Though several AI-based models have been established for COVID-19 diagnosis, the machine-based diagnostic gap is still ongoing, making further efforts to combat this epidemic imperative. So, we tried to create a new feature selection (FS) method because of the persistent need for a reliable system to choose features and to develop a model to predict the COVID-19 virus from clinical texts. This study employs a newly developed methodology inspired by the flamingo's behavior to find a near-ideal feature subset for accurate diagnosis of COVID-19 patients. The best features are selected using a two-stage. In the first stage, we implemented a term weighting technique, which that is RTF-C-IEF, to quantify the significance of the features extracted. The second stage involves using a newly developed feature selection approach called the improved binary flamingo search algorithm (IBFSA), which chooses the most important and relevant features for COVID-19 patients. The proposed multi-strategy improvement process is at the heart of this study to improve the search algorithm. The primary objective is to broaden the algorithm's capabilities by increasing diversity and support exploring the algorithm search space. Additionally, a binary mechanism was used to improve the performance of traditional FSA to make it appropriate for binary FS issues. Two datasets, totaling 3053 and 1446 cases, were used to evaluate the suggested model based on the Support Vector Machine (SVM) and other classifiers. The results showed that IBFSA has the best performance compared to numerous previous swarm algorithms. It was noted, that the number of feature subsets that were chosen was also drastically reduced by 88% and obtained the best global optimal features.
The coronavirus disease 2019 (COVID-19) pandemic and related public health intervention measures have been reported to have resulted in the reduction of infections caused by influenza viruses and other common respiratory viruses. However, the influence may be varied in areas that have different ecological, economic, and social conditions. This study investigated the changing epidemiology of 8 common respiratory pathogens, including Influenza A (IFVA), Influenza B (IFVB), Respiratory syncytial virus (HRSV), rhinovirus (RV), Human metapneumovirus Adenovirus, Human bocavirus, and Mycoplasma pneumoniae, among hospitalized children during spring and early summer in 2019-2021 in two hospitals in Hainan Island, China, in the COVID-19 pandemic era. The results revealed a significant reduction in the prevalence of IFVA and IFVB in 2020 and 2021 than in 2019, whereas the prevalence of HRSV increased, and it became the dominant viral pathogen in 2021. RV was one of the leading pathogens in the 3 year period, where no significant difference was observed. Phylogenetic analysis revealed close relationships among the circulating respiratory viruses. Large scale studies are needed to study the changing epidemiology of seasonal respiratory viruses to inform responses to future respiratory virus pandemics.
Scrub typhus, caused by mite-borne Orientia tsutsugamushi (O. tsutsugamushi), is a major febrile disease in the Asia-Pacific region. The DNA load of O. tsutsugamushi in the blood was previously found to be significantly higher in patients with fatal disease than those with non-fatal disease and correlated with the duration of illness, presence of eschar, and hepatic enzyme levels. In this prospective observation study, we analyzed the association of bacterial DNA load with clinical features, disease severity, and genotype using real-time PCR targeting the 56 kDa TSA gene of O. tsutsugamushi in the blood samples of 117 surviving patients with scrub typhus who had not received appropriate antibiotic treatment. The median O. tsutsugamushi DNA load was 3.11×103 copies/mL (range, 44 to 3.3×106 copies/mL). The severity of patients was categorized as mild, moderate, and severe based on the number of dysfunctional organs, and no significant difference in O. tsutsugamushi DNA load was found among these groups. Patients infected with the Karp group showed a significantly higher O. tsutsugamushi DNA load than those in the Gilliam (P