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简介：AbstractBackground:Nucleic acid test (NAT) could effectively control the spread of COVID-19 caused by large-scale sports competitions. However, quantitative analysis on the appropriate frequency of NAT is scarce, and the cost-effectiveness and necessity of high-frequency NAT remain to be fully explored and validated. This study aims to optimize the COVID-19 surveillance strategies through cost-effectiveness analysis for the Tokyo 2020 Olympic Games and the upcoming Beijing 2022 Olympic Winter Games.Methods:A total of 18 scenarios were designed regarding the NAT frequency, symptom monitoring, and strengthening close-contact control. An agent-based stochastic dynamic model was used to compare the cost-effectiveness of different NAT scenarios and optimize the surveillance strategies. The dynamics of the proposed model included the arrival and departure of agents, transmission of the disease according to Poisson processes, and quarantine of agents based on regular NATs and symptom onset. Accumulative infections, cost, and incremental cost-effectiveness ratio (ICER) were simulated in the frame of the model. ICER was used to compare the cost-effectiveness of different scenarios. Univariate sensitivity analysis was performed to test the robustness of the results.Results:In Scenario 16, where the competition-related personnel (CRP) received NAT daily and national sports delegation (NSD) with quarantined infections accepted an additional NAT daily, accumulative infection was 320.90 (90 initial infections), the total cost was (United States Dollar) USD 8 920 000, and the cost of detecting out each infection was USD 27 800. Scenario 16 would reduce the total cost by USD 22 570 000 (avoid 569.61 infections), USD 1 420 000 (avoid 47.2 infections) compared with Scenario 10 (weekly NAT, strengthened close contact control) and Scenario 7 (daily NAT, no strengthened close contact control), respectively. Sensitivity analysis showed that the result was most sensitive to the change in basic reproductive number.Conclusions:High-frequency NATs such as bidaily, daily, and twice a day were cost-effective. NAT daily for CRP with strengthening close-contact control could be prioritized in defense against COVID-19 at large-scale sports competitions. This study could assist policymakers by assessing the cost-effectiveness of NAT scenarios and provide the host country with an optimal COVID-19 surveillance strategy.

简介：AbstractAround 450 million people are affected by pneumonia every year, which results in 2.5 million deaths. Coronavirus disease 2019 (Covid-19) has also affected 181 million people, which led to 3.92 million casualties. The chances of death in both of these diseases can be significantly reduced if they are diagnosed early. However, the current methods of diagnosing pneumonia (complaints + chest X-ray) and Covid-19 (real-time polymerase chain reaction) require the presence of expert radiologists and time, respectively. With the help of deep learning models, pneumonia and Covid-19 can be detected instantly from chest X-rays or computerized tomography (CT) scans. The process of diagnosing pneumonia/Covid-19 can become faster and more widespread. In this paper, we aimed to elicit, explain, and evaluate qualitatively and quantitatively all advancements in deep learning methods aimed at detecting community-acquired pneumonia, viral pneumonia, and Covid-19 from images of chest X-rays and CT scans. Being a systematic review, the focus of this paper lies in explaining various deep learning model architectures, which have either been modified or created from scratch for the task at hand. For each model, this paper answers the question of why the model is designed the way it is, the challenges that a particular model overcomes, and the tradeoffs that come with modifying a model to the required specifications. A grouped quantitative analysis of all models described in the paper is also provided to quantify the effectiveness of different models with a similar goal. Some tradeoffs cannot be quantified and, hence, they are mentioned explicitly in the qualitative analysis, which is done throughout the paper. By compiling and analyzing a large quantum of research details in one place with all the data sets, model architectures, and results, we aimed to provide a one-stop solution to beginners and current researchers interested in this field.

简介：AbstractBackground:In-hospital mortality in patients with coronavirus disease 2019 (COVID-19) is high. Simple prognostic indices are needed to identify patients at high-risk of COVID-19 health outcomes. We aimed to determine the usefulness of the CONtrolling NUTritional status (CONUT) index as a potential prognostic indicator of mortality in COVID-19 patients upon hospital admission.Methods:Our study design is of a retrospective observational study in a large cohort of COVID-19 patients. In addition to descriptive statistics, a Kaplan-Meier mortality analysis and a Cox regression were performed, as well as receiver operating curve (ROC).Results:From February 5, 2020 to January 21, 2021, there was a total of 2969 admissions for COVID-19 at our hospital, corresponding to 2844 patients. Overall, baseline (within 4 days of admission) CONUT index could be scored for 1627 (57.2%) patients. Patients’ age was 67.3 ± 16.5 years and 44.9% were women. The CONUT severity distribution was: 194 (11.9%) normal (0-1); 769 (47.2%) light (2-4); 585 (35.9%) moderate (5-8); and 79 (4.9%) severe (9-12). Mortality of 30 days after admission was 3.1% in patients with normal risk CONUT, 9.0% light, 22.7% moderate, and 40.5% in those with severe CONUT (P < 0.05). An increased risk of death associated with a greater baseline CONUT stage was sustained in a multivariable Cox regression model (P < 0.05). An increasing baseline CONUT stage was associated with a longer duration of admission, a greater requirement for the use of non-invasive and invasive mechanical ventilation, and other clinical outcomes (all P < 0.05). The ROC of CONUT for mortality had an area under the curve (AUC) and 95% confidence interval of 0.711 (0.676-0746).Conclusion:The CONUT index upon admission is potentially a reliable and independent prognostic indicator of mortality and length of hospitalization in COVID-19 patients.

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简介：AbstractBackground:The damage inflicted by the coronavirus diseases 2019 (COVID-19) pandemic upon humanity is and will continue to be considerable. Unprecedented progress made in global health over the past 20 years has reverted and economic growth has already evaporated, giving rise to a global recession, the likes of which we may not have experienced since the Second World War. Our aim is to draw the attention of the neglected tropical disease (NTD) community towards some of the major emerging economic opportunities which are quickly appearing on the horizon as a result of COVID-19.Main text:This scoping review relied on a literature search comprised of a sample of articles, statements, and press releases on initiatives aimed at mitigating the impact of COVID-19, while supporting economic recovery. Of note, the donor scenario and economic development agendas are highly dynamic and expected to change rapidly as the COVID-19 pandemic unfolds, as are donor and lender priorities.Conclusions:The NTD community, particularly in low-and middle-income countries (LMICs), will need to work quickly, diligently, and in close collaboration with decision-makers and key stakeholders, across sectors at national and international level to secure its position. Doing so might enhance the odds of grasping potential opportunities to access some of the massive resources that are now available in the form of contributions from corporate foundations, trust funds, loans, debt relieve schemes, and other financial mechanisms, as part of the ongoing and future economic development agendas and public health priorities driven by the COVID-19 pandemic. This paper should serve as a starting point for the NTD community to seek much needed financial support in order to sustain and revitalize control and elimination efforts pertaining to NTDs in LMICs.

简介：AbstractSouth Asian (SA) countries have been fighting with the pandemic novel coronavirus disease 2019 (COVID-19) since January 2020. Earlier, the country-specific descriptive study has been done. Nevertheless, as transboundary infection, the border sharing, shared cultural and behavioral practice, effects on the temporal and spatial distribution of COVID-19 in SA is still unveiled. Therefore, this study has been revealed the spatial hotspot along with descriptive output on different parameters of COVID-19 infection. We extracted data from the WHO and the worldometer database from the onset of the outbreak up to 15 May, 2020. Europe has the highest case fatality rate (CFR, 9.22%), whereas Oceania has the highest (91.15%) recovery rate from COVID-19. Among SA countries, India has the highest number of cases (85,790), followed by Pakistan (38,799) and Bangladesh (20,065). However, the number of tests conducted was minimum in this region in comparison with other areas. The highest CFR was recorded in India (3.21%) among SA countries, whereas Nepal and Bhutan had no death record due to COVID-19 so far. The recovery rate varies from 4.75% in the Maldives to 51.02% in Sri Lanka. In Bangladesh, community transmission has been recorded, and the highest number of cases were detected in Dhaka, followed by Narayanganj and Chattogram. We detected Dhaka and its surrounding six districts, namely Gazipur, Narsingdi, Narayanganj, Munshiganj, Manikganj, and Shariatpur, as the 99% confidence-based hotspot where Faridpur and Madaripur district as the 95% confidence-based spatial hotspots of COVID-19 in Bangladesh. However, we did not find any cold spots in Bangladesh. We identified three hotspots and three cold spots at different confidence levels in India. Findings from this study suggested the "Test, Trace, and Isolation" approach for earlier detection of infection to prevent further community transmission of COVID-19.

简介：摘要乳腺癌已经成为中国女性发病率第一位的恶性肿瘤。在中国抗击COVID-19疫情取得阶段性胜利的时刻，乳腺外科医师应认真总结疫情期间开展乳腺肿瘤诊治的经验，并指导"后疫情阶段"的临床实践。其中，必须坚持患者最大获益和最小受害的理念，优化选择综合治疗方案。而综合评价乳腺癌患者的临床分期和分子分型是制定临床决策的关键。同时，美国外科学会以临床危险度为参考依据，针对临床外科处理原则制定了宏观指导意见，并提出基于疫情防控的需要，乳腺癌患者外科手术可能需要推迟6~8周时间的观点。

简介：摘要目的认知我国COVID-19疫情发展规律，分全国、湖北省、中国其他地区(以下简称"湖北域外地区")三类疫情发展趋势进行预测。方法使用传染病动力学中的分块房室模型对现有数据进行拟合并估计参数，用定参后的模型对未来疫情发展进行模拟。结果湖北省与湖北域外地区模型拟合参数及在不同人群中的转移模式具有一定地理差异性，湖北域外地区显示出更好的态势。预测湖北省和湖北域外地区现有确诊病例降至0人的时间分别为2020年5月和2020年4月。结论预测疫情可于2020年5月下旬结束，充足的医疗资源投入和对疑似人群进行更加全面和准确的排查，对控制疫情具有重要作用。

简介：摘要目的探究肛拭子阳性患者临床特征及其价值。方法选取104例COVID-19确诊患者，在入院时采集咽拭子、痰液、血液和肛拭子检测2019-nCoV核酸；依据不同标本核酸阴阳性分组比较临床特征和血液学指标；选取15例肛拭子核酸阳性患者追踪分析其不同标本核酸转阴时间。结果与肛拭子阴性患者相比，阳性患者具有较低的淋巴细胞(LYM)和较高的乳酸脱氢酶(LDH)及超敏C反应蛋白(HsCRP)，且重症比例更高。咽拭子阳性患者HsCRP、IL-6和重症比例亦显著高于阴性患者。痰液阴阳性患者间血液学指标和重症比例差异无统计学意义。血液阳性比例仅为1.92%，但均为重症患者；痰液阳性率最高为46.15%。咽拭子和肛拭子均阳性患者LYM显著下降，而HsCRP、IL-6和危重比例均显著增高。追踪结果显示肛拭子和痰液转阴时间较长，警惕痰液复阳现象。结论肛拭子阳性患者具有更低的LYM和更高的炎症水平及重症比例，提示其可能成为预测重症发生的因素。且转阴时间长于咽拭子，联合咽拭子和肛拭子检测有助于预测重症发生。

简介：摘要：目的：为了提高样本采集质量，提高工作效率，提升 COVID-19康观人员的满意度，减少防护用品的消耗，降低院内感染发生风险，我院组建样本采集队承担隔离区全部样本的采集任务。方法：组建由 13名护士、 2名指导专家组成的样本采集队，全员经传染病及医院感染管理相关知识及 COVID-19诊疗指南，咽拭子，肛拭子采集操作规范等培训合格，制定规范的操作流程后于 3月 2日开展临床工作。 结果： 2020 年 02 月 26 日至 3 月 31 日，共采集鼻咽拭子、肛拭子、血液样本 1369份（其中鼻咽拭子 609份、肛拭子 599份、血液标本 161份），对比组建采样队前后两组（ 3月 1日前、 3月 2日后）采样样本阳性率分别为咽拭子 2.44%、 7.39%，肛拭子 0、 2.3%，总样本阳性率 1.3%、 4.86%，提示采样队采样阳性率远远高于病区护士组；两组采样发生缺陷、错误比较分别为 2.60%、 0.7%，提示病区护士组远远高于采样组， 2组均未发生采样遗漏、样本泄漏、样本质量不合格及样本丢失等不良事件；我们也对两组防护用品的消耗量进行了对比， P 0.0005，具有极显著统计学意义；采样队成员零感染；观察人员入住期间整体满意度 97%。结论：组建采样队的工作模式在 COVID-19出院后集中隔离观察区的运用卓有成效，有临床推广价值。

简介：摘要新型冠状病毒造成的2019冠状病毒性疾病(COVID-19)是目前中国乃至全球的临床关注焦点。世界卫生组织及国家卫健委均发布了关于COVID-19诊疗的临时指南和诊疗方案，这些综合性指导文件为一线临床工作制定了基本规范。然而心血管外科疾病有其特殊病理生理特点，尤其是心血管急危重症常须急诊手术治疗，亟需制定相应管理策略。自2020年1月16日至2月12日，武汉协和医院心血管外科共完成各类心血管急危重症急诊手术15例，其中明确排除COVID-19感染9例，疑似感染6例，无确诊感染病例。围手术期成功率100%，无相关医护人员感染及患者交叉感染，取得满意治疗效果。本文基于该中心临床实践经验，总结相关经验及管理策略，与世卫组织临时指南和国家卫健委方案进行对比，希望能与之互为补充，为COVID-19疫情下心血管外科医师临床工作提供参考。

简介：【摘 要】 2019年起始于我国的新型冠状病毒感染（ COVID-19）已经成为全球关注的重大公共卫生事件。新型冠状病毒传播途径多样，人群普遍易感，使疫情防控难度增大。因此，切断传染源，阻断传播途径，才能最大限度控制疫情的播散。医院是病人聚集的流动性场所，是疫情防控的重要环节；而护理人员在临床工作中密切接触各类病人，是感染的高危人群，也是疫情防控的中坚力量。本文通过分析与护理工作相关的 COVID-19传播风险，进而提出相应的防控措施，为 2019-nCoV的医院防控提供参考。

简介：【摘要】 目的 探讨152例疑似和确诊新型冠状病毒肺炎COVID-19住院患者的心理干预。方法：在隔离治疗期间通过访谈了解患者心理反应，予以相应的心理支持与人文关怀、提供依赖型护理、紧密护理及舒适、安全的住院环境。结果：患者提高了对隔离及治疗的认知水平，住院期间心理压力降低，积极配合隔离治疗。结论：本研究显示通过及时对患者实施心理支持，使患者感受到医护人员对他们的关心、照顾，真正满足了患者的生理和心理需求，降低了患者对突发传染病的恐惧、紧张，坚定了康复信心。

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简介：摘要目的多层螺旋CT观察新型冠状病毒肺炎（COVID-19）患者肾上腺的大小、密度及其动态变化。方法回顾性分析67例COVID-19患者（简称新冠组）和70例正常对照组的肾上腺CT平扫图像。新冠组根据临床分型分为普通型、重型两组。测量对照组（单时相）和新冠组（多时相）的肾上腺厚度和CT值，并计算肾上腺/竖脊肌CT密度比值。结果双侧肾上腺的体部、内外侧支厚度在新冠组入院、出院时与对照组比较差异均有统计学意义（P<0.05），新冠组大于对照组；肾上腺/竖脊肌CT值比差异均无统计学意义。右侧肾上腺内侧支最大厚度作为诊断标准所得的ROC曲线下面积最大（0.881）。新冠组患者双侧肾上腺体部、内外侧支厚度和肾上腺/竖脊肌CT值比在不同时期组间比较差异均无统计学意义。结论COVID-19患者双侧肾上腺轻微肿胀，体部、内外侧支厚度略大于正常肾上腺，密度无异常，在病程中无明显动态变化。

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简介：AbstractFollowing the emergence of COVID-19 outbreak, numbers of studies have been conducted to curtail the global spread of the virus by identifying epidemiological changes of the disease through developing statistical models, estimation of the basic reproduction number, displaying the daily reports of confirmed and deaths cases, which are closely related to the present study. Reliable and comprehensive estimation method of the epidemiological data is required to understand the actual situation of fatalities caused by the epidemic. Case fatality rate (CFR) is one of the cardinal epidemiological parameters that adequately explains epidemiology of the outbreak of a disease. In the present study, we employed two statistical regression models such as the linear and polynomial models in order to estimate the CFR, based on the early phase of COVID-19 outbreak in Nigeria (44 days since first reported COVID-19 death). The estimate of the CFR was determined based on cumulative number of confirmed cases and deaths reported from 23 March to 30 April, 2020. The results from the linear model estimated that the CFR was 3.11% (95% CI: 2.59% - 3.80%) with R2 value of 90% and p-value of < 0.0001. The findings from the polynomial model suggest that the CFR associated with the Nigerian outbreak is 3.0% and may range from 2.23% to 3.42% with R2 value of 93% and p-value of <0.0001. Therefore, the polynomial regression model with the higher R2 value fits the dataset well and provides better estimate of CFR for the reported COVID-19 cases in Nigeria.

简介：摘要目的回顾性分析新型冠状病毒肺炎(COVID-19)患者合并细菌及真菌感染的临床特点和耐药情况。方法收集同济医院2020年2月10日至3月31日血液、尿液、痰液和纤支镜冲洗液培养阳性的COVID-19患者的临床资料，采用WHONET5.6分析统计药敏数据。结果共收集病原菌培养阳性COVID-19患者95例，非危重型患者23例，危重型72例，临床症状主要为发热、咳嗽咳痰、乏力、呼吸困难等，危重型男性患者占63.89%，女性患者占36.11%，危重型患者以男性居多，患者合并多种细菌和真菌感染以危重型为主，占23.61%，非危重型和危重型患者的死亡率分别为13.04%和61.11%,危重型患者的死亡率明显高于非危重型患者。病原菌共179株，大肠埃希菌在非危重型患者中检出率较危重型高，占37.50%,鲍曼不动杆菌和肺炎克雷伯菌在危重型患者中检出率较非危重型都高，各占29.87%，革兰阳性菌及真菌在非危重型和重型患者中的差异无统计学意义，但危重型患者血液真菌培养中提示近平滑念珠菌占比较高，为36.40%，临床不容忽视。药敏分析结果显示未发现大肠埃希菌对碳青霉烯类药物的耐药株，肺炎克雷伯菌对碳青霉烯类药物的耐药率为60.87%，鲍曼不动杆菌对3种抗菌药物的耐药率均为100%，耐甲氧西林金黄色葡萄球菌占71.43%，未发现万古霉素耐药的革兰阳性球菌。结论COVID-19患者危重型以男性患者居多，其容易合并多种细菌和真菌感染，且死亡率比非危重型患者高。危重型患者常合并感染细菌为鲍曼不动杆菌和肺炎克雷伯菌等医院获得性菌株，其耐药性较高。