We explored the secondary attack rate in different types of contact with persons presymptomatic for coronavirus disease (COVID-19). Close contacts who lived with or had frequent contact with an index case-patient had a higher risk for COVID-19. Our findings provide population-based evidence for transmission from persons with presymptomatic COVID-19 infections.

Background: Quantitative evidence on the impact of meteorological factors on influenza transmissibility across different virus types/subtypes is scarce, and no previous studies have reported the effect of hourly temperature variability (HTV) on influenza transmissibility. Herein, we explored the associations between meteorological factors and influenza transmissibility according to the influenza type and subtype in Guangzhou, a subtropical city in China. Methods: We collected influenza surveillance and meteorological data of Guangzhou between October 2010 and December 2019. Influenza transmissibility was measured using the instantaneous effective reproductive number (R_t). A gamma regression with a log link combined with a distributed lag non-linear model was used to assess the associations of daily meteorological factors with R_t by influenza types/subtypes. Results: The exposure-response relationship between ambient temperature and R_t was non-linear, with elevated transmissibility at low and high temperatures. Influenza transmissibility increased as HTV increased when HTV < around 4.5 °C. A non-linear association was observed between absolute humidity and R_t, with increased transmissibility at low absolute humidity and at around 19 g/m³. Relative humidity had a U-shaped association with influenza transmissibility. The associations between meteorological factors and influenza transmissibility varied according to the influenza type and subtype: elevated transmissibility was observed at high ambient temperatures for influenza A(H3N2), but not for influenza A(H1N1)pdm09; transmissibility of influenza A(H1N1)pdm09 increased as HTV increased when HTV < around 4.5 °C, but the transmissibility decreased with HTV when HTV < 2.5 °C and 3.0 °C for influenza A(H3N2) and B, respectively; positive association of R_t with absolute humidity was witnessed for influenza A(H3N2) even when absolute humidity was larger than 19 g/m³, which was different from that for influenza A(H1N1)pdm09 and influenza B. Conclusions: Temperature variability has an impact on influenza transmissibility. Ambient temperature, temperature variability, and humidity influence the transmissibility of different influenza types/subtypes discrepantly. Our findings have important implications for improving preparedness for influenza epidemics, especially under climate change conditions.

From 11 March to 6 July 2020, a total of 268 imported cases of COVID-19 from abroad were confirmed in Guangzhou. 74% of the imported cases were detected during customs inspection and 19% under centralized quarantine. We advocate for legally enforced quarantine and monitoring of quarantined persons.

Background: Studies related to the SARS-CoV-2 spikes in the past few months, while there are limited studies on the entire outbreak-suppressed cycle of COVID-19. We estimate the cause-specific excess mortality during the complete circle of COVID-19 outbreak in Guangzhou, China, stratified by sociodemographic status. Methods: Guangzhou Center for Disease Control Prevention provided the individual data of deaths in Guangzhou from 1 January 2018 through 30 June 2020. We applied Poisson regression models to daily cause-specific mortality between 1 January 2018 and 20 January 2020, accounting for effects of population size, calendar time, holiday, ambient temperature and PM_2.5. Expected mortality was estimated for the period from 21 January through 30 June 2020 assuming that the effects of factors aforementioned remained the same as described in the models. Excess mortality was defined as the difference between the observed mortality and the expected mortality. Subgroup analyses were performed by place of death, age group, sex, marital status and occupation class. Results: From 21 January (the date on which the first COVID-19 case occurred in Guangzhou) through 30 June 2020, there were three stages of COVID-19: first wave, second wave, and recovery stage, starting on 21 January, 11 March, and 17 May 2020, respectively. Mortality deficits were seen from late February through early April and in most of the time in the recovery stage. Excesses in hypertension deaths occurred immediately after the starting weeks of the two waves. Overall, we estimated a deficit of 1051 (95% eCI: 580, 1558) in all-cause deaths. Particularly, comparing with the expected mortality in the absence of COVID-19 outbreak, the observed deaths from pneumonia and influenza substantially decreased by 49.2%, while deaths due to hypertension and myocardial infarction increased by 14.5 and 8.6%, respectively. In-hospital all-cause deaths dropped by 10.2%. There were discrepancies by age, marital status and occupation class in the excess mortality during the COVID-19 outbreak. Conclusions: The excess deaths during the COVID-19 outbreak varied by cause of death and changed temporally. Overall, there was a deficit in deaths during the study period. Our findings can inform preparedness measures in different stages of the outbreak.

From June 7th to 11th, 2023, eight cases of Mpox were identified in Guangzhou, China. This is the first report of multiple local sporadic cases after the imported case in Chongqing, China. Epidemiological investigation revealed that these cases had no history of international travel and no connections with each other. Haplotype network and phylogenetic analyses indicated that the possible origin is likely from Japan, although the direct origin may remain uncertain due to limited genomic sequences and sampling bias in GISAID. The three Guangzhou sequences have accumulated several novel mutations, suggesting the local transmission of Mpox may have been ongoing for some time. Based on the daily cases during the early stage of Mpox outbreak in four other countries, the number of possible infected cases in Guangzhou is inferred to be more than 300, suggesting that swift and efficient control measures must be implemented to mitigate the risk of a potential epidemic.

Lnc-RAB11B-AS1 is reported to be dysregulated in several types of cancers and can function as both an oncogene and tumor suppressor gene. To evaluate the potential role of lnc-RAB11B-AS1 in hepatocellular carcinoma (HCC), we investigated and evaluated its expression in HCC based on the data mining of a series of public databases, including TCGA, GEO, ICGC, HPA, DAVID, cBioPortal, GeneMIANA, TIMER, and ENCORI. The data showed downregulation of lnc-RAB11B-AS1 in HCC and was accompanied by the synchronous downregulation of the targeted RAB11B mRNA and its protein. Low expression of lnc-RAB11B-AS1 was associated with shorter overall survival (OS) and disease-free survival (DFS) of HCC patients, PD1/PD-L1 was correlated with low expression of RAB11B. Furthermore, Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed a correlation between immune cell change and non-alcoholic fatty liver disease. The above findings revealed that lnc-RAB11B-AS1 was down-regulated in HCC and closely associated with the clinical stage of the HCC patients, suggesting that lnc-RAB11B-AS1 could be a possible predictor for HCC and a potential new therapeutic target for the treatment of HCC.