased outside China (OR = 1.56, 95%CI: 1.12, 2.19; I 2 = 1.00%). Moreover, a lower risk for critical outcomes was detected among coinfection patients (OR = 0.64, 95%CI: 0.43, 0.97; p = 0.04, I 2 = 0.00%). Additionally, coinfection patients presented different laboratory indexes compared with the single SARS-CoV-2 infection, including lymphocyte counts and APTT. Conclusion: Our study revealed that coinfection with SARS-CoV-2 and influenza had no effect on overall mortality. However, risk for critical outcomes was lower in coinfection patients and different associations were detected in the studies from different regions and specific laboratory indexes. Further studies on influenza strains and the order of infection were warranted. Systematic testing for influenza coinfection in COVID-19 patients and influenza vaccination should be recommended.


Subject(s)
COVID-19 , Coinfection , Influenza, Human , Humans , Influenza, Human/complications , Influenza, Human/epidemiology , SARS-CoV-2 , Severity of Illness Index
17.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-291851

ABSTRACT

Digital contact tracing has been recently advocated by China and many countries as part of digital prevention measures on COVID-19. Controversies have been raised about their effectiveness in practice as it remains open how they can be fully utilized to control COVID-19. In this article, we show that an abundance of information can be extracted from digital contact tracing for COVID-19 prevention and control. Specifically, we construct a temporal contact graph that quantifies the daily contacts between infectious and susceptible individuals by exploiting a large volume of location-related data contributed by 10,527,737 smartphone users in Wuhan, China. The temporal contact graph reveals five time-varying indicators can accurately capture actual contact trends at population level, demonstrating that travel restrictions (e.g., city lockdown) in Wuhan played an important role in containing COVID-19. We reveal a strong correlation between the contacts level and the epidemic size, and estimate several significant epidemiological parameters (e.g., serial interval). We also show that user participation rate exerts higher influence on situation evaluation than user upload rate does. At individual level, however, the temporal contact graph plays a limited role, since the behavior distinction between the infected and uninfected contacted individuals are not substantial. The revealed results can tell the effectiveness of digital contact tracing against COVID-19, providing guidelines for governments to implement interventions using information technology.

19.
Parasit Vectors ; 14(1): 517, 2021 Oct 07.
Article in English | MEDLINE | ID: covidwho-1463263

ABSTRACT

BACKGROUND: Although visceral leishmaniasis (VL) was largely brought under control in most regions of China during the previous century, VL cases have rebounded in western and central China in recent decades. The aim of this study was to investigate the epidemiological features and spatial-temporal distribution of VL in mainland China from 2004 to 2019. METHODS: Incidence and mortality data for VL during the period 2004-2019 were collected from the Public Health Sciences Data Center of China and annual national epidemic reports of VL, whose data source was the National Diseases Reporting Information System. Joinpoint regression analysis was performed to explore the trends of VL. Spatial autocorrelation and spatial-temporal clustering analysis were conducted to identify the distribution and risk areas of VL transmission. RESULTS: A total of 4877 VL cases were reported in mainland China during 2004-2019, with mean annual incidence of 0.0228/100,000. VL incidence showed a decreasing trend in general during our study period (annual percentage change [APC] = -4.2564, 95% confidence interval [CI]: -8.0856 to -0.2677). Among mainly endemic provinces, VL was initially heavily epidemic in Gansu, Sichuan, and especially Xinjiang, but subsequently decreased considerably. In contrast, Shaanxi and Shanxi witnessed significantly increasing trends, especially in 2017-2019. The first-level spatial-temporal aggregation area covered two endemic provinces in northwestern China, including Gansu and Xinjiang, with the gathering time from 2004 to 2011 (relative risk [RR] = 13.91, log-likelihood ratio [LLR] = 3308.87, P < 0.001). The secondary aggregation area was detected in Shanxi province of central China, with the gathering time of 2019 (RR = 1.61, LLR = 4.88, P = 0.041). The epidemic peak of October to November disappeared in 2018-2019, leaving only one peak in March to May. CONCLUSIONS: Our findings suggest that VL is still an important endemic infectious disease in China. Epidemic trends in different provinces changed significantly and spatial-temporal aggregation areas shifted from northwestern to central China during our study period. Mitigation strategies, including large-scale screening, insecticide spraying, and health education encouraging behavioral change, in combination with other integrated approaches, are needed to decrease transmission risk in areas at risk, especially in Shanxi, Shaanxi, and Gansu provinces.


Subject(s)
Epidemics/statistics & numerical data , Epidemiological Monitoring , Leishmaniasis, Visceral/epidemiology , Public Health/statistics & numerical data , Spatio-Temporal Analysis , Adolescent , Child , Child, Preschool , China/epidemiology , Humans , Incidence , Infant , Infant, Newborn , Leishmaniasis, Visceral/mortality , Population
20.
N Engl J Med ; 382(18): 1708-1720, 2020 04 30.
Article in English | MEDLINE | ID: covidwho-1428982

ABSTRACT

BACKGROUND: Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. METHODS: We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. RESULTS: The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. CONCLUSIONS: During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.).


Subject(s)
Betacoronavirus , Coronavirus Infections , Disease Outbreaks , Pandemics , Pneumonia, Viral , Adolescent , Adult , Aged , COVID-19 , Child , China/epidemiology , Coronavirus Infections/complications , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/therapy , Female , Fever/etiology , Humans , Male , Middle Aged , Patient Acuity , Pneumonia, Viral/complications , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Pneumonia, Viral/therapy , SARS-CoV-2 , Young Adult
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