The World Health Organization (WHO) classified COVID-19 as a global pandemic, with the situation ultimately requiring unprecedented measures to mitigate the effects on public health and the global economy. Although SARS-CoV-2 (the virus responsible for COVID-19) is primarily respiratory in nature, multiple studies confirmed its genetic material could be detected in the feces of infected individuals, thereby highlighting sewage as a potential indicator of community incidence or prevalence. Numerous wastewater surveillance studies subsequently confirmed detection of SARS-CoV-2 RNA in wastewater and wastewater-associated solids/sludge. However, the methods employed in early studies vary widely so it is unclear whether differences in reported concentrations reflect true differences in epidemiological conditions, or are instead driven by methodological artifacts. The current study aimed to compare the performance of virus recovery and detection methods, detect and quantify SARS-CoV-2 genetic material in two Southewhen interpreting wastewater surveillance data.The recent pandemic caused by SARS-CoV-2 has led the world to a standstill, causing a medical and economic crisis worldwide. This crisis has triggered an urgent need to discover a possible treatment strategy against this novel virus using already-approved drugs. The main protease (Mpro) of this virus plays a critical role in cleaving the translated polypeptides that makes it a potential drug target against COVID-19. Taking advantage of the recently discovered three-dimensional structure of Mpro, we screened approved drugs from the Drug Bank to find a possible inhibitor against Mpro using computational methods and further validating them with biochemical studies. The docking and molecular dynamics study revealed that DB04983 (denufosol) showed the best glide docking score, -11.884 kcal/mol, and MM-PBSA binding free energy, -10.96 kcal/mol. Cobicistat, cangrelor (previous computational studies in our lab), and denufosol (current study) were tested for the in vitro inhibitory effects on Mpro. The IC50 values of these drugs were ∼6.7 μM, 0.9 mM, and 1.3 mM, respectively, while the values of dissociation constants calculated using surface plasmon resonance were ∼2.1 μM, 0.7 mM, and 1.4 mM, respectively. We found that cobicistat is the most efficient inhibitor of Mpro both in silico and in vitro. In conclusion, cobicistat, which is already an FDA-approved drug being used against HIV, may serve as a good inhibitor against the main protease of SARS-CoV-2 that, in turn, can help in combating COVID-19, and these results can also form the basis for the rational structure-based drug design against COVID-19.To estimate the size of the novel coronavirus (COVID-19) outbreak in the early stage in Italy, this paper introduces the cumulated and weighted average daily growth rate (WR) to evaluate an epidemic curve. On the basis of an exponential decay model (EDM), we provide estimations of the WR in four-time intervals from February 27 to April 07, 2020. By calibrating the parameters of the EDM to the reported data in Hubei Province of China, we also attempt to forecast the evolution of the outbreak. We compare the EDM applied to WR and the Gompertz model, which is based on exponential decay and is often used to estimate cumulative events. Specifically, we assess the performance of each model to short-term forecast of the epidemic, and to predict the final epidemic size. Based on the official counts for confirmed cases, the model applied to data from February 27 until the 17th of March estimate that the cumulative number of infected in Italy could reach 131,280 (with a credibility interval 71,415-263,501) by April 25 (credibility interval April 12 to May 3). With the data available until the 24st of March the peak date should be reached on May 3 (April 23 to May 23) with 197,179 cumulative infections expected (130,033-315,269); with data available until the 31st of March the peak should be reached on May 4 (April 25 to May 18) with 202,210 cumulative infections expected (155.235-270,737); with data available until the 07st of April the peak should be reached on May 3 (April 26 to May 11) with 191,586 (160,861-232,023) cumulative infections expected. Based on the average mean absolute percentage error (MAPE), cumulated infections forecasts provided by the EDM applied to WR performed better across all scenarios than the Gompertz model. An exponential decay model applied to the cumulated and weighted average daily growth rate appears to be useful in estimating the number of cases and peak of the COVID-19 outbreak in Italy and the model was more reliable in the exponential growth phase.Recently an outbreak that emerged in Wuhan, China in December 2019, spread to the whole world in a short time and killed >1,410,000 people.  https://www.selleckchem.com/products/tas-102.html  It was determined that a new type of beta coronavirus called severe acute respiratory disease coronavirus type 2 (SARS-CoV-2) was causative agent of this outbreak and the disease caused by the virus was named as coronavirus disease 19 (COVID19). Despite the information obtained from the viral genome structure, many aspects of the virus-host interactions during infection is still unknown. In this study we aimed to identify SARS-CoV-2 encoded microRNAs and their cellular targets. We applied a computational method to predict miRNAs encoded by SARS-CoV-2 along with their putative targets in humans. Targets of predicted miRNAs were clustered into groups based on their biological processes, molecular function, and cellular compartments using GO and PANTHER. By using KEGG pathway enrichment analysis top pathways were identified. Finally, we have constructed an integrative pathway network analysis with target genes. We identified 40 SARS-CoV-2 miRNAs and their regulated targets. Our analysis showed that targeted genes including NFKB1, NFKBIE, JAK1-2, STAT3-4, STAT5B, STAT6, SOCS1-6, IL2, IL8, IL10, IL17, TGFBR1-2, SMAD2-4, HDAC1-6 and JARID1A-C, JARID2 play important roles in NFKB, JAK/STAT and TGFB signaling pathways as well as cells' epigenetic regulation pathways. Our results may help to understand virus-host interaction and the role of viral miRNAs during SARS-CoV-2 infection. As there is no current drug and effective treatment available for COVID19, it may also help to develop new treatment strategies.