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  • Research article
  • Open Access
  • Open Peer Review

Demand-side determinants of timely vaccination of oral polio vaccine in social mobilization network areas of CORE Group polio project in Uttar Pradesh, India

BMC Infectious Diseases201818:222

https://doi.org/10.1186/s12879-018-3129-2

  • Received: 9 January 2017
  • Accepted: 3 May 2018
  • Published:
Open Peer Review reports

Abstract

Background

Children who receive all doses of scheduled vaccines reduce their susceptibility to vaccine-preventable diseases. In India, full immunization coverage has increased significantly. However, only a small proportion of children are immunized on time. Globally, studies on factors affecting coverage of childhood immunization have found a significant impact by demand and supply-side determinants. This paper explores the demand-side determinants of timely immunization of the third dose of oral polio vaccine (OPV3) among children aged 6–11 months in the catchment areas of CORE Group Polio Project India.

Methods

We analyzed secondary de-identified data from a household level ‘Doers and Non-doers survey’ conducted in 2015. Determinants of timely OPV3 immunization were identified by modeling the characteristics of index children and survey respondents, surveyed households, respondents’ media habits, their exposure to immunization services and perceptions towards child immunization, through a multinomial regression analysis.

Results

The eight demand-side predictors based on the background characteristics and perceptions of caregivers determined timely vaccination of OPV3. The strongest predictor of timely OPV3 immunization was found to be the fathers’ educational level. Children of uneducated or lesser educated fathers had increased odds of not receiving the OPV1 vaccination, as compared to children of more educated fathers (OR > 10). Respondents who strongly perceived other (non-health) benefits of child immunization were three times more likely to timely vaccinate their children than those who do not. Furthermore, mothers who disagreed with the positive attributes of child immunization were 25 times more likely to delay or not to take their children for OPV immunization on time.

Conclusions

This study found eight essential factors that are responsible for timely OPV3. Despite limitations in data collection and analysis, immunization programs in India could use the eight identified demand-side determinants of timeliness and tailor communication strategies accordingly. We suggest that program communication efforts be directed at male community members; such messaging should address parents’ perceptions of non-health benefits and stress the positive attributes of child immunization. Further investigation would be helpful to assess the various risk factors of under-vaccination as well as vaccinators’ understating about timely immunization.

Keywords

  • Polio
  • Timely immunization
  • CGPP
  • India

Background

Worldwide, tremendous progress has been reported in the reduction in the numbers of child deaths. Routine childhood immunization has proven to be among the most practical and most cost-effective health interventions [13]. Vaccination has contributed to saving millions of lives each year, resulted in the eradication of smallpox, reduced the global incidence of polio by 99% and lowered morbidity and mortality from diphtheria, tetanus, whooping cough, measles, Haemophilus influenza type B and meningococcal A meningitis [3]. In India, an increase has been observed in the overall coverage of childhood routine immunization (RI); at the national level, full immunization coverage has increased from 44% in 2005–06 to 62% in 2015–16 [4].

Timeliness is an essential component of child immunization that substantially reduces susceptibility to vaccine-preventable diseases (VPDs). An adequate number of on-time immunized children is the primary requirement for interrupting disease transmission. Delayed vaccination against childhood diseases, therefore, is known to result in increased rates of mortality and morbidity [5]. A study based on district level household survey (DLHS–3) data reported that a lack of timeliness vaccination of key childhood vaccines like DPT3 and MCV1 is one of the main challenges in India. This study found that only a small proportion of children aged 0–60 months in India are immunized on time: 30% of children received BCG vaccine by 4 weeks (recommended at birth); 28% received DPT1 by 8 weeks (recommended at 6 weeks); and only 12% received MCV1 by the recommended age of 9 months [6]. Another study conducted in high immunization coverage areas of South India found that delay in vaccination for more than two weeks from the due date for DPT1, DPT2, DPT3 and measles was 7.4, 41.9%, 6 4.4 and 38.8%, respectively [7].

Project administrative data and periodic external evaluations of CORE Group Polio Project (CGPP)1 from Uttar Pradesh, a northern state of India, showed a significant increase in RI coverage. The percentage of fully immunized children (received BCG, 3 DPTs, 3 OPVs and Measles) in the catchment areas of CGPP India has increased from 64% in 2010 to 78% in 2015 [8, 9]. In 2014, an analysis of administrative data of CGPP India found that only 19% of children received OPV3 at the ages of 14–20 weeks. However, OPV3 coverage among children aged 12–23 months was 86% [10, 11]. This identified gap between the crude and timely immunization with OPV3 led to the query ‘Why are children not getting immunized on time?’

Worldwide, individual studies and systematic reviews found a myriad of factors determines the coverage of child immunization [1, 5, 1225]. One systematic review of low and middle-income countries categorized the determinants of vaccination coverage into three groups: intent to vaccinate, health facility readiness, and community access [26]. Known determinants of child immunization can be broadly categorized into two categories: ‘Supply-side’ and ‘Demand-side’.

In India, childhood immunization coverage differs by states and districts [2729]. Districts’ per-capita income is a strong predictor of better vaccination outcomes for children [27]. A review of studies conducted across India found that availability and access to health/immunization services [7, 29, 30], attitudes and practices of health/immunization staff [30, 31], quality/reliability of health/immunization services [30] and supply of vaccines and logistics [31] are the main supply-side factors affecting vaccination coverage. Identified demand-side determinants are: characteristics of children (gender [29, 32, 33] and birth order [7, 29, 34]); maternal characteristics (age [34], education level [27, 28, 32, 33, 35, 36], occupation/employment status [34, 37]), place of delivery [31, 32, 38], ante-natal visits [32], mothers’ tetanus immunization status during the previous delivery [28, 31, 32], exposure to communication interventions [14]); parents’ characteristics (education level [28, 29, 31, 38]); parents’, knowledge of immunization schedule [30, 33, 36, 37, 39], their attitudes/perceptions towards immunization [30, 37, 40], fear of side effects [30, 36], conflicting priorities and beliefs [30]); characteristic of families (family type/family size [31], religion [29, 32, 38], caste [29, 32], socio-economic status of households/household wealth index [28, 29, 33]); and community level factors (place/area of residence [29, 32], community norms/customs and location/distance to immunization site/health care services [28]). In a nutshell, supply-side factors largely affect the reach of vaccination services and influence the vaccination status of children (vaccinated or not vaccinated). Drop-out in vaccination of vaccines that are given in a series (e.g. DPT, Penta, OPV, Measles) is mostly affected by demand-side factors rather than by supply-side factors [35].

An information gap and an apprehension of an adverse event following immunization (AEFI) were found to be the two main reasons (22 and 23%, respectively) for children not being fully immunized (i.e., unvaccinated or dropped-out children) [41], according to RI monitoring data2 from Uttar Pradesh in May 2014. Vaccine acceptance can be undermined by ignorance or negative attitudes of caregivers towards vaccination by indicating inadequate and inappropriate information sharing [42] and poor communication [43]. An effective communication response to address the awareness gap requires a better understanding of the target audience and key messages [4447]. However, a review of literature found insufficient information about appropriate target audience and content of messages on program communication for increasing timeliness of childhood immunization, particularly among Indian children. Responding to this information gap, along with other information needs of the project, CGPP India conducted an in-depth investigation for effectively designing its communication interventions and revamping the strategies to generate demand for routine polio immunization. Although DPT is the commonly used vaccine for assessing coverage or determinants of RI, this particular study used OPV instead. Along with RI, children under five years old in India were also vaccinated through polio vaccination campaigns (supplementary immunization activities - SIAs). OPV vaccination through RI becomes very crucial in building/maintaining population immunity against polio, as the frequency of polio SIAs is minimized to four-five activities per year.

According to the latest national immunization schedule of India, children should be vaccinated with polio vaccine at birth (within two weeks of birth, as OPV0 dose), 6 weeks (OPV1 & IPV1), 10 weeks (OPV2), 14 weeks (OPV3 & IPV2) and 16–24 months as OPV booster. Most of the previously conducted studies assessed determinants of vaccination coverage either by comparing ‘Vaccinated children vs. Unvaccinated’ or ‘Dropped-out vs. No drop-out’ [7, 14, 2325, 2729, 31, 32, 34, 35, 37, 39]. Our earlier analysis has also explored the determinants of routine immunization performance by analyzing drop-out rate of DPT3 in CGPP India areas [14]. However, the CGPP India functionaries observed that the profile of ‘Not at all vaccinated children’ differs from ‘Dropped-out children’. In this paper, we examine the influence of caregivers’ characteristics and perceptions in timeliness of OPV immunization by comparing ‘timely vaccinated children’ with ‘unimmunized and dropped-out children’. Our main hypothesis is that demand-side determinants of timely OPV3 immunization are likely to be different from determinants of routine immunization performance (measured in the form of ‘Vaccinated vs. ‘Unvaccinated’).

Methods

Study design

This paper is based on secondary analysis of de-identified data, originally collected on the principles of ‘Doers and Non-doers survey’3. The study followed a case-control type design.

Study area and description of data

Data was collected from the catchment areas of CGPP India, consisting of 44 work areas of community mobilization coordinators4 (villages/urban areas) from three districts of Uttar Pradesh. The observed level of full immunization coverage (FIC)5 among children aged 12–23 months (through RI monitoring) was the key criterion used for the selection of study districts. The three selected study districts represented the high (Saharanpur district, FIC was 68%), average (Rampur district, FIC was 54%) and low (Sambhal district, FIC was 41%) levels of FIC from among the 12 catchment districts of CGPP India [41].

Defining doers and non-doers of the study

Time-appropriate vaccination is measured either at the exact recommended age of a particular vaccine or by adding additional time after the scheduled immunization date for an individual vaccine [7, 48]. This study collected information for children age 6–11 months to collect sufficient numbers of samples among the unvaccinated, dropped-out and timely vaccinated children. ‘OPV vaccination status of children aged 6-11 months was the key indicator to determine the study respondents. The ‘Doers’ were defined as mothers of timely immunized children (children aged 6–11 months who received the third dose of OPV vaccine before reaching the age of four months). The ‘Non-doers’ were divided into two categories: mothers of children who have not received the first dose of OPV and mothers of children who received only the first or second dose of OPV (representing actual/potential dropout). These three non-overlapping subgroups of children were considered as strata.

Recruitment of study respondents

Samples were selected in two stages from each of the three independent strata. In the first stage, 10 clusters (CMC work areas) were randomly selected from each of the study districts. As data collectors did not locate the desired number of children without OPV1 immunization (non-doers), more clusters were added to result in 44 clusters. From every selected cluster (CMC area), investigators listed children aged 6–11 months and recorded each child’s vaccination history. The survey respondents were exclusively selected on the basis of recorded OPV vaccination status in the immunization (RI) cards6 to avoid possible misclassification bias (respondents’ limitations in the recall of vaccination dates/age at vaccination) in the selection of ‘Doers’ and ‘Non-doers’. Children who did not have any type of RI cards were excluded from the study.

A total of 611 children were randomly selected from three sampling frames, comprising 266 children who received timely immunization of OPV3 (Doers), 72 children without OPV1 immunization (Non-doers – type A) and 273 who received OPV1 or OPV2 (Non-doers - type B). Mothers of these children were contacted and requested to participate in the study. Out of 611 prospective respondents, a total of 583 face-to-face interviews of mothers were conducted, consisting of 254 doers, 68 non-doers–type A and 261 non-doers- type B. The survey included interviews with 583 mothers representing about 50,000 mothers of children aged 6–11 months from the catchment areas of CGPP India (See Additional file 1: Table S1).

Trained investigators collected the data from May 19 to June 27, 2015. Data was collected through a pre-tested semi-structured interview instrument. The survey data included information about the following: immunization status of index children7; mothers’ awareness about RI status of index children; mothers’ perceptions of positive/negative consequences of child immunization, social norms about immunization, child’s susceptibility and severity of selected VPDs, delivery of RI services; mothers’ exposure to RI services; her information sources on child immunization and media habits, lifestyle related information; background characteristics of survey households (house type, household size, family type, ownership of domestic goods/facilities), respondent mothers (age, education, marital status, working status, religion), respondents’ spouse (age, education and working), chief wage earner in the household (age, education, occupation) and index children (age, sex and place of birth).

Data processing and statistical analysis

The survey dataset was analyzed using the statistical software, IBM SPSS, version 20. A descriptive overview of survey data is presented using frequency distribution and cross-tabulations. OPV immunization status of children aged 6–11 months is the outcome (dependent) variable of the study, which is polytomous with three categories, i.e., a) not received the first dose of OPV, b) received first or second dose of OPV and c) received three doses of OPV on time.

As the study samples were selected using a multi-stage sampling, a complex samples analysis option available in IBM SPSS 20 was used to identify determinants of OPV immunization outcomes (No OPV1, OPV1/OPV2, and OPV3) by performing exploratory analysis and multinomial logistic regression [49]. Using a ‘Complex Sample Analysis’ tool, we first used univariate logistic regression to identify determinants (our covariates) associated with the outcome variable. Odds Ratios (OR) and the corresponding 95% confidence intervals (CI) estimated the strength of association. Potential determinants included socio-demographic variables, media habits, lifestyle-related practices, exposure to immunization activities/services, interactions with health care functionaries, exposure to specific Information, Education and Communication (IEC) materials8 of CGPP and perceptions on child immunization and health.

All the explanatory variables (covariates) found significantly associated (p-value < 0.05) with the dependent variables in univariate logistic regression analysis were considered for multinomial regression analysis. All the covariates were assessed for multicollinearity before including in the multinomial regression model. The religion and gender of index children are the known risk factors for immunization coverage, but the univariate logistic regression analysis did not find a significant association of these factors with the outcome variable. Hence, the final multinomial model included all the significantly associated factors of univariate analysis, and it was adjusted for the two confounders of religion and gender of index children. While performing multinomial logistic regression analysis, all the predictors were transformed into categorical variables and results were given for no OPV1 and OPV1/OPV2 immunization with reference to timely OPV3 immunization. The performance of Model was estimated with the Nagelkerke Pseudo-R2 statistic (a measure of explained variation in the model). Cases with missing data were excluded from all the analysis.

Results

Background characteristics of three independent samples of doers and non-doers survey are presented in Additional file 1: Table S2 to Table S6. Out of 583 surveyed index children, 54% were male and 46% female. About 56% of children were born in institutions (government or private hospital). The mean age of the interviewed mothers was 26.2 years. The majority of mothers (62%) reported having no formal education. Almost all (99%) mothers stayed at home, and a large proportion (94%) of respondents reported doing no income generation work. The majority (83%) of the interviewed mothers were Muslims. The mean age of the husbands of respondents was 30.0 years. About half of the respondents’ husbands had formal education, and 21% of them had completed schooling of grade (standard) 10 and above. In contrary to study respondents, almost all (99%) of respondents’ husbands were doing income generation work, and most (91%) of them worked outside of the home. Half of the mothers stayed with joint families, and about two-thirds (64%) of the interviewed mothers stayed in Pucca houses (houses made with high-quality materials). A greater proportion of timely immunized children were from households with higher wealth quintile, whereas the children without OPV1 or with OPV1/OPV2 immunization belong to households with comparatively lower wealth quintile.

Regarding media habits of respondents, about one-third of mothers did not have exposure to print or electronic media. Television is the most common media, watched by over two-thirds of respondent mothers across the three sample groups. The newspaper is the second common media, read by around 15% of respondents and newspaper readership differs by the independent samples. Less than one-tenth of respondents reported listening to the radio, and a negligible proportion of interviewed mothers traveled to cinema halls to watch movies. The survey respondents had limited mobility from their place of residence. About two-thirds of interviewed mothers have mobile phones in their households. Less than half of the mothers can use it on their own, and a small proportion of them could even send text messages.

Over three-fourths of the mothers reported ever visiting the sites of RI or supplementary immunization activities (SIAs). The proportion of mothers who ever visited any immunization site is considerably lower among the mothers of not immunized children, compared to timely immunized children. A large proportion of interviewed mothers stated that they ever discussed the importance of childhood immunization with the local health provider, including CMCs deployed by CGPP India (See Additional file 1: Table S7).

The majority (> 80%) of mothers from all the three independent samples stated that the ‘CMC’ was an information source for childhood immunization. Compared to the mothers of unimmunized children, more mothers of timely immunized children stated that they learned about the upcoming vaccination (due immunization) through the local health care providers (other than CMCs) as well as from their family members or neighbors. More than two-thirds of respondents said they had been exposed to at least one CGPP Indian-developed IEC resource, during a visit to the immunization session site or routine communication activities of CMCs in the community. More mothers of timely immunized children had more exposure to CGPP India’s IEC material than mothers of unimmunized had children (Refer to Additional file 1: Table S8 and S9). The majority (> 85%) of interviewed mothers heard of VPDs like tuberculosis, polio, tetanus, pertussis, jaundice, diarrhea and measles, but about half had not heard of diphtheria (See Additional file 1: Table S10).

Mothers’ perceptions on the importance of childhood immunization presented in Table 1 significantly vary among the three groups of respondents (Computation details are presented in the Additional file 2). More mothers of timely immunized children perceived benefits of child immunization when compared with the other groups of respondents. The survey respondents disagreed with a statement ‘There is no particular age, week or day; we can get the child immunized at any time’. However, more mothers of children with timely immunization agree with the positive attributes of child immunization and hospital delivery (See Table 2).
Table 1

Perception of respondents on the importance of child immunization by three independent samples of the survey

Perception

Score (quintile)

Percentage of mothers of children with:

Overall

(n = 583)

p value$

No OPV1 immunization

(n = 68)

OPV1/OPV2 immunization

(n = 261)

Timely OPV3 immunization

(n = 254)

Perceived core benefits of immunization

Lower quintile

48.8

32.2

28.5

33.2

0.030*

Middle quintile

29.2

26.9

41.7

32.6

 

Upper quintile

22.0

40.9

29.8

34.2

 

Perceived no harm in immunization and have trust in government initiatives

Lower quintile

28.2

37.3

34.9

35.2

0.200

Middle quintile

42.0

35.9

29.0

34.2

 

Upper quintile

29.8

26.8

36.1

30.6

 

Perceived other (non-heath) benefits of immunization

Lower quintile

55.4

34.7

29.4

35.6

0.045*

Middle quintile

19.6

33.0

33.7

31.4

 

Upper quintile

25.0

32.3

36.9

33.0

 

Perceived that educated/ aware parents go for immunization

Lower quintile

29.2

24.6

44.1

32.3

0.041*

Middle quintile

26.5

41.5

29.1

34.9

 

Upper quintile

44.3

33.9

26.9

32.8

 

Percentages are weighted by population size, adjusted for stratification, and clustering

$p value based on chi-square test; *statistically significant at p < 0.05; ** p < 0.01; ***p < 0.001

Table 2

Agreement of respondents on attributes of child immunization and place of delivery by three independent samples of the survey

Perception

Agreement level

Percentage of mothers of children with:

Overall

(n = 583)

p value$

No OPV1 immunization

(n = 68)

OPV1/OPV2 immunization

(n = 261)

Timely OPV3 immunization

(n = 254)

Positive attributes/benefits of child immunization and it is essentials these days (in polluted environment/ contaminated eatables & water)

Strongly disagree/ Disagree

46.9

30.7

10.1

25.4

0.030*

Neither agree nor disagree

34.2

41.7

38.1

39.4

 

Strongly agree/ Agree

18.9

27.6

51.8

35.2

 

Negative attributes/ no benefit of child immunization

Strongly disagree/ Disagree

76.7

86.1

81.4

83.1

0.379

Neither agree nor disagree

17.3

10.8

15.0

13.2

 

Strongly agree/ Agree

6.0

3.1

3.6

3.7

 

Positive attributes of hospital delivery and child immunization is discussed among friends

Strongly disagree/ Disagree

30.1

11.1

11.8

14.0

0.134

Neither agree nor disagree

30.5

29.7

28.9

29.5

 

Strongly agree/ Agree

39.4

59.2

59.3

56.5

 

Child immunization is meant for educated/moving/progressive families

Strongly disagree/ Disagree

27.4

27.3

33.7

29.7

0.446

Neither agree nor disagree

43.8

30.7

30.3

32.4

 

Strongly agree/ Agree

28.8

41.9

36.0

37.9

 

Gender selective immunization

Strongly disagree/ Disagree

89.8

92.9

93.8

92.8

0.016*

Neither agree nor disagree

6.9

5.9

1.6

4.5

 

Strongly agree/ Agree

3.4

1.2

4.6

2.7

 

Percentages are weighted by population size, adjusted for stratification, and clustering

$p value based on chi-square test; *statistically significant at p < 0.05; ** p < 0.01; ***p < 0.001

Responding to the specific question that was enquired only to the non-doer mothers, ‘child was sick’ is the main reason stated by 42% of respondents. About one-fifth (21%) of mothers stated that the child was out of home/village. About 15% of respondents perceived adverse effects of vaccination, and about 8 % of respondents were unaware of the significance. Very minimal proportion (< 2%) of mothers stated the reasons related to the availability and quality of vaccination services (See Additional file 1: Table S11).

Determinants of OPV immunization

Results of univariable logistics regression analysis found that timely OPV3 immunization is significantly associated with multiple factors like background characteristics of mothers and fathers, wealth index of households and perception of respondents. Table 3 shows the results of the multinomial logistic regression analysis of determinants of timely OPV3 immunization. The main effects model explaining 48% of the variance (Nagelkerke R2 = 0.481) identified eight predictors of timely immunization: income generation status of mothers, education of fathers, wealth status of households, newspaper reading habit of mothers, having a mobile phone in the household, mothers’ visit to immunization site, mothers’ agreement with benefits of child immunization and perception that ‘child immunization is essential these days’.
Table 3

Predictors of timely OPV3 immunization after multinomial logistic regression

Factors

No OPV1 vs. OPV3®

OPV1/OPV2 vs. OPV3®

Unadjusted

OR (95% CI)

Adjusted$

OR (95% CI)

Unadjusted

OR (95% CI)

Adjusted$

OR (95% CI)

Maternal age (in years)[a]

 < 20 years

6.80 (1.46, 31.72)*

2.23 (0.17, 28.79)

1.37 (0.32, 5.85)

1.12 (0.29, 4.38)

 20–24 years

1.10 (0.37, 3.24)

0.45 (0.10, 2.09)

0.82 (0.43, 1.58)

0.76 (0.34, 1.70)

 25–29 years

1.26 (0.41, 3.90)

0.58 (0.15, 2.20)

0.97 (0.44, 2.15)

1.04 (0.43, 2.49)

 30–34 years

2.62 (0.98, 7.00)

1.04 (0.26, 4.09)

1.03 (0.56, 1.87)

0.83 (0.41, 1.70)

 > 34 years

1

1

1

1

Education level of mothers (respondents)

 No formal education

3.83 (1.39, 10.59)*

0.51 (0.13, 1.94)

3.04 (1.37, 6.76)*

1.93 (0.78, 4.77)

 Grade (Standard) 1–4

4.93 (1.15, 21.25)*

0.88 (0.15, 4.98)

2.26 (0.49, 10.33)

1.89 (0.44, 8.21)

 Grade (Standard) 5–9

1.68 (0.68, 4.19)

0.71 (0.15, 3.32)

1.61 (0.62, 4.19)

2.00 (0.64, 4.24)

 Grade (Standard) 10 and above

1

1

1

1

Place of income generation of mothers

 Income generation work from home

0.19 (0.06, 0.56)*

0.12 (0.03, 0.57)*

0.33 (0.16, 0.68)**

0.35 (0.12, 0.99)*

 Income generation work from outside home

1.00 (0.29, 3.45)

1.72 (0.31, 9.62)

0.83 (0.32, 2.16)

1.77 (0.47, 6.63)

 No income generation work (stay at home)

1

1

1

1

Education level of fathers

 No formal education

21.04 (5.77, 76.73)**

39.63 (7.26, 216.19)**

2.02 (1.09, 3.76)*

0.80 (0.41, 1.59)

 Grade (Standard) 1–4

7.05 (2.30, 21.62)**

10.04 (2.04, 49.35)*

0.83 (0.46, 1.50)

0.31 (0.16, 0.60)**

 Grade (Standard) 5–9

9.50 (2.36, 38.21)**

17.40 (2.48, 122.03)*

1.13 (0.50, 2.57)

0.65 (0.36, 1.17)

 Grade (Standard) 10 and above

1

1

1

1

Wealth quintile of households

 Lowest

4.65 (1.33, 16.28)*

5.07 (0.89, 28.83)

3.40 (1.13, 10.28)*

1.96 (0.49, 7.80)

 Second

5.30 (1.89, 14.89)**

3.86 (0.78, 19.00)

2.90 (1.10, 7.66)*

1.56 (0.43, 5.66)

 Middle

2.94 (1.15, 7.48)*

2.52 (0.56, 11.29)

1.34 (0.59, 3.03)

1.06 (0.35, 3.22)

 Fourth

4.27 (1.53, 11.94)*

4.69 (1.35, 16.30)*

2.25 (0.82, 6.22)

2.33 (0.83, 6.57)

 Highest

1

1

1

1

Respondents habit of reading news paper

 Do not read

1.57 (0.47, 5.22)

0.30 (0.12, 0.75)*

3.55 (1.50, 8.45)*

2.75 (1.36, 5.58)*

 Read

1

1

1

1

Respondents having a family member, who works in a big metro town (like Delhi)

 No

0.46 (0.23, 0.94)*

0.27 (0.06, 1.18)

1.30 (0.61, 2.81)

1.00 (0.38, 2.65)

 Yes

1

1

1

1

Respondents having a mobile phone in the household

 No

1.88 (1.33, 2.66)**

3.35 (1.36, 8.24)*

1.97 (1.35, 2.87)**

1.71 (0.86, 3.41)

 Yes

1

1

1

1

Respondents know how to use a mobile phone, use it independently

 No

2.49 (1.36, 4.59)*

0.67 (0.31, 1.44)

2.13 (1.18, 3.85)*

1.06 (0.72, 1.58)

 Yes

1

1

1

1

Respondents know how to use mobile for sending messages (SMS)

 No

3.27 (1.03, 10.37)*

1.43 (0.24, 8.36)

4.94 (1.80, 13.51)**

1.65 (0.61, 4.45)

 Yes

1

1

1

1

Respondents visited any immunization site (either RI site or polio booth)

 Never visited

8.57 (2.95, 24.87)**

11.30 (3.72, 34.30)**

1.65 (0.69, 3.94)

2.13 (0.90, 5.06)

 Ever visited

1

1

1

1

Respondents’ discussion with local health care providers on the importance of child immunization

 Never discussed

5.08 (2.40, 10.76)**

1.83 (0.45, 7.49)

1.87 (1.00, 3.48)

2.19 (0.82, 5.83)

 Ever discussed

1

1

1

1

Respondents’ information sources on child immunization (getting a child immunized): Community Mobilization Coordinators (CMC)

 No

2.42 (1.16, 5.04)*

4.45 (0.90, 21.98)

1.83 (0.92, 3.64)

3.40 (0.83, 13.99)

 Yes

1

1

1

1

Respondents’ exposure to CGPP India’s IEC materials: CMC Potli

 No

2.79 (1.35, 5.75)*

1.59 (0.39, 6.46)

2.11 (1.05, 4.25)*

1.36 (0.45, 4.13)

 Yes

1

1

1

1

Respondents’ exposure to CGPP India’s IEC materials: Flash card

 No

6.04 (2.83, 12.91)**

2.35 (0.78, 7.02)

2.64 (1.36, 5.12)*

1.81 (0.74, 4.43)

 Yes

1

1

1

1

Respondents’ exposure to CGPP India’s IEC materials: Flipbook (Aao Jane)

 No

3.48 (1.99, 6.08)**

1.28 (0.43, 3.79)

2.11 (1.24, 3.61)*

1.00 (0.53, 1.86)

 Yes

1

1

1

1

Respondents perceived core benefits of immunization

 Lower quintile

2.32 (0.74, 7.27)

1.68 (0.58, 4.85)

0.83 (0.30, 2.24)

0.70 (0.29, 1.69)

 Middle quintile

0.95 (0.48, 1.88)

1.29 (0.46, 3.63)

0.47 (0.26, 0.85)*

0.59 (0.30, 1.15)

 Upper quintile

1

1

1

1

Respondents perceived no harm in immunization and have trust in government initiatives

 Lower quintile

0.98 (0.44, 2.20)

0.36 (0.07, 1.83)

1.44 (0.60, 3.48)

0.59 (0.13, 2.59)

 Middle quintile

1.76 (1.08, 2.88)*

0.31 (1.03)

1.67 (1.15, 2.42)*

0.93 (0.57, 1.53)

 Upper quintile

1

1

1

1

Respondents perceived other (non-health) benefits of immunization

 Lower quintile

2.78 (1.74, 4.42)**

3.00 (1.27, 7.12)*

1.35 (0.89, 2.04)

1.53 (0.80, 2.95)

 Middle quintile

0.85 (0.34, 2.17)

0.99 (0.38, 2.59)

1.12 (0.51, 2.46)

1.06 (0.61, 1.86)

 Upper quintile

1

1

1

1

Respondents’ agreement level with - Positive attributes/benefits of child immunization and it is essentials these days

 Strongly disagree/ Disagree

12.66 (1.46, 109.93)*

25.68 (1.10, 599.24)*

5.70 (0.71, 45.80)

9.17 (0.49, 171.82)

 Neither agree nor disagree

2.46 (0.84, 7.19)

2.55 (0.66, 9.80)

2.06 (0.74, 5.76)

2.17 (0.71, 10.34)

 Strongly agree/ Agree

1

1

1

1

Respondents’ agreement level with – Gender selective immunization

 Strongly disagree/ Disagree

1.31 (0.32, 5.38)

3.94 (0.26, 59.61)

3.78 (1.23, 11.64)*

2.24 (0.61, 8.19)

 Neither agree nor disagree

5.75 (0.46, 72.12)

8.34 (0.46, 152.97)

13.71 (1.57, 119.63)*

6.38 (0.58, 70.00)

 Strongly agree/ Agree

1

1

1

1

n = 575; Model explaining 48% of variance (Nagelkerke = 0.481)

®Reference category: OPV3 (timely immunization of OPV3); * statistically significant at p < 0.05; ** p < 0.01; ***p < 0.001; Missing data: [a] = 1 (0.2%)

$Adjusted for gender of index children, religion of mothers and other covariates of model

Fathers’ education is the strongest predictor of timely OPV immunization. Children of uneducated or less educated fathers had increased odds of ‘No OPV1 immunization’, as compared to the children of more educated fathers. Children of mothers who never visited any immunization site are 11 times more unlikely to immunize in a timely manner for OPV3. Children of mothers who are engaged in income generation activities are more likely to be immunized on time, compared to the children of mothers without any income-generation work. Children from the lower wealth quintile are more likely not to receive OPV1. Children from households without a mobile phone are 3.35 times more likely not to receive OPV1. Children of mothers who do not read newspapers are 2.75 times more likely to delay OPV3 immunization, compared to mothers who read newspapers. Mothers who disagree with the positive attributes of child immunization and do not perceive ‘child immunization is essential these days’ are much more (25 times more) likely to delay or not take their children for OPV immunization on time; mothers who perceived other benefits (non-health) of immunization are three times more likely to timely immunize their children.

Discussion

Limitations

Data collection and analysis have several limitations. First, the data was limited to the work areas of CGPP India in selected high-risk polio areas (villages and urban wards) of study districts where specific social mobilization interventions have been executed to improve polio immunization coverage. The social mobilization interventions of CGPP might have influenced the knowledge, attitude, and perceptions of the community towards immunization. Second, the data excluded children without any record of immunization in the form of an RI card. At the time of stratification, children who received three doses of OPV after the age of 4 months were excluded as they did not fit under the original study criteria of either Doers or Non-doers. The survey followed a case-control type design, excluded specific group children, and precluded calculation of attributable risk for identified risk factors. Third, some factors like media habits of respondents, exposure to immunization site or IEC materials did not include detailed information about investigated habits or quality of exposure; media habits of respondents were investigated as the current practice of listening/watching/reading specific media. Hence, the results based on this data are to be generalized with caution, and it should be remembered that the results are solely based on the demand side factors collected only from caregivers.

Determinants of timely immunization of OPV3

This study found that time-appropriate vaccination of OPV3 is determined by following eight demand-side factors: a) Father’s education, b) Mother’s income generation status, c) Mother’s visit to immunization site, d) Mother’s newspaper reading habits, e) Mother’s perception about ‘positive attributes/essentiality of immunization’, f) Mother’s perception about non-health benefits of immunization, g) Household wealth status, and h) Households having a mobile phone. Out of these eight determinants, ‘Mother’s income generation status’ is a most reliable predictor with a smaller degree of variability. However, father’s education is the strongest predictor of timely OPV3 vaccination (OR = 39), but it is likely to have a wide range of variation (95% CI is 7, 216). Similarly, other six determinants also have more width of variation. This observed degree of a greater variability inherent in most the estimates might be a result of small size (68) among a group of samples (stratum 2- Children without OPV1 vaccination).

Gender of children and religion are the known factors affecting child immunization in India, but this study did not find an association of these factors with timely OPV3 immunization. No association was observed between gender and timely OPV3 vaccination; this could be due to the changing social norms and the interventions of CGPP’s SM Net activities in the study area. Recent NFHS-4 data from Uttar Pradesh [50] showed a marginal variation of two percentage points between the OPV3 immunization of boys and girls, whereas, OPV3 coverage varied by five percentage points between the children of Hindu (69%) and Muslim religion (64%) [50]. The majority Muslim population could explain not finding an association between religion and OPV3 immunization.

This study found that influence of maternal education on OPV3 immunization is of low significance in the presence of father’s education and other household-level characteristics like wealth status and ownership of a mobile phone. However, determining factors in timely immunization were mothers’ empowerment-related factors like income generation status, newspaper reading habit, and going out for child immunization. Mothers’ perceptions towards child immunization, particularly believing in ‘positive attributes/essentiality of immunization’ and ‘non-health benefits like ‘immunization, ensured general well-being of a child’ also determines timely vaccination of children.

The background characteristics of parents and the profile of households are key determinants of timely OPV immunization, the study found. Other determinants are more sensitive to change through the specific program efforts. Immunization programs can tailor their communication strategies and create a sense of urgency to address the issue of timeliness in child immunization. This issue needs to be conveyed to service providers, including vaccinators and shared with the community.

Although more than half of the mothers from all three strata of this study do not agree with a statement ‘There is no particular age, week or day, we can get the child immunized at any time’; program communication efforts must continue to inform the community about immunization with a greater focus on timeliness.

Children from households with lower wealth quintile or less educated parents should be the focus of personalized messaging and the communication tools and techniques should be appropriate to illiterate or less educated populations. Study findings signify the necessity of involving males, as the children of educated fathers are more likely to be immunized on time. The immunization program must attempt to reach the male members of the community and convey the significance of immunizing children on time.

Since two-thirds (67%) of households have a mobile phone and it is one of the predictors of timely OVP3 immunization, the immunization program can attempt to reach these households by sending personalized messages or reminders about the immunization. Even though only less than half (44%) of the respondent mothers can use the phone on their own and majority of them (92%) could not use the phone for sending text messages, it is observed that at least one person in most families checks for messages or missed calls daily. With the growing reach of the internet and reduced-price availability of internet services, social media usage is increasing rapidly in India [51, 52]. Hence, audio-visual messaging would be helpful to mothers and family members in understanding the importance of timely immunization.

The key message of communication should be centered on the significance of timeliness in child immunization and its benefits. Alongside the core benefits of immunization, communication materials must include the messages related to other benefits and positive attributes of immunization like ‘Immunization prevents children from a physical deformity,’ ‘Immunization ensures the general well-being of children,’ and ‘Child immunization is essential these days.’ Mothers’ exposure to immunization activities is another predictor of timeliness, and the immunization program should motivate caregivers for visiting the immunization site, along with making the community aware of the place (venue), day and timing of immunization services. Frontline health workers, including CMCs, should prioritize age-appropriate vaccination. Finally, to overcome the stated limitations of the study, one may conduct in-depth investigations and assess the role of service delivery and service providers on timeliness. Further research would be useful to estimate attributable risk for various risk factors of ‘No vaccination’ and ‘delayed vaccination’ as well as assessing frontline vaccinators’ knowledge, perceptions, and practices about timely immunization.

Conclusions

The study identified eight demand-side predictors of timely OPV3 immunization, and some of them are somewhat similar to the conventionally known predictors of routine childhood immunization, such as the socio-economic characteristics of caregivers. Key determinants are background characteristics of parents, like education and income generation status of mothers as well as the wealth status of households. Other important determinants are the caregivers’ perceptions towards the benefits or positive attributes of immunization. The immunization program needs to consider these factors when shaping communication strategies. There is also the need to create a sense of urgency among service providers and clients to address the issue of timeliness in child immunization. The immunization program must attempt to reach male members of the community and convey the significance of immunizing children on time. Every component of program communication must emphasize the need for timeliness. Along with routine monitoring of RI coverage, immunization programs should also track timeliness in the performance of child immunization. Further investigation would be useful to assess the attributable risks of various risk factors of under-immunization and vaccinators understanding about timely immunization.

Footnotes
1

The CORE Group is a USAID supported umbrella organization of nongovernmental organizations (NGOs) that collaborate on international health and development programs. In India, the CORE Group Polio Project (CGPP) works across twelve districts in the state of Uttar Pradesh (UP) and is a member of the Social Mobilization Network (SM Net) in India along with UNICEF, Rotary, the Indian Government’s and WHO/National Polio Surveillance Project (NPSP) as partners. The SM Net supports polio eradication through the following efforts: identifying high-risk areas and working with underserved communities in planning, implementing and monitoring social mobilization and other immunization activities. The primary effort of the SM Net is carried out by a three-level network of mobilizers (community, block and district level).

 
2

RI Monitoring is a concurrent evaluation of RI program. In Uttar Pradesh, India it is jointly performed by the Government of U.P, WHO, UNICEF, CORE (CGPP India) and other stakeholders.

 
3

Doers and Non-doers survey – is a quantitative tool of barrier analysis, widely recommended for designing behavior change strategies. This tool helps in identifying behavioral determinants (barriers and facilitating factors) of a particular behavior [44].

 
4

The Community Mobilization Coordinators (CMCs) are deployed in high-risk areas (HRAs) for polio. As the backbone of the SM Net, they are assigned responsibility for mobilizing about 500 households in either a rural or an urban area, and keep records of the immunization status of all children less than five years of age in those households. CMC areas are groups of communities in a block where the SM Net is deployed. See Weiss et al. (2013) for more details about the CMCs and CMC areas [14].

 
5

Full immunization coverage (FIC) measured as ‘Proportion of children aged 12-23 months vaccinated with BCG, 3 doses of OPV, 3 doses of DPT and first dose of MCV’.

 
6

RI cards – Immunization card also known as RI card or MCP card (Mother and Child Protection Card). In India, children receive RI cards from the public (government) and private health delivery system. In government health system, the pubic health care provider (e.g. Auxiliary Nurse Midwife) provides MCP cards to pregnant women at the time of antenatal registration. The MCP card has a provision for recording the vaccination status and maternal health care services (including tetanus toxoid injection); whereas most of the RI cards provided by private institutions contain only immunization status. Whenever a child is vaccinated, the vaccinator records the date of immunization in the card.

 
7

Index children – were the 6-11 months old children who received OPV3 before the age of 4 months or were yet to receive the third dose (received only first or second dose of OPV). Children who received OPV3 after the age of 4 months were excluded from the study.

 
8

Information Education and Communication (IEC) materials are the tools used by communicators to support the target audience in decision making about behaviors. CGPP India provides various types of print and electronic (audio-visual) materials to CMCs.

 

Abbreviations

CGPP: 

CORE Group Polio Project

CMC: 

Community mobilization coordinator

DPT: 

Diphtheria, Pertussis and Tetanus

FIC: 

Full immunization coverage

IEC: 

Information, Education and Communication

IPV: 

Inactivated polio vaccine

MCV: 

Measles-containing vaccine

OPV: 

Oral polio vaccine (given under routine immunization program)

OPV1: 

First dose of oral polio vaccine (given under routine immunization program)

OPV2: 

Second dose of oral polio vaccine (given under routine immunization program)

OPV3: 

Third dose of oral polio vaccine (given under routine immunization program)

PCA: 

Principal Component Analysis

RI: 

Routine immunization

VPD: 

Vaccine-preventable disease

Declarations

Acknowledgments

All authors have received salary support from the US Agency for International Development (USAID) under Cooperative Agreement AID-OAA-A-12-00031. This salary support has covered implementation of the project described. The authors want to acknowledge the editorial assistance of Lydia Bologna (CORE Group Polio Project, Technical Advisor, Communications) and Kathy Vassos Stamidis (CGPP, Technical Advisor, Monitoring & Evaluation) who also receive salary support from the same USAID agreement. USAID was not involved in the following: in study design; in the collection, analysis, and interpretation of data; and in the writing of the manuscript.

Funding

Primary data of this paper was collected under USAID supported the project - Cooperative Agreement AID-OAA-A-12-00031.

Availability of data and materials

De-identified data and investigation instruments are available with the authors.

Authors’ contributions

MC wrote main sections of the Background, Methods, Results, Discussions, and Conclusions. He also designed and carried out exploratory and statistical analysis. RS wrote vital sections of the Background, Discussions and edited the manuscript. JA and RD wrote important sections of Discussions and Conclusion. All authors have read and approved the final version of the manuscript.

Ethics approval and consent to participate

This paper is based on a ‘Doers and Non-doers survey’ that was originally carried out for project management and not research. Hence, the project management team did not take approval from the ethics committee of any research/academic institute. However, this study followed the guidelines issued by National Committee for Ethics in Social Science Research in Health (NCESSRH) and ethical behavior guidelines developed by Coral Research Services. Verbal consent was obtained from the child’s caretaker before administrating the survey instruments. The authors of this paper later conducted secondary data analysis of de-identified survey data and did not have access to personal identifiers of the survey respondents or have any further contact with survey respondents for the secondary data analysis.

Competing interests

All authors have received salary support from the US Agency for International Development (USAID) under Cooperative Agreement AID-OAA-A-12-00031. This salary support has covered implementation of the project described.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
CORE Group Polio Project – India, 303, Bestech Chambers, B-Block, Sushant Lok-I, Gurgaon, Haryana, 122002, India

References

  1. Merten S, Hilber AM, Biaggi C, Secula F, Bosch-Capblanch X, Namgyal P, et al. Gender determinants of vaccination status in children: evidence from a meta-ethnographic systematic review. PLoS One [Internet]. 2015 [cited 2017 Jun 6];10:e0135222. Available from: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0135222&type=printable
  2. UNICEF. The state of the World’s children 2016 [internet]. Unicef. New York: United Nations Children’s Fund (UNICEF); 2016s. Available from: http://www.unicef.org/sowc2016/index_91471.html
  3. WHO. Global vaccine action plan 2011–2020 [internet]: World Health Organization (WHO); 2013. Available from: http://www.who.int/immunization/global_vaccine_action_plan/GVAP_doc_2011_2020/en/
  4. International Institute for Population Sciences (IIPS). National Family Health Survey (NFHS-4), 2015–16: India fact sheet [internet]. Mumbai; 2016. Available from: http://rchiips.org/NFHS/pdf/NFHS4/India.pdf
  5. Shrivastwa N. Understanding disparities in vaccination coverage among Indian children [internet] [Ph. D. Dissertation]. University of Michigan; 2015 [cited 2017 Jun 20]. Available from: https://deepblue.lib.umich.edu/bitstream/handle/2027.42/111362/nijikas_1.pdf?sequence=1&isAllowed=y
  6. Shrivastwa N, Gillespie BWW, Lepkowski JMM, Boulton MLL. Vaccination timeliness in children under India’s universal immunization program. Pediatr Infect Dis J [Internet]. 2016 [cited 2016 Aug 17];35:955–960. Available from: http://insights.ovid.com/crossref?an=00006454-201609000-00005
  7. Ramaswamy G, Pruthu T, Selvaraj K, Vinayagamurthy V, Chinnakali P. Timeliness of primary childhood vaccination in a rural area of Puducherry, South India: evidence from routine management information system. Int J Contemp Pediatr [Internet]. 2014;1:131. Available from: http://www.ijpediatrics.com/index.php/ijcp/article/view/597/517. [cited 2017 May 17].
  8. CGPP India. Midterm evaluation of CGPP India, 2010. India: CORE Group Polio Project; 2010.Google Scholar
  9. CGPP India. Midterm evaluation of CGPP India, 2015. Gurgaon; 2015.Google Scholar
  10. CGPP India. Monthly progress report - February 2014: CORE Group Polio Project; 2014.Google Scholar
  11. CGPP India. Monthly progress report - September 2014. Gurgaon: CORE Group Polio Project; 2014.Google Scholar
  12. CDC. Epidemiology of the unimmunized child: findings from the peer-reviewed published literature. Atlanta: Centers for Disease Control and Prevention (CDC); 2009.Google Scholar
  13. Sawhney M, Favin M. Epidemiology of the unimmunized child: findings from the Grey literature [internet]. Arlington: IMMUNIZATIONbasics; 2009 Oct. Available from: http://www.comminit.com/global/content/epidemiology-unimmunized-child-findings-grey-literatureGoogle Scholar
  14. Weiss WM, Choudhary M, Solomon R. Performance and determinants of routine immunization coverage within the context of intensive polio eradication activities in Uttar Pradesh, India: social mobilization network (SM net) and Core Group polio project (CGPP). BMC Int Health Hum Rights [Internet]. 2013 [cited 2018 Feb 28];13:25. Available from: http://www.biomedcentral.com/1472-698X/13/25
  15. Ataguba JE, Ojo KO, Ichoku HE. Explaining socio-economic inequalities in immunization coverage in Nigeria. Heal Policy Plan [Internet]. 2016;31. Available from: https://doi.org/10.1093/heapol/czw053
  16. Egondi T, Oyolola M, Mutua M, Elung’ata P. Determinants of immunization inequality among urban poor children: evidence from Nairobi’s informal settlements. Int J Equity Health [Internet] BioMed Central; 2015 [cited 2017 Dec 6];14:24. Available from: http://www.equityhealthj.com/content/14/1/24
  17. Russo G, Miglietta A, Pezzotti P, Biguioh RM, Mayaka GB, Sanou Sobze M, et al. Vaccine coverage and determinants of incomplete vaccination in children aged 12–23 months in Dschang, west region, Cameroon: a cross-sectional survey during a polio outbreak. BMC Public Health [Internet]. 2015 [cited 2017 Dec 6];15. Available from: https://bmcpublichealth.biomedcentral.com/track/pdf/10.1186/s12889-015-2000-2?site=http://bmcpublichealth.biomedcentral.com
  18. Hu Y, Chen E, Li Q, Chen Y, Qi X. Immunization coverage and its determinants among children born in 2008-2009 by questionnaire survey in Zhejiang, China. Asia Pacific J Public Heal [Internet]. SAGE PublicationsSage CA: Los Angeles, CA; 2015 [cited 2017 Dec 6];27:NP1132-NP1143. Available from: http://journals.sagepub.com/doi/10.1177/1010539511430995
  19. de Cantuária Tauil M, Sato APS, Waldman EA. Factors associated with incomplete or delayed vaccination across countries: a systematic review. Vaccine [Internet]. Elsevier; 2016 [cited 2017 Dec 6];34:2635–2643. Available from: http://www.sciencedirect.com/science/article/pii/S0264410X16301451
  20. Asmamaw A, Getachew T, Gelibo T, Taye G, Bekele A, Teklie H, et al. Determinants of full valid vaccine dose administration among 12-32 months children in Ethiopia: evidence from the Ethiopian 2012 national immunization coverage survey. Ethiop J Heal Dev. [Internet]. National Health Development Network--Ethiopia; 2016 [cited 2017 Dec 6];20. Available from: http://www.ejhd.org/index.php/ejhd/article/viewFile/822/624
  21. Farzad F, Reyer JA, Yamamoto E, Hamajima N. Socio-economic and demographic determinants of full immunization among children of 12–23 months in Afghanistan. Nagoya J Med Sci [Internet]. 2017 [cited 2017 Dec 6];79. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5472543/pdf/2186-3326-79-0179.pdf
  22. Khan MT, Zaheer S, Shafique K. Maternal education, empowerment, economic status and child polio vaccination uptake in Pakistan: a population based cross sectional study. BMJ Open [Internet]. British Medical Journal Publishing Group; 2017 [cited 2017 Dec 6];7:e013853. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28283489.
  23. Rainey JJ, Watkins M, Ryman TK, Sandhu P, Bo A, Banerjee K. Reasons related to non-vaccination and under-vaccination of children in low and middle income countries: findings from a systematic review of the published literature, 1999-2009. Vaccine [Internet]. 2011;29:8215–21. Available from: https://www.sciencedirect.com/science/article/pii/S0264410X11013661?via%3Dihub. [cited 2017 Dec 14].
  24. Schoeps A, Ouedraogo N, Kagone M, Sie A, Müller O, Becher H. Socio-demographic determinants of timely adherence to BCG, Penta3, measles, and complete vaccination schedule in Burkina Faso. Vaccine [Internet]. 2013;32. Available from: https://doi.org/10.1016/j.vaccine.2013.10.063
  25. de Waroux OLP, Schellenberg JRA, Manzi F, Mrisho M, Shirima K, Mshinda H. Timeliness and completeness of vaccination and risk factors for low and late vaccine uptake in young children living in rural southern Tanzania. Int Heal [Internet]. 2013;5. Available from: https://doi.org/10.1093/inthealth/iht006
  26. Phillips DE, Dieleman JL, Lim SS, Shearer J. Determinants of effective vaccine coverage in low and middle-income countries: a systematic review and interpretive synthesis. BMC Health Serv Res. [Internet]. 2017 [cited 2017 Oct 4];17:681. Available from: https://bmchealthservres.biomedcentral.com/track/pdf/10.1186/s12913-017-2626-0?site=bmchealthservres.biomedcentral.com
  27. Rammohan A, Awofeso N. District-level variations in childhood immunizations in India: the role of socio-economic factors and health infrastructure. Soc Sci Med. [Internet]. Pergamon; 2015 [cited 2017 Dec 5];145:163–172. Available from: http://www.sciencedirect.com/science/article/pii/S0277953615002774?via%3Dihub
  28. Sissoko D, Trottier H, Malvy D, Johri M. The Influence of Compositional and Contextual Factors on Non-Receipt of Basic Vaccines among Children of 12–23-Month Old in India: A Multilevel Analysis. Fernandez-Reyes D, editor. PLoS One [Internet]. Public Library of Science; 2014;9:e106528. Available from: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0106528. [cited 2017 Dec 6].
  29. Mathew JL. Inequity in childhood immunization in India: a systematic review. Indian Pediatr. [Internet]. 2012 [cited 2017 Dec 5];49. Available from: http://medind.nic.in/ibv/t12/i3/ibvt12i3p203.pdf
  30. Favin M, Steinglass R, Fields R, Banerjee K, Sawhney M. Why children are not vaccinated: a review of the grey literature. Int Health. 2012;4:229–38.View ArticlePubMedGoogle Scholar
  31. Rathi A, Meena G. Demand and supply side factors affecting utilization of immunization Services in an Urban Village of Delhi. Adv Tech Biol Med [Internet] 2017 [cited 2017 Dec 6];5. Available from: https://www.researchgate.net/profile/Akanksha_Rathi/publication/315064751_Demand_and_Supply_Side_Factors_Affecting_Utilization_of_Immunization_Services_in_an_Urban_Village_Of_Delhi/links/58caa790458515fa53c81379/Demand-and-Supply-Side-Factors-Affecting-Ut
  32. Francis MR, Nohynek H, Larson H, Balraj V, Mohan VR, Kang G, et al. Factors associated with routine childhood vaccine uptake and reasons for non-vaccination in India: 1998–2008. Vaccine [Internet]. Elsevier; 2017 [cited 2017 Dec 6]; Available from: https://www.sciencedirect.com/science/article/pii/S0264410X17310939
  33. Devasenapathy N, Jerath SG, Sharma S, Allen E, Shankar AH, Zodpey S. Determinants of childhood immunisation coverage in urban poor settlements of Delhi, India: a cross-sectional study. BMJ Open [Internet]. 2016;6. Available from: http://bmjopen.bmj.com/content/6/8/e013015. [cited 2017 Dec 6].
  34. Awasthi A, Pandey CMM, Singh U, Kumar S, Singh TBB. Maternal determinants of immunization status of children aged 12–23 months in urban slums of Varanasi, India. Clin Epidemiol Glob Heal [Internet]. Elsevier; 2015 [cited 2017 17];3:110–116. Available from: http://www.sciencedirect.com/science/article/pii/S2213398414000438
  35. Ghosh A, Laxminarayan R. Demand- and supply-side determinants of diphtheria-pertussis-tetanus nonvaccination and dropout in rural India. Vaccine [Internet]. Elsevier; 2017 [cited 2017 Dec 5];35:1087–93. Available from: https://www.sciencedirect.com/science/article/pii/S0264410X16312312
  36. Gupta P, Prakash D, Srivastava JP. Determinants of immunization coverage in Lucknow district. N Am J Med Sci [Internet]. Wolters Kluwer -- Medknow Publications; 2015 [cited 2017 Dec 5];7:36–40. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25789246
  37. Kumar S, Prabhu S, Jose AP, Bhat S, Souza OD, V. N. Assessment of under-five immunization coverage among the population of slum areas in Mangalore taluk, India. Int. J. Community Med. Public Heal. [Internet]. 2017 [cited 2017 Dec 6];4:781. Available from: http://www.ijcmph.com/index.php/ijcmph/article/view/523
  38. Singhal G, Mathur H, Dixit M, Khandelwal A. Factors affecting immunization among children of rural population of block Malpura, district Tonk, Rajasthan, India. Int J Community Med Public Heal. [Internet]. 2016;3:641–6. Available from: http://www.ijcmph.com/index.php/ijcmph/article/viewFile/769/654. [cited 2017 Dec 6].
  39. Srivastava AK, Shankar G. A study of immunization coverage and its determinants among under five children residing in urban field practice area of S. N. Medical college, Bagalkot, Karnataka, India. Indian J Forensic Community Med. [Internet]. 2017 [cited 2017 Dec 6];4:48–52. Available from: https://www.innovativepublication.com/admin/uploaded_files/IJFCM_4(1)_48-52.pdf
  40. Mukherjee S, Madhivanan P, Li T, Albatineh A, Srinivas V, Jaykrishna P, et al. Correlates of completing routine vaccination among children in Mysore, India. J Infect Public Health [Internet]. Elsevier; 2015 [cited 2017 Dec 6];8:62–71. Available from: http://www.sciencedirect.com/science/article/pii/S1876034114000768
  41. MoHFW Uttar Pradesh. Routine immunization monitoring report - may 2014: house-to-house monitoring of immunization coverage. 2014.Google Scholar
  42. Waisbord S, Larson HJ, Mueller F. Why Invest in Communication for Immunization? Evidence and Lessons Learned [Internet]. Health Communication Partnership based at Johns Hopkins Bloomberg School of Public Health/Center for Communication Programs (Baltimore) and the United Nations Children’s Fund (New York); 2005. Available from: http://www.who.int/immunization/hpv/communicate/why_invest_in_communication_for_immunization_unicef_healthcommunicationspartnership_path_usaid.pdf. [cited 2017 Dec 7].
  43. Goldstein S, MacDonald NE, Guirguis S, Eskola J, Liang X, Chaudhuri M, et al. Health communication and vaccine hesitancy. Vaccine [Internet]. 2015;33:4212–4. Available from: https://www.sciencedirect.com/science/article/pii/S0264410X1500506X. [cited 2017 Jun 6].
  44. Davis J, Thomas P. Barrier analysis Facilitator’s guide: a tool for improving behavior change communication in child survival and community development programs [internet]. Washington D.C.: Food for the Hungry; 2004 [cited 2017 Dec 3]. Available from: https://coregroup.org/wp-content/uploads/media-backup/Tools/Barrier_Analysis_2010.pdf
  45. WHO. Vaccine safety basics - learning manual [internet]. Geneva: World Health Organization (WHO); 2013 [cited 2017 Dec 7]. Available from: http://www.who.int/vaccine_safety/initiative/tech_support/Vaccine-safety-E-course-manual.pdf
  46. WHO Western Pacific Region. Vaccine safety communication guide for immunization programme managers and national regulatory authorities [internet]. Geneva; 2016. Available from: http://iris.wpro.who.int/bitstream/handle/10665.1/12621/9789290617464_eng.pdf?ua=1
  47. European Centre for Disease Prevention and Control (ECDC). Communication on immunisation – building trust [internet]. Stockholm; 2012. Available from: https://ecdc.europa.eu/sites/portal/files/media/en/publications/Publications/TER-Immunisation-and-trust.pdf
  48. Yadav K, Srivastava R, Kumar R, Chinnakal P, Rai SK, Krishnan A. Significant vaccination delay can occur even in a community with very high vaccination coverage: evidence from Ballabgarh, India. J Trop Pediatr [Internet]. 2012;58:133–138. Available from: https://www.ncbi.nlm.nih.gov/pubmed/21742766. [cited 2017 Aug 22].
  49. IBM Corporation. IBM SPSS statistics 20: IBM Corporation; 2011.Google Scholar
  50. International Institute for Population Sciences (IIPS), ICF. National Family Health Survey (NFHS-4), India, 2015–16: Uttar Pradesh [internet]. Mumbai; 2017. Available from: http://rchiips.org/NFHS/NFHS-4Reports/UttarPradesh.pdf
  51. Statista. WhatsApp: number of monthly active users in India as of February 2017 [Internet]. statista.com. 2017 [cited 2017 Dec 1]. Available from: https://www.statista.com/statistics/280914/monthly-active-whatsapp-users-in-india/
  52. Balachandran M. BharatNet: India’s plan to connect thousands of its villages to the internet is finally moving up a gear — Quartz [Internet]. Quartz India. 2017 [cited 2017 Dec 1]. Available from: https://qz.com/1127650/bharatnet-indias-plan-to-connect-thousands-of-its-villages-to-the-internet-is-finally-moving-up-a-gear/

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