HIV/AIDS
Samuel Olorunfemi Adams; Haruna Umar Yahaya; Tanimu Mohammed
Abstract
Background: The HIV/AIDS epidemic has made a nasty dent on sub-Saharan Africa’s development and has contributed to discrimination against those who live on the fringes of society or people at risk of contracting virus because of their behaviours, race, ethnicity, gender, sexual orientation or social ...
Read More
Background: The HIV/AIDS epidemic has made a nasty dent on sub-Saharan Africa’s development and has contributed to discrimination against those who live on the fringes of society or people at risk of contracting virus because of their behaviours, race, ethnicity, gender, sexual orientation or social characteristics. Methods: Cluster Analysis techniques were implemented on cluster HIV prevalence rate in Sub- Saharan Africa so as to find out countries that could be considered same category and to investigate the concentration of the disease in respect to Socio-economic status of the country. Analysis was implemented through the general methods of Hierarchical (Agglomerative nesting) and Partitioning methods (K-Means). Relative type of validation was used for cluster validation (a mechanism for evaluating the correctness of clustering). Results: The result shows a steady increase in the prevalence of HIV/AIDs from 1990 (6.74) to 1995(9.13) after which the incidence began to decline to (2.60) in 2018. The analysis created 3 clusters from the 44 observations supplied. After clustering, Only Lesotho and Eswatini belong to the third cluster. South Africa, Zambia, Zimbabwe, Namibia, Malawi, Mozambique and Botswana belong to the second clusters which are the countries with the highest HIV/AID prevalence over the years of this study. All other countries fall in the first cluster. Conclusion: The high prevalence rate of HIV/AIDS in the sub-saharan Africa countries has created an unprecedented effect. So, understanding these variables that have influenced the path of HIV/AIDS scourge constitutes an important stake, both on the humanitarian and economic aspects due to the
COVID-19
Samuel Olorunfemi Adams; Godwin Somto
Abstract
Background: COVID-19 has claimed the lives of millions of people in Nigeria and around the world during the last two years. It is a recognized global health crisis of our day, as well as a persistent threat to the earth. The goal of this study was to examine the trend and fit an Error Trend and Seasonal ...
Read More
Background: COVID-19 has claimed the lives of millions of people in Nigeria and around the world during the last two years. It is a recognized global health crisis of our day, as well as a persistent threat to the earth. The goal of this study was to examine the trend and fit an Error Trend and Seasonal (ETS) exponential smoothing and Autoregressive Integrated Moving Average (ARIMA) model to Nigeria's COVID-19 daily fatalities.Methods: A dataset of daily COVID-19 confirmed fatality cases was used in the investigation. Data was acquired from the Nigerian Centre for Disease Control (NCDC) web database between the 10th of July 2020 and the 2nd of December 2021. The ARIMA model and twelve (12) ETS exponential smoothing techniques were investigated using a dataset of COVID-19 pandemic deaths in Nigeria. The ARIMA and ETS exponential smoothing algorithms were evaluated using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Hannan Quinn Information Criterion (HQC), and Average Mean Squared Error (AMSE) selection criteria.Result: The ARIMA (0,1,0) model was the best time series modeling for the coronavirus (COVID-19) epidemic in Nigeria since it had the lowest AIC=2863.51, BIC=2866.90, HQ = 2866.90, and AMSE = 0.55471 values.Conclusion: The ARIMA (0,1,0) model is preferred above the other thirteen (13) competing models based on daily confirmed COVID-19 deaths in Nigeria. This research would assist the Nigerian government in better understanding the pestilence's evolution pattern and providing adequate provisions, prompt mediation, and treatment to prevent additional deaths caused by the virus.
