HIV/AIDS
Samuel Olorunfemi Adams; Haruna Umar Yahaya; Tanimu Mohammed
Abstract
Background: The HIV/AIDS epidemic has had a negative impact on Sub-Saharan Africa's development and has contributed to discrimination against those on the margins of society or those who are at risk of contracting the virus due to their behaviors, race, ethnicity, gender, sexual orientation, or social ...
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Background: The HIV/AIDS epidemic has had a negative impact on Sub-Saharan Africa's development and has contributed to discrimination against those on the margins of society or those who are at risk of contracting the virus due to their behaviors, race, ethnicity, gender, sexual orientation, or social characteristics. Against this backdrop, the purpose of this study is to examine the countries that could be considered in the same category and to investigate the concentration of diseases in relation to the socioeconomic status of Sub-Saharan African countries.Methods: HIV prevalence rates in Sub-Saharan African countries were studied using Cluster Analysis techniques. It was implemented using hierarchical (Agglomerative nesting) and partitioning methods (K-Means) in general. For cluster validation (a mechanism for evaluating the correctness of clustering), the relative type of validation was used.Results: HIV/AIDS prevalence increased steadily from 1990 (6.74) to 1995 (9.13), after which it began to fall to (2.60) in 2018. The analysis produced three clusters based on the 44 observations provided. After clustering, only Lesotho and Eswatini are in the third cluster. Over the course of the study, South Africa, Zambia, Zimbabwe, Namibia, Malawi, Mozambique, and Botswana had the highest HIV/AIDS prevalence. The rest of the world is classified as part of the first cluster.Conclusion: The high prevalence of HIV/AIDS in Sub-Saharan African countries has had a far-reaching impact. Understanding the variables that have influenced the path of the HIV/AIDS scourge is therefore critical, both from a humanitarian and economic standpoint, because it is a significant step toward eradicating the virus.
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 ...
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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.