Aim: The study evaluates the in-vitro antimicrobial activity of Hunteria umbellata against Escherichia coli, Staphylococcus aureus and Streptococcus sp. Place and Duration of Study: The study was carried out for three months in 2019 in Biochemistry Laboratory, Department of Chemical Sciences (Biochemistry unit), School of Pure and Applied Sciences, Lagos State Polytechnic, Ikorodu, Lagos- Nigeria. Methodology: The qualitative and GC-MS analysis of Hunteria umbellata methanolic seed extract were determined using standard procedure. The antimicrobial activity was evaluated by the disc diffusion method and agar well diffusion method. The experimental data was resampled 1000 times to allow for higher degrees of freedom in carrying out t-test to test for the difference of the effect of in-vitro antimicrobial activity of H. umbellata against E. coli, S. aureus and Streptococcus sp using mathematical software R language (3.6.1 version). Line plots, histogram and t-test are used to explain the effect of antimicrobial activity of H. umbellate on the selected bacteria. MIC and MBC were determined using standard methods. Results: The Phytochemical analysis of methanolic seed extract of Hunteria umbellata showed the presence of secondary metabolites like saponins, tannins, flavonoids, steroids, phenol among others. GC-MS assay of the H. umbellata seed extract revealed the presence of eight different compounds. Agar well diffusion method was characterized by inhibition zones of 18.36±0.87, 19.13±1.03 and 21.62±2.53 mm for E.coli, S. aureus and Streptococcus sp respectively at 300 mg/ml-1 and 21.70± 1.60, 23.83± 2.64 and 28.57± 1.52 for E.coli, S. aureus and Streptococcus sp respectively at 500 mg/ml. The results of the analysis show that there is a significant difference between the effects of in-vitro antimicrobial activity of H. umbellate on 3001 and 500 mg/ml on each bacteria tested at 5% level of significance. E.coli, S. aureus and Streptococcus sp were tested against 12 standard antimicrobial agents, of which six was sensitive and another six was resistance to E .coli, seven was sensitive, and five was resistance to S. aureus while four was resistance and eight sensitive to Streptococcus sp. The minimum inhibitory concentration (MIC) for E.coli, S. aureus, and  Streptococcus sp were 250, 125 and 31.25 mgml-1 while their minimum bactericidal concentration (MBC) were 500, 250 and 125 respectively. MIC and MBC tests showed that H. umbellata methanolic seed extract had noticeable bactericidal effects with MBC/MIC values ranging between 2 to 4. The extract has strong potency against these microorganisms with Streptococcus sp being the most susceptible. Conclusions: Hunteria umbellata has potential as natural therapeutic agents against E. coli, S. aureus and Streptococcus sp and they may prevent pathogenic diseases.

In this work, a three-parameter Weibull Inverse Rayleigh (WIR) distribution is proposed. The new WIR distribution is an extension of a one-parameter Inverse Rayleigh distribution that incorporated a transformation of the Weibull distribution and Log-logistic as quantile function. The statistical properties such as quantile function, order statistic, monotone likelihood ratio property, hazard, reverse hazard functions, moments, skewness, kurtosis, and linear representation of the new proposed distribution were studied theoretically. The maximum likelihood estimators cannot be derived in an explicit form. So we employed the iterative procedure called Newton Raphson method to obtain the maximum likelihood estimators. The Bayes estimators for the scale and shape parameters for the WIR distribution under squared error, Linex, and Entropy loss functions are provided. The Bayes estimators cannot be obtained explicitly. Hence we adopted a numerical approximation method known as Lindley's approximation in other to obtain the Bayes estimators. Simulation procedures were adopted to see the effectiveness of different estimators. The applications of the new WIR distribution were demonstrated on three real-life data sets. Further results showed that the new WIR distribution performed credibly well when compared with five of the related existing skewed distributions. It was observed that the Bayesian estimates derived performs better than the classical method.

Objectives This paper is aimed at modelling the effect of COVID-19 mortality per population (CMP), a proxy for COVID-19 on the Gross Domestics Product (GDP) per capita per COVID-19 cases (RGDPC), a proxy for the economic wellbeing of a nation. Methods Nine models divided into three groups (Gaussian polynomial, other non-linear, and Gamma generalized polynomial models) were fitted for RGDPC data on CMP, collected from 1st June to 31st December 2020. Results The result showed that the gamma cubic model was selected as the best model out of the 9 competing models to predict the economic wellbeing of Nigeria. Predictions were made for the whole day in the year 2021. Conclusion It is therefore concluded that there is a non-linear relationship between COVID-19 mortality and the economic wellbeing of Nigerians. Thus, COVID-19 mortality has an adverse effect on the wellbeing of Nigerians. The economic wellbeing of Nigerians can be improved if COVID-19 mortality is stopped.

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