Severe fever with thrombocytopenia syndrome (SFTS) was first reported in China in 2011. Human-to-human transmission of the virus occurred occasionally in family clusters. However, pneumonia as an onset syndrome was not common in most SFTS cases. Our aim is to report a family cluster of SFTS with clinical manifestation of pneumonia in Shanghai. Epidemiologic investigations were conducted when a family cluster of severe fever with thrombocytopenia syndrome virus (SFTSV) infection was identified in Shanghai in June 2016. Samples were collected from two secondary cases and two close contacts with fever. SFTSV was detected by Real-Time reverse transcription polymerase chain reaction (RT-PCR). There were two confirmed STFS cases and one potential index case. The potential index case became ill on 21 May and died on 31 May. Case A had onset from 4 to 23 June and case B from 8 June to 25 June. All the three cases experienced pneumonia at the early stage of SFTSV infection. Three (3) out of thirty two (32) close contacts had symptoms of fever or cough but were detected STFSV negative by real-time RT-PCR. According to epidemiologic investigations, the potential index case had outdoor activities on a nearby hill. A tick bite could have been the reason for the SFTSV infection in the potential index case as ticks were found both in grassland or shrubs on the hill and also found on mice caught in her house. Both cases A and B had provided bedside care for the potential index case without any protection and had contacted with blood and other body fluids. It was a family cluster of SFTSV infection imported from Jiangsu province located in the east of China. We suggested to become alert to atypical SFTSV infected cases.

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

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: Aedes albopictus is a well-recognized vector of major arboviral diseases and a primary pest in tropical and temperate regions of China. In the current monitoring system for the spread of Ae. albopictus based on the sub-district scale in most cities of China, spatial distribution has not been considered for the analysis of the density of species. So, the system is not accurate enough for epidemic investigations, especially in big cities like Shanghai.Methods: In this study, an improved surveillance program integrating the actual monitoring locations was used to investigate the temporal and spatial distribution of Ae. albopictus abundance in an urban area of Shanghai, China, from 2018 to 2019 by using the mosquito-oviposition trap (MOT) method. The study area of 14 sub-districts was divided into 133 grids. The vector abundance and spatial structure of Ae. Albopictus were predicted by the indicator Kriging based on eight MOTs in each grid. Meanwhile, the light trap (LT) method was also used for the analysis and compared with the MOT method.Results: A total of 8,192 MOTs were placed in the study area in 2018, and 7,917 (96.6%) were retrieved with a positive rate of 6.45%, while in 2019, 22,715 (97.0%) of 23,408 MOTs were recovered with a positive rate of 5.44%. When 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 in the urban area of Shanghai increased slowly from May, reached a peak in July, and declined gradually from September. The MOT positivity index (MPI) showed a significant positive spatial autocorrelation across the study area, while LT collections indicated a non-significant spatial autocorrelation. The MPI was suitable for spatial interpolation by using the indicator Kriging and showed different hotspots in different years.Conclusions: The improved surveillance system integrating geographic information can help improve our understanding of the spatial and temporal distribution of Ae. albopictus in urban areas of Shanghai and could provide a practical method for decision-makers to implement vector control and management of mosquitoes.