Phylogenetic and full-length genome mutation analysis of SARS-CoV-2 in Indonesia prior to COVID-19 vaccination program in 2021.

BACKGROUND: Indonesia has started the big project of COVID-19 vaccination program since 13 January 2021 by employing the first shot of vaccine to the President of Indonesia as the outbreak and rapid transmission of COVID-19 have endangered not only Indonesian but the global health and economy. This study aimed to investigate the full-length genome mutation analysis of 166 Indonesian SARS-CoV-2 isolates as of 12 January 2021. RESULTS: All data of the isolates were extracted from the Global Initiative on Sharing All Influenza Data (GISAID) EpiCoV database. CoVsurver platform was employed to investigate the full-length genome mutation analysis of all isolates. This study also focused on the phylogeny analysis in unlocking the mutation of S protein in Indonesian SARS-CoV-2 isolates. WIV04 isolate that was originated from Wuhan, China was used as the virus reference according to the CoVsurver default. The result showed that a full-length genome mutation analysis of 166 Indonesian SARS-CoV-2 isolates was successfully generated. Every single mutation in S protein was described and then visualized by utilizing BioRender platform. Furthermore, it also found that D614G mutation appeared in 103 Indonesian SARS-CoV-2 isolates. CONCLUSIONS: To sum up, this study helped to observe the spread of COVID-19 transmission. However, it also proposed that the epidemiological surveillance and genomics studies might be improved on COVID-19 pandemic in Indonesia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s42269-021-00657-0.

The emergence of COVID-19 in Indonesia: analysis of predictors of infection and mortality using independent and clustered data approaches

BackgroundAnalyses of correlates of SARS-CoV-2 infection or mortality have usually assessed individual predictors. This study aimed to determine if patterns of combined predictors may better identify risk of infection and mortality MethodsFor the period of March 2nd to 10th 2020, the first 9 days of the COVID-19 pandemic in Indonesia, we selected all 18 confirmed cases, of which 6 died, and all 60 suspected cases, of which 1 died; and 28 putatively negative patients with pneumonia and no travel history. We recorded data for travel, contact history, symptoms, haematology, comorbidities, and chest x-ray. Hierarchical cluster analyses (HCA) and principal component analyses (PCA) identified cluster and covariance patterns for symptoms or haematology which were analysed with other predictors of infection or mortality using logistic regression. ResultsFor univariate analyses, no significant association with infection was seen for fever, cough, dyspnoea, headache, runny nose, sore throat, gastrointestinal complaints (GIC), or haematology. A PCA symptom component for fever, cough, and GIC tended to increase risk of infection (OR 3.41; 95% CI 1.06-14; p=0.06), and a haematology component with elevated monocytes decreased risk (OR 0.26; 0.07-0.79; 0.027). Multivariate analysis revealed that an HCA cluster of 3-5 symptoms, typically fever, cough, headache, runny nose, sore throat but little dyspnoea and no GIC tended to reduce risk (aOR 0.048; <0.001-0.52; 0.056). In univariate analyses for death, an HCA cluster of cough, fever and dyspnoea had increased risk (OR 5.75; 1.06 - 31.3, 0.043), but no other individual predictor, cluster or component was associated. Other significant predictors of infection were age [≥] 45, international travel, contact with COVID-19 patient, and pneumonia. Diabetes and history of contact were associated with higher mortality. ConclusionsCluster groups and co-variance patterns may be stronger correlates of SARS-CoV-2 infection than individual predictors. Comorbidities may warrant careful attention as would COVID-19 exposure levels.

In Silico Analysis of the Potential of the Active Compounds Fucoidan and Alginate Derived from Sargassum Sp. as Inhibitors of COX-1 and COX-2.

INTRODUCTION: The enzyme cyclooxygenase (COX) is an enzyme that catalyzes the formation of one of the mediators of inflammation, the prostaglandins. Inhibition of COX allegedly can improve inflammation-induced pathological conditions. AIM: The purpose of the present study was to evaluate the potential of Sargassum sp. components, Fucoidan and alginate, as COX inhibitors. MATERIAL AND METHODS: The study was conducted by means of a computational (in silico) method. It was performed in two main stages, the docking between COX-1 and COX-2 with Fucoidan, alginate and aspirin (for comparison) and the analysis of the amount of interactions formed and the residues directly involved in the process of interaction. RESULTS: Our results showed that both Fucoidan and alginate had an excellent potential as inhibitors of COX-1 and COX-2. Fucoidan had a better potential as an inhibitor of COX than alginate. COX inhibition was expected to provide a more favorable effect on inflammation-related pathological conditions. CONCLUSION: The active compounds Fucoidan and alginate derived from Sargassum sp. were suspected to possess a good potential as inhibitors of COX-1 and COX-2.