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Understanding the relative transmissibility of SARS-CoV-2 virus across different contact settings and the possibility of superspreading events is important for prioritizing disease control. Such assessment requires proper consideration of individual level exposure history, which is made possible by contact tracing.The case-ascertained study in Shandong, China including 97 laboratory-confirmed index cases and 3158 close contacts. All close contacts were quarantined after their last exposure of index cases. Contacts were tested for COVID-19 regularly by PCR to identify both symptomatic and asymptomatic infections. We developed a Bayesian transmission model to the contact tracing data to account for different duration of exposure among individuals to transmission risk in different settings, and the heterogeneity of infectivity of cases.We estimate secondary attack rates (SAR) to be 39% (95% credible interval (CrI): 20-64%) in households, 30% (95% CrI: 11-67%) in healthcare facilities, 23% (95% CrI: 7-51%) at workplaces, and 4% (95% CrI: 1-17%) during air travel. Models allowing heterogeneity of infectivity of cases provided a better goodness-of-fit. We estimated that 64% (95% CrI: 55-72%) of cases did not generate secondary transmissions, and 20% (95% CrI: 15-26%) cases explained 80% of secondary transmissions.Household, healthcare facilities and workplaces are efficient setting for transmission. Timely identification of potential superspreaders in most transmissible settings remains crucial for containing the pandemic.

Background: The roles of air pollutants including nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3) in influenza incidence at nationwide level of China remained obscure. Methods: Data from two complementary nation-wide influenza surveillance systems were applied to examine the association between air pollutants and influenza incidences. Spatial epidemiological analyses were performed on both air pollutants and influenza incidences in 31 provinces of mainland China. Cities with consistent data patterns between the two surveillance systems were chosen to examine the effects of pollutants on monthly influenza incidences using generalized estimating equations (GEE) and on daily incidence using the distributed lag non-linear model (DLNM). Results: Out of five common air pollutants (NO2, SO2, O3, CO, PM2.5), the concentration of NO2 was found spatially correlated with annual average influenza positive rates at province level (Pearson’s correlation coefficient=0.69, P

Acute influenza infection has been reported to be associated with neurological symptoms such as influenza-associated encephalopathy (IAE). Although the pathophysiology of this condition remain unclear, neuroinflammation and associated alterations in the central nervous system (CNS) are usually induced. Microglia (MGs), CNS-resident macrophages, are generally the first cells to be activated in response to brain infection or damage. We performed reverse transcriptase droplet digital PCR (RT-ddPCR) and luminex assays to investigate virus proliferation and immune reactions in BV2 MGs infected with influenza A(H1N1)pdm09 virus. Furthermore, isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics methods were used to investigate the dynamic change in the protein expression profile in BV2 MGs to gain insight into the CNS response to influenza A (H1N1) pdm09 infection. Our results showed that the influenza A(H1N1)pdm09 virus was replicative and productive in BV2 MG cells, which produced cytokines such as interleukin (IL)-1β, IL-6, tumour necrosis factor (TNF)-α and monocyte chemoattractant protein (MCP)-1. The expression of osteopontin (OPN) in the influenza A (H1N1) pdm09-infected BV2 MGs was upregulated at 16 and 32 h post-infection (hpi) compared to that in the control group, resulting in aggravated brain damage and inflammation. Our study indicates that OPN signalling might provide new insights into the treatment of CNS injury and neurodegenerative diseases in IAE.