Investigating Factors Associated with Immunization Incompletion of Children Under Five in Ebonyi State,Southeast Nigeria: Implication for Policy Dialogue

Abstract

Purpose. To investigate factors associated with immunization incompletion of children under 5 years in Ebonyi state, Southeastern part of Nigeria. Method. A cross-sectional and a cluster sampling design were implemented; 400 women of childbearing age in families with children between 0 to 59 months of age were interviewed in Ebonyi state. Demographic characteristics of the child and mother, the child’s immunization history, and reasons for partial immunization were obtained with the use of a self-administered questionnaire. Data were analyzed using descriptive statistics of mean, standard deviation, t-test and ANOVA with SPSS version 23 and hypothesis tested at P < .05. Results. Findings revealed that 180 (48.1%) females, and 194 (51.9%) males’ children were immunized; Less than half 155 (41.9%) of the children had 1 missed dose, considered as partial immunization cases indicating low coverage. Of the reasons given for incomplete immunization mothers, mothers agreed that immunization centers are far from home (x̄ = 2.55 ± 0.92). This reason significantly affects mothers who were young (≤20 years) (x = 2.86 ± 0.94; P = .018), single (x = 2.84 ± 1.05; 0.037), had secondary education (x = 2.65 ± 1.08;0.000), students (2.89 ± 1.08; P = .000), poor (x = 2.63 ± 1.05; P = .009), and primiparous (x = 2.50 ± 1.08; P = .036) are more affected and they agreed (grand mean >2.50). Conclusion. Immunization coverage was low, and far location from health facility was indicted thus policy implementers should locate health facilities close to homes. also health education on the importance of immunization should be given to mothers especially those who are young and has low socio-economic status.

Keywords

immunization status children under 5 complete immunization partial immunization maternal Ebonyi state

What do we already know about this topic?

There is low immunization in Nigeria.

How does your research contribute to the field?

This article investigated the routine immunization of children under 5 years in Ebonyi state, Southeast Nigeria using a cross-sectional study, and findings agreed with the report of the National Demographic Health Survey. Reasons given for incomplete immunization were long waiting time, far distance, attitudes of health workers, inconvenient schedules of immunization, and beliefs.

What are your research’s implications toward theory, practice, or policy?

Efforts to increase accessibility, reduction in waiting time, sensitization on the need for antenatal and hospital delivery, girl-child education, and family planning should be enhanced by policy makers and relevant agencies.

Introduction

More than 2.7 million children die annually, even when existing immunization would have prevented 2 to 3 million deaths.¹ The under-5 mortality is caused by malaria, pneumonia, diarrhea, and other vaccine-preventable diseases like pertussis, measles, and meningitis,^2,3 and one of the utmost public health challenges today is suboptimal vaccine uptake rates. Moreover, the reduction of under-5 mortality rate in Nigeria is important because among the lower-middle-income country (LMC) in West Africa she has the highest under-5 child mortality rate (U5MR) with 714 000 deaths occurring every year, and that accounts for 13% U5MR globally.² Immunization is the first line of action against vaccine-preventable diseases and one of the most effective health benefits available to children for reducing under-5 mortalities.^4,5 In Nigeria, vaccine-preventable diseases (VPD) are known to account for 22% of childhood death amounting to over 200 000 children per annum.^6-8 About 87% of post-neonatal mortality can be tackled by addressing malaria, pneumonia, and diarrhea and improving immunization. The incidence of disabilities, including mental retardation, hearing loss or deafness, meningitis, intellectual disability as well as mobility impairment, has been greatly reduced by immunization against polio as well as rubella, meningitis, measles, diarrhea and pneumonia.² To guarantee children full protection against vaccine-preventable diseases, caregivers (mothers) need to be mandated to taking the provided vaccines at the right time. According to CDC children before the age of 2 years should be fully immunized against 14 potentially deadly diseases which include polio, rubella, hepatitis, measles, yellow fever, tuberculosis, pertussis tetanus, and rotavirus among others.⁹ Also, WHO planned a 9-month vaccine plan for infants at their priming age of life such as Bacilli Calmette Guerin (BCG), Oral Polio Vaccine (OPV), Hepatitis B vaccine (HBV), Hemophilus Influenza B vaccine, Diphtheria, Pertussis and Tetanus (DPT), inactivated polio vaccine (IPV) Measles vaccine and Yellow fever vaccine.^10,11 The underlying goal of the immunization schedule is to achieve effective, lasting immunity against vaccine-preventable diseases.¹²

Currently, it is recommended that all children when born should be vaccinated with the appropriate vaccine. At birth they should be given Bacille Calmette–Guerin (BCG, OPV0, and Hep B0, at 6th weeks-Pentavalent 1 (DPT1, Hep B, and Hib), PCV1, OPV1 and Rota1, at 10 weeks-Pentavalent 2 (DPT, Hep B, and Hib), PCV2, OPV2 and Rota 2. At 14 weeks- Pentavalent 3 (DPT, Hep B and Hib), PCV3, OPV3, and IPV. At 6 months the children should receive Vitamin A 1st dose. In the 9th month, each surviving child should be given 1st dose measles, yellow fever, and meningitis vaccines. At age 15 to 23 months a child should be vaccinated with measles second dose.^13,14 Therefore, a fully immunized child must have had the above.^4,15

The estimated global vaccination coverage in 2018 according to the World Health Organization, were: Bacilli Calmette Guerin (BCG)-47%, 3 doses of Oral Polio Vaccine (OPV)-85%, Hepatitis B vaccine (HBV)-84%, 3 doses of Hemophilus Influenza B (Hib) vaccine-22%, 3 doses of Diphtheria, Pertussis, and Tetanus (DTP3) vaccine-86%, 1 dose of Measles vaccine-86%, 2 doses of measles vaccine-69%, Rotavirus vaccine-35%, and Yellow fever vaccine-49%.^16-18 Immunization programs have become more difficult over the past years’ due principles and factors of consideration in introduction, and availability of new vaccines,¹⁹ and setting up of desired worldwide target for disease control such as polio eradication and measles elimination.¹⁰ Polio which is targeted for worldwide eradication has stopped in all nations except for Pakistan, Afghanistan, and Nigeria. All the countries, especially those experiencing conflict and instability remain at risk until polio is fully eradicated.¹⁷ However, Since August 2016 Nigeria has not recorded any case of wild polio and is on the point of polio eradication; this success rests on highly granular monitoring and evaluation (M&E), the deployment of digital technology, and reaching the most isolated communities.²

Though the country has recently made some progress in immunization rates with current coverage at 50.1% which is low.² To address this crisis, numerous approaches were deployed to boost immunization in Nigeria but these interventions still encounter challenges.²⁰ The Federal Government of Nigeria (FGoN) has committed itself to improve its human capital to reduce under-5 mortality by half by 2030. The proposed Multiphase Programmatic Approach (MPA) includes Improving utilization and quality of immunization which is the Intermediate Program Outcome (Phase I) among others.² Despite the awareness and struggle in immunization program the immunization coverage of children still lags. Children who are not immunized most time are likely to come from families of low socioeconomic status.^21,22 To prioritize immunization, parents are supposed to perceive immunization as one of the safest and most effective interventions to prevent morbidity and early child mortality. Contrary to this, due to much engagement, customs, and tradition, they missed many opportunities which in turn lead to childhood mortality. In the country for instance, vaccines are made available to the public freely, yet over 20% of Nigerian children are not fully immunized each year.¹⁶

This study, therefore, investigated the factors affecting the routine immunization utilization of children under 5 in Ebonyi state, Nigeria.

Materials and Methods

Study Design

This study adopted a population-based cross-sectional survey. According to Abonyi et al,²³ a descriptive survey consists of study in which data are collected collected from a small sample of a large population that enables the researcher to describe systematically and interpret the characteristic features and facts about things that exist.

Study Setting

The study was conducted in 6 LGAs in Ebonyi state which has 13 Local Government Areas and 156 autonomous communities. Ebonyi state occupies a land area of 5,954 square kilometers and situated between longitude 70 and 80 301 E and latitude 50 401 and 60 541 north of the equator. The state is part of the southeast geopolitical zone and bounded in the north by Benue state, in the west by Enugu state, in the east by Cross River State and in the south by Abia state. The population of Ebonyi state for 2019 is 3 027 449 (projected from 2006 census of 2 173 501 with a projected growth rate of 2.8%). The population of children under 5 years was 622 444 (20.56%), pregnant women 155 611 (5.14%) and women of childbearing age 684 688 (22.62%).²⁴ see Appendix 1

Study Population

For this study, the population comprised of 684688 women of childbearing age in Ebonyi state projected from the 2006 census of 2,173,501 with a projected growth rate of 2.8% for the year 2019.²⁴

Sample and Sampling Technique

The sample size of the study consisted of 400 women of childbearing age which was determined using Taro Yamen formula used by Uzoagulu.²⁵ Ebonyi state was divided into 3 senatorial zones namely: Ebonyi north, central, and south zones. 6 out 13 LGAs were purposively selected, 3 rural and 3 Urban. The respondents were recruited purposively from the households that have women of childbearing age with under 5 children ensuring that there was proportional representation in the villages (there were 20 302 households that met these criteria). Households were assigned random numbers and the required proportion generated using random numbers, if the visited household did not have an under 5 child the next household was picked until the required numbers were obtained. It should be noted that only 1 respondent was selected from the participating households.

Data Collection Instrument

The instrument for data collection was self- administered questionnaire consisted of 3sections; section A on child’s demography (Age, Sex, Birth order, place of birth and immunization Status); B on mother demography (Age, parity, marital status, occupation, no of antenatal visit, level of Education, location and number of children living in the household); C, 7 items on factors using a 4-point Likert scale of strongly agreed (SA), agreed (A), disagree (D), strongly disagree (SD). Three experts’ facilitators from the Department of Public Health established the face validity of the instrument. This ensured clarity of instructions; proper wording of items, appropriateness, and adequacy of the items in addressing the objectives of the study. The reliability of the instrument was established using data collected from 20 Women of Child-Bearing Age not included in the study sample. The process yielded an overall reliability of the coefficient of 0.934 which is reliable for use in this study. Five research assistants interpreted the questions in the local language to the non-literate’s mothers.

Data Analysis

In this study, fully immunized children are children who were immunized based on WHO classification. Childs’ immunization cards were used to ascertain their immunization status. Of 400 copies distributed 374 representing 94% return rate were used for data analysis. Thereafter, data were analyzed using mean (x) score, standard deviation, t-test and Analysis of Variance (ANOVA). Mean score was used to answer all the research questions. The criterion mean (x) of 2.50 was set for the study. A criterion mean was derived by adding up the scale values and dividing the sum by the number of scale options thus: 4 + 3 + 2 + 1 = 10/4 + 2.50. Uzoagulu²⁵ criterion mean adopted from Likert’s scaling was applied to categorize the different constructs being studied for description. A criterion means of 2.50 and above was “agreed” and below 2.50 was considered “disagreed.” On the other hand, t-test and ANOVA were used to test hypotheses at 0.05 level of significance.

Results

Result revealed that majority of children whose mothers participated in the study were 2 years 98(26.1%) and ≤1year 82(21.9%), females 180(40.1%), in Birth order [1-2] 273(73.0%), fully immunized 219(58.6%), born in the home of TBAs 105(28.1%) and their mothers had antenatal visits of 4 and above 181(48.4%). Also out of 374 mothers’ respondents, the majority were 21-30 years of age 232(62.0%), married 291(77.8%), rural dwellers 353(94.4%), had secondary education 155(41.4%), self-employed 221(59.1%), wealth of middle class 229(61.2%), multi-parous 224(59.9%) and had 3-4 number of children living in their household 159(42.5%) Table 1.

Table 1.

Socio-Demographic Characteristics of Respondents (Mothers) and Children (n = 374).

Variable	Frequency (f)	Percentages (%)
CHILD
Age (years)
<1	82	21.9
1	54	14.4
2	98	26.2
3	75	20.1
4	65	17.4
Sex
Male	194	51.9
Female	180	48.1
Birth order
1–2	273	73.0
3–4	75	20.1
5–6	21	5.6
>6	5	1.3
Immunization status
Fully immunized	219	58.6
Partially immunized	155	41.4
Place of delivery
Home of TBAs	105	28.1
Health facility	87	23.3
Public hospital	91	24.3
Private hospital	91	24.3
No of antenatal visit
Non	61	16.3
1-3 times	132	35.3
4 and above	181	48.4
Maternal
Age (years)
<20	49	13.1
21–30	232	62.0
31–40	89	23.8
>40	4	1.1
Marital status
Single	32	8.6
Married	291	77.8
Divorced	25	6.7
Widowed	26	7.0
Location
Urban	21	5.6
Rural	353	94.4
Level of education
Non formal	45	12.0
Primary	128	34.2
Secondary	155	41.4
Tertiary	46	12.3
Occupation
No job	71	19.0
Self employed	221	59.1
Student	56	15.0
Civil servant	26	7.0
Wealth index
Poor	113	30.2
Middle class	229	61.2
Rich	32	8.6
Parity
Primipara (1)	82	21.9
Multipara (2–4)	224	59.9
Grand multipara (>4)	68	18.2
No of children in household
1–2	120	32.1
3–4	159	42.5
5–6	68	18.2
>6	27	7.2
Total	374	100.0

Factors investigated were: health workers’ behavior, experience with past immunization, location, beliefs, schedules, time and vaccine unavailability. In result of Table 2, A majority of the mothers 205(54.8%) disagreed to health worker’s negative behavior (x̄ = 2.11 ± 0.86); 169(45.2%) agreed that immunization was effective (x̄ = 2.11 ± 0.86); 123(32.9%) agreed that immunization centers were far from home (x̄ = 2.44 ± 1.02); 184(49.2%) disagreed to no belief in immunization; 246(65.8%) disagreed that there was inconvenient immunization schedule (x̄ = 2.00 ± 0.68); 174(46.5%) disagreed to long time spent during immunization (x̄ = 2.35 ± 0.99); and 180(48.1%) disagreed to unavailability of respondents (x̄ = 1.82 ± 0.81). It was reported that a mean score of ≥2.50 was agreed and <2.50 as disagreed. Thus, mothers have a positive attitude toward immunization and agreed that immunization was effective (Table 2).

Table 2.

Frequency and Percentage of Mothers Responses to Each Likert Scale on the Factors Affecting Routine Immunization Utilization.

S/N	Factors	SA (%)	A (%)	D (%)	SD (%)	Mean ± SD
1.	Health workers’ behavior are negative	37(9.9)	49(13.1)	205(54.8)	83(22.2)	2.11 ± 0.86
2.	Immunization was effective	97(25.9)	169(45.2)	53(14.2)	55(14.7)	2.82 ± 0.98
3.	Vaccination centers far from home	63(16.8)	123(32.9)	102(27.3)	86(23.0)	2.44 ± 1.02
4.	No belief in immunization	23(6.1)	27(7.2)	184(49.2)	140(37.4)	1.82 ± 0.81
5.	Inconvenient immunization Schedule	15(4.0)	42(11.2)	246(65.8)	71(19.0)	2.00 ± 0.68
6.	Time spent during immunization was long	69(18.4)	61(16.3)	174(46.5)	70(18.7)	2.35 ± 0.99
7.	Unavailability of vaccine	12(3.2%)	26(7.0)	180(48.1)	156(41.7)	1.72 ± 0.73

Abbreviations: SA, Strongly Agree; A, Agree; D, Disagree; SD, Strongly Disagree.

Fifty-eight point 6% (58.6%) of children of the sampled mothers were fully immunized while 41.4% were partially immunized. Mothers of children who were fully immunized only agreed that past immunization were effective (x̄ = 2.82 ± 0.93). While they strongly disagreed to other factors which were: negative health workers’ behavior (x̄ = 1.94 ± 0.73), vaccination centers far from home (x̄ = 2.36 ± 1.08), no belief in immunization (x̄ = 1.59 ± 0.61), inconvenient immunization schedule (x̄ = 1.94 ± 0.63), long time spent during immunization (x̄ = 2.26 ± 1.02), and unavailability of vaccine (x̄ = 1.69 ± 0.69). Also, mothers whose children were partially immunized agreed that immunization was effective (x̄ = 2.78 ± 1.02) immunization center was far from home (x̄ = 2.55 ± 0.93) and time spent during immunization was long (x̄ = 2.55 ± 0.92). Also they strongly disagree to unavailability of vaccine (x̄ = 1.75 ± 0.79) and slightly disagreed that health workers’ behavior were negative (x̄ = 2.34 ± 0.97), no belief in immunization (x̄ = 2.14 ± 0.95) and inconvenient immunization schedule (x̄=2.08 ± 0.75). Thus factors that mostly contributed to mothers’ negative attitude to routine immunization were: immunization center being far from home. Table 3.

Table 3.

Mean and Standard Deviation Scores on Mothers Responses Based on the Immunization Status of the Child.

S/n	Factors	Completely immunized n = 219(58.6%)			Partially immunized n = 155(41.4%)
S/n	Factors	Mean	Std. dev	Dec	Mean	Std dev	Dec
1.	Health workers’ behavior are negative	1.94	0.73	Disagree	2.34	0.97	Disagree
2.	Immunization was effective	2.82	0.93	Agree	2.78	1.02	Agree
3.	Vaccination centers far from home	2.36	1.08	Disagree	2.55	0.93	Agree
4.	No belief in immunization	1.59	0.61	Disagree	2.14	0.95	Disagree
5.	Inconvenient immunization Schedule	1.94	0.63	Disagree	2.08	0.75	Disagree
6.	Time spent during immunization was long	2.26	1.02	Disagree	2.55	0.92	Agree
7.	Unavailability of vaccine	1.69	0.69	Disagree	1.75	0.79	Disagree

Abbreviations: Dec, Decision; Std dev, standard deviation.

The independent variables are the socio-demographics while mother’s responses (attitudes in mean score) is dependent. Overall, mothers disagreed to negative health workers’ behavior (grand mean = 2.11 ± 0.86). This disagreement was more among older mothers >40 years (2.00 ± 0.00), those who delivered at private hospital (1.85 ± 0.79) (P = .002), those who had up to 4 antenatal visit (1.96 ± 0.77), birth order [1-2] (2.04 ± 0.083), (P = .014) widowed (2.00 ± 1.02), urban residents (2.10 ± 1.04), those with secondary education (1.94 ± 0.70), civil servants (1.92 ± 0.56), the rich (2.03 ± 0.93), primiparous (1.88 ± 0.76) (P = .002*), and those with less number of children (1.99 ± 0.75). however, only place of delivery, birth order, and parity were significant (P < .05). [Table 4].

Table 4.

Summary of Analysis of Variance and Independent Sample t Test on Mother’s Responses on Health Workers’ Behavior Based on the Socio Demographic Characteristics.

Variable	Mean	Std dev	F value	t-value	P-value	Dec
Mothers’ age (years)
≤20	2.14	0.89	0.482		.695	NS
21–30	2.07	0.85
31–40	2.19	0.89
>40	2.00	0.00
Place of delivery
Home of TBAs	2.32	0.89	5.196		.002*	S
Health facility	2.10	0.86
Public hospital	2.12	0.83
Private hospital	1.85	0.79
No of antenatal visit
Non	2.31	1.01	5.804		.003*	S
1-3 times	2.22	0.87
4 and above	1.96	0.77
Birth order
1-2	2.04	0.83	3.567		.014*	S
3-4	2.21	0.87
5-6	2.62	0.97
>6	2.20	1.10
Marital status
Single	2.13	0.91	0.159		.924	NS
Married	2.12	0.86
Divorced	2.08	0.70
Widowed	2.00	1.02
Location
Urban	2.10	1.04	2.287	−0.064	.949	NS
Rural	2.11	0.85
Level of education
Non formal	2.31	0.90	5.002		.002*	S
Primary	2.28	0.96
Secondary	1.94	0.70
Tertiary	1.97	0.93
Occupation
No job	2.25	0.92	1.172		.320	NS
Self employed	2.10	0.88
Student	2.05	0.80
Civil servant	1.92	0.56
Wealth index
Poor	2.04	0.82	0.841		.432	NS
Middle class	2.15	0.87
Rich	2.03	0.93
Parity
Primipara (1)	1.88	0.76	6.204		.002*	S
Multipara (2-4)	2.11	0.83
Grand multipara (>4)	2.37	0.99
No of children in household
1-2	1.99	0.75	6.172		.000*	S
3-4	2.03	0.82
5-6	2.28	0.91
>6	2.67	1.14
Grand mean	2.11	0.87

Abbreviations: Dec, Decision; S, Significant; NS, Not Significant.

Overall, mothers agreed that past immunization was effective (grand mean = 2.82 ± 0.98). this agreement was more among mothers of older age (3.00 ± 1.41), those who delivered at public hospital (2.98 ± 1.03), had up to 4 antenatal visits (2.86 ± 1.01), child’s birth order [3-4] (2.88 ± 1.09), singles (2.91 ± 0.59), rural residents (2.84 ± 0.97), those with secondary education (2.90 ± 0.82) (P = .020*) civil servants (3.08 ± 1.29), the middle class (2.87 ± 1.02), multiparous (2.90 ± 0.93), and those with the least number of children [1-2] (2.90 ± 0.85). However, only level of education was significant (P < .05) with this response (Table 5).

Table 5.

Summary of Analysis of Variance and Independent Sample t Test on Mothers Responses on Experience with Past Immunization Based on the Socio Demographic Characteristics.

Variable	Mean	Std dev	F value	t-value	P-value	Dec
Mothers age (years)
<20	2.92	0.73	0.482		.695	NS
21–30	2.84	0.93
31–40	2.72	1.20
>40	3.00	1.41
Home of TBAs	2.77	0.95	1.324		.266	NS
Health facility	2.70	1.05
Public hospital	2.98	1.03
Private hospital	2.85	0.88
No of antenatal visit
Non	2.75	1.03	0.265		.767	NS
1-3 times	2.81	0.92
4 and above	2.86	1.01
Birth order
1-2	2.82	0.92	1.264		.287	NS
3-4	2.88	1.09
5-6	2.81	1.17
>6	2.00	1.41
Marital status
Single	2.91	0.59	0.362		.781	NS
Married	2.82	1.01
Divorced	2.88	0.97
Widowed	2.65	1.09
Location
Urban	2.57	1.08	1.556	−1.214	.226	NS
Rural	2.84	0.97
Level of education
Non formal	2.80	1.01	3.324		.020*	S
Primary	2.63	1.03
Secondary	2.90	0.82
Tertiary	2.82	1.20
Occupation
No job	2.85	0.90	0.674		.569	NS
Self employed	2.79	0.96
Student	2.80	1.05
Civil servant	3.08	1.29
Wealth index
Poor	2.77	0.79	1.177		.309	NS
Middle class	2.87	1.02
Rich	2.63	1.26
Parity
Primipara (1)	2.78	0.90	2.621		.074	NS
Multipara (2–4)	2.90	0.93
Grand multipara (>4)	2.60	1.19
No of children in household
1–2	2.90	0.85	2.089		.101	NS
3–4	2.89	0.94
5–6	2.68	1.14
>6	2.48	1.22
Grand mean	2.82	0.98

Abbreviations: Dec, Decision; S, Significant; NS, Not Significant.

Table 6 showed that on geographic factors, mothers generally disagreed that vaccination centers were far from home (grand mean = 2.44 ± 1.02). This response was more among mothers who were middle age (2.31 ± 0.90), (P = .018*), those that delivered at a public hospital (2.29 ± 1.03), those with no antenatal visit (2.33 ± 2.00), the widowed (2.08 ± 1.09), (P = .037*), urban residents (2.24 ± 1.03), those with tertiary education (1.85 ± 0.92), (P = .000), civil servants (2.08 ± 0.93, (P = .000*), the rich (2.03 ± 1.00), (P = .009*), grand multiparous (2.15 ± 0.93 (P = .036*), and those with more than 6 number of children (2.07 ± 1.00). Age, marital status, level of education, occupation, wealth index, and parity were significant (P < .05) (Table 6).

Table 6.

Summary of Analysis of Variance and Independent Sample t Test on Mothers Responses on Location [Vaccination Centers Being Far From Home] Based on the Socio Demographic Characteristics.

Variable	Mean	Std dev	F-value	t-value	P-value	Dec
Age (years)
<20	2.56	0.94	3.400		.018*	S
21–30	2.39	1.07
31–40	2.31	0.90
>40	2.50	1.00
Place of delivery
Home of TBAs	2.42	0.93	1.503		.213	NS
Health facility	2.61	0.98
Public hospital	2.29	1.03
Private hospital	2.44	1.15
No of antenatal visit
Non	2.33	2.00	1.589		.206	NS
1–3 times	2.56	0.97
4 and above	2.38	1.07
Birth order
1–2	2.47	1.04	1.306		.272	NS
3–4	2.37	0.94
5–6	2.43	0.98
>6	1.60	1.34
Marital status
Single	2.84	1.05	2.848		.037*	S
Married	2.42	1.02
Divorced	2.48	0.87
Widowed	2.08	1.09
Location
Urban	2.24	0.94	1.439	−0.912	.362	NS
Rural	2.45	1.03
Level of education
Non formal	2.42	0.94	7.870		.000*	S
Primary	2.39	0.92
Secondary	2.65	1.08
Tertiary	1.85	0.92
Occupation
No job	2.31	0.94	6.187		.000*	S
Self employed	2.43	1.06
Student	2.89	0.85
Civil servant	2.08	0.93
Wealth index
Poor	2.63	1.05	4.764		.009*	S
Middle class	2.40	1.00
Rich	2.03	1.00
Parity
Primipara (1)	2.50	1.08	3.356		.036*	S
Multipara (2-4)	2.60	1.02
Grand multipara (>4)	2.55	0.93
No of children in household
1–2	2.51	1.10	1.574		.195	NS
3–4	2.52	1.00
5–6	2.51	0.93
>6	2.52	1.00
Grand mean	2.55	0.93

Abbreviations: Dec, Decision; S, Significant; NS, Not Significant.

Table 7 showed that on beliefs, overall, majority of the mothers strongly disagreed to no belief in immunization (grand mean = 1.82 ± 0.81). Their responses with regard to the socio demographic characteristics of the respondents showed that those who had the highest disagreement were the middle age mothers (1.80 ± 0.89), delivered in a public hospital (1.58 ± 0.65) (P = .000*) mothers who had 1 to 3 antenatal visits. (1.61 ± 0.65) P = .000*), birth order 3 to 4 (1.79 ± 0.93), widowed (1.73 ± 0.78), urban dwellers (1.81 ± 0.98), had tertiary education (0.46 ± 0.81) P = .002*, civil servants (x = 1.46 ± 0.81), P = .002*, the rich (x = 1.37 ± .66), P = .003*, primiparous (x = 1.77 ± 0.73), and those who had 3-4 number of children in the household (x = 1.77 ± 0.79). place of birth, level of education, occupation, and wealth index were significant with this response.

Table 7.

Summary of Analysis of Variance and Independent Sample t Test on Mothers Responses on Beliefs, Based on the Socio Demographic Characteristics.

Variable	Mean	Std dev	F-value	t-value	P-value	Dec
Age (years)
<20	1.90	0.94	0.565		.638	NS
21–30	1.81	0.75
31–40	1.80	0.89
>40	2.25	1.26
Place of delivery
Home of TBAs	2.12	0.10	8.739		.000*	S
Health facility	1.84	0.73
Public hospital	1.58	0.65
Private hospital	1.69	0.69
No of antenatal visit
Non	2.31	1.06	19.478		.000*	S
1–3 times	1.89	0.78
4 and above	1.61	0.65
Birth order
1–2	1.82	0.85	0.385		.764	NS
3–4	1.79	0.93
5–6	2.00	1.10
>6	1.80	0.84
Marital status
Single	1.84	0.77	0.238		.870	NS
Married	1.82	0.82
Divorced	1.92	0.86
Widowed	1.73	0.78
Location
Urban	1.81	0.98	1.927	−0.066	.948	NS
Rural	1.82	0.80
Level of education
Non formal	2.27	1.05	11.754		.000*	S
Primary	1.96	0.85
Secondary	1.70	0.64
Tertiary	1.41	0.69
Occupation
No job	2.10	0.93	4.883		.002*	S
Self employed	1.80	0.73
Student	1.73	0.88
Civil servant	1.46	0.81
Wealth index
Poor	2.03	0.77	9.054		.003*	S
Middle class	1.78	0.82
Rich	1.37	0.66
Parity
Primipara (1)	1.77	0.73	0.470		.625	NS
Multipara (2–4)	1.82	0.81
Grand multipara (>4)	1.90	0.92
No of children in household
1–2	1.81	0.71	1.347		.259	NS
3–4	1.77	0.79
5–6	1.84	0.87
>6	2.11	1.20
Grand mean	1.82	0.81

Abbreviations: Dec, Decision; S, Significant; NS, Not Significant.

Table 8 revealed that on geographic factors, majority mothers disagreed to inconvenient immunization schedules no belief in immunization (grand mean = 2.00 ± 0.68). Their responses with regard to the socio demographic characteristics of the respondents showed that those who had the highest disagreement were middle age mothers who were 31 to 40 years (1.91 ± 0.56), delivered in public hospital (1.85 ± 0.73) (P = .007*), mothers who had ≥4 antenatal visits, (1.90 ± 0.62) (P = .004*), child’s birth order >6 (1.60 ± 0.89), widowed (1.88 ± 0.59), rural dwellers (2.00 ± 0.67), those that have tertiary education (1.61 ± 0.65) (P = .000*), civil servants (x = 1.85 ± 0.78), the rich (2.00 ± 0.80), (P = .040), grand multi-parous (1.90 ± 0.63), and those who had 5 to 6 number of children in the household (1.88 ± 0.61), (P = .044*).

Table 8.

Summary of Analysis of Variance and Independent Sample t Test on Mothers Responses on Schedules Arrangement, Based on the Socio Demographic Characteristics.

Variable	Mean	Std dev	F-value	t-value	P-value	Dec
Age (years)
<20	2.14	0.76	1.248		.292	NS
21–30	2.01	0.71
31–40	1.91	0.56
>40	2.00	0.00
Place of delivery
Home of TBAs	2.12	0.66	4.136		.007*	S
Health facility	2.11	0.74
Public hospital	1.85	0.73
Private hospital	1.91	0.55
No of antenatal visit
Non	1.95	0.72	5.615		.004*	S
1–3 times	2.16	0.72
4 and above	1.90	0.62
Birth order
1–2	1.99	0.65	2.316		.075	NS
3–4	2.00	0.70
5–6	2.33	0.91
>6	1.60	0.89
Marital status
Single	2.09	0.47	0.486		.692	NS
Married	2.01	0.71
Divorced	1.96	0.68
Widowed	1.88	0.59
Location
Urban	2.05	0.86	2.024	0.311	.756	NS
Rural	2.00	0.67
Level of education
Non formal	1.78	0.69	7.262		.000*	S
Primary	2.14	0.78
Secondary	2.01	0.55
Tertiary	1.61	0.65
Occupation
No job	1.97	0.65	0.813		.487	NS
Self employed	2.01	0.71
Student	2.09	0.55
Civil servant	1.85	0.78
Wealth index
Poor	2.02	0.58	0.040		.961	NS
Middle class	2.00	0.71
Rich	2.00	0.80
Parity
Primipara (1)	1.96	0.67	1.478		.229	NS
Multipara (2–4)	2.05	0.70
Grand multipara (>4)	1.90	0.63
No of children in household
1–2	1.92	0.66	2.723		.044*	S
3–4	2.11	0.71
5–6	1.88	0.61
>6	2.07	0.73
Grand mean	2.00	0.68

Abbreviations: Dec, Decision; S, Significant; NS, Not Significant.

Table 9 showed that, on time spent during immunization, the majority of mothers disagreed on a long time spent during immunization (x = 2.34 ± 0.99). this response was significant with older mothers >40 years (1.75 ± 0.50) (P = .000), the divorced (2.04 ± 0.84), (P = .001*), those with tertiary education, (1.76 ± 0.67), civil servants (1.73 ± 0.53), (0.010*) and the rich (1.91 ± 1.00), (P = .000)

Table 9.

Summary of Analysis of Variance and Independent Sample t Test on Mothers Responses on Long Time Spent During Immunization, Based on the Socio Demographic Characteristics.

Variable	Mean	Std dev	f-value	t-value	P-value	Dec
Age (years)
<20	2.69	0.94	7.169		.000*	S
21–30	2.42	1.02
31–40	1.99	0.80
>40	1.75	0.50
Place of delivery
Home of TBAs	2.48	0.90	1.718		.163	NS
Health facility	2.28	0.90
Public hospital	2.19	0.95
Private hospital	2.42	1.16
No of antenatal visit
Non	2.48	0.87	2.568		.078	NS
1–3 times	2.45	0.96
4 and above	2.23	1.03
Birth order
1–2	2.41	1.03	1.306		.272	NS
3–4	2.19	0.83
5–6	2.29	0.85
>6	1.60	0.55
Marital status
Single	2.94	1.08	5.711		.001*	S
Married	2.33	0.95
Divorced	2.04	0.84
Widowed	2.04	1.11
Location
Urban	2.33	0.91	0.300	−0.055	.956	NS
Rural	2.35	0.99
Level of education
Non formal	2.27	0.89	8.665		.000*	S
Primary	2.31	0.90
Secondary	2.57	1.08
Tertiary	1.76	0.67
Occupation
No job	2.34	0.88	3.839		.010*	S
Self employed	2.42	1.04
Student	2.36	1.00
Civil servant	1.73	0.53
Wealth index
Poor	2.63	1.07	8.928		.000*	S
Middle class	2.27	0.91
Rich	1.91	1.00
Parity
Primipara (1)	2.40	1.02	0.867		.421	NS
Multipara (2–4)	2.37	0.99
Grand multipara (>4)	2.21	0.92
No of children in household
1–2	2.42	1.04	0.999		.393	NS
3–4	2.38	0.98
5–6	2.18	0.90
>6	2.26	0.98
Grand Mean	2.34	0.99

Abbreviations: Dec, Decision; S, Significant; NS, Not Significant.

In Table 10, it was shown that majority mothers disagreed strongly to unavailability of vaccine (x = 1.72 ± 0.73). This disagreement is significant with birth order [1-2] (1.71 ± 0.016), those with tertiary education, (1.52 ± 0.72), (0.049) civil servants (1.42 ± 0.70) (P = .000*), middle class (1.61 ± 0.71) (0.000*), and those with up to 5 number of children (1.53 ± 0.66), (P = .035*).

Table 10.

Summary of Analysis of Variance and Independent Sample t Test on Mothers Responses on Vaccine Unavailability, Based on the Socio Demographic Characteristics.

Variable	Mean	Std dev	F value	t-value	P-value	Dec
Age (years)
<20	1.76	0.78	1.516		.210	NS
21–30	1.76	0.71
31–40	1.61	0.76
>40	1.25	0.50
Place of delivery
Home of TBAs	1.76	0.73	0.955		.414	NS
Health facility	1.70	0.78
Public hospital	1.62	0.65
Private hospital	1.78	0.77
No of antenatal visit
Non	1.72	0.73	0.694		.500	NS
1–3 times	1.77	0.80
4 and above	1.67	0.68
Birth order
1–2	1.71	0.69	3.463		.016*	S
3–4	1.61	0.77
5–6	2.05	0.97
>6	2.40	0.89
Marital status
Single	1.94	0.57	2.032		.109	NS
Married	1.74	0.76
Divorced	1.60	0.76
Widowed	1.42	0.50
Location
Urban	1.86	0.79	0.078	0.905	.366	NS
Rural	1.71	0.73
Level of education
Non formal	1.73	0.81	2.648		.049*	S
Primary	1.65	0.74
Secondary	1.83	.69
Tertiary	1.52	0.72
Occupation
No job	1.79	0.72	4.757		.003*	S
Self employed	1.79	0.75
Student	1.46	0.63
Civil servant	1.42	0.70
Wealth index
Poor	1.96	0.70	9.016		.000*	S
Middle class	1.61	0.71
Rich	1.63	0.83
Parity
Primipara (1)	1.79	0.75	2.474		.086	NS
Multipara (2–4)	1.74	0.74
Grand multipara (>4)	1.54	0.68
No of children in household
1–2	1.85	0.77	2.449		.035*	S
3–4	1.70	0.72
5–6	1.53	0.66
>6	1.70	0.72
Total	1.72	0.73

Abbreviations: Dec, Decision; S, Significant; NS, Not Significant.

Discussion

Immunization Status of the Children

The result of the study showed that 219(58.6%) of children were fully immunized showing low coverage which is in line with the findings of Etana and Deressa,¹³ Noh et al,²¹ Al-lela et al,²⁶ Akwataghibe et al,²⁷ Basheer et al,⁵ Brown et al,²⁸ who reported low immunization coverage in their study areas. At variance, Kassahun et al,²⁹ Konwea et al,³⁰ reported a high-level immunization coverage.

Factors Affecting the Routine Immunization Utilization

Factors investigated were: behavior, experience with past immunization, location, Beliefs, schedules, time and vaccine unavailability

Health workers’ behavior

In this study respondents disagree that health workers’ behavior were negative (grand mean = 2.11 ± 0.86), though those whose children were partially immunized were more likely to agree (x = 2.34 ± 0.97) than the fully immunized (x = 1.94 ± 0.73), hence negative health workers are more likely to affect those whose children had partial immunization. With respect to the socio-demographic characteristics, mothers of children of birth order 5 to -6, (x = 2.62 ± 0.97), delivered at Home of TBA (x = 2.32 ± 0.89), having no antenatal visit (x = 2.31 ± 1.01), having no formal education (2.31 ± 0.99), Grand multiparous (x = 2.37 ± 0.99) and having ≥6 number of children living in the household (x = 2.67 ± 1.14) were significantly associated with complain of negative health workers’ behavior (P = .014, .002, .003, .002, .002, .000) respectively. This finding aligns with the other findings of Akwataghbe et al²⁷ whose respondents reported health workers’ behavior as “helpful” or “very helpful” while Al-lela et al²⁶ and Rahji and Ndikom³¹ who found that health workers’ attitude, is a factor hindering compliance with immunization schedules.

Experience with Past Immunization

The majority of the mothers agreed that past immunization of their children was effective (grand mean = (x = 2.82 ± 0.98). Both the mothers of fully and partially immunized children strongly agreed that past immunization was effective (x = 2.80 ± 0.93; 2.78 ± 1.02). This showed that experience with past immunization had no negative influence on routine immunization utilization of children. This report is significantly associated with the level of education among those who have secondary education (x = 2.90 ± 0.82, P = .020). Contrastingly, Akwataghibe et al²⁷ reported that AEFI promoted fear among young mothers and, thereby discouraging initial use of immunization.

Location of Health Facility

The respondents whose children were partially immunized agreed that vaccination centers were far from home (x = 2.55 ± 0.93) while those who had their children fully immunized reported otherwise (x = 2.36 ± 1.08). This finding revealed that the location of vaccination centers can influence the routine immunization of children. It will have a negative influence when it is far from mothers and not easily assessable but will influence it positively when situated close to their homes. However, mothers who were young (≤20 years) (x = 2.86 ± 0.94), single (x = 2.84 ± 1.05), had secondary education (x = 2.65 ± 1.08), students (2.89 ± 1.08), poor (x = 2.63 ± 1.05), and primiparous (x = 2.50 ± 1.08) are more affected and they agreed (grand mean >2.50) hence significant (P = .018, .037, .000, .000, .009, and .036) respectively. Similarly, Abdulraheem and Onajole,³² and Rahman and Obaida-Nasrin,³³ reported that long walking distances, is associated with incomplete immunization. Contrastingly, respondents in the study of Akwataghibe et al²⁷ reported health facilities as being generally within walking distance to their households.

Beliefs

The respondents generally disagreed that they have no belief in immunization (x = 1.82 ± 0.81). This showed that mothers believed that immunization is beneficial to them having also agreed to its effectiveness in disease prevention. However, those whose children were partially immunized were more likely to disbelief in immunization (x = 2.14 ± 0.95). Socio-demographic characteristics significantly associated with beliefs as recorded in this study were place of birth (P = .000), number of antenatal visits (P = .000), level of education (P = .000), occupation (P = .002) and wealth index (P = .003). In addition, those who gave birth at home of TBAs (x = 2.12 ± 0.10), had no antenatal visits (x = 2.31 ± 1.06), no formal education (x = 2.27 ± 1.05), no job (x = 2.10 ± 0.93), and poor (x = 2.03 ± 0.77) were more likely not to belief in immunization. At variance with this report Akwataghibe et al²⁷ reported superstitious belief among respondents hindering immunization completion among children.

Schedule

The mothers generally disagreed with inconvenient immunization schedules (x = 2.00 ± 0.68). However, those whose children were partially immunized disagreed less (x = 2.08 ± 0.75) than those who had their children fully immunized (x = 1.94 ± 0.63) thus inconvenient schedules slightly affect completion of immunization. Socio-demographic characteristics that are significantly associated with this response were, place of delivery (P = .007), no of antenatal visits (P = .004), level of education (P = .000), and number of children living in the household (P = .044). Therefore, those gave birth at home of TBA (x = 2.12 ± 0.66), had no antenatal visit (x = 2.16 ± 0.72), no formal education (x = 1.78 ± 0.69), and up to 6 or more number of children living in the household (x = 2.07 ± 0.73) were more likely to complain of inconvenient immunization schedule.

Time

Respondents slightly disagreed that time spent during immunization was long, however, those whose children were partially immunized agreed (x = 2.50 ± 0.92) to this long duration. Hence log waiting time at immunization negatively affects the immunization utilization of children. Mothers’ age, marital status occupation, and wealth index were significantly associated with this response (P = .000, .0001, .010, and .000) respectively. So mothers who were young (x = 2.69 ± 0.94), single (x = 2.94 ± 1.08), self-employed (x = 2.42 ± 1.04) and poor (x = 2.63 ± 1.07) agreed to long time spent during immunization. Similarly, Abdulraheem and Onajole,³² Rahji and Ndikom (2013), reported that long waiting time at the facility, is associated with poor completion of RI schedules.

Vaccine Unavailability

The mothers generally disagreed with vaccine unavailability (x = 1.72 ± 0.73). However, those whose children were partially immunized disagreed less (x = 1.75 ± 0.79) than those who had their children fully immunized (x = 1.69 ± 0.69) thus vaccine unavailability slightly affect completion of immunization. Socio-demographic characteristics that is significantly associated with this response were, birth order (P = .016), occupation (P = .003), wealth index (P = .000) and number of children living in the household (P = .035). Therefore, those whose children are older (4 years) (x = 1.94 ± 0.93), birth order >6 (x = 2.40 ± 0.89), had no job (x = 1.79 ± 0.72), poor (x = 1.96 ± 0.70) and having less number of children (1-2) living in the household (x = 1.85 ± 0.77) were more likely to complain of vaccine unavailability. Contrastingly, Unavailability of vaccines at the scheduled times was the most frequent complaint by respondents in other studies.²⁷

Socio-Demographic Determinants

Birth order, place of delivery, and number of antenatal visits were not significant with factors affecting immunization in this study (P = 0 > .05). The findings of this study are in line with the findings of Noh et al,²¹ Al-lela et al,²⁶ Abdullahi,³⁴ De Oliveira et al.³⁵ However, the findings from this study are in complete contrast to other findings from a study in rural Bangladesh which found that sex discrimination plays an important role in immunization coverage, with male children more likely to be fully immunized than their females’ counterparts and mothers having received TT injection were also found to be one of the significant predictors of full immunization coverage for children.^33,34,36 Odiit and Amuge,³⁷ Tagbo et al,³⁸ Yunusa et al³⁹ reported that delivery in a health facility is a determinant of parental compliance with routine childhood immunization.

Mothers age, marital status, location, parity, and number of children in the household were not significant (P > .05) with factors affecting immunization. This is in line with the findings of Al-lela et al²⁶ who found no significant associations between the immunization completeness group and mother’s age. At variance Basheer et al,⁵ Rahman and Obaida-Nasrin,³³ Awasthi et al,⁴⁰ Adefolalu et al⁴¹ found age to be significant. Also, Yunusa et al³⁹ opined that there was a significant association between the number of children and the completion of immunization. Also other studies found that parity is a very important determinant of immunization schedule completion.^33,40 While Munthali³⁶ reported that location was significant

Furthermore, in this study mothers’ level of education, occupation, and wealth index were significant (P < .005). This is in line with the findings of Basheer et al,⁵ Adefolalu et al,⁴¹ Konwea et al,³⁰ Antai,⁴² Noh et al,²¹ Al-lela et al,²⁶ Yunusa et al,³⁹ Bbaale,⁴³ Gidado et al,⁴⁴ Tagbo et al,³⁸ Canavan et al,⁴⁵ Feiring et al,⁴⁶ Maina et al.⁴⁷ Contrastingly, the study of Bbaale,⁴³ did not indicate any association between the higher income of parents/caregivers and the completion of immunization schedules while Ramavhoya et al⁴⁸ and Etana and Deressa,¹³ reported not significant in level of education. The difficult terrain of our study area made the work to take extra days. It also took some women time to find their child’s immunization cards which limited the study.

Conclusion

In conclusion, there was a low immunization coverage among children under 5; and among other factorsinvestigated, mothers generally agreed that immunization centers were far from their homes. Reasons for non-completion of immunization was common among mothers whose children were partially immunized. The health facility location factor was significant with mothers who were young (≤20 years), single, had secondary education, students, poor, and primiparous (P < .05) Therefore, we recommend that government and donor agencies involved in policy making should locate health facilities close to homes. Also health education on the importance of immunization should be given to mothers especially those who are young and has low socio-economic status.

Footnotes

Appendix

Appendix 1.

2019 State Population Projected From 2006.

					Pregnant Women	Population Under 1/Birth Cohort	Population Under 5	Population Under 15	6-59mths	6-11mths	12-59mths
District_Name		Total Population of the District (2018)	Growth Rate (2.8%)	Total Population of the District 2019 (2.8%)	RI		SIAs	AFP	Vita A	Vita A	Vita A	WCBA	9 -59mths (17%)
Abakaliki	20	211,333	5,917	217,251	10,863	8,690	43,450	103,411	39105	4345	34760	47795	36,933
Afikpo North	16	218,142	6,108	224,250	11,212	8,970	44,850	106,743	40365	4485	35880	49335	38,122
Afikpo South	13	218,784	6,126	224,910	11,245	8,996	44,982	107,057	40484	4498	35986	49480	38,235
Ebonyi	20	176,670	4,947	181,617	9,081	7,265	36,323	86,450	32691	3632	29059	39956	30,875
Ezza North	15	202,831	5,679	208,511	10,426	8,340	41,702	99,251	37532	4170	33362	45872	35,447
Ezza South	19	185,540	5,195	190,735	9,537	7,629	38,147	90,790	34332	3815	30518	41962	32,425
Ikwo	30	298,920	8,370	307,290	15,364	12,292	61,458	146,270	55312	6146	49166	67604	52,239
Ishielu	30	210,394	5,891	216,285	10,814	8,651	43,257	102,952	38931	4326	34606	47583	36,768
Ivo	18	168,427	4,716	173,143	8,657	6,926	34,629	82,416	31166	3463	27703	38091	29,434
Izzi	25	326,037	9,129	335,166	16,758	13,407	67,033	159,539	60330	6703	53627	73737	56,978
Ohaozara	25	207,019	5,797	212,816	10,641	8,513	42,563	101,300	38307	4256	34051	46820	36,179
Ohaukwu	40	273,476	7,657	281,134	14,057	11,245	56,227	133,820	50604	5623	44981	61849	47,793
Onicha	25	329,875	9,237	339,112	16,956	13,564	67,822	161,417	61040	6782	54258	74605	57,649
Total	296	3,027,449	84,769	3,112,218	155,611	124,489	622,444	1,481,416	560199	62244	497955	684688	529,077

Source: Ebonyi State Ministry of Health, 2019.

Acknowledgements

We acknowledge all the community heads who directed and gave consent for the research to be carried out in their regions.

Author Contributions

All the authors participated fully in overall development of the paper.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was self-sponsored.

Ethical Approval

Ethical approval was obtained from the Ethics Committee of Ebonyi State Ministry of Health Abakaliki (Reference number: EBS/MOH/ERC/V.53/039).

Informed Consent

Written informed consent was obtained from all subjects before the study.

ORCID iDs

MaryJoy Umoke

Chioma Adaora Nwalieji

References

World Health Organization. Immunization coverage. Updated 2016. http://www.who.int/

The World Bank. Nigeria improved child survival program for human capital multiphase programmatic approach for the immunization plus and malaria (P167156) January 22, 2020. Accessed February 21, 2020. https://projects.worldbank.org/en/projects-operations/project-detail/P167156

World Health Organization. Europe observes a 4 fold increase in measles cases in 2017 compared to a previous year 2018. https://www.euro.who.int/en/media-centre/sections/press-releases/2018/europe-observes-a-4-fold-increase-in-measles-cases-in-2017-compared-to-previous-year

Omale

Anukum

Otubo

Suwaiba

Assessment of immunization coverage in Jos North Local Government Area of Plateau State, Nigeria. World J Pharm Res. 2019;8:11-25. doi:10.20959/wjpr20198-15235

Basheer

Somrongthong

Viwattanakulvanid

Kumar

Factor’s influencing immunization coverage among children under 2years of age in rural local government areas in Kebbi state, Nigeria. Pak J Public Health. 2018;8:206-212. doi:10.32413/pjph.v8i4.249.

PAN Advisory Committee on Immunization (2010-2012): Esangbedo

Tagbo

Olowo

, et al. Paediatric Association of Nigeria (PAN) recommended routine immunization schedule for Nigerian children. Niger J Paed. 2012;39:152-158. doi:10.4314/njp.v39i4.1

Tagbo

Uleanya

Nwokoye

Eze

Omotowo

IB.

Mothers’ knowledge, perception and practice of childhood immunization in Enugu. Niger J Paediatr. 2012;39:90-96.

Adedire

Ajayi

Fawole

Kasasa

Wassawa

Nguku

Immunization coverage and its determinants among children aged 12-13 months in Atak Umosa-west district, Osun state Nigeria. A cross sectional study. BMC Public Health. 2016;16:905.

Centres for Disease Control and Prevention. In collaboration with National Center for Immunization and Respiratory Diseases. Immunity types. Updated 2017. https://www.cdc.gov/vaccines/vac-gen/immunity-types.htm

10.

World Health Organization. Global Measles and Rubella Strategic Plan 2012–2020. WHO; 2012. https://reliefweb.int/report/world/global-measles-and-rubella-strategic-plan-2012-2020

11.

World Health Organization. Immunization Supply Chain and Logistics. A Neglected Bust Essential System for National Immunization Program. WHO, Department of Immunization, Vaccines and Biologicals; 2014.

12.

Shetty

Chaudhuri

Sabella

Rationale for the immunization schedule: why is it the way it is?

Pediatr Rev. 2019;40:26-36. doi:10.1542/pir.2018-0033

13.

Etana

Deressa

Factors associated with complete immunization coverage in children aged 12–23 months in Ambo Woreda, Central Ethiopia. BMC Public Health. 2012;12:566.

14.

NERICC 2-National Emergency Routine Immunization Coordination Center. Training manual for the introduction of measles containing vaccine second dose (MCV2) into Routine Immunization in Nigeria 2019 with collaboration with NPHCDA. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwiKl4qb2cPuAhWVRxUIHQ1QBCIQFjAAegQIARAC&url=https%3A%2F%2Fwww.who.int%2Fimmunization%2Fpolicy%2FImmunization_routine_table2.pdf%3Fua%3D1&usg=AOvVaw0-auAuV2tu7-Jj6MSMhOnT

15.

Adokiya

Banguune

Ndago

JA.

Evaluation of immunization coverage and its associated factors among children 12 – 23 months of age in Techiman Municipality Ghana 2016. Arch Public Health. 2017;75:28. doi:10.1186/s13690-017-0196-6

16.

WHO and UNICEF. Estimates of immunization coverage: 2018 revision. WHO and UNICEF estimates of national immunization coverage. Updated 2019; 1-30. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjL4dbp2cPuAhXgTxUIHUpDBfgQFjAAegQIAhAC&url=https%3A%2F%2Fwww.who.int%2Fimmunization%2Fmonitoring_surveillance%2Froutine%2Fcoverage%2FWUENIC_notes.pdf&usg=AOvVaw1ACQG0XvdNDLAizPd66WZS

17.

World Health Organization. Immunization coverage. WHO fact sheet 2019. https://www.who.int/news-room/fact-sheets/detail/immunization-coverage

18.

Grundy

Biggs

BA.

The impact of conflict on immunisation coverage in 16 countries. Int J Health Policy Manag. 2019;8:211-221. doi:10.15171/ijhpm.2018.127

19.

World Health Organization. Principles and Considerations for Adding a Vaccine to a National Immunization Program: From Decision to Implementation and Monitoring. World Health Organization; 2014. https://apps.who.int/iris/handle/10665/111548

20.

Oku

Oyo-Ita

Glenton

, et al. Factors affecting the implementation of childhood vaccination communication strategies in Nigeria: a qualitative study. BMC Public Health. 2017;17:200. doi:10.1186/s12889-017-4020-6

21.

Noh

Kim

Akram

, et al. Factors affecting complete and timely childhood immunization coverage in Sindh, Pakistan; a secondary analysis of cross-sectional survey data. PLoS ONE. 2018;13:e0206766. doi:10.1371/journal.pone.0206766

22.

Mihigo

Okeibunor

Anya

Mkanda

Zawaira

Challenges of immunization in the African Region. Pan Afr Med J. 2017;27:12. doi:10.11604/pamj.supp.2017.27.3.12127

23.

Abonyi

Okereke

Omebe

Anugwo

Foundations of Educational Research and Statistics. Fred-Ogah Publishers; 2006.

24.

Ebonyi State Ministry of Health. 2019 Ebonyi state population projected from 2006. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjt2pqo2sPuAhXCQxUIHdICBmsQFjAAegQIARAC&url=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC6785898%2F&usg=AOvVaw2b6UVtX6pfjyL6QqknCI-u

25.

Uzoagulu

EU.

Practical Guide to Written Research Project Report in Tertiary Institutions. Cheston; 2011.

26.

Al-lela

Bahari

Baderden

Basher

Hamoodi

HK.

Factors affecting on immunization compliance: Iraq. J Pharm Pract Community Med. 2017;3:246-253. doi:10.5530/jppcm.2017.4.67

27.

Akwataghibe

Elijah

Ogunsola

, et al. Exploring factors influencing immunization utilization in nigeria—a mixed methods study. Front Public Health. 2019;7:392. doi:10.3389/fpubh.2019.00392

28.

Brown

Oluwatosin

Ogundeji

MO.

Experiences, perceptions and preferences of mothers towards childhood immunization reminder/recall in Ibadan, Nigeria: a cross sectional study. Pan Afr Med J. 2019;20:243. doi:10.11604/pamj.2015.20.243.6019

29.

Kassahun

Biks

Teferra

AS.

Level of immunization coverage and associated factors among children aged 12–23 months in Lay Armachiho District, North Gondar Zone, Northwest Ethiopia: a community based cross sectional study. BMC Res Notes. 2015;8:239. doi:10.1186/s13104-015-1192-y

30.

Konwea

David

Ogunsile

SE.

Determinants of compliance with child immunization among mothers of children under five years of age in Ekiti State, Nigeria. J Health Res. 2018;32:229-236. doi:10.1108/JHR-05-2018-024

31.

Rahji

Ndikom

CM.

Factors influencing compliance with immunization regimen among mothers in Ibadan, Nigeria. IOSR-JNHS. 2013;2:1-9.

32.

Abdulraheem

Onajole

Reasons for incomplete vaccination and factors for missed opportunities among rural Nigerian children. J Public Health Epidemiol. 2011;3:194-203.

33.

Rahman

Obaida-Nasrin

Factors affecting acceptance of complete immunization coverage of children under five years in rural Bangladesh. Salud Publica Mex. 2010;52:134-140.

34.

Abdullahi

Factors Affecting Completion of Childhood Immunization in North West Nigeria. Walden University Dissertations and Doctoral Studies; 2018. https://scholarworks.waldenu.edu/dissertations

35.

De Oliveira

MFS

Martinez

Rocha

JSY.

Factors associated with vaccination coverage in children < 5 years in Angola. Rev Saúde Pública. 2014;48:906-915. doi:10.1590/S0034-8910.2014048005284

36.

Munthali

AC.

Determinants of vaccination coverage in Malawi: evidence from the demographic and health surveys. Malawi Med J. 2007;19:79-82. doi:10.4314/mmj.v19i2.10934

37.

Odiit

Amuge

Comparison of vaccination status of children born in health units and those born at home. East Afr Med J. 2003;80:3-6.

38.

Tagbo

Eke

Omotowo

Onwuasigwe

Onyeka

Mildred

UO.

Vaccination coverage and its determinants in childrenaged 11-23 months in an urban district of Nigeria. World J Vaccines. 2014;4:175-183. doi:10.4236/wjv.2014.44020

39.

Yunusa

Irinoye

Bello

Timothy

Determinants of parental compliance with routine childhood immunization schedule in Nassarawa State, Nigeria. Int J Nur Care. 2017;1:7.

40.

Awasthi

Pandey

Singh

Kumar

Singh

TB.

Maternal determinants of immunization status of children aged 12-23 months in urban slums of Varanasi, India. Clin Epidemiol Glob Health. 2015;3:110-116. doi:10.1016/j.cegh.2014.07.004

41.

Adefolalu

Kanma-Okafo

Balogun

MR.

Maternal knowledge, attitude and compliance regarding immunization of under five children in Primary Health Care centres in Ikorodu Local Government Area, Lagos State. Clin Sci. 2019;16:7-14.

42.

Antai

Inequitable childhood immunization uptake in Nigeria: a multilevel analysis of individual and contextual determinants. BMC Infect Dis. 2009;9:181. doi:10.1186/1471-2334-9-181

43.

Bbaale

Factors influencing childhood immunization in Uganda. J Health Popul Nutr T. 2015;31:118-129. doi:10.3329/jhpn.v31i1.14756

44.

Gidado

Nguku

Biya

, et al. Determinants of routine immunization coverage in Bungudu, Zamfara State, Northern Nigeria, May 2010. Pan Afr Med J. 2014;18:9. doi:10.11694/pamj.supp.2014.18.1.4149

45.

Canavan

Sipsma

Kassie

Bradley

EH.

Correlates of complete childhood vaccination in East African countries. PLoS ONE. 2014;9:e95709. doi:10.1371/journal.pone.0095709

46.

Feiring

Laake

Molden

, et al. Do parental education and income matter? A nationwide register-based study on HPV vaccine uptake in the school-based immunization Program in Norway. BMJ Open. 2015;5:1-11. doi:10.1136/bmjopen-2014-006422

47.

Maina

Karanja

Kombich

Immunization coverage and its determinants among children aged 12–23 months in a peri-urban area of Kenya. Pan Afr Med J. 2013;14:3. doi:10.11604/pamj.2013.14.3.2181

48.

Ramavhoya

Maputle

Lebese

RT.

Knowledge of mothers with regard to immunization of children in Vhembe district, Limpopo province. Hum Ecol. 2015;51:9-15.