城市社区尺度花粉致敏风险评估方法研究进展

目前,花粉过敏性疾病在国内外城市中均具有较高发病率。作为城市居民生活的基本单元,社区对居民健康有重要的影响。因此,社区尺度的花粉致敏风险评估研究是提升居民健康的重要抓手。鉴于此,研究从花粉产生的植物本体角度和影响花粉传播的空间环境角度系统地综述了影响社区花粉致敏风险的相关因素,并进一步梳理了花粉致敏风险的评估方法。研究发现:在空间尺度上,目前国内外评估花粉致敏风险相关方法主要应用于微观的植物尺度与宏观的城市尺度,在中观尺度的应用仅局限于校园、公园中的绿地,尚未对社区进行研究;在评估因素上,现有评估方法多关注植物自身因素,如树木高度、冠幅等因素,而较少涉及诸如通风、温湿度等环境因素;然而社区中环境条件复杂,建筑环境不容忽视,因此了解植物与环境的综合作用对于社区花粉致敏风险的评估至关重要。基于上述发现,提出未来建立适宜社区尺度的致敏评估方法的可能途径:首先应建立适用于评估社区常用植物的统一标准数据集,在综合考虑植物因子、社区环境因子和临床患病率等各类因子的基础上建立社区花粉致敏风险评估方法,还可利用可视化技术建立包含社区三维特征的模型来模拟社区花粉分布及扩散规律,确立社区尺度下花粉致敏风险评估方法,降低社区花粉致病率,进一步提升居民健康水平。     

对想定北京和广州发生输入性埃博拉疫情的计算实验研究

本次西非埃博拉疫情引起了世界范围内的高度重视,各国纷纷开展风险评估研究。我们采用仓室模型和基于Agent模型,对北京市和广州市想定发生输入性埃博拉疫情的后续疫情发展态势开展计算实验研究,对影响疫情发展的主要因素进行分析。结果显示,在严格执行埃博拉防控预案、尽快隔离传染性病例的情况下,埃博拉在两地暴发的风险很小。同时,以数据为驱动的计算流行病学也对公共卫生应急部门的基础数据准备工作提出了更高要求。     

基于机器学习的环氧合酶-2抑制剂分类模型的构建

摘要 目的：构建环氧合酶-2（Cyclooxygenase-2,COX-2）抑制剂分类模型,用以筛选和优化COX-2抑制剂。方法：基于八种机器学习算法构建模型,比较不同模型的预测性能,筛选出最优模型后利用Y随机验证法对其进行测试,最后运用SHAP（Shapley Additive eXplanation）算法对最优模型进行可解释性分析。结果：八种不同模型的性能比较结果显示,基于随机森林算法建立的模型最优,其预测准确率、平衡准确率、马修斯相关系数、特征曲线下面积和F1分数（分别为0.893、0.825、0.673、0.909和0.933）最高;Y随机验证结果表明最优模型的预测结果并非偶然;此外,通过SHAP算法挖掘出20个最有可能影响COX-2抑制剂活性的结构片段。结论：本研究为新型COX-2抑制剂的开发提供理论依据,可供本领域其他研究人员对先导化合物进行优化或设计更好的COX-2抑制剂。     

基于机器学习算法的草地地上生物量估测——以祁连山草地为例

草地地上生物量（Aboveground Biomass,AGB）是指导畜牧业生产管理的重要指标,是草畜平衡综合分析的基础。目前,有关祁连山草地AGB反演的研究较少,且多源数据间的尺度差异问题并未得到很好的解决。为了解祁连山草地AGB的空间分布状况,利用Sentinel-2多光谱数据、无人机（Unmanned Aerial Vehicle,UAV）数据以及2021年植被生长期实测草地AGB数据实现了空天地一体化监测,通过决策树回归（Decision Tree Regression,DTR）、随机森林回归（Random Forest Regression,RFR）、梯度提升决策回归树（Gradient Boosting Regression Tree,GBRT）以及极致梯度提升（eXtreme Gradient Boosting,XGBoost）共4种算法反演草地AGB的适用性分析,利用最优模型反演了祁连山草地的AGB空间分布状况。结果表明：研究区内多种植被指数所表现出的特性有所差异。祁连山地区AGB在空间分布上呈现出由西北向东南递增的趋势,平均AGB为925.43kg/hm²。6种植被指数与实测AGB之间均表现为显著正相关,适合作为祁连山草地AGB遥感反演的指标;XGBoost模型较其它模型具有最高的R²值（0.78）和精度（74.75%）、最低的均方根误差（RMSE,99.74 kg/hm²）和平均绝对误差（MAE,71.60 kg/hm²）,模型反演效果最好;UAV数据能够提供更加详细的空间细节特征,减小Sentinel-2数据和实地采样数据间的尺度差异;因此,基于6种植被指数与祁连山草地AGB间的相关性,构建XGBoost模型反演研究区草地AGB空间分布状况是具有实践意义的。研究结果将为指导祁连山草地畜牧业的发展和维护草地生态系统的平衡提供一定的参考价值与数据支撑。     

新冠疫情对全球生物多样性热点地区森林面积的影响

森林是维持生物多样性的重要保障,森林面积的损失常常会导致区域生物多样性的降低或丧失。为探讨新冠疫情对全球生物多样性的影响,该文利用Image J软件筛选出全球生物多样性热点地区占国土面积超60%的国家作为研究对象,以全球生物多样性热点地区的森林损失面积、生物多样性完整性数据、年度(2020年和2021年)新冠疫情感染数据、国内生产总值(GDP)为研究对象,进行关联分析、线性混合效应模型构建和回归预测。结果表明:虽然新冠病毒的每百万人口感染数量与森林损失面积表现为显著负相关,具体表现为新冠疫情显著减少了因城市和农业大规模扩张而导致的森林损失面积,但在新冠疫情暴发的2年(2020年和2021年)期间,全球生物多样性热点地区的森林损失总量仍然持续上升,主要原因是新冠疫情间接加速了人工林和天然林的采伐。回归模型预测显示,新冠疫情期间,全球生物多样性热点地区的森林损失面积在2020年和2021年分别增加了5.83%和21.78%。综上表明,虽然新冠疫情对生物多样性热点地区的森林损失具有一定的抑制作用,但森林损失面积仍然在增加。该研究结果为制定生物多样性的保护措施提供了数据支撑。     

基于森林资源清查、卫星影像数据与随机协同模拟尺度转换方法的森林碳制图

当前,全球变暖对地球生态系统的影响正引起世界的广泛关注.为减缓其影响进程,让决策者获得准确的碳源/碳汇空间分布信息与动态至关重要.目前面临的重大挑战是如何准确估计森林碳的空间分布和分析估计结果的不确定性.本研究基于森林资源连续清查样地数据和遥感影像数据发展了一个森林碳制图的一般方法.基于序列高斯协同模拟算法,结合样地数据与卫星影像数据进行模拟,将森林碳汇分布图的尺度从30 m×30 m转换到900m×900m(区域、国家和全球森林碳制图单位大小).以临安市为例,利用全市2004年森林资源清查样地数据和同年度Landsat TM影像数据,进行研究区森林碳(地上部分)模拟和尺度转换.结果显示,方法准确重现了森林碳空间分布和变异规律,在分布上模拟结果与地面样地属性具有较好的一致性,在数量上模拟结果的总体平均值较地面样地的总体平均值低约24.9%;模拟还提供了其估计结果的不确定性, 包括估计值的方差和估计值大于一定阈值的概率,这些可用于不确定性传播模型的模拟分析,进而实现对森林碳估计结果的评价.     

基于不同空间尺度遥感影像估算森林叶面积指数的差异

地面测量点对遥感像元的代表性如何,怎样获取像元的相对真值,多大的空间分辨率可以真实地反映森林区域的叶面积指数(LAI),这些都是定量遥感中的重要问题.本研究计算LAI-2200和TRAC两种冠层分析仪测量的空间范围,并结合GF-2(4.1 m)、Sentinel-2(10 m)、Landsat-8(30 m)3种不同空间分辨率遥感影像,找到各尺度下像元的相对真值,在保持真值观测面积和遥感获取面积一致的条件下,基于一元指数和多元回归模型,对比分析不同空间分辨率影像对估算森林LAI的影响,并对3种影像模型进行30和100 m尺度下的检验以及各自数据集的空间代表性评价,比较得出最适合表达研究区域森林LAI的尺度.结果表明:对于森林来说,高分辨率并不一定能充分反映森林LAI.基于3种分辨率影像的统计模型都能很好地估测森林LAI,其中,基于Sentinel-2的反演精度最高,基于GF-2的反演精度最低.30和100 m尺度下的检验结果表明,基于GF-2反演模型高估了森林LAI,基于Landsat-8的反演模型低估了森林LAI,基于Sentinel-2分辨率的统计模型可以很好地估测研究区域森林LAI.     

水生动物进口风险评估综述

随着全球水产养殖业的发展,水产动物活体或水产品贸易日益频繁,不可避免地给进口国带来病原风险,造成疾病引入和传播,甚至生物入侵,严重危害水产养殖业的发展。水生动物进口风险评估(IRA),是指从别国或地区进口水生动物活体包括其受精卵、稚鱼、幼鱼、苗种、成体以及商品等的风险分析。风险分析是指对风险事件进行科学、透明、系统分析的一个过程,它由危害识别、风险评估、风险交流和风险管理4个部分构成。目前,常用的风险评估方法有定性风险评估、半定量风险评估和定量风险评估3种。定性风险评估具有灵活性强、适用范围广、易掌握的特点,能够综合各种资料、数据和信息,尤其适合初次风险评估,但容易受评估人员主观因素的影响。定量风险评估可避免主观因素的影响,评估结果准确、可靠,但需要收集大量数据,工作量巨大,评估成本也很高。通常,定性评估结果若能够提供很好的防范措施,则不必进行定量评估。将外来水生病原阻止在引进之初远比引入后根除更加容易。因此,开展水生动物进口风险评估对于阻止水生动物疾病传播和水生态环境破坏具有重要意义,同时也可为各国进行水产贸易提供参考。     

基于植被和环境因子的亚高山森林土壤水源涵养功能空间尺度上推模型构建——以岷江上游杂谷脑流域为例

土壤层水源涵养功能是森林水源涵养功能的主体。目前关于森林土壤水源涵养功能的研究主要集中在林地或坡面尺度上。由于流域尺度,尤其是环境空间异质性强的西南亚高山区流域,如何将林地尺度实测结果上推至流域或更大空间尺度仍是生态水文领域面临的巨大挑战之一。以川西岷江上游杂谷脑流域为研究对象,融合多种森林类型样地实测与流域尺度多源遥感数据,构建了基于植被和环境因子的林地-流域森林土壤水源涵养功能尺度转换模型,实现了流域尺度土壤水源涵养功能快速评价及其空间分布预测。样地尺度研究结果表明各类型森林的土壤水文特性各异,总体表现为天然林优于人工林,混交林优于单纯林。林地土壤持水能力受到区域气候、植被、土壤及地形等因子的共同影响,其中风速、NDVI及林龄与土壤最大持水量、毛管持水量及非毛管持水量均呈极显著正相关（P<0.01）。基于关键植被和环境因子构建的林地-流域土壤水源涵养功能尺度上推模型精度较高,土壤最大持水量、土壤毛管持水量和土壤非毛管持水量模型拟合优度R²分别为0.700、0.720和0.908;土壤最大持水量、土壤毛管持水量和土壤非毛管持水量的模型预测值与野外实测值的相关系数介于0.69-0.79之间,平均误差均低于20%,表明模型预测结果可靠。利用构建的土壤水源涵养功能尺度上推模型,估算得出流域尺度森林土壤持水量的空间分布,其结果表明杂谷脑流域森林土壤持水量空间分异明显,海拔较高区域森林土壤持水量最高,其次为距道路和河流有一定距离的缓坡地带,下游干旱河谷地区土壤持水量最低。本研究为亚高山森林生态功能的恢复和提升提供了科学依据和评价工具。     

涡度相关观测的太湖CH4通量数据插补方法评价

涡度相关法是在湖泊开展CH₄通量长期连续观测的重要方法。受到多种因素的影响,CH₄通量观测数据存在大量缺失。为重构完整的CH₄通量时间序列,就需要适宜的数据插补方法。本研究利用太湖涡度通量观测网络东部的避风港站点2014—2017年的常规气象数据及涡度相关观测的CH₄通量数据,在分析半小时尺度以及日尺度CH₄通量影响要素的基础上,测试了非线性回归法以及随机森林算法和误差反向传播算法在半小时尺度及日尺度上插补CH₄通量缺失数据的可行性。结果表明: 在半小时尺度上,避风港站生长季CH₄通量主要受到底泥温度、摩擦风速、气温、相对湿度、潜热通量和20 cm处水温的影响,非生长季主要受到相对湿度、潜热通量、风速、感热通量和底泥温度的影响,而在日尺度上CH₄通量主要受潜热通量和相对湿度的影响。在对CH₄通量缺失数据的插补中,随机森林模型在所有时间尺度上都表现为最佳的插补性能,其中,将日序、太阳高度角、底泥温度、摩擦风速、气温、20 cm处水温、相对湿度、气压和风速作为输入变量的随机森林模型更适用于半小时尺度缺失数据的插补;将日序、底泥温度、摩擦风速、气温、20 cm处水温、相对湿度、气压、风速和向下短波辐射作为输入变量的随机森林模型更适用于日尺度缺失数据的插补;整体上,插补模型对日尺度缺失数据的插补优于半小时尺度。     

Characteristics of SARS-CoV-2 transmission in a medium-sized city with traditional communities during the early COVID-19 epidemic in China

The nationwide COVID-19 epidemic ended in 2020, a few months after its outbreak in Wuhan, China at the end of 2019. Most COVID-19 cases occurred in Hubei Province, with a few local outbreaks in other provinces of China. A few studies have reported the early SARS-CoV-2 epidemics in several large cities or provinces of China. However, information regarding the early epidemics in small and medium-sized cities, where there are still traditionally large families and community culture is more strongly maintained and thus, transmission profiles may differ, is limited. In this study, we characterized 60 newly sequenced SARS-CoV-2 genomes from Anyang as a representative of small and medium-sized Chinese cities, compared them with more than 400 reference genomes from the early outbreak, and studied the SARS-CoV-2 transmission profiles. Genomic epidemiology revealed multiple SARS-CoV-2 introductions in Anyang and a large-scale expansion of the epidemic because of the large family size. Moreover, our study revealed two transmission patterns in a single outbreak, which were attributed to different social activities. We observed the complete dynamic process of single-nucleotide polymorphism development during community transmission and found that intrahost variant analysis was an effective approach to studying cluster infections. In summary, our study provided new SARS-CoV-2 transmission profiles representative of small and medium-sized Chinese cities as well as information on the evolution of SARS-CoV-2 strains during the early COVID-19 epidemic in China.     

生态位模型在流行病学中的应用

随着新冠肺炎(COVID-19)疫情在全球逐渐开始蔓延, 对其传播范围以及强度的风险评估工作越来越受到人们的重视。作为生态学和生物地理学中常用的研究手段, 生态位模型也被应用到该项工作中来。虽然预测流行病的传播热点和趋势是生态位模型的应用方向之一, 但由于新冠病毒(SARS-CoV-2)自身特点, 生态位模型并非预测其潜在传播范围的有力工具。本文回顾了近些年来生态位模型在各种流行病学研究中的应用, 比较了疫病传播中常用生态位建模方法的优势与不足, 分析了适用生态位建模的疫病案例以及不适用于生态位建模的疫病特点, 明确指出, 生态位模型只能用于分析流行病在传播过程中受自然环境干扰的部分, 如中间宿主的潜在分布等。而对于包括COVID-19在内的主要通过人传人的流行病, 生态位模型尚无有效的手段进行预测。尽管生态位模型可用于分析流行病的传播范围, 但在使用时需要根据疾病特点有针对性地选择合适的建模方法与建模对象。为了量化疫病传播风险, 还需要考虑其他干扰因素, 以便准确测试和评估生态位模型。若不加选择地滥用生态位模型的工具, 反而会误导决策者的判断。总之, 在应用生态位模型进行研究工作, 特别是预测流行病的传播范围时, 首先要考虑建模对象是否满足生态学假设。     

Estimating direct and spill-over impacts of political elections on COVID-19 transmission using synthetic control methods

Mass gathering events have been identified as high-risk environments for community transmission of coronavirus disease 2019 (COVID-19). Empirical estimates of their direct and spill-over effects however remain challenging to identify. In this study, we propose the use of a novel synthetic control framework to obtain causal estimates for direct and spill-over impacts of these events. The Sabah state elections in Malaysia were used as an example for our proposed methodology and we investigate the event’s spatial and temporal impacts on COVID-19 transmission. Results indicate an estimated (i) 70.0% of COVID-19 case counts within Sabah post-state election were attributable to the election’s direct effect; (ii) 64.4% of COVID-19 cases in the rest of Malaysia post-state election were attributable to the election’s spill-over effects. Sensitivity analysis was further conducted by examining epidemiological pre-trends, surveillance efforts, varying synthetic control matching characteristics and spill-over specifications. We demonstrate that our estimates are not due to pre-existing epidemiological trends, surveillance efforts, and/or preventive policies. These estimates highlight the potential of mass gatherings in one region to spill-over into an outbreak of national scale. Relaxations of mass gathering restrictions must therefore be carefully considered, even in the context of low community transmission and enforcement of safe distancing guidelines.     

新型冠状病毒病(COVID-19)研究进展

2019年12月,湖北省武汉市暴发了一种由新型冠状病毒引起的肺炎(COVID-19)随后蔓延到中国所有省区以及多个国家和地区,WHO宣布其为全球关注的突发公共卫生事件。及时了解和表征该病毒对抗击疫情至关重要。通过收集和梳理该疫情暴发之后2个月内全球多领域研究人员关于COVID-19的论文,发现这些研究主要集中在溯源分析、检测手段、病患治疗、临床表现、药物研发、致病机理、传播途径、流行特征等方面。该冠状病毒与蝙蝠冠状病毒以及穿山甲冠状病毒相关,其利用与SARS-CoV相同的人受体ACE2,感染途径证实为呼吸系统和消化系统。该病毒具有人际传播能力,并且出现无症状传播。COVID-19确诊病例多数与武汉有关,大多数为轻症,年老者病死率较高。快速灵敏核酸检测通常作为确诊依据,目前已经筛选出有价值的候选药物如瑞德西韦进行临床试验。中国采取的旅行禁令和隔离等干预措施有效减轻了疫情蔓延。     

Accumulating Impact of Smoking and Co-morbidities on Severity and Mortality of COVID-19 Infection: A Systematic Review and Meta-analysis

BackgroundHigh prevalence, severity, and formidable morbidity have marked the recent emergence of the novel coronavirus disease (COVID-19) pandemic. The significant association with the pre-existing co-morbid conditions has increased the disease burden of this global health emergency, pushing the patients, healthcare workers and facilities to the verge of complete disruption.MethodsMeta-analysis of pooled data was undertaken to assess the cumulative risk assessment of multiple co-morbid conditions associated with severe COVID-19. PubMed, Scopus, and Google Scholar were searched from January 1^st to June 27^th 2020 to generate a well-ordered, analytical, and critical review. The exercise began with keying in requisite keywords, followed by inclusion and exclusion criteria, data extraction, and quality evaluation. The final statistical meta-analysis of the risk factors of critical/severe and non-critical COVID-19 infection was carried out on Microsoft Excel (Ver. 2013), MedCalc (Ver.19.3), and RevMan software (Ver.5.3).ResultsWe investigated 19 eligible studies, comprising 12037 COVID-19 disease patients, representing the People’s Republic of China (PRC), USA, and Europe. 18.2% (n = 2200) of total patients had critical/severe COVID-19 disease. The pooled analysis showed a significant association of COVID-19 disease severity risk with cardiovascular disease (RR: 3.11, p < 0.001), followed by diabetes (RR: 2.06, p < 0.001), hypertension (RR: 1.54, p < 0.001), and smoking (RR: 1.52, p < 006).ConclusionThe review involved a sample size of 12037 COVID-19 patients across a wide geographical distribution. The reviewed reports have focussed on the association of individual risk assessment of co-morbid conditions with the heightened risk of COVID-19 disease. The present meta-analysis of cumulative risk assessment of co-morbidity from cardiovascular disease, diabetes, hypertension, and smoking signals a novel interpretation of inherent risk factors exacerbating COVID-19 disease severity. Consequently, there exists a definite window of opportunity for increasing survival of COVID-19 patients (with high risk and co-morbid conditions) by timely identification and implementation of appropriately suitable treatment modalities.     

The significance of advanced COVID-19 diagnostic testing in pandemic control measures

During the 2 years since the start of the novel coronavirus disease 2019 (COVID-19) pandemic, the scientific world made an enormous effort to fight against this disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has high transmissibility. Advancements in vaccine and treatment strategies have reduced both the hospitalization and mortality rates. However, the virus has shown its ability to evolve and evade from our COVID-19 combating armamentaria by the most common evolution mechanism—mutation. Diagnostic testing has been the first line of defense following the identification of the causative agent. Ever since, the scientific community has developed nuclei acid-based, antigen-based, and antibody-based diagnostic tests, and these testing methodologies are still playing a central role in slowing down viral transmission. These testing methods have different sensitivity and specificity and could be optimally used in areas facing different challenges owing to different level and conditions of COVID-19 outbreak. In this review, we discuss these testing methodologies as well as the considerations on how to apply these diagnostic tests optimally in the community to cope with the ever-changing pandemic conditions.     

从新型冠状病毒疫情看生物安全三级实验室的应急能力及内涵建设

面对突发疫情,生物安全三级（biosafety level 3,BSL-3）实验室是否能及时启动并稳定、安全运行,为科研攻关提供安全、可靠的技术平台,是对实验室应急能力的考验。针对2019年12月爆发的2019冠状病毒病疫情,复旦大学BSL-3实验室在接到任务后,立即按照国家规定,启动实验室冠状病毒新实验活动申请流程。经国家合格评定认可委员会（China National Accreditation Service for Conformity Assessment,CNAS）和国家卫生委员会批准,实验室在开展实验活动一周内就从来自上海患者标本中分离到新型冠状病毒毒株,体现了平时实验室内涵建设的重要性。BSL-3实验室的内涵建设包括实验室风险评估及管理、不同人员针对性培训、设施和设备管理等生物安全管理体系的建设。本文将介绍复旦大学BSL-3实验室在应急能力及内涵建设方面的经验和体会,期望对BSL-3实验室的建设和管理提供参考。     

COVID-19 under spotlight: A close look at the origin,transmission, diagnosis,and treatment of the 2019-nCoV disease

Months after the outbreak of a new flu-like disease in China, the entire world is now in a state of caution. The subsequent less-anticipated propagation of the novel coronavirus disease, formally known as COVID-19, not only made it to headlines by an overwhelmingly high transmission rate and fatality reports, but also raised an alarm for the medical community all around the globe. Since the causative agent, SARS-CoV-2, is a recently discovered species, there is no specific medicine for downright treatment of the infection. This has led to an unprecedented societal fear of the newly born disease, adding a psychological aspect to the physical manifestation of the virus. Herein, the COVID-19 structure, epidemiology, pathogenesis, etiology, diagnosis, and therapy have been reviewed.     

Current scenario of COVID-19 in pediatric age group and physiology of immune and thymus response

COVID-19 pandemic caused by SARS-CoV-2, continues to manifest with severe acute respiratory syndrome among the adults, however, it offers a convincing indication of less severity and fatality in pediatric age group (0–18 years). The current trend suggests that children may get infected but are less symptomatic with less fatality, which is concordant to earlier epidemic outbreaks of SARS-CoV and MERS-CoV, in 2002 and 2012, respectively. According to the available data, children appear to be at lower risk for COVID-19, as adults constitute for maximum number of the confirmed cases (308,592) and deaths (13,069) as on 22nd March (https://www.worldometers.info/coronavirus). However, rapid publications and information of the adult patients with COVID-19 is in progress and published, on the contrary, almost no comprehensive data or discussion about the COVID-19 in children is available. Therefore, in this review, we outline the epidemiology, clinical symptoms, diagnosis, treatment, prevention, possible immune response and role of thymus in children to combat the COVID-19 outbreak.     

Dispersal dynamics of SARS-CoV-2 lineages during the first epidemic wave in New York City

During the first phase of the COVID-19 epidemic, New York City rapidly became the epicenter of the pandemic in the United States. While molecular phylogenetic analyses have previously highlighted multiple introductions and a period of cryptic community transmission within New York City, little is known about the circulation of SARS-CoV-2 within and among its boroughs. We here perform phylogeographic investigations to gain insights into the circulation of viral lineages during the first months of the New York City outbreak. Our analyses describe the dispersal dynamics of viral lineages at the state and city levels, illustrating that peripheral samples likely correspond to distinct dispersal events originating from the main metropolitan city areas. In line with the high prevalence recorded in this area, our results highlight the relatively important role of the borough of Queens as a transmission hub associated with higher local circulation and dispersal of viral lineages toward the surrounding boroughs.