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Introduction Immunization is a vital component in the drive to decrease global childhood mortality, yet challenges remain in ensuring wide coverage of immunization and full immunization, particularly in low- and middle-income countries. This study assessed immunization coverage and the determinants of immunization in a semi-rural area in The Gambia.Methods Data were drawn from the Farafenni Health and Demographic Surveillance System. Children born within the surveillance area between January 2000 and December 2010 were included. Main outcomes assessed included measles, BCG and DTP vaccination status and full immunization by 12 months of age as reported on child healthcards. Predictor variables were evaluated based on a literature review and included gender, ethnicity, area of residence, household wealth and mother’s age.Results Of the 7363 children included in the study, immunization coverage was 73% (CI 72-74) for measles, 86% (CI 86-87) for BCG, 79% (CI 78-80) for three doses of DTP and 52% (CI 51-53) for full immunization. Coverage was significantly associated with area of residence and ethnicity, with children in urban areas and of Mandinka ethnicity being least likely to be fully immunized.Conclusions Despite high levels of coverage of many individual vaccines, delivery of vaccinations later in the schedule and achieving high coverage of full immunization remain challenges, even in a country with a committed childhood immunization programme, such as The Gambia. Our data indicate areas for targeted interventions by the national Expanded Programme of Immunization. © The Author 2013.
The Government is the major provider of health care in The Gambia. Primary health care (PHC) is delivered via the PHC strategy, adopted in 1979 to ‘make healthcare more accessible and affordable to the majority of Gambians’ (Government of The Gambia 2007), with a particular focus on rural settlements with a population of more than 400. As part of the PHC strategy, these rural areas have been served by volunteer village health workers and traditional birth attendants (TBAs) since the 1980s. Maternal and Child Health (MCH) services have also been a core part of the PHC strategy as it began including outreach services. MCH services are delivered via both static and mobile health clinics with the core objectives to maintain high immunization coverage levels, decrease maternal deaths and improve child nutrition. Before 2009, a 5 Dalasi fee (about US$0.17) was charged for a child healthcard and then all subsequent care was free but now vaccinations, along with all health care for children under five, are free of charge. This study was carried out in the North Bank East Health Region of The Gambia, within the Farafenni Health and Demographic Surveillance System (FHDSS). The FHDSS was established in 1981, initially including only the rural villages surrounding Farafenni town but has since expanded and the surveillance area now comprises 42 rural villages, the town of Farafenni and the area within a 5-km radius of the town (designated the ‘peri-urban’ area). There is one static MCH clinic in the region based in Farafenni town running six MCH sessions per month. There are three mobile clinics held monthly in the surrounding villages. All villages in the region are within 3 km of a mobile clinic and women mostly walk or use donkey carts to reach there (North Bank East Health Region Public Health Officer, personal communication). The population covered by the FHDSS was ∼44 000 as of June 2007, made up of three main ethnic groups: Fula (21%), Mandinka (34%) and Wolof (38%). It is predominantly young, with an average age of 22 years and has a high level of fertility with almost half of all women being in the reproductive age bracket (15–49 years). The study area is relatively poor; most houses are constructed of mud brick and only 3% of the rural and 45% of the urban population have electricity. The study area and population under surveillance are described in more detail elsewhere (MRC 2004). Data for this study were drawn from the FHDSS. Demographic and immunization data are collected during 4-monthly rounds whereby every household is visited and details of every individual in the household updated, including new members (through birth or entry into the surveillance area). Full details of the FHDSS process and procedures are documented elsewhere (MRC 2004). For this analysis, a snapshot of the FHDSS was taken after update round 62, which occurred between 1 September 2010 and 31 December 2010. Data on the immunization status of children under 5 years of age have been collected routinely since 2005 as part of the standard FHDSS process. Data on the immunization status of children born before 2005 were entered retrospectively during a survey in 2005 which covered children aged five or under at the time. All children born after 1 January 2000 who had reached 1 year of age by the final data collection round, and for whom immunization data had been collected, were included in the analysis. In the analysis, immunization status was interpreted as ‘immunized’ for all those who had a vaccination date recorded and ‘not immunized’ for all children who had no vaccination date recorded in the FHDSS. In the majority of cases (98%), immunization data were captured from the child healthcard. If no healthcard was available (2% of children in our analysis), immunization data were based on caregiver’s recall. Socio-economic details including household head’s occupation, ownership of assets, water supply, toilet facilities, main materials of walls, roof and floor of accommodation, access to electricity and income were elicited through interviewer-administered questionnaires as part of a household survey conducted across the surveillance area between April and June 2007. For this analysis, a wealth index was created using principal components analysis (PCA), based on the ownership of the individual assets included in the household survey (radio; TV; telephone; refrigerator; iron or wooden bed; cart; bicycle; motorbike or scooter; car, truck or tractor) and publicly provided resources, such as electricity, water and toilet facilities. A similar approach in measuring wealth has been used by others (Gwatkin et al. 2000). For all analyses, the primary outcome of interest was coverage of immunization. Immunization coverage was calculated as: Coverage was calculated for the individual vaccinations listed in Figure 1 and for full immunization at 1 year (defined as receiving BCG, three doses of OPV, three doses of DTP and one dose of measles vaccine by 1 year of age). This is the definition of full immunization used in the national MICS in the Gambia and therefore was used here to enable comparison. Vaccinations selected as measures of immunization coverage. In addition, the proportions of children who received more than half of the 16 recommended vaccine doses in the national schedule, and the proportion who received all 16, were calculated to further assess programme performance. The outcome measures chosen for the analysis of possible factors influencing immunization were: Variables that might affect immunization coverage, therefore of interest in this study, were selected from a review of the relevant literature. These variables are listed in Figure 2. Predictor variables selected for regression analysis. Immunization coverage, with 95% confidence intervals, was calculated for the total population over the whole time period 2000–9 and stratified by area of residence. Multiple logistic regression analysis was carried out on the set of individuals for which observations were available for all predictor variables. Results were adjusted for year of birth to account for any variations in coverage over time. Correlation between predictor variables was also tested for. Predictor variables for inclusion in the multiple regression models were first tested individually for significance of the relationship with each outcome variable using univariable logistic regression (i.e. unadjusted analyses). Those resulting in P-value <0.25 were included in an adjusted analysis, as recommended by Hosmer and Lemeshow (2000). The variables ‘mother’s age’ and ‘sex of the child’ did not meet this significance level and were not included in the final model. The Hosmer and Lemeshow goodness-of-fit test was used to check the fit of the final model. The software package STATA 10 (StataCorp 2007) was used for all statistical analysis.
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