Development of Multi-epitope Based Subunit Vaccine Against Crimean-Congo Hemorrhagic Fever Virus Using Reverse Vaccinology Approach.

Crimean-Congo hemorrhagic fever (CCHF) is a viral disease caused by the Crimean-Congo hemorrhagic fever virus (CCHFV) of the Nairovirus genus. CCHF has occurred endemically in several regions of Africa, Southern Europe, and Central and Southeast Asia, with a case fatality rate of 5 to 80%. The World health organization enlisted CCHF as one of the top prioritized diseases for research and development in emergency contexts that making it a public health concern as no effective vaccine is available till date. Therefore, the present study aims to develop an effective multi-epitope subunit vaccine using immunoinformatics and reverse vaccinology approach against this virus. The B-cell and T-cell epitopes were predicted from structural and non-structural proteins, and filtered by immunogenicity, allergenicity, toxicity, conservancy, and cross-reactivity. The computational analysis revealed that the epitopes could induce an adequate immune response and had strong associations with their respective human leukocyte antigen (HLA) alleles with 98.94% of total world population coverage. Finally, the vaccine with 427 amino acids was constructed by connecting 8 cytotoxic T-lymphocytes, 4 helper T-lymphocytes, and 10 B-cell epitopes with appropriate linkers and ß-defensin as an adjuvant. The antigenicity, allergenicity, solubility, and physiochemical properties of the vaccine were evaluated, followed by structural modelling, refinement, and validation. In addition, molecular docking and molecular dynamic simulations revealed a robust binding affinity and stability of the vaccine-immune receptor complex. Moreover, the codons were optimized for its higher expression in Escherichia coli (E. coli) K12 strain followed by in silico cloning. The proposed subunit vaccine developed in this study could be a potential candidate against CCHFV. However, further experimental validation is required to ensure the immunogenicity and safety profile of the proposed vaccine for combating and eradicating CCHFV. Supplementary Information: The online version contains supplementary material available at 10.1007/s10989-022-10430-0.

Impact of Lockdown Measures and Meteorological Parameters on the COVID-19 Incidence and Mortality Rate in Bangladesh.

The coronavirus disease 2019 (COVID-19) pandemic has become a public health crisis and a global catastrophe for human societies. In the absence of a vaccine, non-pharmaceutical interventions have been implemented across the world to reduce COVID-19 transmission. Recently, several studies have articulated the influence of meteorological parameters on COVID-19 infections in several countries. The purpose of this study was to investigate the effect of lockdown measures and meteorological parameters on COVID-19 daily confirmed cases and deaths in Bangladesh. Different parameters, such as case fatality rate, recovery rate, number of polymerase chain reaction tests, and percentages of confirmed cases were calculated for data covering March to September 2020. The meteorological data include daily average temperature, humidity, and wind speed, and their effects on COVID-19 data were analyzed after 0, 3, 7, and 14 days. A linear regression analysis revealed that all the studied meteorological parameters were positively correlated with the daily new cases and deaths in Bangladesh, while the highest correlations were observed for the 14 days incubation period. These results provide useful implications for the healthcare authorities to contain the pandemic in Bangladesh and beyond.