The novel coronavirus is a new disease threatening the population size and economic activities across the world. Due to the poverty rate in Africa, as well as poor access to quality health care, inadequate medical staff and poor technology, Africa has been predicted to be one of the most severely affected continents in the world by COVID-19. The objective of this study was to examine the survival rate of COVID-19 patients in Nigeria using the Autoregressive Integrated Moving Average (ARIMA) forecasting approach. The source of the data used for this study was the secondary data obtained from the daily publication/report of the Nigeria Centre for Disease Control (NCDC) from 28 th February 2020 to 30 th June 2020. The mean daily survival rate of COVID-19 patients was found to be 27.5% with a median survival rate of 25.4% which is below 50%. Also, the ARIMA (0, 1, 1) was identified to be appropriate for predicting the survival rate of COVID-19 patients in Nigeria within the observed period. Further findings showed that little variation exists between the predicted and actual survival rate of COVID19 for June 2020 which indicates that the obtained ARIMA model (0, 1, 1) was adequate for the estimation of the survival rate of COVID-19 in Nigeria. Based on the findings of the study, the need for the Nigerian government to explore effective treatment strategies both internationally and locally to improve the survival rate of patients with the disease was strongly recommended. Also, the need for the government to encourage local manufacturing of Personal Protective Equipment (PPE) such as garment, which is expected to help health workers effectively manage affected persons without being infected at the front line was recommended.

Aims: Economic openness has been identified as a tool that provides countries with an avenue to explore advances on technology, creation of exchanges through the reallocation of resources especially from less efficient to efficient producer, and economic growth. This study examined the short-run and long-run impact of economic determinants such as foreign direct investment, unemployment rate and percentage of the urban population on economic openness in Nigeria.  Place and Duration of Study: The study employed a secondary source of data collection obtained from the Central Bank of Nigeria (CBN), Statistical Bulletin and National Bureau of Statistics (NBS) Annual Publication. The data comprises of variables such as economic openness which is proxy by trade openness, foreign direct investment, unemployment rate and percentage of the urban population from 2006 - 2019. Methodology: The impacts of the economic determinants considered in this study were examined using the Autoregressive Distributed Lag (ARDL) co-integration technique and the error correction parameterization of the ARDL model. The R-3.6.3 programming package was used to perform the analysis. Results: The outcome of the study revealed that the appropriate ARDL model for estimating economic openness was the ARDL (1,1,1,1) selected based on the Schwarz Bayesian Criterion. Also, the error correction model identified the sizable speed of adjustment by 30.0% of disequilibrium correction yearly for reaching the long-run equilibrium steady-state position. It was found that the lag of the Unemployment Rate (UNER) and the percentage of the urban population have a significant short-term effect on economic openness. Also, the distribution of economic openness was found to be stable over the observed period. Also, it was found that the relationship amongst the variables was independent except for the relationship between the percentage of the Urban Population (PUP) and Foreign Direct Investment (FDI) which was found to be is unidirectional. Conclusion: The outcome of this study suggested the urgent need for policymakers to implement policies such as the "ease of doing business"  of the federal government of Nigeria which is anticipated to make foreign direct investment more attractive and in turn is expected to boost economic growth and thereby impact positively on urbanization in Nigeria.

This study examined the performance of two proposed permutation methods for Chow test analysis and the Milek permutation method for testing structural break in linear models. The proposed permutation methods are: (1) permute object of dependent variable and (2) permute object of the predicted dependent variable. Simulation from gamma distribution and standard normal distribution were used to evaluate the performance of the methods. Also, secondary data were used to illustrate a real-life application of the methods. The findings of the study showed that method 1(permute object of dependent variable) and Method2 (permute object of the predicted dependent variable) performed better than the traditional Chow test analysis while the Chow test analysis was found to perform better than the Milek permutation for structural break. The methods were used to test whether the introduction of Nigeria Electricity Regulatory Commission (NERC) in the year 2005 has significant impact on economic growth in Nigeria. The result revealed that all the methods were able to detect presence of structural break at break point 2005. Also, the methods were used to test for structural break at January, 2015 for monthly reported cases of appendicitis in Nigeria. Result revealed that all the methods were able to detect presence of structural break at break point January, 2015.

Aims: This study examined the impact of the lockdown measure on the confirmed cases of the Novel Coronavirus (COVID-19) in Nigeria.  The objectives of the study include to identifying an appropriate autoregressive integrated moving average (ARIMA) model that is adequate for estimating the reported cases of COVID-19 in Nigeria and to ascertain whether the ease of lockdown has a significant impact on the reported cases of COVID-19 in Nigeria.  Place and Duration of Study: The source of the data used for this study was the secondary data obtained from the daily report of the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) from 1st February 2020 to 30th June 2020. Methodology: The statistical tools used for data analysis are the ARIMA time series model and the Chow test analysis. Results: Nigeria ranked 1st in West Africa sub-region with a total of 25, 133 confirmed COVID-19 cases, followed by Ghana with 17, 351 confirmed cases while Gambia recorded the least number of confirmed cases with 47 cases of COVID19. The ARIMA (0, 1, 1) was identified as the best model for forecasting the confirmed COVID-19 cases in Nigeria within the observed period. It was found that there exists a significant difference in the number of confirmed cases of COVID-19 during the lockdown period and the post lockdown period. Conclusion: The study revealed that Nigeria has the most confirmed cases of COVID-19 in West Africa region. Also, the ease of the lockdown was found to increase the number of confirmed virus cases in Nigeria.

Aim: This study examined the physicochemical and bacteriological parameters of Odor River in Orumba North, Anambra State. The parameters considered were pH, turbidity, temperature, Dissolved Oxygen (DO), Alkalinity, total hardness, Sulphate ( ), Chloride, Calcium ( ) hardness, Magnesium ( ) hardness, Iron (Fe), Nitrate  (NO3-), Conductivity, Total Dissolved Solids (TDS), Total coliform and Escherichia coli (E. coli).  The objectives of the study were to assess the similarities that exist amongst the physicochemical and bacteriological parameters of Odor River in Orumba North, Anambra State. Also, to test whether water from Odor river is safe for drinking by the people of Orumba North and its environs. Methodology: The Cluster analysis and the one-sample T-test method were used to analyze the data obtained for this study. Results: The findings of the study revealed that the parameters can be grouped in two groups as follows: group A consists of pH, turbidity, temperature, Dissolved Oxygen (DO), Alkalinity, total hardness, Sulphate ( ), Chloride, Calcium ( ) hardness, Magnesium ( ) hardness, Iron (Fe), Nitrate  (NO3-), and Conductivity while group B consists of Total Dissolved Solids (TDS), Total coliform and E.coli. The physicochemical parameters were found to impact significantly on the variation of the water quality at 5% significant level and their measures did not exceed the World Health Organization (WHO) standard. Further findings revealed that the bacteriological parameters such as the Escherichia Coli and Total Coliform do not significantly impact on the water quality variation of the river and their measures do not exceed the WHO standard.   Conclusion: The physicochemical and bacteriological parameters of Odor River were found to be within the WHO Standard. However, the physicochemical parameters were found to impact on the water quality variation of the river while the bacteriological parameters do not impact on the variation of the water quality of the river. The implication of the physicochemical and bacteriological parameters not exceeding the WHO standard indicates no risk for the users of the river. Hence, water from Odor River is safe for human consumption and agricultural purposes.