On COVID-19 vaccination in Nigeria: an empirical study

This study assessed the knowledge and perception of Nigerians about COVID-19 vaccination. A cross-sectional survey was conducted comprising Health and Non-health workers in Nigeria. The knowledge, attitude, and perception of respondents on COVID-19 vaccination in Nigeria was obtained through an online. Logistic regression was employed to determine which factor imparted on COVID-19 vaccination decision. The study showed a significant relationship between COVID-19 vaccination and immigration requirements. The survey showed that 74.07% of the health workers had been vaccinated, while 47.06% of non-Health Workers had been vaccinated. This study recommends that Governments at all levels should create more awareness of the importance of COVID-19 vaccination to increase the number of vaccinated individuals.

Relationship Between the Standard of Living, Economic Situation, and Security Situation of Nigerians During The Covid-19 Pandemic. A Non-Parametric Analysis Approach

The Covid-19 pandemic has crippled the economic activities of so many nations across the globe since its outbreak in 2019. This study is focused on the resultant effect of the covid-19 pandemic in terms of standard of living, perception of economic and security situation of Nigerians. This study used a non-parametric approach involving Spearman rank correlation and Mann-Whitney U to analyze primary data acquired from NoiPolls' online administration of questionnaires during the Covid-19. The result obtained from this study depicts that there is a significant relationship between the security situation and perception of the country's economic situation. The standard of living of Nigerians was studied alongside their perception of the economic situation and we observed that there is a significant relationship between these two. This was also examined based on gender, the Mann-Whitney U test was used to check if there exists any form of difference between males and females based on the security situation, economic perception, and standard of living. The test result showed that there is no significant difference in the standard of living of both males and females but significant differences were observed in the economic perception and security situations. A bar chart was further used to visually assess these differences where it is seen that females feel more secure compared to males and females feel less satisfied with the country's economic situation compared to the males. © 2023 NSP Natural Sciences Publishing Cor.

Knowledge, Attitude, and Perception of Health and Non-Healthcare Workers Towards COVID-19 Vaccination: Machine Learning Approach

There have been concerns globally as to whether taking COVID-19 vaccination is harmful or not. In this study, we conducted an online survey to measure the knowledge and attitude of people, first about COVID-19, and second about COVID-19 vaccination—various analyses such as descriptive statistics, logistic regression, and support vector regression with k-fold cross-validation. The support vector machine and tuned support vector machine suggest a better fit based on cross-validation error. The results show that immigration requirements significantly explain why an individual would accept the COVID-19 vaccine. This study suggests that people in authority should look into people's concerns regarding taking the COVID-19 vaccine and address them accordingly. The study aims to draw the attention of the people to the concern that surrounds taking COVID-19 vaccination and explored various statistical techniques to draw inference. © 2022 WITPress. All rights reserved.

Modeling and Forecasting the Third wave of Covid-19 Incidence Rate in Nigeria Using Vector Autoregressive Model Approach

Modeling the onset of a pandemic is important for forming inferences and putting measures in place. In this study, we used the Vector autoregressive model to model and forecast the number of confirmed covid-19 cases and deaths in Nigeria, taking into account the relationship that exists between both multivariate variables. Before using the Vector Autoregressive model, a co-integration test was performed. An autocorrelation test and a heteroscedasticity test were also performed, and it was discovered that there is no autocorrelation at lags 3 and 4, as well as no heteroscedasticity. According to the findings of the study, the number of covid-19 cases and deaths is on the rise. To forecast the number of cases and deaths, a Vector Autoregressive model with lag 4 was used. The projection likewise shows a steady increase in the number of deaths over time, but a minor drop in the number of confirmed Covid-19 cases. c 2022 Journal of the Nigerian Society of Physical Sciences. All rights reserved.

Nigerian COVID-19 Incidence Modeling and Forecasting with Univariate Time Series Model

The occurrence of COVID-19 has given rise to dreadful medical difficulties due to its hyper-endemic effects on the human population. This made it fundamental to model and forecast COVID-19 pervasiveness and mortality to control the spread viably. The COVID-19 data used was from February, 28, 2020 to March 1, 2021. ARIMA(1,2,0) was selected for modeling COVID-19 confirmed and ARIMA(1,1,0) for death cases. The model was shown to be adequate for modeling and forecasting Nigerian COVID-19 data based on the ARIMA model building results. The forecasted values from the two models indicated Nigerian COVID-19 cumulative confirmed and death case continues to rise and maybe in-between 189,019–327,426 and interval 406–3043, respectively in the next 3 months (May 30, 2021). The ARIMA models forecast indicated an alarming rise in Nigerian COVID-19 confirmed and death cases on a daily basis. The findings indicated that effective treatment strategies must be put in place, the health sector should be monitored and properly funded. All the protocols and restrictions put in place by the NCDC, Nigeria should be clung to diminish the spread of the pandemic and possible mortality before immunizations that can forestall the infection is developed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Vector Autoregressive Modeling of COVID-19 Incidence Rate in Nigeria

With the outbreak of COVID-19, a lot of studies have been carried out in various science disciplines to either reduce the spread or control the increasing trend of the disease. Modeling the outbreak of a pandemic is pertinent for inference making and implementation of policies. In this study, we adopted the Vector autoregressive model which takes into account the dependence that exists between both multivariate variables in modeling and forecasting the number of confirmed COVID-19 cases and deaths in Nigeria. A co-integration test was carried out prior to the application of the Vector Autoregressive model. An autocorrelation test and a test for heteroscedasticity were further carried out where it was observed that there exists no autocorrelation at lag 3 and 4 and there exists no heteroscedasticity respectively. It was observed from the study that there is a growing trend in the number of COVID-19 cases and deaths. A Vector Autoregressive model of lag 4 was adopted to make a forecast of the number of cases and death. The forecast also reveals a rising trend in the number of infections and deaths. The government therefore needs to put further measures in place to curtail the spread of the virus and aim towards flattening the curve. © 2021 WITPress. All rights reserved.