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PLOS ONE logoLink to PLOS ONE
. 2023 Jan 6;18(1):e0279399. doi: 10.1371/journal.pone.0279399

Spatial distribution of complete basic childhood vaccination and associated factors among children aged 12–23 months in Ethiopia. A spatial and multilevel analysis

Getanew Aschalew Tesfa 1,*, Delelegn Emwodew Yehualashet 1, Addisu Getnet 2, Kirubel Biweta Bimer 3, Binyam Tariku Seboka 1
Editor: Demisu Zenbaba Heyi4
PMCID: PMC9821487  PMID: 36608032

Abstract

Background

Complete childhood vaccination considerably aids in the reduction of morbidity and mortality from vaccine-preventable childhood diseases. Understanding the geographical disparity of complete basic childhood vaccination and Identifying associated factors is vital to designing appropriate interventions. This study aimed to assess the spatial distribution and associated factors of complete basic childhood vaccination among children aged 12–23 months in Ethiopia.

Methods

A two-stage stratified sampling technique was used based on the 2019 Ethiopian mini demographic and health survey data. A total weighted sample of 1,028 children was included in the analysis. ArcGIS version 10.8 software was used to visualize the spatial distribution of complete basic childhood vaccination. The Bernoulli-based model was used to detect significant clusters of areas using SaTScan version 9.6 software. To identify associated factors, multilevel logistic regression analyses were used, and all variables with a p-value less than 0.05 were reported as statistically significant predictors.

Results

Complete basic childhood vaccination among children aged 12–23 months had a significant variation in Ethiopia (Moran’s I = 0.276, p<0.001). The spatial scan analysis identified the most likely significant primary clusters with low complete basic childhood vaccination coverage in the Somali region’s Afder, Liben, Shabelle, and Nogobe zones; the Southern Nation Nationality and Peoples Region’s (SNNPR) Gedeo and Sidama zones; and the Oromia region’s Bale and Guji zones. The second significant cluster was found in the Afar region’s zones 1, 4, and 5, as well as the northern Somali region’s Siti zone. In the multivariable multilevel analysis, maternal age 20–24, 25–29, 35–39, and 40–44 years, delivery at a health facility, four or more antenatal care (ANC) visits, orthodox religion fellowship, maternal primary education, Muslim religion fellowship, living in the Afar, Somalia, and Oromia regions, and living in rural areas were all found to be significantly associated with complete basic childhood vaccination.

Conclusion

A geographically significant variation of complete basic childhood vaccination was observed. Maternal age, maternal education, religion, place of delivery, ANC visit, region, and residence were significantly associated with complete basic childhood vaccination. Developing immunization campaigns targeting areas that had low basic vaccination coverage and designing healthcare programs that can motivate facility-based delivery and ANC follow-up is recommended.

Introduction

Immunization is one of the most cost-effective and impactful available interventions in public health [1]. Complete vaccination of infants and children has a significant benefit in the prevention of morbidity and mortality from childhood disease [2, 3]. Currently, immunization prevents 2–3 million deaths every year from diseases such as diphtheria, pertussis, tetanus, influenza, and measles, and 86% of infants received three doses of the DPT3 (diphtheria, tetanus, pertussis) vaccine worldwide, in 2019 [4]. World Health Organization (WHO) and UNICEF (United Nations Children’s Fund) warn of a decline in vaccination during covid-19, in 2019, nearly 14 million children missed out on life-saving vaccines such as DPT3, and measles; Two-third of them are in low and middle-income countries namely: Ethiopia, Pakistan, Philippines, Nigeria, Mexico, India, Indonesia, Brazil, the Democratic Republic of the Congo, and Brazil [4].

Global immunization coverage has increased during the past decades [5]. The African region still fallen lags behind other regions of the world in access to vaccines and approximately one in five children don’t receive all the necessary and basic vaccines [6]. As a result, over half a million children die from vaccine-preventable diseases annually [7]. Basic childhood immunization coverage in Sub-Saharan African countries is low (59.4%), with disparities between countries [8]. In east Africa, complete basic childhood vaccination is low (69.21% in 2016) ranging from 39.5% in Ethiopia to 85% in Burundi, and remains a major public health issue [9].

In Ethiopia, the major health problem of the country remains preventable communicable diseases including vaccine-preventable diseases for children and nutritional disorders [10]. The Ethiopian Expanded Program on Immunization (EPI) was first launched in 1980, to reduce vaccine-preventable maternal and child morbidity and mortality [11]. An integrated effort was made by the government and the expanded program on immunization for the prevention and control of communicable diseases [10].

Childhood vaccination in Ethiopia is being given on a routine and outreach basis and the immunization schedule strictly follows the WHO recommendations for developing countries; infants should be vaccinated with one dose of BCG at birth or as soon as possible, while the three doses of pentavalent (DPT-HepB-Hib) and polio vaccines (at approximately age 6,10, and 14 weeks), and measles (MCV1) vaccine at the age of 9 months [12, 13]. The EPI in Ethiopia considers a child to have received all basic vaccinations if he/she has also received three doses of the pneumococcal conjugate vaccine (PCV) at age 6,10, and 14 weeks and two doses of the rotavirus vaccine (at age 6 and 10 weeks) [14]. According to the Ethiopian demographic and health survey (EDHS) report, there is an improvement in complete basic childhood vaccination representing one dose of BCG, three doses of pentavalent (DPT-HepB-Hib), three doses of polio, and one dose of measles vaccine among children aged 12–23 months in the country, increased from 24% in 2011, 39% in 2016, to 44% in 2019 [1416]. However, complete basic childhood vaccination status is yet very low compared with the national (at least 90% nationally with 80% in each district) and WHO (> = 90%) targets [17].

Previous studies conducted in Ethiopia focused on the prevalence and associated factors of childhood vaccination at the subnational level, with limited studies at the national level. Understanding the geographical disparity of complete basic childhood vaccination using a spatial analysis has become essential to developing focused public health interventions. Therefore, this study aimed to investigate the spatial distribution and associated factors of complete basic childhood vaccination among children aged 12–23 months in Ethiopia using national representative data. The result of this study might be helpful for policymakers and program managers in augmenting complete basic childhood vaccination coverage.

Methods and materials

Study design, setting, and data source

This study was conducted using secondary data, the Ethiopian mini demographic and health survey 2019 (EMDHS), retrieved from https://www.dhsprogram.com/data. EMDHS 2019 was a population-based cross-sectional study conducted from March 21, 2019, to June 28, 2019, using a representative sample across the country and it is the second mini-demographic and health survey [15]. Ethiopia is located in the horn of Africa (3°−14° N and 33°−48° E). Administratively, it has nine regional states (Tigray, Afar, Amhara, Oromia, Somalia, Benishangul-Gumuz, Southern Nation Nationalities, and Peoples Region (SNNPR), Gambela and Harari) and two city administrations (Addis Ababa and Dire Dawa). Each region is further subdivided into zones, districts, towns, and kebeles (the lowest unit) [18].

Sample size and sampling procedure

The sampling frame used for the EMDHS 2019 is a frame of all census enumeration areas created for the Ethiopian population and housing census (PHC) which was conducted by the central statistical agency (CSA) in 2019. During the census, each kebele was subdivided into enumeration areas (EAs). The 2019 EMDHS used a two-stage stratified cluster sampling. In the first stage, a total of 305 EAs (212 in rural areas and 93 in urban areas) were selected with probability proportional to EA size based on the 2019 PHC frame and with independent selection in each sampling stratum. A household listing operation was carried out in all of the selected EAs and served as a sampling frame for the selection of households in the second stage. In the second stage, a fixed number of 30 households per cluster were selected with an equal probability of systematic selection from the newly created household listing [15]. In this study, a total weighted sample of 1028 living children aged 12–23 months with their mothers was included.

Variables of the study

Outcome variable

Complete basic childhood vaccination status of children aged 12–23 months was the outcome variable of the study, which has a binary outcome coded as “yes” if the child received one BCG vaccine, three doses of the polio vaccine, three doses of pentavalent vaccine, and one dose of measles vaccine and “no” if the child failed to take the recommended doses of vaccine. Information on vaccination status was obtained in three ways: from written vaccination cards, the mothers’ verbal reports, and health facility records.

Independent variables

The predictor variables of the study were categorized into individual-level factors including sociodemographic variables such as maternal age (categorized as 15–19, 20–24, 25–29, 30–34, 35–39, 40–45), marital status (categorized as never married, married, and widowed/divorced/separated), sex of household head (categorized as male and female), sex of the child (categorized as male and female), maternal education (no formal education, primary, and secondary and above), wealth index (poor, middle, and rich), and Child and maternal related characteristics such as place of delivery (categorized as home delivery and health facility), mode of delivery(cesarean delivery and vaginal delivery), birth order (categorized as 1st, 2nd -5th, and > = 6), ANC visit (no ANC visit, 1–3 visit, and > = 4 visits).

Community-level factors such as residence (categorized as urban and rural), and region (categorized as Addis Ababa, Afar, Amhara, Oromia, Beneshangul, Gambela, SNNPR, Somali, Harari, Tigray, and Dire Dawa).

Data management and analysis

After we accessed the data; data extraction, cleaning, weighting, and recoding were done before any statistical analysis. Descriptive statistics were done to describe the characteristics of the study population using STATA. ArcGIS version 10.7 and Spatial Scan Statistics (SaTScan TM version 9.6) software were used to execute the spatial data analysis. To determine the presence of spatial autocorrelation, Global Moran’s Index (Moran’s I) was used. Moran’s I is a statistic that measures whether complete basic childhood vaccination patterns were clustered, dispersed, or randomly distributed in the study area by producing an output ranging from -1 to +1. Moran’s I value close to -1 indicated complete basic childhood vaccination dispersed, whereas Moran’s I +1 indicated complete basic childhood vaccination clustered, and complete basic childhood vaccination distributed randomly if Moran’s I value was zero. A statistically significant Moran’s I (P-value < 0.05) indicated the presence of spatial autocorrelation and can lead to the rejection of the null hypothesis (complete basic childhood vaccination is randomly distributed). Spatial scan analyses were applied to identify the most likely significant clusters. In the SaTScan, a Bernoulli-based model was used and the scanning window with maximum likelihood was the most likely significant cluster, a Log-likelihood ratio (LLR), and p-value were assigned to these clusters.

To rule out a substantial association between variables, a multi-collinearity test was done using the variance inflation factor (VIF). There is no multi-collinearity because all variables have VIF less than 5 and tolerance greater than 0.1. The intra-cluster correlation coefficient (ICC) was used to assess cluster variation. To identify factors associated with complete basic childhood vaccination, we used a multilevel logistic regression model to take into account the hierarchical nature of the DHS data. After fitting a bi-variable multilevel logistic regression analysis, variables with a p-value of < 0.2 in the bi-variable analysis were further considered in the multivariable multilevel logistic regression analysis. For the multilevel logistic regression, four models were constructed. The null model was the first model with no independent variables to detect the extent of the possible contextual effect; model I (a model with only individual-level factors), model II (which was adjusted for community-level factors), and model III (containing both individual and community level factors). Adjusted odds ratio (AOR) with 95% CI and p-value<0.05 in the multivariable multilevel logistic regression model were used to declare statistically significant variables associated with complete basic childhood vaccination.

Ethical issues

This study was based on secondary data analysis, and permission to download and use the data for our research was obtained from the measure DHS program. As a result, ethical approval and participant consent are not necessary for this particular study. From preliminary, the data were collected by “The DHS program” by taking informed consent from individuals. The dataset is publicly available anonymously in the DHS program’s official database.

Results

Sociodemographic and socioeconomic characteristics of the study participants

A total weighted sample of 1028 children aged 12–23 months was included in the analysis. 399 (38.8%) of the total children were between the ages of 12 and 15 months and 533 (51.8%) of them were female. The majority of the children, 359(34.9%) were born to mothers aged 25–29. Regarding region, four hundred five (39.4%), two hundred eighteen (21.2%), and one hundred ninety-nine (19.4%) were from Oromia, Amhara, and Southern Nation Nationalities and Peoples Region (SNNPR) respectively. Of the total, 715 (69.5%) lived in rural areas and 383 (37.3%) of the child’s mothers were Orthodox Christian religion followers. 431 (41.9%) were from poor household wealth status (Table 1).

Table 1. Sociodemographic and socioeconomics characteristics of the study participants.

Variables Weighted frequency Percent
Region
 Tigray 77 7.53
 Afar 15 1.46
 Amhara 218 21.19
 Oromia 405 39.41
 Somali 56 5.43
 Benishanguel 11 1.04
 SNNP 199 19.38
 Gambela 4 0.40
 Harari 3 0.25
 Addis Ababa 34 3.32
 Dire Dawa 6 0.59
Residence
 Urban 313 30.47
 Rural 715 69.53
Maternal age
 15–19 73 7.06
 20–24 237 23.03
 25–29 359 34.89
 30–34 160 15.56
 35–39 134 13.04
 40–44 53 5.16
 45–49 13 1.26
Maternal educational status
 No formal education 464 45.14
 Primary 418 40.66
 Secondary and above 146 14.20
Marital status
 Never in union 2 0.2
 married 983 95.62
 divorced/widowed/separated 43 4.18
sex of household head
 male 887 86.28
 female 141 13.72
Religion
 Orthodox 383 37.28
 Protestant 265 25.80
 Muslim 350 34.09
 Traditional and other 29 2.84
Household wealth index
 Poor 431 41.89
 Middle 179 17.37
 Rich 419 40.74
sex of child
 Male 495 48.17
 Female 533 51.83
Child age in months
 12–15 399 38.84
 16–19 334 32.45
 20–23 295 28.71

Maternal and child health-related characteristics

Among the total participants, 439 (44.0%) were born to mothers who had greater than or equal to four ANC visits, and nearly half of them, 551(53.6%) were born in the health facility. Regarding birth order, the majority of them, 598 (58.2) were in the second to fifth birth order. Concerning the mode of delivery, 70 (6.8%) were born by cesarean delivery (Table 2).

Table 2. Maternal and child health-related characteristics.

Variables Weighted frequency Weighted %
ANC visit
 No visit 251 25.22
 1–3 306 30.74
 > = 4 visits 439 44.04
Mode of delivery
 Caesarian delivery 70 6.83
 Vaginal delivery 958 93.17
Birth order
 1st 242 23.53
 2–5 598 58.17
 > = 6 188 18.31
Place of delivery
 Home 477 46.36
 Health facility 551 53.64

Basic childhood vaccination coverage

The overall complete basic childhood vaccination coverage among children aged 12–23 months in Ethiopia was 44%. The percentage of children who had all of their basic childhood vaccinations varied by area, ranging from 83% in Addis Ababa to 73% in Tigray, one-fifth (20%) in Afar, and 19% in the Somalia region. In terms of specific vaccine utilization at the national level; nearly three-fourths (72.96%) of the children received BCG, 60.9% pentavalent third dose, 59.94% polio third dose, and 58.53% measles first dose vaccine (Fig 1).

Fig 1. Prevalence of complete basic childhood vaccination and its components among children aged 12–23 months in Ethiopia, EMDHS 2019.

Fig 1

Spatial analysis result of complete basic childhood vaccination

Spatial distribution of complete basic childhood vaccination: A low proportion of complete basic childhood vaccination was observed almost in the entire Somali region, Afar, Northwest Gambella, western and eastern parts of SNNPR, some southwest parts of Amhara, and Oromia regions ranging from 0%-20%. However, high coverage of complete basic childhood vaccination was observed in Addis Ababa, central and western Tigray, northeast Amhara, some parts of SNNP, and the Oromia regions of Ethiopia (Fig 2).

Fig 2. Spatial distribution of complete basic childhood vaccination among children aged 12–23 months across regions of Ethiopia, EMDHS 2019.

Fig 2

The global spatial autocorrelation analysis based on attribute values and feature locations revealed the spatial distribution of complete basic childhood vaccination among children aged 12–23 months in Ethiopia was non-random (Global Moran’s I = 0.275696, p-value = 0.000). The result has shown that the observed Moran’s Index value (0.275696) was greater than the expected Index (-0.003509) and the p-value is <0.05, which is statistically significant. Given the Z-score of 5.330904 Indicates there is a less than 1% likelihood that this clustered pattern could be the result of random chance (Fig 3).

Fig 3. Spatial autocorrelation report of complete basic childhood vaccination among children aged 12–23 months in Ethiopia, EMDHS 2019.

Fig 3

Spatial scan statistical analysis result

The spatial scan analysis found 61 significant clusters of areas with low complete basic childhood vaccination rates, indicating that complete basic childhood immunization rates are lower inside the SaTScan window than outside the SaTScan window. Of these, 24 were primary clusters. The primary clusters were located in Somali (Afder, Liben, Shabelle, and Nogobe zones), SNNPR (Gedeo and Sidama zones), and Oromia region (Bale, and Guji zones) centered at 4.028421 N, 41.180723 E with 409.92 km radius, a relative risk (RR) of 1.65, and LLR of 23.58 at p = 0.001. The second most likely significant clusters were located in almost the entire Afar (zone 1, zone 4, and zone 5) and northern Somalia (Siti zone) regions centered at 11.558430 N, 41.440210 E) with 172.92 km radius, RR of 1.69, and LLR of 18.45 at p = 0.001.

The third most significant cluster was located in southern Afar (zone 3) and Oromia (North Shewa and west Harerge zones) region centered at 9.073631 N, 40.134473 E with 118.15 km radius, RR of 1.63, and LLR of 10.90 at p = 0.001. While, the fourth significant cluster with low complete basic childhood vaccination was detected in the northern Somalia region (Fafan zone) and eastern Oromia region (east Harerge zone) centered at 9.673818 N, 42.836549 E) with 84.49 km radius, RR of 1.57, and LLR of 9.67 at p = 0.006 and the fifth clustered located in Nuer and Kelem Welega zones centered at 8.356129 N, 33.766046 E with 70.96 km, RR of 1.67, and LLR = 8.59 at p = 0.04 (Table 3 and Fig 4).

Table 3. SaTScan analysis of complete basic childhood vaccination among children aged 12–23 months in Ethiopia.
Cluster type Significant EAs (clusters) detected Coordinates/radius Population cases RR LLR p-value
1 144, 141, 125, 143, 142, 114, 136, 138, 137, 111, 89, 113, 123, 110, 183, 117, 134, 188, 186, 172, 181 (4.028421 N, 41.180723 E)/409.92 km 95 83 1.65 23.58 0.001
2 26, 32, 31, 30, 33, 34, 126, 47, 45, 48, 49, 44, 29, 46, 50 (11.558430 N, 41.440210 E)/172.92 km 58 53 1.69 18.48
3 41, 28, 105, 88, 42, 40, 102, 106, 127, 43, 90 (9.073631 N, 40.134473 E)/118.15 km 39 35 1.63 10.9 0.001
4 128, 130, 121, 109, 107, 129, 254, 255, 249, 251, 248 (9.673818 N, 42.836549 E)/84.49 km 44 38 1.57 9.67 0.006
5 220, 218, 229, 230, 219 (8.356129 N, 33.766046 E)/70.96 km 26 24 1.67 8.59 0.04

Notes: RR = relative risk, LLR = log likelihood ratio.

Fig 4. Spatial scan analysis of complete basic childhood vaccination among children aged 12–23 months in Ethiopia.

Fig 4

Factors associated with complete basic childhood vaccination

Multivariable multilevel logistic regression analyses were fitted to identify the significant individual and community-level predictor variables associated with complete basic childhood vaccination. In the full model, which included all individual and community level variables, the age of the mother, place of delivery, ANC visits, region, religion, and place of residency were factors significantly associated with complete basic childhood vaccinations among children aged 12–23 months.

Individual-level factors

Maternal age was significantly associated with complete basic childhood vaccination. Children born to mothers who were 20–24 years old were approximately two times (AOR = 2.12, 9S%CI: 1.06–4.24) more likely to be fully vaccinated than children whose mothers were 15–19 years old. Children born from mothers who attained primary education were 1.67 times more likely (AOR = 1.67, 95% CI: 1.13–2.47) to be fully vaccinated than children whose mothers didn’t attain any formal education.

The odds of being completely vaccinated among children whose mothers were orthodox Christian and Muslim religion followers were 2.17 times (AOR = 2.17, 95%CI: 1.23–3.84) and 2.25 times (AOR = 2.25, 95%CI: 1.30–3.89) higher log-likelihood of fully vaccinated than whose mothers were protestant religion followers respectively. Children born in the health facility were 1.85 times (AOR = 1.85, 95%CI: 1.27–2.71) higher odds of being completely vaccinated than children born at home. Children born to mothers who had more than or equal to four ANC visits were approximately two times more likely to have complete basic childhood vaccination than children born to women who did not have ANC visits (AOR = 2.2, 95% CI: 1.03–4.73) (Table 4).

Table 4. Multivariable multilevel analysis of complete basic childhood vaccination among children aged 12–23 months.
Variables Null model Model I (AOR 95%CI) Model II (AOR 95%CI) Model III (AOR 95%CI)
Maternal age
 15–19 1 1
 20–24 1.84(0.94–3.62) 2.12(1.06–4.24)*
 25–29 2.46(1.27–4.75) ---- 2.78(1.42–5.47)**
 30–34 1.86(0.92–3.79) 1.78(0.86–3.68)
 35–39 3.83(1.79–8.20) 4.34(1.98–9.48)**
 40–44 3.63(1.43–9.24) 3.65(1.40–9.47)**
 45–49 1.45(0.37–5.66) 1.62(0.43–6.16)
Maternal education
 No education 1 ----- 1
 Primary 1.74(1.20–2.52) 1.67(1.13–2.47)**
 Secondary and above 1.47(0.89–2.42) 1.41(0.83–2.39)
Religion
 Protestant 1 1
 Orthodox 3.63(2.34–5.63) ---- 2.17(1.23–3.84)**
 Muslim 1.63(1.07–2.48) 2.25(1.30–3.89)**
 Traditional and other 0.81(0.27–2.43) 0.84(0.28–2.51)
Household wealth index
 Poor 1 1
 Middle 0.81(0.51–1.28) ---- 0.75(0.47–1.20)
 Rich 1.43(0.98–2.06) 1.06(0.69–1.65)
ANC visit
 No visit 1 1
 1–3 1.67(0.81–3.43) ---- 1.47(0.70–3.10)
 > = 4 2.80(1.35–5.83) 2.2(1.03–4.73)*
Mode of delivery
 Caesarian delivery 1 ---- 1
 Vaginal delivery 0.82(0.45–1.47) 0.79(0.43–1.45)
Place of delivery
 Home 1 1
 Health facility 2.23(1.56–3.20) --- 1.85(1.27–2.71)**
Region
 Addis Ababa 1 1
 Afar 0.09(0.04–0.21) 0.13(0.05–0.34)**
 Amhara 0.72(0.31–1.65) 0.95(0.38–2.36)
 Oromia ---- ---- 0.23(0.10–0.51) 0.40(0.16–0.99) *
 Somali 0.10(0.40–0.25) 0.21(0.07–0.58)**
 Benishangule 0.88(0.38–2.08) 1.03(0.41–2.60)
 SNNPR 0.33(0.14–0.74) 0.68(0.27–1.72)
 Gambela 0.26(0.11–0.62) 0.52(0.20–1.37)
 Harari 0.35(0.15–0.81) 0.43(0.17–1.06)
 Tigray 1.32(0.56–3.09) 1.56(0.61–3.98)
 Dire Dawa 0.50(0.22–1.14) 0.62(0.25–1.53)
Residence
 Urban ---- ----- 1 1
 Rural 0.31(0.22–0.45) 0.51(0.32–0.80)**
Model fitness and comparison
Variance 2.950871 1.078944 1.15517 .7395723
ICC (%) 47.3 24.7 26.0 18.4
PCV (%) Ref. 63.44 60.85 74.94
MOR 5.15 2.7 2.8 2.3
LLR -630.71424 -528.02119 -568.73318 -507.60068
Deviance 1,261.42848 1,056.04238 1,137.46636 1,015.20136

Notes:

* = p-value< = 0.05,

** = p-value< = 0.01,

1 = reference group, AOR = adjusted odds ratio, null model = without the predictors, model I = adjusted for individual factors, model II = adjusted for community-level factors, model III = adjusted for both individual level and community level factors.

Community-level factors

The odds of complete basic childhood vaccination among children living in the Afar region were 87% times (AOR = 0.13, 95%CI: 0.05–0.34), Somalia region 79% times (AOR = 0.21, 95%CI: 0.07–0.58), and Oromia region 60% times (AOR = 0.40, 95%CI: 0.16–0.99) less likely to be vaccinated compared with children living in Addis Ababa respectively. Children residing in rural areas were 49% times (AOR = 0.51, 95%CI: 0.32–0.80) less likely to be fully vaccinated than children residing in urban areas (Table 4).

Multilevel analysis (random effect analysis)

The result shows that the complete basic childhood vaccination rate was not similarly distributed across the communities. According to the ICC value, cluster/EA variability accounted for 47.3% of overall complete basic childhood vaccination variability in the null model. In the full model, 18.4% of the chances of complete basic childhood vaccination variation were detected across the communities. The MOR for complete basic childhood vaccination was 5.15 in the null model, showing that there was variation between communities. The unexplained community variation in complete basic childhood vaccination decreased to 2.3 in the final model. And still, the effect of clustering is statistically significant in the full model when all factors are included. Deviance was used to verify model comparability and fitness. The fourth model (the full model) was chosen as the final best-fitted model since it has the minimum deviation value (Table 4).

Discussion

Complete basic childhood vaccination in Ethiopia among children aged 12–23 months was low (44%). This result was in line with the study done in the Wonago district [19], and Mozambique [20]. But, lower than the study done in east Africa (69.2%) [9], and a study in northwest Ethiopia [21]. This might be due to that this study was done based on national-level data and thus a high variability of immunization services among regions is the possible reason for the observed differences [22]. Additionally, health system differences and access to information on maternal and child health might be a possible explanation [23]. Complete basic childhood vaccination among children aged 12 to 23 months varied significantly between Ethiopian regions, according to this study. It was low in Afar, Somalia, eastern SNNPR, and northeast Oromia areas. While, high complete basic childhood vaccination was found in Addis Ababa, western Tigray, central Tigray, northern Oromia, central Oromia, and western Benishanguel-Gumuz regions.

In the multivariable multilevel analysis maternal age, region, maternal education, place of delivery, ANC visits, religion, and residence were significantly associated with complete basic childhood vaccination. Mothers aged 20–24, mothers aged 25–29, mothers aged 35–39, and mothers aged 40–44 were more likely to vaccinate their children compared with mothers aged 15–19. The finding of this study was related to the study done in east Africa [9], and a study done in Afghanistan [24]. This might be due to that younger parents may have relied on the approval or decision of their older family members. in contrast, older mothers may have a sense of responsibility and accumulated knowledge about immunization services in the modern healthcare system [25].

This study showed that maternal education was a significant predictor of complete basic childhood vaccination, children born to mothers who attained education had higher odds of being fully vaccinated than children whose mothers didn’t attain any formal education. Supported by a systematic review done in 45 countries [26], a study conducted in Uganda [27], and a study done in Sekota district, northern Ethiopia [28]. This could be because when a woman’s educational standing increases, so does her ability to make decisions, as well as increasing access to health information, changing attitudes, and addressing some of the negative cultural behaviors that prevent children from receiving basic vaccines [27]. In contrast to this result, the study done in the Oromia region has shown complete basic childhood vaccination didn’t have any statistically significant association with maternal educational level [29]. The variation in the study setting and sample size could be one explanation for the discrepancy. This study was based on a nationally representative sample, whereas the prior study in the Oromia region exclusively included children from the Ambo district. Children whose mothers had ANC follow up were more likely to be completely vaccinated than those whose mothers didn’t have ANC follow up. This result was supported by the study done in sub-Saharan African countries [29], and a study done in Ethiopia [30]. Awareness created by healthcare professionals about basic immunization services when they meet mothers during follow-up could be the possible explanation for this [31].

There is a statistically significant relationship between complete basic childhood vaccination among children living in urban and rural areas. Children living in urban areas had higher odds of being fully vaccinated than children living in rural areas. Supported by a study done in Afghanistan [32], and a study done in Ghana [33]. This could be due to the difference in the accessibility of healthcare institutions between urban and rural areas, accessing health facilities at a near distance motivates mothers to get their children vaccinated but a geographically long distance to reach health facilities demotivates mothers to get their children immunized [28].

A statistically significant association between place of delivery and complete basic childhood vaccination was observed. Children born in the health facility had higher odds of being completely vaccinated than children born at home. Supported by the study done in Tanzania [34], and a study done in east Africa [9]. The possible reason might be due to children born at health facilities getting Polio 0 and BCG vaccines at birth and mothers may get further information about full childhood immunization with their appropriate schedules [35].

Our analysis revealed region was significantly associated with complete basic childhood vaccination among children aged 12–23 months. Children residing in Afar, Somalia, and Oromia regions were less likely to be vaccinated compared to children living in Addis Ababa. It is supported by a previous study done in Ethiopia [36], Indonesia [37], and a study done in Afghanistan [24]. This might be due to the difference in healthcare infrastructures between regions, particularly pastoralist or nomadic communities living in Afar and Somalia regions are difficult to reach immunization services within the appropriate calendar due to their seasonal movement [38].

Conclusion

The spatial distribution of complete basic childhood vaccination among children aged 12–23 months in Ethiopia was non-random (Moran’s I = 0.275696). The spatial analysis identified that complete basic childhood vaccination has a significant spatial variation across the country. The most likely significant primary clusters were detected in Afder, Liben, Shabelle, and Nogobe zones of the Somalia region; Gedeo and Sidama zones of SNNPR; and Bale, and Guji zones of the Oromia region. The second significant clusters were observed in zone 1, zone 4, and zone 5 of the Afar region and Siti zone of the northern Somali region.

Both individual and community-level factors were significantly associated with complete basic childhood vaccination among children aged 12–23 months. Individual-level predictors such as maternal age, ANC visit, religion, and place of delivery were significantly associated with complete basic childhood vaccination. Community-level determinants such as region and place of residence were associated with complete basic childhood vaccination. Developing immunization campaigns by considering areas that had low complete basic childhood immunization coverage and designing healthcare programs that can motivate facility-based delivery, ANC follow-up, and enhancing maternal education is recommended.

Limitation

There are some limitations to this study. Since the study was cross-sectional, it doesn’t show the cause and effect relationship between basic childhood vaccination and its predictors. Variables such as media exposure and paternal education were not included in this study because data about such variables were not found in the 2019 EMDS, and maybe they are significant predictors of complete basic childhood vaccination.

Acknowledgments

The authors would like to thank the MEASURE DHS program for providing the data for further analysis.

Abbreviations

ANC

Antenatal care

AOR

Adjusted odds ratio

BCG

Bacillus Calmette Guerin

CI

Confidence interval

CSA

Central statistical agency

DHS

Demographic and health survey

DPT

Diphtheria, Tetanus, and Pertussis

EA

Enumeration area

EDHS

Ethiopian demographic and health survey

EMDHS

Ethiopian mini demographic and health survey

EPI

Expanded Program on Immunization

LLR

Log-likelihood Ratio

OR

Odds Ratio

RR

relative risk

WHO

World Health Organization

Data Availability

Data is available online from https://www.dhsprogram.com/data. A letter of permission for the use of the data was secured from DHS program. We used 2019 EMDHS dataset. The data is publicly available and anyone can access it through reasonable request. The sole requirements for accessing the Demographic and Health Survey (DHS) program datasets are registration and a justification of the request’s objective.

Funding Statement

The Authors received no specific funding for this work.

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Decision Letter 0

Ejaz Ahmad Khan

1 May 2022

PONE-D-21-18735Spatial distribution of complete basic childhood vaccination and associated factors among children aged 12-23 months in Ethiopia. a spatial and multilevel analysis.PLOS ONE

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Reviewer #1: The manuscript reports the analysis of data regarding vaccination coverage in Ethiopia. The text is clear and the analysis well performed wuth adequate methods. The main finding is the low complete basic childhood vaccination rate with large geographical variation within the country. A further analysis allowed to identify determinants of complete vaccination, such as mothers age and primary education, religionhealth facility delivery, residence in rural area, and region of residence. I suggest to edit the text and to slightly modify the abstract, specifying that some of those factors are associated with complete vaccination (i.e. mother age or religion) while other with incomplete vaccination (i.e. some specific regions).

Reviewer #2: Manuscript title: Spatial distribution of complete basic childhood vaccination and associated factors among children aged 12-23 months in Ethiopia. a spatial and multilevel analysis.

Reviewer comments:

The authors presented an intriguing public health issue in Ethiopia. I thoroughly read the manuscript and well written. However, I have some questions for the authors that I would like to see included in the revised manuscript.

1. The manuscript contains numerous typographical errors that should be addressed in the revised manuscript.

2. You conducted a four-model multilevel binary logistic regression analysis. My main concerns are:

• Have you checked the interaction between individual level factors with the level factors? For instance, interaction between religion and regions of the participants?

• If no why? and If so, what were your findings?

3. You've used a null model (a model without any variables). What was the percentage of complete basic childhood vaccination that could be explained by level 2 factors? To what extent does one's place of residence and/or region explain complete basic childhood vaccination? What exactly was the ICC? Was it significant?

4. The manner in which you write the relationship between the individual level factor age and complete vaccination is not as simple. Please keep it short and simple for the layperson to understand.

5. How can inequalities in immunization service be used to justify low coverage of complete basic childhood vaccination? Do you mean that Ethiopia's immunization coverage is low? If this is the case, could you please provide evidence and explain how immunization coverage affects complete basic childhood immunization?

**********

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Reviewer #1: Yes: Giovanni Rezza

Reviewer #2: No

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Attachment

Submitted filename: Reviewer comments.docx

PLoS One. 2023 Jan 6;18(1):e0279399. doi: 10.1371/journal.pone.0279399.r002

Author response to Decision Letter 0


20 May 2022

…. point by point response...….

Academic editor comments:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. Thank you for the comment. We tried to revise the manuscript based on PLOS ONE's style requirements.

2. Please provide additional details regarding participant consent in the Methods section. Thank you for the comment. We explained it. Refer page 7 line 171-175.

3. Please note that PLOS ONE is unable to publish previously copyrighted maps or satellite images, or images created using proprietary data. For these reasons, we cannot publish images generated by software which copyrights their output (such as Google Maps, Street View, and Earth). In order to use these images in your submission, we require explicit permission from the copyright owner to publish the figures under the CC BY 4.0 license.

At this time, please kindly clarify the following regarding Figure 2:

a) Where did the authors obtain the maps, basemaps, shapefiles, map data, etc. in Figure 2?

b) If any of the map images have been previously copyrighted, we require specific consent from the copyright holder to publish these images in PLOS ONE, under the CC BY 4.0 license.

Authors' response: Editor, thank you for the concern. Figure 2 is not copyrighted rather we have done using ArcGIS and SaTScan software based on the shapefile of Ethiopia received from Ethiopian Central Statistical Agency (CSA) and GPS data (longitude and latitude) from the measure demographic and health survey (DHS) program by explaining the objective of the study through online requesting and allowed us to access the shapefile and GPS data. Because we need to analyze the spatial distribution of complete basic childhood vaccination, we cited the shapefile's source. Therefore, the map presented in our study is not copyrighted; rather it shows the result of our spatial analysis.

c) Were any sample data used in the map in Figure 2 proprietary data (e,g,. from ArcGIS and/or SaTScan)?

Authors’ response: Thank you for the concern, editor. We used ArcGIS and SaTScan statistical software to illustrate the spatial distribution of complete basic childhood vaccination using data from the measure DHS program. After describing the objective of using the data, we obtained the data and acquired approval from the Measure DHS program. The DHS dataset is open to the public, and figures obtained as a final analysis result are not copyrighted.

4. Please review your reference list to ensure that it is complete and correct. Thank you. We tried to review it carefully.

Reviewer #1:

1. I suggest to edit the text and to slightly modify the abstract, specifying that some of those factors are associated with complete vaccination (i.e. mother age or religion) while other with incomplete vaccination (i.e. some specific regions). Thank you very much for the comments. We tried to revise it carefully.

Reviewer #2:

1. The manuscript contains numerous typographical errors that should be addressed in the revised manuscript. Thank you very much for the comment. We tried to make a substantial revision on the typography.

2. You conducted a four-model multilevel binary logistic regression analysis. My main concerns are:

• Have you checked the interaction between individual level factors with the level factors? For instance, interaction between religion and regions of the participants?

• If no why? and If so, what were your findings? Thank you for the comment. Refer page 6 line 156-159.

3. You've used a null model (a model without any variables). What was the percentage of complete basic childhood vaccination that could be explained by level 2 factors? To what extent does one's place of residence and/or region explain complete basic childhood vaccination? What exactly was the ICC? Was it significant? Thank you for your interesting comment. We included it based on your comment. Refer page 13 line 253-259 and Table 4 page 16.

4. The manner in which you write the relationship between the individual level factor age and complete vaccination is not as simple. Please keep it short and simple for the layperson to understand. Thank you for the comment. We rephrased it. Refer page 13 line 270-273.

5. How can inequalities in immunization service be used to justify low coverage of complete basic childhood vaccination? Do you mean that Ethiopia's immunization coverage is low? If this is the case, could you please provide evidence and explain how immunization coverage affects complete basic childhood immunization? Thank you for the comment. We corrected it. Refer page 17 line 306-311.

Attachment

Submitted filename: Response to Reviewers.docx

Decision Letter 1

Demisu Zenbaba Heyi

25 Oct 2022

PONE-D-21-18735R1Spatial distribution of complete basic childhood vaccination and associated factors among children aged 12-23 months in Ethiopia. a spatial and multilevel analysis.PLOS ONE

Dear Dr. Tesfa,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Demisu Zenbaba Heyi, MPH

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

Please, address previous reviewer comments properly e.g. why you not calculated the PCV(proportion of change in variance for Model I, II, II), and better to calculate the median odds ratio for all models as well?

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PLoS One. 2023 Jan 6;18(1):e0279399. doi: 10.1371/journal.pone.0279399.r004

Author response to Decision Letter 1


7 Nov 2022

General comment (Journal Requirements)

1. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references.

Response: thank you very much for your suggestion. We tried to revise our reference and change was made on the following references.

- L Arevshatiana, C.C., SK Lwangac, AO Misored, P Ndumbee, JF Sewardf, P Taylorg. An evaluation of infant immunization in Africa: is a transformation in progress? ; Available from: https://www.who.int/bulletin/volumes/85/6/06-031526/en/.: Removed and Replaced by: Lindstrand, A., et al., The World of Immunization: Achievements, Challenges, and Strategic Vision for the Next Decade. The Journal of Infectious Diseases, 2021. 224(Supplement_4): p. S452-S467.

- Organization, W.H. Immunization, Vaccines and Biologicals. Available from: https://www.who.int/immunization/documents/immunological_basis_series/en/. : removed

- Ministry of Health-Ethiopia. Expanded Program on Immunization (EPI). Available from: https://www.moh.gov.et/ejcc/am/EPI. Removed and replaced by: Belete, H., et al., Routine immunization in Ethiopia. The Ethiopian Journal of Health Development, 2015. 29.

- 14. Federal Ministry of Health, E. ETHIOPIA NATIONAL EXPANDED PROGRAMME ON IMMUNIZATION COMPREHENSIVE MULTI-YEAR PLAN 2011 - 2015. 2010; Available from: https://bidinitiative.org/wpcontent/files_mf/1405630243EthiopiaComprehensivemultiyearplanfor20112015Year2010.pdf. Removed and replaced by: Boulton, M.L., et al., Vaccination timeliness among newborns and infants in Ethiopia. PLOS ONE, 2019. 14(2): p. e0212408.

Editor comment

2. Please, address previous reviewer comments properly. Why you not calculated the PCV (proportion of change in variance for Model I, II, II), and better to calculate the median odds ratio for all models as well?

Response: Thank you for your insight. We have already addressed it. Please refer page 14, line 280-290 and Table 4, page 16.

Attachment

Submitted filename: Response to Reviewers_v2.docx

Decision Letter 2

Demisu Zenbaba Heyi

14 Nov 2022

PONE-D-21-18735R2Spatial distribution of complete basic childhood vaccination and associated factors among children aged 12-23 months in Ethiopia. a spatial and multilevel analysis.PLOS ONE Dear Dr. Tesfa,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

​The following previous reviewer comments are not addressed:

  • Have you checked the interaction between individual level factors with the level factors? For instance, interaction between religion and regions of the participants?

  • If no why? and If so, what were your findings?

  • The manner in which you write the relationship between the individual level factor age and complete vaccination is not as simple. Please keep it short and simple for the layperson to understand.

  • How can inequalities in immunization service be used to justify low coverage of complete basic childhood vaccination? Do you mean that Ethiopia's immunization coverage is low? If this is the case, could you please provide evidence and explain how immunization coverage affects complete basic childhood immunization?

Please submit your revised manuscript by Dec 29 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Demisu Zenbaba Heyi, MPH

Academic Editor

PLOS ONE

PLoS One. 2023 Jan 6;18(1):e0279399. doi: 10.1371/journal.pone.0279399.r006

Author response to Decision Letter 2


17 Nov 2022

*****************

We note that your Data Availability statement states the following: "Data is available online from https://www.dhsprogram.com/data. A letter of permission for the use of the data was secured from DHS program. We used 2019 EMDHS dataset."

Before we can proceed, please clarify if the authors had special access to the data that other researchers would not have.

If not, please also provide a direct link to the dataset.

Response: The data is publicly available and anyone can access it through reasonable request. The sole requirements for accessing the Demographic and Health Survey (DHS) program datasets are registration and a justification of the request's objective.

********************************

….point by point response...

1. Have you checked the interaction between individual level factors with the level factors? For instance, interaction between religion and regions of the participants? If no why? and If so, what were your findings?

Response: Thank you for your comment. Understanding geographical distributions of complete basic childhood vaccination and identifying associated predictors is crucial for designing effective policies and strategies that help to improve vaccination coverage. Keep in mind this, the first main specific objective of our study was to identify the spatial distribution of complete basic childhood vaccination. To attain this objective and to answer the question of where the hotspots for low vaccinations are located, spatial statistical analysis is required. So, our spatial analysis looked at only the dependent variable. Second, to identify potential predictor variables, regression analysis is required. Hence, we used multilevel multivariable logistic regression analysis. As stated above we identified predictors using regression analysis and regression models consider linear relationships (stationary relationships). Since one of the assumptions of regression models is that relationships are constant across the entire study area. Therefore, estimates generated in this model assume averages. Due to that, we didn't consider the interaction between individual-level factors with the level factors. However, we have checked the absence of multicollinearity between these independent variables using the variance inflation factor.

2. The manner in which you write the relationship between the individual level factor age and complete vaccination is not as simple. Please keep it short and simple for the layperson to understand.

Response: we revised it accordingly and corrected it as follows

“Maternal age was significantly associated with complete basic childhood vaccination. Children born to mothers who were 20-24 years old were approximately two times (AOR=2.12, 9S%CI: 1.06-4.24) more likely to be fully vaccinated than children whose mothers were 15-19 years old.” Refer page 13, line 263-266 (on the tracked version)

3. How can inequalities in immunization service be used to justify low coverage of complete basic childhood vaccination? Do you mean that Ethiopia's immunization coverage is low? If this is the case, could you please provide evidence and explain how immunization coverage affects complete basic childhood immunization?

Response: Thank you for your constructive comment. We mean that variability of immunization service access across areas might be one of the reasons for the low prevalence of complete basic childhood vaccination. Since our study was done based on the national representative data that took into account both rural and urban areas, the overall prevalence of complete basic childhood vaccination was varied compared to previous studies that were done in specific districts. Anyways, in order to minimize such type of misunderstanding, we have made some modifications in that sentence and additional explanations were added in the main document. Refer page 17, line 305-309 (on the tracked version)

Attachment

Submitted filename: Response to Reviewers_v3.docx

Decision Letter 3

Demisu Zenbaba Heyi

7 Dec 2022

Spatial distribution of complete basic childhood vaccination and associated factors among children aged 12-23 months in Ethiopia. a spatial and multilevel analysis.

PONE-D-21-18735R3

Dear Dr. Tesfa,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Demisu Zenbaba Heyi, MPH

Academic Editor

PLOS ONE

Reviewers' comments:

Acceptance letter

Demisu Zenbaba Heyi

27 Dec 2022

PONE-D-21-18735R3

Spatial distribution of complete basic childhood vaccination and associated factors among children aged 12-23 months in Ethiopia. A spatial and multilevel analysis.

Dear Dr. Tesfa:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Demisu Zenbaba Heyi

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Reviewer comments.docx

    Attachment

    Submitted filename: Response to Reviewers.docx

    Attachment

    Submitted filename: Response to Reviewers_v2.docx

    Attachment

    Submitted filename: Response to Reviewers_v3.docx

    Data Availability Statement

    Data is available online from https://www.dhsprogram.com/data. A letter of permission for the use of the data was secured from DHS program. We used 2019 EMDHS dataset. The data is publicly available and anyone can access it through reasonable request. The sole requirements for accessing the Demographic and Health Survey (DHS) program datasets are registration and a justification of the request’s objective.


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