Background: The unpredictability of the progression of coronavirus disease 2019 (COVID-19) may be attributed to the low precision of the tools used to predict the prognosis of this disease. Objective: To identify the predictors associated with poor clinical outcomes in patients with COVID-19. Methods: Relevant articles from PubMed, Embase, Cochrane, and Web of Science were searched and extracted as of April 5, 2020. Data of interest were collected and evaluated for their compatibility for the meta-analysis. Cumulative calculations to determine the correlation and effect estimates were performed using the Z test. Results: In total, 19 papers recording 1,934 mild and 1,644 severe cases of COVID-19 were included. Based on the initial evaluation, 62 potential risk factors were identified for the meta-analysis. Several comorbidities, including chronic respiratory disease, cardiovascular disease, diabetes mellitus, and hypertension were observed more frequent among patients with severe COVID-19 than with the mild ones. Compared to the mild form, severe COVID-19 was associated with symptoms such as dyspnea, anorexia, fatigue, increased respiratory rate, and high systolic blood pressure. Lower levels of lymphocytes and hemoglobin; elevated levels of leukocytes, aspartate aminotransferase, alanine aminotransferase, blood creatinine, blood urea nitrogen, high-sensitivity troponin, creatine kinase, high-sensitivity C-reactive protein, interleukin 6, D-dimer, ferritin, lactate dehydrogenase, and procalcitonin; and a high erythrocyte sedimentation rate were also associated with severe COVID-19. Conclusion: More than 30 risk factors are associated with a higher risk of severe COVID-19. These may serve as useful baseline parameters in the development of prediction tools for COVID-19 prognosis.

Highlights We reported dengue and COVID-19 co-infection for the first time in Indonesia. We revealed possible cross-reactivity between SARS-CoV-2 and DENV antibodies based on rapid serological tests. Cross-reactivity of SARS-CoV-2 and DENV will be a significant hurdle to have a simple point-of-care test for COVID-19 in dengue-endemic countries.

Background: The unpredictability of the progression of coronavirus disease 2019 (COVID-19) may be attributed to the low precision of the tools used to predict the prognosis of this disease. Objective: To identify the predictors associated with poor clinical outcomes in patients with COVID-19. Methods: Relevant articles from PubMed, Embase, Cochrane, and Web of Science were searched as of April 5, 2020. The quality of the included papers was appraised using the Newcastle-Ottawa scale (NOS). Data of interest were collected and evaluated for their compatibility for the meta-analysis. Cumulative calculations to determine the correlation and effect estimates were performed using the Z test. Results: In total, 19 papers recording 1,934 mild and 1,644 severe cases of COVID-19 were included. Based on the initial evaluation, 62 potential risk factors were identified for the meta-analysis. Several comorbidities, including chronic respiratory disease, cardiovascular disease, diabetes mellitus, and hypertension were observed more frequent among patients with severe COVID-19 than with the mild ones. Compared to the mild form, severe COVID-19 was associated with symptoms such as dyspnea, anorexia, fatigue, increased respiratory rate, and high systolic blood pressure. Lower levels of lymphocytes and hemoglobin; elevated levels of leukocytes, aspartate aminotransferase, alanine aminotransferase, blood creatinine, blood urea nitrogen, high-sensitivity troponin, creatine kinase, high-sensitivity C-reactive protein, interleukin 6, D-dimer, ferritin, lactate dehydrogenase, and procalcitonin; and a high erythrocyte sedimentation rate were also associated with severe COVID-19. Conclusion: More than 30 risk factors are associated with a higher risk of severe COVID-19. These may serve as useful baseline parameters in the development of prediction tools for COVID-19 prognosis.

Broad‐spectrum antiviral agents targeting viral RNA‐dependent RNA polymerase (RdRp) are expected to be a key therapeutic strategy in the ongoing coronavirus disease 2019 (COVID‐19) pandemic and its future variants of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), the virus that causes COVID‐19. Molnupiravir is a nucleoside analog that in vivo experiments have been reported to inhibit the replication of SARS‐CoV‐2, the virus that causes COVID‐19. Clinical trials of molnupiravir as a therapy for patients with mild‐to‐moderate COVID‐19 also suggest its significant therapeutic efficacy in comparison to placebo. Molnupiravir is lethally mutagenic against viral RNA, but its effect on host cell DNA is being questioned. Herein, the safety concerns of molnupiravir are discussed with recent findings from published reports and clinical trials. The unchanged efficacy of molnupiravir against mutated SARS‐CoV‐2 variants is also highlighted. With its administration via the oral route, molnupiravir is expected to turn the tide of the COVID‐19 pandemic.

A high number of dengue cases are reported annually in Bali. Despite the endemicity, limited data on dengue is available for Bali localities. Molecular surveillance study was conducted to explore the clinical and virological characteristics of dengue patients in urban Denpasar and rural Gianyar areas in Bali during the peak season in 2015. A total of 205 adult dengue-suspected patients were recruited in a prospective cross-sectional study. Demographic and clinical information were obtained, and dengue screening was performed using NS1 and IgM/IgG ELISAs. Viral RNA was subsequently extracted from patients’ sera for serotyping using conventional RT-PCR and Simplexa Dengue real-time RT-PCR, followed by genotyping with sequencing method. We confirmed 161 patients as having dengue by NS1 and RT-PCR. Among 154 samples successfully serotyped, the DENV-3 was predominant, followed by DENV-1, DENV-2, and DENV-4. Serotype predominance was different between Denpasar and Gianyar. Genotyping results classify DENV-1 isolates into Genotype I and DENV-2 as Cosmopolitan Genotype. The classification grouped isolates into Genotype I and II for DENV-3 and DENV-4, respectively. Clinical parameters showed no relationship between infecting serotypes and severity. We observed the genetic diversity of circulating DENV isolates and their relatedness with historical data and importation to other countries. Our data highlights the role of this tourist destination as a potential source of dengue transmission in the region.