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Abstract Background Metagenomic next-generation sequencing (mNGS) has been increasingly applied in sepsis. We aimed to evaluate the diagnostic and therapeutic utility of mNGS of paired plasma and peritoneal drainage (PD) fluid samples in comparison to culture-based microbiological tests (CMTs) among critically ill patients with suspected acute intra-abdominal infections (IAIs). Methods We conducted a prospective study from October 2021 to December 2022 enrolling septic patients with suspected IAIs (n = 111). Pairwise CMTs and mNGS of plasma and PD fluid were sent for pathogen detection. The mNGS group underwent therapeutic regimen adjustment based on mNGS results for better treatment. The microbial community structure, clinical features, antibiotic use and prognoses of the patients were analyzed. Results Higher positivity rates were observed with mNGS versus CMTs for both PD fluid (90.0% vs. 48.3%, p

Abstract Background Dengue fever is a well-studied vector-borne disease in tropical and subtropical areas of the world. Several methods for predicting the occurrence of dengue fever in Taiwan have been proposed. However, to the best of our knowledge, no study has investigated the relationship between air quality indices (AQIs) and dengue fever in Taiwan. Results This study aimed to develop a dengue fever prediction model in which meteorological factors, a vector index, and AQIs were incorporated into different machine learning algorithms. A total of 805 meteorological records from 2013 to 2015 were collected from government open-source data after preprocessing. In addition to well-known dengue-related factors, we investigated the effects of novel variables, including particulate matter with an aerodynamic diameter 30 °C. The AQIs were not as important as temperature, but one was selected in the process of filtering the variables and showed a certain influence on the final results. Conclusions Our study is the first to demonstrate that AQI negatively affects dengue fever occurrence in Taiwan. The proposed prediction model can be used as an early warning system for public health to prevent dengue fever outbreaks.

Abstract Background Dengue virus (DENV) is the leading cause of arboviral diseases in humans worldwide. Currently Dengvaxia, the first dengue vaccine licensed in 20 countries, was recommended for DENV seropositive individuals aged 9–45 years. Studying dengue seroprevalence can improve our understanding of the epidemiology and transmission dynamics of DENV, and facilitate future intervention strategies and assessment of vaccine efficacy. Several DENV envelope protein-based serological tests including IgG and IgG-capture enzyme-linked immunosorbent assays (ELISAs) have been employed in seroprevalence studies. Previously DENV IgG-capture ELISA was reported to distinguish primary and secondary DENV infections during early convalescence, however, its performance over time and in seroprevalence study remains understudied. Methods In this study, we used well-documented neutralization test- or reverse-transcription-polymerase-chain reaction-confirmed serum/plasma samples including DENV-naïve, primary and secondary DENV, primary West Nile virus, primary Zika virus, and Zika with previous DENV infection panels to compare the performance of three ELISAs. Results The sensitivity of the InBios IgG ELISA was higher than that of InBios IgG-capture and SD IgG-capture ELISAs. The sensitivity of IgG-capture ELISAs was higher for secondary than primary DENV infection panel. Within the secondary DENV infection panel, the sensitivity of InBios IgG-capture ELISA decreased from 77.8% at 20 years (p

Abstract Background COVID-19 infection can cause life-threatening respiratory disease. This study aimed to fully characterize the clinical features associated with postponed viral shedding time and disease progression, then develop and validate two prognostic discriminant models. Methods This study included 125 hospitalized patients with COVID-19, for whom 44 parameters were recorded, including age, gender, underlying comorbidities, epidemiological features, laboratory indexes, imaging characteristics and therapeutic regimen, et al. Fisher's exact test and Mann–Whitney test were used for feature selection. All models were developed with fourfold cross-validation, and the final performances of each model were compared by the Area Under Receiving Operating Curve (AUROC). After optimizing the parameters via L2 regularization, prognostic discriminant models were built to predict postponed viral shedding time and disease progression of COVID-19 infection. The test set was then used to detect the predictive values via assessing models’ sensitivity and specificity. Results Sixty-nine patients had a postponed viral shedding time (> 14 days), and 28 of 125 patients progressed into severe cases. Six and eleven demographic, clinical features and therapeutic regimen were significantly associated with postponed viral shedding time and disease progressing, respectively (p

Abstract Background The major infectious diseases of hepatitis B has constituted an acute public health challenge in China. An effective and affordable HBV control model is urgently needed. A national project of Community-based Collaborative Innovation HBV (CCI-HBV) demonstration areas has optimized the existing community healthcare resources and obtained initial results in HBV control. Methods Based on the existing community healthcare network, CCI-HBV project combined the community health management and health contract signing service for long-staying residents in hepatitis B screening. Moreover, HBV field research strategy was popularized in CCI-HBV areas. After screening, patients with seropositive results were enrolled in corresponding cohorts and received treatment at an early stage. And the uninfected people received medical supports including health education through new media, behavior intervention and HBV vaccinations. In this process, a cloud-based National Information Platform (NIP) was established to collect and store residents’ epidemiological data. In addition, a special quality control team was set up for CCI project. Results After two rounds of screening, HBsAg positive rate dropped from 5.05% (with 5,173,003 people screened) to 4.57% (with 3,819,675 people screened), while the rate of new HBV infections was 0.28 per 100 person-years in the fixed cohorts of 2,584,322 people. The quality control team completed PPS sampling simultaneously and established the serum sample database with 2,800,000 serum samples for unified testing. Conclusions CCI-HBV project has established a large-scale field research to conduct whole-population screening and intervention. We analyzed the HBsAg prevalence and new infection rate of HBV in the fixed population for the epidemic trend and intervention effect. The purpose of CCI-HBV project is to establish and evaluate a practical model of grid management and field strategy, to realize the new goal to control hepatitis B in China. To provide policymakers with a feasible model, our results are directly applicable. Trial registration The project was funded by the Major Projects of Science Research for the 11th and 12th five-year plans of China, entitled “The prevention and control of AIDS, viral hepatitis and other major infectious diseases”, Grant Nos. 2009ZX10004901, 2011ZX10004901, 2013ZX10004904, 2014ZX10004007 and 2014ZX10004008.