Intervention Analysis of COVID-19 Vaccination in Nigeria: The Naive Solution Versus Interrupted Time Series

Bartholomew, Desmond Chekwube; Nwaigwe, Chrysogonus Chinagorom; Orumie, Ukamaka Cynthia; Nwafor, Godwin Onyeka

doi:10.1007/s40745-023-00462-8

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…The SARIMAX model results suggested that both season [45], precipitation [18; 20; and 25], and government policies [46; 47] have significant effects on malaria cases in Rivers State, Nigeria, with dry seasons and transition from government policies of 2007 -2015 to governmebt polices of 2016 -2021 correlating with fewer malaria cases, while higher levels of precipitation correspond to increased malaria cases. The results did not identify relative humidity and temperature as significant variables for malaria, which disagrees with other works conducted in Nigeria [18]; [20]; [21]; and [22].…”

Section: Model Diagnosticsmentioning

confidence: 99%

Exploring the Interplay of Meteorological Variables, Government Policies, and Malaria Epidemiology: Towards an Optimal Predictive Model for Malaria Spread in Rivers State, Nigeria

Egbom,

Nduka,

Nzeako

et al. 2024

Preprint

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Background: Malaria continues to be a serious public health issue, especially in tropical and subtropical areas where the dynamics of its transmission are greatly influenced by environmental conditions. The objective of this research is to examine the impact of meteorological factors, and governmental policies on malaria epidemiology to determine the most effective model for forecasting and comprehending the transmission of malaria in Rivers State, Nigeria. Method: Three statistical models for count data were compared to identify the most influential meteorological variables and government policy and establish their associations with malaria transmission. The best count data model was compared with a seasonal autoregressive integrated moving average model using some known model evaluation metrics. Results: The results obtained showed that the best count data model out of the two models considered in this study is the Quasi-Poisson Model because it resulted in a smaller Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) value. The SARIMAX Model outperformed the Quasi-Poisson model and showed that season, precipitation and government policies were significant at a 5% level of significance in explaining the variations in the monthly number of malaria cases in Rivers State, Nigeria (Jan. 2007 – Dec. 2021). Further, the SARIMAX (1,1,0)(1,1,1)12 model showed that the current number of malaria cases depends on the past year’s number of cases. Conclusion: The findings of this study highlight the need for a multifaceted approach to malaria control in Rivers State, addressing not only the meteorological factors but also the governance-related determinant of the disease. The identified optimal model serves as a valuable resource for policymakers, researchers, and healthcare practitioners, enabling them to make informed decisions and implement targeted interventions to mitigate the impact of malaria outbreaks.

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Section: Model Diagnosticsmentioning

confidence: 99%

Exploring the Interplay of Meteorological Variables, Government Policies, and Malaria Epidemiology: Towards an Optimal Predictive Model for Malaria Spread in Rivers State, Nigeria

Egbom,

Nduka,

Nzeako

et al. 2024

Preprint

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“…The COVID-19 vaccination program in Nigeria has been implemented in both urban and rural areas, with primary healthcare centers across all 774 local government areas providing free vaccines ( 6 ). The first batch of COVID-19 vaccines (Oxford-AstraZeneca) was received from the Japanese government in March 2021, with additional doses received from various sources throughout 2021 and 2022 ( 7 ).…”

Section: Introductionmentioning

confidence: 99%

Nigerian parents and caregivers knowledge, attitude and willingness to vaccinate their children against COVID-19

Ajose,

Akinde,

Ilo

et al. 2023

Front. Public Health

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ObjectivesIn order to achieve herd immunity against COVID-19, a significant proportion of the population will need to be vaccinated. Experts have recommended that African children be allowed to get vaccinated to protect them from emerging variants of COVID-19 infection. This study investigated Nigerian parents and caregivers’ knowledge, attitude, and willingness to vaccinate their children against COVID-19 once the vaccines are made available to them.MethodsA cross-sectional online survey of 500 parents/caregivers was conducted in Nigeria. Participants were asked to complete a questionnaire about their sociodemographic characteristics, knowledge of and attitude toward COVID-19 infection and vaccination, willingness to vaccinate their child and factors that could influence their decision to vaccinate their child. A scoring system was used to classify the level of knowledge and attitude of participants into 2 categories, namely poor, and good. We analyzed data obtained using SPSS Version 22.ResultsMajority of the participants were females (63.6%). Analysis of responses revealed good knowledge and attitude in 265 (53.0%) and 266 (53.2%) respondents, respectively. Overall, less than half of the parents/caregivers (48.4%) expressed intention to vaccinate their children against COVID-19. Factors associated with willingness to vaccinate children against COVID-19 included age greater than 40 years, male gender, residing in Southern Nigeria, having good knowledge, knowing an infected person or a vaccinated person, feeling they or their child is at risk of contracting COVID-19 infection, willingness to vaccinate self against COVID-19 and good attitude. Significant predictors of willingness to vaccinate their child include age greater than 40 years [AOR: 2.56; 95% CI = (1.14–5.76)], willingness to vaccinate self [AOR: 1016.81; 95% CI = (128.51–8045.60)] and good attitude [AOR: 6.21; 95% CI = (2.83–13.64)].ConclusionThis study revealed that parental willingness to vaccinate their children against COVID-19 is low and identified factors influencing it. It is important to develop and implement health education programs iterating the risk of children getting infected with SARS-CoV-2 and its emerging variants to ensure optimal uptake of the COVID-19 vaccine in Nigerian children.

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Willingness to receive COVID-19 vaccines, associated factors and reasons for not taking a vaccine: a cross sectional study among persons aged 13–80 years in Wakiso, Central Uganda

Daama,

Rashid,

Asani

et al. 2024

BMC Infect Dis

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Background Vaccination has been recommended as one of the approaches for the control of COVID-19 pandemic. However, adequate vaccine coverage is critical to the effectiveness of the vaccine at population level. Data on acceptability of the vaccine in Ugandan urban areas are limited. This study examined the prevalence, factors associated with willingness to accept COVID-19 vaccine including reasons for not taking COVID-19 vaccine in a predominantly urban population of Wakiso, central Uganda. Methods Data were obtained from a cross-sectional study conducted between March 1st, 2021 and September 30th, 2021 in the urban population-based cohort of the Africa Medical and behavioral Sciences Organization (AMBSO). A Multivariable modified Poisson regression analysis was used to estimate adjusted prevalence ratios (aPR) and 95% confidence intervals of willingness to accept the COVID-19 vaccine. Results A total of 1,903 participants were enrolled in this study; 61% of whom were females. About 63% of participants indicated their willingness to accept the COVID-19 vaccine. Persons aged 13–19 years (aPR = 0.79; [95% CI: 0.74, 0.84]) or 20-29years (aPR = 0.93; [95% CI: 0.88, 0.98]) were less likely to accept the vaccine compared to persons aged 40–49 years. Persons with post-primary level of education (aPR = 1.05; [95% CI: 1.02, 1.09]) were more likely to accept the vaccine compared to persons with primary level of education. Additionally, students or individuals working in government (aPR = 1.13; [95% CI: 1.04, 1.23]) were more likely to accept the vaccine compared to individuals doing construction and Mechanic work as their main occupation. Reported reasons for not taking a COVID-19 vaccine included; concerns about side effects of the vaccine 154(57.0%), 64(23.7%) did not think the vaccines were effective, while 32(11.9%) did not like the vaccines. Conclusion A substantial proportion of individuals were not willing to accept the COVID-19 vaccine. Health education campaigns on vaccination within urban communities could help reduce COVID-19 vaccine misconceptions in the urban populations more especially the young and persons with low levels of formal education.

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Intervention Analysis of COVID-19 Vaccination in Nigeria: The Naive Solution Versus Interrupted Time Series

Cited by 4 publications

References 24 publications

Exploring the Interplay of Meteorological Variables, Government Policies, and Malaria Epidemiology: Towards an Optimal Predictive Model for Malaria Spread in Rivers State, Nigeria

Exploring the Interplay of Meteorological Variables, Government Policies, and Malaria Epidemiology: Towards an Optimal Predictive Model for Malaria Spread in Rivers State, Nigeria

Nigerian parents and caregivers knowledge, attitude and willingness to vaccinate their children against COVID-19

Willingness to receive COVID-19 vaccines, associated factors and reasons for not taking a vaccine: a cross sectional study among persons aged 13–80 years in Wakiso, Central Uganda

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