Objective To describe the epidemiological and clinical characteristics of a cluster of severe fever with thrombocytopenia syndrome (SFTS) cases in Shanghai and assess the potential risk of healthcare-associated transmission. Methods Epidemiological and clinical data were collected from seven patients, including the index case, four family members, and two healthcare workers. Serum samples from five patients were tested for SFTS virus (SFTSV) RNA and SFTSV-specific IgM antibodies. Results The index case developed symptoms on June 12, 2018, and died on June 23. Between June 30 and July 6, three family members and one healthcare worker developed fever, thrombocytopenia, and leukopenia; SFTSV RNA was detected in their blood samples. One family member died of multiple organ failure 11 days after symptom onset. Another family member and one doctor developed febrile symptoms and were positive for SFTSV IgM antibodies. Overall, seven cases were identified, including two deaths and two infections among healthcare workers. Conclusions This cluster suggests possible family and healthcare-associated transmission of SFTSV in Shanghai, a non-endemic area of China. Improved clinical awareness and infection prevention are needed when managing unexplained febrile hemorrhagic illnesses.

As COVID-19 transitions from pandemic to endemic, our prevention and control policies have shifted from broad, strict community interventions to focusing on the prevention of cluster outbreaks. Currently, information on the characteristics of cluster outbreaks remains limited. This study describes the features of COVID-19 clusters in Shanghai. It aims to provide valuable insights for managing localized outbreaks. We conducted a retrospective analysis of clusters of confirmed COVID-19 cases. Epidemiological descriptions, the transmission characteristics of clusters, and individual risk factors for contagiousness were analyzed. A total of 381 cases of COVID-19 were confirmed and 67 clusters were identified. Most clusters (58.21%, 39/67) only had two cases, with a declining proportion held by clusters of more cases. Familial transmission was predominant, accounting for 79.10% (53/67) of clusters. Although other types of cluster outbreaks, such as those in workplaces (1.49%, 1/67), occur less frequently compared to household clusters, they tend to involve larger scales and more cases. Workplaces and similar venues are more likely to experience large-scale cluster outbreaks. Contagiousness was higher among cases with runny nose (risk ratio [RR]: 4.8, 95% CI: 1.40-16.44, p-value = 0.01) and those with diabetes (RR: 3.8, 95% CI: 1.01-14.60, p-value = 0.05). In conclusion, household cluster outbreaks, in particular, are both a key priority and a foundational issue. Establishing an indicator system based on the transmissibility of cases holds significant practical value for infectious disease prevention and control. By enhancing household hygiene and developing a case classification and management system based on transmissibility, it is possible to better prevent and control regional COVID-19 outbreaks.

Background: Little is known about the characteristics of those who transmit SARS-CoV-2 infection vs those who do not, but this information could inform disease control policies. This study described the features of clusters in the first wave of COVID-19 in Shanghai and compared contagiousness by clinical and health care risk factors. Methods: In this retrospective cohort study of cases in Shanghai in January and February 2020, cases with successive generations were considered to be “contagious.” Characteristics of contagious and non-contagious cases were compared in log-binomial models that also adjusted for age and sex. Results: Between January 21 and February 17, 2020, 333 cases of COVID-19 were reported in Shanghai across 28 known infection chains. Contagiousness was higher among cases with a sore throat (risk ratio [RR]: 3.41, 95% CI: 1.59, 7.35, P=0.0051), and those with heart disease (RR: 2.06, 95% CI: 0.72, 5.90). Delays in diagnosis were also associated with higher risk of contagiousness. Having ≥2 medical visits before diagnosis was associated with 4.46 times higher risk of contagiousness (95% CI: 2.03, 9.83, P=0.0002), and there was a non-significant increase in risk with increasing numbers of days between disease onset and isolation (for each day, RR: 1.08, 95% CI: 1.01, 1.16, P=0.1734). Conclusions: Individuals with mild COVID-19 symptoms in the upper respiratory tract may still be contagious, and such individuals should be prioritized for early diagnosis and isolation to limit further chains of transmission.

Aedes albopictus (Diptera: Culicidae) is a major vector of multiple diseases. While vaccines have been developed, preventing these Aedes-borne diseases continues to primarily depend on monitoring and controlling the vector population. Despite increasing research on the impacts of various factors on Ae. albopictus population dynamics, there is still no consensus on how meteorological or environmental factors affect vector distribution. In this study, the relationships between mosquito abundance and meteorological and environmental indicators were examined at the town level based on data collected from July to September, the peak abundance period of 2019 in Shanghai. In addition to performing Poisson regression, we employed the geographically weighted Poisson regression model to account for spatial dependency and heterogeneity. The result showed that the environmental factors (notably human population density, the Normalized Difference Vegetation Index (NDVI), socioeconomic deprivation, and road density) had more significant impacts than the meteorological variables in accounting for the spatial variation of mosquito abundance at a city scale. The dominant environmental variable differed in urban and rural places. Furthermore, our findings indicated that deprived townships are more susceptible to higher vector densities compared to non-deprived townships. Therefore, it is crucial not only to allocate more resources but also to increase attention towards controlling the vectors responsible for their transmission in these townships.

BackgroundAedes albopictus is the dominant mosquito species in residential areas in Shanghai. There are many types of small containers with accumulated water in residential areas, providing a large number of breeding environments for Aedes alpopicuts and leading to an increasing transmission risk of mosquito-borne diseases.ObjectiveTo use random forest to predict breeding of Aedes mosquitoes in small aquatic container habitat in two concentrated reconstruction communities of rural areas in Shanghai, and to understand associated influence of environmental factors on the breeding of Aedes mosquitoes in the process of urbanization.MethodsSmall-scale habitat surveys of Aedes mosquitoes were carried out in two suburb concentrated reconstruction communities (Community A and B) in Shanghai, and the environment where the habitat was located was recorded and analyzed in both communities. The habitat where eggs, larvae, or pupae were found was recorded as positive. Spatial weight matrix was applied on a household basis, and global Moran's I index was used to carry out spatial autocorrelation analysis on the small-scale habitat and positive habitat in the environment of the two communities. When Moran's I is greater than 0, it means that the data present a positive spatial correlation; when Moran's I is less than 0, it means that the data are spatially negatively correlated; when Moran's I is 0, the spatial distribution is random. Combining the results of P and Z values, we explored the spatial distribution characteristics of small-scale habitat and positive habitat in the community environment. Random forest algorithm in machine learning was used to classify and sort environmental-related factors, and predict the breeding of Aedes mosquitoes in small aquatic habitat; receiver operating characteristic (ROC) curve was used to carry out model fitting evaluation.ResultsThe environmental factors including building location (χ2=23.35, P<0.001), open space (χ2=8.83, P=0.003), and having trees (χ2=11.02, P=0.001) had a significant impact on the positive rate of small-scale habitat. The results of spatial characteristics analysis showed that the global Moran's I index of small-scale habitat was −0.092 (Z=−1.09, P=0.274) in Community A and 0.034 (Z=0.52, P=0.602) in Community B, and the global Moran's I index of positive habitat was −0.092 (Z=−1.14, P=0.255) in Community A and 0.070 (Z=0.95, P=0.342) in Community B. Since the P values of Community A and B were greater than 0.1 and the Z values were between −1.65 and 1.65, for both small-scale habitat and positive habitat the spatial characteristics were randomly distributed and no significant spatial aggregation was found. In the fitted random forest algorithm classification prediction model with the top 10 characteristic factors of importance, the area under curve (AUC) value was 0.95, and the prediction fitting effect was satisfactory. The results of classification and sorting indicated that counts of household small-scale habitat and positive habitat were the most important factors for breeding.ConclusionThe random forest model constructed by environmental factor indicators can be used to predict the breeding situation of Aedes mosquitoes in small-scale aquatic habitat, and provide a basis for scientific prevention and control of mosquito breeding for the target area.

Background The duration of antibodies against SARS-CoV-2 in Covid-19 patients remains uncertain. Longitudinal serological studies are needed to prevent disease and transmission of the virus. Methods In 2020, 414 blood samples were tested, obtained from 157 confirmed Covid-19 patients, in a prospective cohort study in Shanghai. Results The seropositive rate of IgM peaked at 40.5% (17/42) within 1 month after illness onset and then declined. The seropositive rate of IgG was 90.6% (58/64) after 2 months, remained above 85% from 2 to 9 months and was 90.9% (40/44) after 9 months. Generalized estimating equations models suggested that IgM (P < 0.001) but not IgG significantly decreased over time. Age ≥ 40 years (adjusted odds ratio [aOR] 4.531; 95% confidence interval [CI] 1.879–10.932), and cigarette smoking (aOR 0.344; 95% CI 0.124–0.951) were associated with IgG, and age ≥ 40 years (aOR 2.820; 95% CI 1.579–5.036) was associated with IgM. After seroconversion, over 90% and 75.1% of subjects were estimated to remain IgG-positive 220 and 254 days, respectively. Of 1420 self-reported symptoms questionnaires, only 5% reported symptoms 9 months after onset. Conclusions In patients with a history of natural infection, anti-SARS-CoV-2 IgG is long-lived, being present for at least 9 months after illness onset. The long duration of natural immunity can mitigate and eliminate Covid-19 and the ongoing pandemic.

目的 研究2018-2020年上海市本地感染及输入性来源登革1型病毒(Dengue Serotype 1 virus,DENV-1)分离株全基因组序列特征.方法 收集登革热疑似病例血清样本,对DENV-1阳性样本进行病毒分离、全基因组扩增与测序,进一步通过构建进化树对全基因组序列进行同源性分析、核苷酸序列及氨基酸序列相似性分析、编码蛋白氨基酸位点差异分析.结果 从88份DENV-1阳性样本中获得31株分离株的全基因组核苷酸序列,其中3株为本地感染病例来源,28株为输入病例来源.进化分析显示,28株分离株的基因型为G-Ⅰ型,与G-Ⅰ型参考序列的核苷酸(氨基酸)相似性均值为96.47％～97.37％(98.78％～99.16％);3株分离株的基因型为G-Ⅳ型,与G-Ⅳ型参考序列的核苷酸(氨基酸)相似性均值为96.66％～96.86％(99.01％～99.26％);3株本地感染病例来源分离株均为G-Ⅰ型,根据同源性分析,存在输入性病例引起本地感染可能.分离株与对照株比较各结构蛋白与非结构蛋白氨基酸位点均存在差异,其中E蛋白的495个氨基酸位点中,有31个位点存在差异.结论 2018-2020年上海市DENV-1包含G-Ⅰ与G-Ⅳ两种基因型,以G-Ⅰ型为主;首次分离得到3株上海市本地感染病例来源DENV-1,为G-Ⅰ型,存在输入性病例引起本地感染可能.

目的 建立基于温度差的CO2诱蚊灯抽样模型,为CO2诱蚊灯监测频次的确定提供科学依据.方法 在上海市15个区,于2019和2020年的4-11月每旬设置229个CO2诱蚊灯监测1次淡色库蚊密度.以2019年的监测数据为训练集,2020年的监测数据为测试集.通过泰勒幂法则建立均数与标准差间的函数,代入两样本均数比较的样本量公式,建立基于密度差的抽样模型.使用线性回归模型建立临近2次CO2诱蚊灯监测结果密度差和该2次监测前1旬的温度差的回归方程,代入基于密度差的抽样模型,建立基于温度差的抽样模型.两样本均数比较使用Wilcoxon秩和检验,模型验证使用准确率、召回率和调和平均值(F-measure)进行评价.结果 2019年相邻2旬、间隔1旬、间隔2旬淡色库蚊监测密度比较,均值差异均有统计学意义(Wilcoxon秩和检验,均P＜0.05),占比分别为34.78％、59.09％和76.19％;2020年相邻2旬、间隔1旬和间隔2旬密度比较,均值的差异有统计学意义(均P＜0.05),占比分别为21.74％、59.09％和66.67％.以2020年数据验证基于温度差的抽样模型,准确率为0.563,召回率为0.720,F-measure为0.632.结论 基于温度差的抽样模型具备实用意义,可以根据温度差估算CO2诱蚊灯监测的最佳监测频次.目前上海市的CO2诱蚊灯监测每年4-11月每旬监测1次,建议间隔1旬开展监测,并根据温度变化适当增加频次.

目的 研究上海市白纹伊蚊媒介丰度的空间稳定性,为登革热防控提供依据.方法 2019年5-11月,在上海市以街镇为监测单位,采用诱蚊诱卵器法对白纹伊蚊密度进行监测.计算诱蚊诱卵器阳性率全局空间自相关Moran'sI指数,探测整个研究区域内白纹伊蚊的空间聚集模式,使用Spearman相关系数计算不同时间行政区或街镇的诱蚊诱卵器阳性率之间的相关性,计算肯德尔和谐系数(Kendall's W)衡量诱蚊诱卵器阳性率等级顺序之间不同时间的一致性.结果 2019年上海市各行政区年平均诱蚊诱卵器阳性率最高为8.70％,最低为1.88％,中位数为5.46％;各街镇年平均诱蚊诱卵器阳性率最高为30.21％,最低为0,中位数为5.51％.空间分析显示全市西部和北部白纹伊蚊密度较高.街镇和行政区尺度上的Spearman相关系数均表现为:与1周前的Spearman相关系数均表现为高于与3周前的,与3周前的相关系数高于与6周前的,行政区尺度的Spearman相关系数大于街镇尺度.研究期间,以行政区为样本单元的诱蚊诱卵器阳性率的肯德尔和谐系数为0.627(x2=197.542,P＜0.001),以街镇为样本单元的诱蚊诱卵器阳性率肯德尔和谐系数为0.436(x2=1 802.154,P＜0.001).结论 诱蚊诱卵器阳性率在行政区尺度空间稳定性好于街镇尺度.因此,在加强白纹伊蚊高密度行政区防控的同时,应关注密度异常变化的街镇区域.

目的 了解上海市徐汇区手足口病(hand-foot-mouth disease,HFMD)病原学及其流行特征,为其防控提供参考依据.方法 采用实时荧光定量聚合酶链式反应(polymerase chain reaction,PCR)对2009-2019年上海市徐汇区采集的上海市徐汇区HFMD病例标本进行肠道病毒检测,并对病原学检测数据进行整理分析.结果 2009-2019年上海市徐汇区共报告现住址在上海市徐汇区HFMD普通病例10 909例,年均报告发病率为84.79/10万(31.32/10万～135.53/10万),累计报告重症病例47例,重症率为0.43％.2009-2012年报告普通病例发病率呈现升高趋势,2013年始,发病率呈现隔年高发.HFMD发病呈现双峰模式,全年发病有2个高峰:4-7月(春夏高峰)占52.38％和9-11月(秋冬高峰)占26.17％,男性发病率(127.60/10万)高于女性发病率(83.58/10万).实验室检测病例共1 239例,阳性标本1 029例(占83.05％).其中,柯萨奇病毒A组6型(CA6)为29.78％、肠道病毒71型(EV71)为21.55％、柯萨奇病毒A组16型(CA16型)为21.23％和其他肠道病毒为10.09％、柯萨奇病毒A组10型(CA10)为0.32％、EV71/CA16混合感染0.08％.上海市徐汇区全年均有HFMD病例报告,发病高峰期为每年3-11月.每年HFMD病毒的型别特征各不相同.病毒核酸检测阳性病例以＜18岁青少儿童为主(99.19％),男性病例阳性检出率(83.24％)略高于女性(82.75％),差异无统计学意义(x2=0.051,P＞0.05).47例重症患者标本中,重症病例EV71型阳性率为16.10％,CA16型为0.38％和其他类型EV为0.80％.结论 2009-2019年上海市徐汇区HFMD病原谱以CA6型为主,除了 EV71和CA16型,还有其他新型肠道病毒,且近年占比呈上升趋势,应予以重视和加强监测.

目的 对上海市一起发生在公共场所的新型冠状病毒肺炎(COVID-19)聚集性疫情回顾性流行病学调查,分析疫情的感染来源、传播方式和传播链.方法 2020年1月-2月,对病例的基本情况、发病与诊疗、临床表现、发病前14天内暴露史和危险因素、密切接触者等信息现场流行病学调查,采集病例的呼吸道标本进行rRT-PCR新型冠状病毒核酸检测,分析病例间的流行病学关联及聚集性疫情的传播链.结果 该起聚集性疫情涉及4例确诊病例,其中3例曾在同一公共场所内活动.病例一2020年1月11日-16日至武汉出差,1月21日确诊;1月17日,病例一发病后至某客户服务中心,与病例二、病例三之间在未佩戴口罩和手套的情况下有多次接触;病例二1月28日发病,2月2日确诊;病例三1月21日发病,2月1日确诊;病例三的妻子病例四2月2日发病,2月4日确诊.与病例一的接触可能为病例二、病例三的感染来源,与病例三的共同生活可能为病例四的感染来源.结论 COVID-19可通过在公共场所的接触而传播导致聚集性疫情,需关注室内公共场所可能的传播风险、加强针对性的防控措施.

目的 研究简单随机抽样和空间分层抽样方法在诱蚊诱卵器监测的应用效果.方法 利用上海市2020年8月4日至9月1日138个诱蚊诱卵器的4次监测数据.使用ArcGIS 10.8软件计算全局空间自相关Moran's I指数和局部Moran's I指数评估样本空间相关性和异质性.采用蒙特卡罗(Monte Carlo)模拟1000次的方法进行简单随机抽样和空间分层抽样,对抽样的结果计算绝对误差与抽样效率,评价不同抽样方法的精度和分层效率.空间抽样方法包括九宫格空间分层抽样、基于树冠面积的空间分层抽样和基于诱蚊诱卵器监测结果的空间分层抽样.结果 研究期间,4次监测的平均诱蚊诱卵指数为49.46.不同半径距离的全局空间自相关分析显示,空间自相关峰值半径为45 m,Moran's I指数为0.289,Z值为7.874(P＜0.001).局部空间自相关分析显示,在研究区域西北角呈现白纹伊纹高密度与高密度聚集区,西南角为低密度与低密度聚集区,东侧大部分为无聚集区.4种抽样方法绝对误差均随着抽样量的增加而逐步减小,其中基于诱蚊诱卵器监测结果的空间分层抽样绝对误差最小,抽样效率最高;其次为基于树冠面积的空间分层抽样和九宫格空间分层抽样.结论 空间分层抽样可以提高诱蚊诱卵器监测效率,不同的分层方法具有不同的效率值,基于先验知识的样点选择的空间分层抽样需做进一步研究.

Background Aedes albopictus is a vector of major arboviral diseases and a primary pest in tropical and temperate regions of China. In most cities of China, the current monitoring system for the spread of Ae. albopictus is based on the subdistrict scale and does not consider spatial distribution for analysis of species density. Thus, the system is not sufficiently accurate for epidemic investigations, especially in large cities. Methods This study used an improved surveillance program, with the mosquito oviposition trap (MOT) method, integrating the actual monitoring locations to investigate the temporal and spatial distribution of Ae. albopictus abundance in an urban area of Shanghai, China from 2018 to 2019. A total of 133 monitoring units were selected for surveillance of Ae. albopictus density in the study area, which was composed of 14 subdistricts. The vector abundance and spatial structure of Ae. albopictus were predicted using a binomial areal kriging model based on eight MOTs in each unit. Results were compared to the light trap (LT) method of the traditional monitoring scheme. Results A total of 8,192 MOTs were placed in the study area in 2018, and 7917 (96.6%) were retrieved, with a positive rate of 6.45%. In 2019, 22,715 (97.0%) of 23,408 MOTs were recovered, with a positive rate of 5.44%. Using the LT method, 273 (93.5%) and 312 (94.5%) adult female Ae. albopictus were gathered in 2018 and 2019, respectively. The Ae. albopictus populations increased slowly from May, reached a peak in July, and declined gradually from September. The MOT positivity index (MPI) showed significant positive spatial autocorrelation across the study area, whereas LT collections indicated a nonsignificant spatial autocorrelation. The MPI was suitable for spatial interpolation using the binomial areal kriging model and showed different hot spots in different years. Conclusions The improved surveillance system integrated with a geographical information system (GIS) can improve our understanding of the spatial and temporal distribution of Ae. albopictus in urban areas and provide a practical method for decision-makers to implement vector control and mosquito management. Graphical abstract

We report three clusters related with potential pre-symptomatic transmission of coronavirus disease (COVID-19) between January and February 2020 in Shanghai, China. Investigators interviewed suspected COVID-19 cases to collect epidemiological information, including demographic characteristics, illness onset, hospital visits, close contacts, activities' trajectories between 14 days before illness onset and isolation, and exposure histories. Respiratory specimens of suspected cases were collected and tested for SARS-CoV-2 by real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) assay. The interval between the onset of illness in the primary case and the last contact of the secondary case with the primary case in our report was 1 to 7 days. In Cluster 1 (five cases), illness onset in the five secondary cases was 2 to 5 days after the last contact with the primary case. In Cluster 2 (five cases) and Cluster 3 (four cases), the illness onset in secondary cases occurred prior to or on the same day as the onset in the primary cases. The study provides empirical evidence for transmission of COVID-19 during the incubation period and indicates that pre-symptomatic person-to-person transmission can occur following sufficient exposure to confirmed COVID-19 cases. The potential pre-symptomatic person-to-person transmission puts forward higher requirements for prevention and control measures.

We used contact tracing to document how COVID‐19 was transmitted across 5 generations involving 10 cases, starting with an individual who became ill on January 27. We calculated the incubation period of the cases as the interval between infection and development of symptoms. The median incubation period was 6.0 days (interquartile range, 3.5‐9.5 days). The last two generations were infected in public places, 3 and 4 days prior to the onset of illness in their infectors. Both had certain underlying conditions and comorbidity. Further identification of how individuals transmit prior to being symptomatic will have important consequences.

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease first identified in Wuhan City, Hubei Province, China. As of 19 February 2020, there had been 333 confirmed cases reported in Shanghai, China. This study elaborates on the epidemiological and clinical characteristics of COVID-19 based on a descriptive study of the 333 patients infected with COVID-19 in Shanghai for the purpose of probing into this new disease and providing reference. Among the 333 confirmed cases in Shanghai, 172 (51.7%) were males and 161 (48.3%) were females, with a median age of 50 years. 299 (89.8%) cases presented mild symptoms. 139 (41.7%) and 111 (33.3%) cases were infected in Wuhan and Shanghai, respectively. 148 (44.4%) cases once had contact with confirmed cases before onset, while 103 (30.9%) cases had never contacted confirmed cases but they had a sojourn history in Wuhan. The onset date of the first case in Shanghai was 28 December, with the peak appearing on 27 January. The median incubation period of COVID-19 was estimated to be 7.2 days. 207 (62.2%) cases had fever symptoms at the onset, whereas 273 (82.0%) cases experienced fever before hospitalization. 56 (18.6%) adults experienced a decrease in white blood cell and 84 (42.9%) had increased C-reactive protein after onset. Elderly, male and heart disease history were risk factors for severe or critical pneumonia. These findings suggest that most cases experienced fever symptoms and had mild pneumonia. Strengthening the health management of elderly men, especially those with underlying diseases, may help reduce the incidence of severe and critical pneumonia. Time intervals from onset to visit, hospitalization and diagnosis confirmed were all shortened after Shanghai's first-level public health emergency response. Shanghai's experience proves that COVID-19 can be controlled well in megacities.

Background In December 2019, the outbreak of coronavirus disease 2019 (COVID-19) began in Wuhan, China, and rapidly spread to other regions. We aimed to further describe the epidemiological and clinical characteristics of discharged COVID-19 cases and evaluate the public health interventions. Methods We collected epidemiological and clinical data of all discharged COVID-19 cases as of 17 February 2020 in Shanghai. The key epidemiological distributions were estimated and outcomes were also compared between patients whose illness were before 24 January and those whose illness were after 24 January. Results Of 161 discharged COVID-19 cases, the median age was 45 years, and 80 (49.7%) cases were male. All of the cases were categorized as clinical moderate type. The most common initial symptoms were fever (85.7%), cough (41.0%), fatigue (19.3%), muscle ache (17.4%), sputum production (14.9%), and there were six asymptomatic cases. 39 (24.2%) cases got infected in Shanghai, and three of them were second-generation cases of Shanghai native cases. The estimated median of the time from onset to first medical visit, admission, disease confirmation, and discharge for 161 cases was 1.0 day (95% CI, 0.6–1.2), 2.0 days (95% CI, 1.5–2.6), 5.2 days (95% CI, 4.6–5.7), 18.1 days (95% CI, 17.4–18.8), respectively. The estimated median of the time from admission to discharge was 14.0 days (95% CI, 13.3–14.6). The time from onset to first medical visit, admission and disease confirmation were all shortened after the Shanghai’s first-level public health emergency response. In Cox regression model, the significant independent covariates for the duration of hospitalization were age, the time from onset to admission and the first-level public health emergency response. Conclusions Local transmission had occurred in Shanghai in late January 2020. The estimated median of the time from onset to discharge of moderate COVID-19 was 18.1 days in Shanghai. Time intervals from onset to first medical visit, admission and disease confirmation were all shortened after the Shanghai’s first-level public health emergency response. Age, the first-level public health emergency response and the time from onset to admission were the impact factors for the duration of hospitalization.

International travel may facilitate the spread of the novel coronavirus disease (COVID-19). The study describes clusters of COVID-19 cases within Chinese tour groups travelling in Europe January 16-28. We compared characteristics of cases and non-cases to determine transmission dynamics. The index case travelled from Wuhan, China, to Europe on 16 January 2020, and to Shanghai, China, on 27 January 2020, within a tour group (group A). Tour groups with the same outbound flight (group B) or the same tourism venue (group D) and all Chinese passengers on the inbound flight (group C) were investigated. The outbreak involved 11 confirmed cases, 10 suspected cases and six tourists who remained healthy. Group A, involving seven confirmed cases and six suspected cases, consisted of familial transmission followed by propagative transmission. There was less pathogenicity with propagative transmission than with familial transmission. Disease was transmitted in shared outbound flights, shopping venues within Europe and inbound flight back to China. The novel coronavirus caused clustered cases of COVID-19 in tour groups. When tourism and travel opens up, governments will need to improve screening at airports and consider increased surveillance of tour groups-particularly those with older tour members.

目的 探讨2017年2月上海市发生的1起境外输入性霍乱病例的应急处置经过,分析其成功经验和不足之处,为制定境外输入性霍乱的防控策略提供依据.方法 按照《霍乱防治手册(第6版)》的相关要求开展流行病学调查和现场处置.结果 感染来源为菲律宾,传播途径可能是由于游泳时误喝入大量不洁泳池水后致病;该起疫情得到科学及时的调查和处置,未发生二代病例.结论 境外输入性霍乱问题不容忽视,需要加强境外输入性霍乱的防控,尤其注意国际和国内联防联控机制的建设.

To investigate the distribution of ticks and to detect the new bunyavirus in ticks and infection rate in animals in Shanghai,outdoor free ticks were captured by flag method and ticks on animals were collected by animal capture.SFTSV in ticks were detected by real-time RT-PCR.Total antibodies against SFTSV in host animal sera were tested by double antigen sandwich method.Results showed that during 2012-2014,free ticks were captured in Chenshan Park and Jinshan Island,which were all Haemaphysalis longicornis.Ten of seventeen districts found ticks on animals which were dominantly Rhipicephalus sanguineus.No nucleic acid of SFTSV was detected in 143 ticks.Main host animal for ticks was dog,sheep was in the second.Sera in 198 dogs from 6 urban districts,120 swine from Pudong and Fenxian districts and 36 sheep from Chongming District were all SFTSV antibody negative.Ticks were not found with SFTSV in Shanghai during 2012-2014.No SFTSV infection was found in host animals.Therefore,there is no evidence that Shanghai is the natural foci of SFTSV.Further surveillance and investigations should be carried out in the future.