Proportion of children aged 9–59 months reached by the 2017 measles supplementary immunization activity among the children with or without history of measles vaccination in Lilongwe district, Malawi

Hamilton Wales Kainga; Steven Ssendagire; Jacquellyn Nambi Ssanyu; Sarah Nabukeera; Noel Namuhani; Fred Wabwire Mangen

doi:10.1371/journal.pone.0243137

. 2021 Jan 11;16(1):e0243137. doi: 10.1371/journal.pone.0243137

Proportion of children aged 9–59 months reached by the 2017 measles supplementary immunization activity among the children with or without history of measles vaccination in Lilongwe district, Malawi

Hamilton Wales Kainga ^1,^*, Steven Ssendagire ¹, Jacquellyn Nambi Ssanyu ¹, Sarah Nabukeera ¹, Noel Namuhani ¹, Fred Wabwire Mangen ¹

Editor: Kavita Singh Ongechi²

PMCID: PMC7799760 PMID: 33428640

Abstract

Background

The measles Supplementary Immunization Activity (SIA) was implemented in June, 2017 to close immunity gaps by providing an additional opportunity to vaccinate children aged between 9 months and up to 14 years in Lilongwe District, Malawi. This study was conducted to determine the proportion of eligible children that were reached by the 2017 measles SIA among those children with or without history of measles vaccination, and possible reasons for non-vaccination.

Methods

A cross-sectional survey using mixed methods was conducted. Caretakers of children who were eligible for the 2017 measles SIA were sampled from 19 households from each of the 25 clusters (villages) that were randomly selected in Lilongwe District. A child was taken to have been vaccinated if the caretaker was able to explain when and where the child was vaccinated. Eight Key Informant Interviews (KIIs) were conducted with planners and health care workers who were involved in the implementation of the 2017 measles SIA. Modified Poisson regression was used to examine the association between non-vaccination and child, caretaker and household related factors. A thematic analysis of transcripts from KIIs was also conducted to explore health system factors associated with non-vaccination of eligible children in this study.

Results

A total of 476 children and their caretakers were surveyed. The median age of the children was 52.0 months. Overall, 41.2% [95% CI 36.8–45.7] of the children included in the study were not vaccinated during the SIA. Only 59.6% of children with previous measles doses received SIA dose; while 77% of those without previous measles vaccination were reached by the SIA. Low birth order, vaccination history under routine services, low level of education among caretakers, unemployment of the household head, younger household head, provision of insufficient information by health authorities about the SIA were significantly associated with non-vaccination among eligible children during the 2017 measles SIA. Qualitative findings revealed strong beliefs against vaccinations, wrong perceptions about the SIA (from caretakers’ perspectives), poor delivery of health education, logistical and human resource challenges as possible reasons for non-vaccination.

Conclusion

Many children (41%) were left unvaccinated during the SIA and several factors were found to be associated with this finding. The Lilongwe District Health Team should endeavor to optimize routine immunization program; and community mobilization should be intensified as part of SIA activities.

Background

Measles is a highly infectious and potentially fatal viral infection which continues to be a key contributor to child mortality particularly in sub-Saharan Africa and South Asia. While substantial progress has been made in recent years, measles still caused approximately 110,000 deaths globally in 2017 with most of the deaths occurring among children under the age of five years despite the availability of a safe and effective vaccine [1]. Infants and young children, especially those who are malnourished are at highest risk of dying. Immunization against measles directly contributes to the reduction of under-five child mortality, and hence the achievement of the sustainable development goal number 3 [2].

The World Health Organization (WHO) in its 2017 position recommends that countries should reach all eligible children with two doses of measles vaccine as the standard for all national immunization programmes [3]. In addition to the first routine dose of measles containing vaccine (MCV1), all countries should include a second routine dose of MCV (MCV2) in their national vaccination schedules regardless of the level of MCV1 coverage. Countries aiming at measles elimination should achieve ≥95% coverage with both doses equitably to all children in every district, and implementing high quality periodic campaign strategies referred to as SIAs [3]. SIAs are vaccination mass campaigns that are implemented in addition to routine vaccination programs with a recommended second dose opportunity to children of different ages regardless of their history of vaccination [4]. WHO also recommended that cessation of SIAs should be considered only when both MCV1 and MCV2 coverage of at least 90% had been achieved at national level for at least three consecutive years. For measles to be eliminated in at least five of the six WHO regions, including Sub-Saharan Africa by 2020 [5], countries should strengthen the routine vaccination program and address missed opportunities for measles vaccination in the routine immunization services through SIAs in order to achieve the necessary high levels of measles vaccination coverage required for population immunity [4].

Although SIAs are implemented widely, some populations that are not vaccinated through routine immunization services are often missed in such campaigns [6]. There is rich literature on why eligible children missed by routine immunization services are also left unvaccinated during mass campaigns. The systematic reviews on the impact of measles SIAs on reaching the zero-dose children that were missed by routine immunization services revealed household wealth, distance to the designated vaccination posts as reasons for non-vaccination [4]. Some studies indicate lack of information about the SIA, parents’ occupation, parents’ level of education, age, parent’s sickness, children’s sickness, religious/cultural beliefs, and parents’ belief that the disease is not serious as factors significantly associated with non-vaccination of eligible children [7, 8] Some studies have highlighted health system factors such as unavailability of vaccines, vaccinators not present at vaccination posts, and failure to health educate and mobilize communities [7–10].

In Malawi, MCV1 should be given when, or soon after, the child reaches 9 months of age. The second dose of measles containing virus (Measles 2) was introduced in Malawi in 2015 in the routine immunization program, which is given at 15 months of age [11]. All these are considered as valid doses of measles vaccine [12]. Routine immunization services are provided through static services (at health facilities) to every attending child who is eligible for measles immunization; and outreach services, which are offered at strategic community-based posts that are established at every 4–5 km away from each health facility, and in hard to reach areas. Immunization services are offered at least once in a month in all outreach posts [11] SIAs are organized periodically (usually every 3 years) to supplement the routine immunization services in an effort to interrupt the transmission and spread of diseases like measles. Despite the progress that has been made tremendously in reducing both mortality and morbidity associated with measles, Malawi has continued to report sporadic cases of the measles disease every 3 years [13]. The estimated coverage for measles vaccination across all districts in Malawi is 84%, but ranges from as low as 61% to high levels of almost 100% [14]. Measles vaccination coverage in Lilongwe District is suboptimal. According to the District Health Information System 2 (DHIS2) records, the measles vaccination coverage in the District has stagnated between 65% and 70% for the last three years. And the current measles vaccination coverage for the district as calculated from routine facility data is 67.4% [11, 15].

The last countrywide measles SIA was implemented in Malawi in June 2017. The SIA targeted all children who were aged between 9 months and up to 14 years irrespective of their vaccination status [11] In addition to the already existing outreach clinic sites, vaccination posts were created in selected churches, primary schools and football grounds in all the communities in every administrative division. Eligible children who were vaccinated were recorded in the health register. However, the vaccine was not being documented in the child’s vaccination card, nor the child being given any document as an evidence of vaccination. The vaccination coverage attained following this SIA was not known because a post vaccination coverage survey was not conducted. Despite the successful implementation of the measles SIA in Lilongwe district in June 2017, there is little evidence to suggest that the measles SIA contributed to raising measles vaccination coverage because the coverage is still below 80%, and sporadic cases of measles still continue to be reported in the district. Therefore, this study was conducted to determine the proportion of eligible children that were reached by the 2017 measles SIA among those children with or without history of measles vaccination and possible reasons for non-vaccination.

Materials and methods

Study setting

The study was conducted in Lilongwe District. Lilongwe is the capital city of Malawi with an estimated population of 1,077,116. [16]. The city is located in the central region of Malawi, near the borders with Mozambique and Zambia, and it is an important economic and transportation hub for central Malawi. It was named after Lilongwe River. Administratively, there are 22 constituencies, and over 500 neighborhoods or villages. Malawi people are of Bantu origin, and Lilongwe comprises mainly the Chewa ethnic group whose main occupation is farming and trade.

In the Malawi health system, health services are predominantly delivered by the public sector (free at the point of use), Christian Health Association of Malawi (CHAM–which is an umbrella body of Christian faith-based health facilities operating on a not-for-profit basis); the private health sector (which charges user fees); and the Non-Governmental Organization (NGO) sector [12]. Public and CHAM health facilities constitute the two largest providers, collectively providing about 90% of health services in urban and rural areas [17]. Lilongwe City is served by 47 public health facilities, of which 11 belong to church missionaries and 36 owned by the government. There is a district hospital, and a central hospital which serves as a specialized facility for the central region of Malawi. In addition, there are over 100 private health facilities [15].However, accessing health care in all levels of the health system still remains a challenge for marginalized children living in the rural areas, urban slums and outskirts of the city [10].

Target population

The study targeted children who were aged 9–59 months during the implementation of the June 2017 measles SIA in Lilongwe District, Malawi. These children were 31–81 months of age in April, 2019 when the survey was conducted. The primary sampling units were households. The study respondents were caretakers or mothers (of at least 15 years of age) of children who were eligible for 2017 measles SIA.

Study design

A cross sectional survey using mixed methods was conducted. Quantitative data were collected from caretakers through a household survey. Key informant interviews (KIIs) with health care workers were used to obtain qualitative data.

Sampling procedure

A two stage sampling technique was employed for the selection of participants for the household survey. Administratively, there are 528 villages in Lilongwe district. These villages represented clusters; therefore, 25 villages (clusters) were randomly selected using probability proportionate to size (PPS). In each selected village, 19 eligible households were selected. Because the total number of households in all the villages was unknown, it was difficult to select the households randomly. The center of the village, or any feature such as a church or market, was located using a local guide. The first eligible household in the village was purposively selected. Then every nearest eligible household was systematically visited.

In each household, a primary caretaker was identified who was interviewed using the interviewer administered electronic questionnaire to obtain information on social demographics of the child, the caretaker, and the entire household. Information was sought from one eligible child in household. If there were more than one eligible child in a household, information was sought from only one child who was randomly selected in that particular household. We relied on maternal recall of measles vaccination status of a child because the measles SIA vaccine was not documented in the child’s vaccination card. A child was taken to have been vaccinated if the caretaker was able to explain when and where the child was vaccinated.

The minimum sample size for this study was determined according to Kish Lesley’s formula [18] with the following assumptions: the percentage point for α error = 5%, precision δ taken as 5% and we estimated that 16.9% of eligible children would be unvaccinated during the mass vaccination campaign according to [4].

We planned to conduct twelve KIIs with health care workers who were involved in the planning and implementation of the vaccination campaign. However, only eight KIIs were conducted because the saturation point was attained by the seventh interview.

Eligibility criteria

Caretaker-child pairs were eligible for study inclusion if they were from households with a child who was aged 9 months to 59 months during the June 2017 measles SIA, and have given consent to participate in the study.

Research team

The research team comprised the principal investigator (PI) and eight research assistants. The assistants had a minimum of post-secondary school education with experience in data collection. They were not related to the study participants, nor to the principal investigator. They were trained for two days before the start of data collection exercise so that they became familiar with the statement of the problem, objectives of the study, sampling procedure, data collection tools and plan for data collection and interview techniques. The PI was responsible for collection of qualitative data by facilitating and conducting KIIs.

Data collection and measurements

Both qualitative and quantitative data were collected simultaneously. Child’s history of vaccination was determined according to the child’s vaccination card and/or caregiver self-reports of prior vaccination. Specifically, for routine vaccination, the interviewer asked to see the child’s vaccination card if it was available and noted the date of vaccination recorded on the card. If the card was not available, interviewers would ask the caretaker/guardian if the child had ever received measles vaccine at the age of 9 months or older, and the number of measles vaccine doses a child received at a health facility. In addition, caretakers were asked whether their children participated in the 2017 measles SIA (with possible answers being “yes” or “no”). Since the SIA vaccine was not being documented in the child’s vaccination card, nor the child being given any evidence of vaccination, a child was taken to have been vaccinated during the measles SIA if the caretaker was able to explain when and where the child was vaccinated in that community. The WHO and some authors argue that recall by vaccination card is considered the best practice for determining vaccination coverage in a household survey and is preferable over self-reported recall [19]. However, some previous studies also concluded that maternal self-reports are trustworthy and are as good as vaccination cards [20, 21]. In addition, data on socio-demographics of the mother and child were collected using an electronic interviewer administered questionnaire.

We planned to conduct twelve KIIs with health care workers from public health facilities who were involved in the planning and implementation of the vaccination campaign. These were environmental health officers (health sub district supervisors) who were responsible for planning, and nurses who were responsible for the implementation. However, only eight KIIS were conducted because the data saturation point was reached after the seventh and eighth interviews. These were purposively selected from three health sub-districts, namely, Bwaila, Nanthenje and Mitundu. A semi structured KII guide was used for each respondent. A priori themes included in the KII guide were about the reasons for non-vaccination of eligible children emanating from health information system, human resources, financing and logistical challenges. Two KIIs were conducted with SIA planners (Environmental Health Officers) and six with the nurses who were involved in the SIA implementation. We used audio recording to collect the data. Field notes were made during and after the interview. Each interview lasted between 15 and 20 minutes, and were all in English. All the KIIs were carried out by the principal investigator who did not have any relationship or prior knowledge with the key informants. The outcome variable in this study was measles vaccination during 2017 measles SIA to an eligible child who had no contraindication to vaccination. This was a binary outcome (‘yes’ or ‘no’, with ‘no’ representing non-vaccination).

Pre-testing and field editing of data

The data collection tools were pre-tested in five households that were not part of the sample. Thereafter the tools were adjusted for content validity before being used in the field. Filled electronic questionnaires were checked while still in the field for completeness and those found incomplete and erroneous were corrected before the respondents were discharged.

Data management

Data entry and cleaning

The interviewer-administered pre-coded electronic questionnaire was used both for collecting data from eligible households and entering the data simultaneously using Open Data Kit (ODK) installed on mobile phones. The data were cleaned and edited when imported into excel spreadsheet. The data were coded and then checked for consistency. Explorative data analysis (EDA) was carried out to check for missing values and completeness of data for all variables of interest. The data were then exported to STATA 14 for further cleaning, manipulation and analysis.

Data analysis

Data were analyzed using STATA version 14 (StataCorp LP, TX, USA). Univariate analysis was done to summarize the data on respondent characteristics utilizing tables and graphs. Means with standard deviations were used to summarize normally distributed continuous variables while medians with interquartile ranges were used for continuous variables that remained non-normally distributed even after transformation, and percentages for the categorical variables.

Bivariate analysis

Modified Poisson regression analysis was carried out to estimate associations between missed opportunities for measles vaccination and the risk factors. The measure of association used was the prevalence ratio (PR).and the corresponding 95% confidence intervals. The effect of each independent variable on the dependent variable was checked at a significance level of 0.05.

Multivariable analysis

Variables with p-value < 0.2 from bivariate analysis were included in the final multivariable model. Log likelihood and Akaike’s Information Criteria (AIC) were used to determine the goodness of fit of the adjusted final model in comparison to the preceding models. The AIC value for each subsequent model was compared, and the model with the lowest value was considered to be the best fit model [22]. The presence of multicollinearity was checked among independent variables using Variance Inflation Factor (VIF) at a cutoff point 10. Predictors having a VIF value less than 10 indicated the absence of multicollinearity [23].

Qualitative data analysis

The qualitative data were analyzed manually by the principal investigator. Verbatim transcription was done to generate data from each KII. Both Deductive and Inductive approaches were used to analyze the data. However, the analysis was more deductively done as the principal investigator had prior themes in the KII guide. After transcription of the audio data, the material was systematically read through in order to identify codes, categories, and themes. During analysis, new categories were developed inductively. The underlying meaning of the categories was formulated into a theme. Illustrative quotations were selected. Qualitative data analysis was done after quantitative data analysis to identify health systems related factors that were classified according to the health system building blocks framework [24]. Fig 1 below summarizes the quantitative and qualitative methods used in this study.

Ethical approval

Approval to conduct this study was obtained from Makerere University School of Public Health Higher Degrees Research and Ethics Committee. Permission was also sought from the EPI of the Lilongwe District Health Office and the National Health Sciences Research Committee of Malawi. Respondents were read an informed consent which clearly stated the following 1) the purpose of the study, 2) what participation in the study would involve, 3) how confidentiality and anonymity would be maintained, 4) the right to refuse to participate in the study or to withdraw from the study without any penalty, 5) the benefits of participating in the study. Confidentiality and anonymity were maintained by the use of code numbers in the interviews during data collection. After explaining the study, the participants who could read and write were asked to sign a consent form.

Results

Four hundred and seventy six eligible children were included in the studyand 52.3% (249) were females. Their ages ranged from 31 months to 81 months with a median age of 52.0 months. Almost all respondents were mothers of these eligible children (97.9%, 466/476). Their mean age was 29.7 years (SD 6.9 years). Most of them [85.7% (408)] were married. More than half of the respondents (61.3%) had primary school education. Lower proportions of those included (16.0%) and (2.1%) had secondary school and tertiary education respectively. Only 16% were fully employed. Table 1 shows background characteristics of the study participants.

Table 1. Background characteristics of the study participants.

Characteristic	Number	Percentage
Sex of the child
Male	227	47.7
Female	249	52.3
Child's age (months) in 2017
9–21	195	41.0
22–34	117	24.6
35–47	80	16.8
48–59	84	17.7
Birth order
1^st born	129	27.1
2^nd - 4^th born	273	57.3
5^th +	74	15.6
Place of delivery
Home	14	2.9
Health facility	462	97.1
Caretaker’s age (years)
16–24	120	25.2
25–34	232	48.7
35+	124	26.1
Marital status
Currently Married	408	85.7
Currently not married	68	14.3
Caretaker’s education level
No education	108	22.7
Primary	283	59.5
Secondary	76	16.0
Post-secondary	9	1.8
Caretaker’s employment status
Unemployed	400	84.0
Self employed	41	8.6
Employed	35	7.4

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Proportion reached by the SIA among children with or without history of vaccination

Seventy six percent, 76% [362/476, 95% CI: 73.4–79.0] that participated in the study were vaccinated against measles at the age of 9 months or older under routine immunization services. Overall, 41.2% [95% CI 36.8–45.7] of these 476 children missed the opportunity of receiving the measles vaccine during the 2017 measles SIA. Only 59.6% [95% CI 54.9–64.1] of those that received measles vaccine under routine immunization services participated in the SIA. On the other hand, 51.5% [95% CI 34.7–68.0] of eligible children that did not receive the measles vaccine at the clinic under routine services also missed the opportunity to get vaccinated during the measles SIA. Figs 2 and 3 below respectively show the overall proportion of eligible children that were not vaccinated, and the proportion of zero-dose (whithout history of measles vaccination) children who were also missed during the 2017 measles SIA in Lilongwe District.

Factors associated with non-vaccination and possible reasons for non-vaccination

Socio-demographic characteristics such as maternal age, education level, employment status, marital status, child’s age, child’s sex, place of delivery, birth order, previous history of vaccination, number of under-five children in household, media exposure, religion, sex of household head, age of household head, education level of household head, and employment status of household head were studied to identify potential factors associated with measles non-vaccination during the mass vaccination campaign. Table 2 below shows bivariate and multivariate analysis of factors associated with non-vaccination during the measles SIA.

Table 2. Bivariate and multivariable analysis of factors associated with non-vaccination.

Factor	Prevalence	Unadjusted PR(95% CI)	Adjusted PR (95% CI)
Birth order
1^st born	50.8 [42.1–59.4]	1.0	1.0
2^nd - 4^th born	38.4 [32.8–44.3]	0.75 [0.55 1.01]	0.80 [0.65–0.98] ^*
5^th + born	34.7 [24.6–46.4]	0.60 [0.44–0.82]	0.73 [0.53–1.02]
Caretaker’s age
16–24	50.0 [41.1–58.9]	1.0
25–34	37.5 [31.5–43.9]	0.75 [0.59–0.96]
35+	39.5 [31.3–48.4]	0.79 [0.60–1.05]
Caretaker’s education
No education	50.1 [40.2–59.8]	1.0	1.0
Primary education	38.0 [32.6–43.7]	0.76 [0.59–0.97]	0.77 [0.62–0.96] ^*
Secondary educ	40.7 [30.3–52.2]	0.82 [0.58–1.14]	0.93 [0.67–1.28]
Post-sec education	48.0 [24.4–73.6]	1.00 [0.52–1.92]	1.55 [0.90–2.68]
Employment status
Employed	25.0 [12.2–40.4]	1.0	1.0
Self employed	41.3 [27.9–56.0]	1.12 [0.95–1.33]	1.19 [0.89–1.27]
Unemployed	51.6 [46.2–59.4]	1.48 [1.31–1.64]	1.28 [1.16–1.40]
Age of household head
16–24	59.0 [42.9–73.3]	1.0
25–34	44.2 [37.5–51.1]	0.75 [0.55 1.01]	0.79 [0.55–1.14]
35+	35.5 [29.6–41.9]	0.60 [0.44–0.82]	0.63 [0.40–0.99] ^*
Employment of h/h head
Employed	47.6 [40.4–54.8]	1.0	1.0
Self employed	41.4 [34.2–49.0]	0.87 [0.69–1.10]	0.84 [0.67–1.04]
Employed	28.8 [20.9–38.3]	0.61 [0.43–0.85]	0.69 [0.51–0.95] ^*
Providing info about SIA
No	85.2 [77.1–90.8]	1.0	1.0
Yes	28.3 [23.8–33.1]	0.33 [0.28–0.40]	0.49 [0.37–0.65] ^**
History of vacc
No	77.3 [66.1–93.0]	1.0	1.0
Yes	33.6 [21.6–44.7]	0.67 [0.55–0.82]	0.65 [0.47–0.88] ^**

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Key

* P-value < 0.05

** P-value < 0.001; APR: Adjusted prevalence ratio.

After adjusting for other factors, the prevalence of non-vaccination among children with higher birth order was 0.80 [APR = 0.80, 95% CI 0.65–0.98] times that of first-born children. In addition, the prevalence of non-vaccination among children with history of measles vaccination under routine programs was 35% [APR = 0.65, 95% CI 0.47–0.88] lower than that of zero-dose children (i.e. with no history of vaccination) during the 2017 measles SIA. The prevalence of non-vaccination among children born from mothers or caretakers having at least primary school education was 23% [APR = 0.77, 95% CI 0.62–0.96] less than that of children born from mothers with no formal education holding other factors constant. The prevalence of non-vaccination was 28% greater among children whose caretakers were unemployed than that of their counterparts from employed caretakers [APR = 1.28, 95%CI 1.12–1.42]. The prevalence of non-vaccination among eligible children decreased with increasing caretaker’s age but this relationship disappeared in the adjusted model.

Similarly, after controlling for other variables, the prevalence of non-vaccination during the 2017 measles SIA was 37% [APR = 0.63, 95% CI 0.40–0.99] lower among children coming from households where the household head was at least 35 years old than that among their counterparts having a household head aged 16–24 years. The prevalence was 31% [APR = 0.69, 95% CI 0.51–0.95] lower if the household head was employed “Health authorities providing information about the SIA” was much significantly associated with non-vaccination among eligible children. The prevalence of non-vaccination among children from households that indicated that health authorities provided information about the measles SIA was 0.66 [APR = 0.66, 95% CI 0.50–0.87] times that of children from households household that indicated they were not provided with information about the measles SIA by the health authoritis. Similarly, “getting information about measles vaccine and its safety” was highly significantly associated with vaccination of eligible children against measles during the campaign. The prevalence of non-vaccination was 51% lower [APR = 0.49, 95% CI 0.37–0.65]. This was also highlighted in the KIIs where it was revealed that some parents had a wrong perception and wrong understanding about the 2017 measles mass vaccination campaign regarding the eligiblity and safety of their children because information was not communicated in a proper way.

“The problem was that some parents believe that their children who are under two years of age receive vaccines at health facilities or under-five clinics. So because of that perception, they did not bring such children for vaccination. I think may be the messages about the campaign were not well clarified.” (Nurse from Bwaila HSD)

Discussions with the planners revealed that the mass vaccination campaign was also hampered by flaws existing in the health information system. This was manifested by the use of wrong estimates of health facility-catchment areas during planning and implementation of the SIA. This ultimately contributed to the logistical and human resources challenges in some health zones.

“Usually we use National Statistical Office (NSO) population figures of all health sub districts for planning purposes. So it happened that in some areas we came up with wrong population estimates because of following NSO figures. This led to inadequate supplies being allocated, and few health workers deployed to such health zones.” (EHO from Bwaila HSD)

A common emerging theme concerned the duration of the measles SIA. All the informants complained that the five days of implementing the campaign was very little considering that they targetted all eligible children, who were representing 46% of the country’s total population (children of 9 months up to 15 years).

“The period (five days) of implementing the campaign was very little to vaccinate all eligible children. May be some children who were missed in the first days because their parents were not available, or because of funerals in the villages would have had another opportunity to be vaccinated if government and other partners would consider extending the period of the campaign may be up to ten days.”(Nurse, Mitundu HSD)

Discussion

A cross-sectional mixed methods study was conducted in Lilongwe district, Malawi, to determine the proportion of eligible children that were reached by the 2017 measles SIA among those children with or without history of measles vaccination in Lilongwe district, Malawi, and to explore the reasons for non-vaccination. Overall, 41.2% of eligible children included in the study were not reached by the SIA during the campaign. Only 59.6% of those children that received measles vaccine under routine immunization services participated in the measles SIA. On the other hand, 51.5% of eligible children that did not receive the measles vaccine at the clinic under routine services also missed the opportunity to get vaccinated during the measles SIA. The possible explanation for this finding might be that there was not enough sensitization and mobilization on the part of planners and implementers, and perhaps holding of strong beliefs and negative attitudes towards vaccination by some parents or caretakers. This finding is in line with a previous study by Allison Portnoy and colleagues on the impact of SIAs on reaching children missed by routine programs, which found that the proportion of zero-dose children reached by SIAs ranged from a low 28% in Sao Tome and Principe to a high 91% in Nigeria [4]. Similar findings were also corroborated by Winter and Barchi in their SIA assessment studies that revealed only 20% of children with no prior doses of measles vaccine being reached by the SIA in Honduras, and up to 22% of zero-dose children in Indonesia were reached by the SIA [25].

Caretaker’s education was important in measles vaccination during the campaign. This analysis showed that the prevalence of non-vaccination was lower among children whose parents had at least primary school education than that among children from caretakers with no formal education. Thus, educated mothers had significant chance of immunizing their children during the campaign. This finding is consistent with the findings of other multilevel analysis studies conducted in 24 Sub Saharan African countries by Wiysonge and colleagues [26], and other cross-sectional studies conducted by Abadura et al [27]. Educated mothers know the importance of immunization. And moreover, education provide greater knowledge of health care utilization and the ability to respond to new knowledge more rapidly [28].

Caretaker’s occupation seemed to be important in getting children vaccinated during the campaign. This research revealed that the prevalence of non-vaccination was 28% greater among children whose caretakers were unemployed than that of their counterparts from employed caretakers. Previous studies also found occupation to be important in influencing childhood immunization [7]. On the other hand, some studies found employment to hinder a caregiver from seeking out immunization services because of lack of time, even in the context of SIAs. However, we noted that those employed caretakers who participated in this study had also acquired some education. Therefore, they were able to find some time to have their children vaccinated because they understood the importance of the vaccination campaign.

The analysis also showed that children from older caretakers had significant chance of being vaccinated against measles. The prevalence of non-vaccination among children from caretakers or mothers who were aged 25–34 years was 25% lower than that of children from caretakers who were younger than 25 years. Some authors have attributed this to experience that older mothers gained over time on the importance of immunization, and perhaps also their knowledge on fatalities that occur to children because of lack of immunization [29]. This finding is in line with that which Babirye and colleagues also found [30].Sridhar and colleagues also reported maternal age as one of the determinants of vaccination [7].

We also found that birth order was an important factor in this research, showing a protective effect against non-vaccination. Younger children had greater chance of being vaccinated against measles during the SIA, thus. the prevalence of non-vaccination was lower among children with higher birth order. This sounds perversely counter-intuitive and not consistent with the findings of other studies [8, 9]. The likely reason for this finding could be that some parents did not perceive any measles threat to their older f children, like first and second born, who most of them were 3 to 5 years old during the time the vaccination campaign was implemented. Therefore, they did not participate in the measles SIA. The prevalence of non-vaccination was lower among children with history of previous measles vaccination than those children with no history of previous vaccination. This finding concurs with what Allison Portnoy and colleagues also found in their study about assessing the impact of SIAs [4].

The key informant interview findings are to a large extent complementing and corroborating our survey findings. Messages and information about the SIA were not well disseminated and explained to the households. Some mothers did not participate in the SIA with their eligible children because information about the SIA did not reach them. Some parents perceived that younger children only get vaccinated routinely at health facilities or at under-five clinics. Therefore, they did not see it as a need to have their children vaccinated during the campaign. This is an indication that health education and communication was not carried out effectively to the masses. Effective health education and health education have positive impact on health services utilization [31].

Flaws in the health information system were evident with the use of wrong population estimates that negatively affected the implementation of the SIA. According to the World Health Organization, sound and reliable information is the foundation of decision-making across all health system building blocks. Accurate information is essential for health system policy development and implementation, governance and regulation, health research, human resources, health education and training, service delivery and financing. It was evident in Lilongwe district that problems in health information system and health education delivery had direct negative impact in service delivery during the implementation of the 2017 measles SIA. Thus, use of wrong population estimates in some health sub districts (HSD) led to logistical problems and allocation of fewer health care workers than required. A study conducted in Kenya by Kinara also highlighted cracks in health information management system which affect health planning and service delivery because of availability of limited data, and of poor quality [32].

Study limitations

Given that the information on measles immunization was recorded retrospectively using immunization card or maternal self-reports where the card was unavailable, mothers might not have been in a position to recall very well all the past immunization events. Therefore, respondents were prone to recall error and perhaps forgetting. The WHO and some authors argue that recall by vaccination card is considered the best practice for determining vaccination coverage in a household survey and is preferable over self-reported recall. However, some previous studies also concluded that maternal self-reports are as good as vaccination cards [20, 21]. And the interview questions were created in such a way that such recall errors should be reduced. Another limitation was that we were unable to reach out to some key stakeholders involved in the immunization programme such as medical officers, district health officers and cold chain technicians. Since the selection of households within the clusters was done purposively, the study might have suffered from selection bias. And finally, as with all cross-sectional studies, we can only describe the associations between the outcome and potential determinants; we cannot infer causality.

Conclusions

Many children (41%) were left unvaccinated during the campaign. There was little impact of the SIA on reaching children missed by routine services as more than 50% of the children who did not receive measles vaccine under routine immunization program also missed the opportunity to be vaccinated against measles during the SIA. The District Health Team of Lilongwe district should endeavor to implement high quality supplementary immunization activities (SIAs) to reach all children, including those missed by routine immunization program. This can be achieved by involving health workers from health sub districts in planning because they know the sizes of their catchment areas by actual head counts other than using some population estimates. There was a positive impact of caretaker’s education level on vaccination of eligible children. Additionally, children with low birth order had significantly lower chances of being vaccinated during the mass vaccination campaign.

Efforts are needed to enhance formal education among the communities with gender parity at the fore front. The DHT should educate the caretakers on the importance of child immunization, thereby vaccinating children irrespective of birth order. In addition, there is need to intensify community mobilization as part of SIA activities. And finally, there was poor delivery of health education to the communities; and flaws in health information system led to logistical challenges and allocation of few health care workers in some areas, which ultimately impacted on the service delivery during the mass vaccination campaign. Media outreach should be increased among the population, and government can use this channel to disseminate standard information about any preventive health program including supplementary immunization activities.

Supporting information

S1 File. Quantitative questionnaire.

An original interviewer-administered questionnaire which was later transferred to Open Data Kit (ODK) to be ectronically administered. These questions were developed specifically for this study.

(DOCX)

Click here for additional data file.^{(16.8KB, docx)}

S2 File. Key informant guide.

This guide was used to collect qualitative data through Key Informant Interviews.

(DOCX)

Click here for additional data file.^{(14.2KB, docx)}

Acknowledgments

We thank the study participants, community leaders, the research assistants and the coordinator for the Expanded Programme on Immunization in Lilongwe district for their support.

Abbreviations

CHAM: Christian Health Association of Malawi
EPI: Extended Program for Immunization
DHO: District Health Office
DHT: District Health Team
HSD: Health Sub District
LL: Lilongwe
MCV: Measles Containing Vaccine
MDG: Millennium Development Goals
MOH: Ministry of Health
MOV: Missed Opportunity for Vaccination
SDG: Sustainable Development Goals
SIA: Supplementary Immunization Activities
UNICEF: United Nations International Children’s Emergency Fund
VPD: Vaccine Preventable Disease
WHO: World Health Organization

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0243137.r001

Decision Letter 0

Kavita Singh Ongechi

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

4 Aug 2020

PONE-D-20-10234

Proportion of children aged 9 – 59 months reached by the 2017 measles Supplementary Immunization Activity among the children with or without history of measles vaccination in Lilongwe district, Malawi.

PLOS ONE

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2) Methods: For some variables consider collapsing categories because of small cell size. For marital status consider categories of currently married and currently not married. For employment, what is the difference between housewife and unemployed. Could these categories be combined.

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Reviewer #1: This is an interesting study with potentially important implications for assessing the effectiveness of supplemental immunization activities. The manuscript is well written with coherent flow of information and argument. The conclusions may be of interest to countries working to reach children that are consistently missed in routine and supplemental immunization services. I have no major issues with the paper and offer the following minor recommendations for revision:

Abstract

1. On line 1, include the month along with year the SIA was conducted.

2. The second sentence where the authors state "...20 households..." is inconsistent with the methods section and should be harmonized with the description in the methods.

3. Line 4 in the methods description in abstract where the authors refer to "true description of when and where the child was vaccinated." The word true is subjective and should be deleted as the data are based on self-report, without an objective way of validating the caregiver's report.

4. Define MOV at first mention.

Background

5. Second paragraph, the WHO recommendation referenced was updated in 2017 and removed the MCV1 threshold for introducing MCV2. This statement should be edited to include the current position. See: https://www.who.int/immunization/policy/position_papers/WHO_PP_measles_vaccine_summary_2017.pdf?ua=1

Methods

6. Last statement in the description of the study sample "Geographical access to all levels of health care has remained stagnant especially among under five children living in the urban slums and outskirts of the city" is unclear and should be edited for clarity.

7. Study design: Indicate the respective targets of the quantitative and qualitative portions of the study. As written, it appears like the quantitative and qualitative data were collected from the same sample.

8. Page 7, sampling procedure: "In each selected village, 19 eligible households were selected." This is inconsistent with what is stated in the abstract where the authors state that 20 household were selected in each village. This should be checked and harmonized for consistency.

9. Page 8, training of research assistants: indicate how many research assistants were trained.

10. Page 8, data collection and measurements: "a child was taken to have been vaccinated during the measles SIA if the caretaker gave a true description of when and where the child was vaccinated." Similar to my comment on the abstract, it is unclear how the research team/enumerators validated the veracity of these reports. This is a subjective statement and the word "true" should be deleted.

11. First paragraph on page 9, a rationale for how the required number of KIIs was determined should be provided.

12. Page 9, still on data collection and measurements: "The outcome variable in this study was measles vaccination during 2017 measles SIA to an eligible child who had no any contraindication to vaccination" Is the outcome referenced here referring to the KIIs or the household questionnaire? This needs to be clarified. Also delete the word "any" from the statement.

Results - from this point forward, for some reason, all pages are numbered "1" and should be fixed.

13. Paragraph 1: "Only 16% were gainfully employed." Authors should clarify what "gainfully" means in this regard. Employed for payment in monetary terms, in-kind, self-employed, agricultural work?

14. Table 1: In caretakers educational level, "no education is repeated.

15. In the description of factors associated with MOVs and possible reasone for non-vaccination, define "APR" at first mention.

16. Table 2, add a footnote to explain what estimates are in bold font face. In addition, there has be a better way of differentiating between employment and self-employment. Consider different verbiage

Discussion

17: Generally, arguments need to be better developed in discussion section. It is not enough to state that a finding concurs with that of some other study without providing plausible explanations for the findings.

18. In second paragraph of the discussion section: "This research revealed that the prevalence of MOV was 28% greater among children whose caretakers were unemployed than that of their counterparts from employed caretakers. Previous studies also found occupation to be important in influencing childhood immunization [8]." There have been mixed findings in this regard. A plausible counter-argument is that employment may preclude a mother from taking time to seek out immunization services. In the context of SIAs which are provided free to the user, what could be the protective effect of employment? There is a need to balance the evidence in support and against.

19. "The prevalence of MOV was lower among children with higher birth order than first born children. This is not consistent with the findings of most studies. The likely reason for this finding could be that some parents did not perceive any measles threat to their first born children, who most of them were old during this time unlike other children with high birth order." The point you are trying to make here is confusing and should be clarified.

20. Paragraph 4 of the discussion section: "According to the World Health Organization, sound and reliable information is the foundation of decision-making across all health system building blocks. Accurate information is essential for health system policy development and implementation, governance and regulation, health research, human resources, health education and training, service delivery and financing." A citation should be provided.

Conclusion

21. "The magnitude of missed opportunities for measles vaccination among eligible children was very high as a greater proportion of eligible children were not vaccinated during the 2017 measles supplementary immunization activity (SIA) in Lilongwe district." I believe this is an inaccurate interpretation. From these findings, more children were vaccinated than not (77 vs. 23%) during the measles SIA, and cannot be interpreted as "greater proportion of eligible children were not vaccinated."

22. The last statement in the conclusion appear out of place or does not flow coherently. I suggest it should be moved to just before the preceding statement ("And finally...").

Reviewer #2: Summary

There is great value in exploring reasons behind missed opportunities for vaccination (MOV). Since the 1980s, the WHO has had several iterations of methodology for assessing MOV. Since MOV is defined in the context of health systems failing to vaccinate an individual eligible for a vaccine, these tools are designed in the context of facilities. Moreover, MOV and supplementary immunization activities (SIA) are separate concepts where SIAs complement routine vaccination. This makes it rather confusing that the proposed study for publication explores MOV in the context of SIA. Individuals not reached through SIAs would not be MOV. If the focus of the study is to assess why children may not have been reached by the measles SIA, this would be different than examining MOV. There are issues with both the design and analysis proposed in the paper.

Specific edits

Background

• The WHO defines missed opportunities for vaccination (MOV) as an individual making contact with the health system and not receiving a vaccination they are eligible for. Supplementary immunization activities (SIA) are intended to complement routine vaccination and are not specifically considered a WHO strategy specifically for addressing MOV. These need to be clearly defined if the paper is framed in the context of MOV and SIA.

• Revisit literature on gaps in reaching children during mass measles vaccination coverage. There is documentation on how SIAs miss marginalized populations/gaps in coverage.

• Revisit citations 4-10 – these primarily look at reasons for MOV in the context of regular vaccination not people being missed through SIA.

• The background should include more robust information on measles coverage (and source) in Malawi and Lilongwe. The paper cited, which were vaccine coverage estimates based on surveillance data, is not the most appropriate data source compared to household survey and DHIS2 in Malawi. In Malawi, a DHS was conducted in 2015/16 and a SPA was conducted in2013/14. The Malawi progress report to Gavi, which includes the measles campaign cites DHS and DHIS2 data to describe measles coverage and measles surveillance data. DHIS2 data in Lilongwe during the SIA campaign period should be cited.

• It’s especially surprising that SPA findings are omitted from the paper given SPA has indicators directly related to MOV.

Methods

• Why was measles SIA not captured on vaccination cards? Recall by vaccination card is considered the best practice for determining vaccination coverage in a household survey and is preferable over self-reported recall. The WHO MOV guidelines specifically advise to not accept verbal vaccination recall from mothers.

• Insufficient justification why only eight KIIs were conducted. Were KIIs all with public health facility providers or CHAM/NGOs as well?

• Insufficient justification on how the IDI guides for both parents and health workers deviate from MOV suggested protocol and standard question approaches with core omitted questions such as “Has this child ever been vaccinated?” Also would be important to describe the choice of choosing a prompted approach for asking “why was the child not vaccinated against measles” instead of an unprompted approach since this is a core question for the study.

• Asking about sex of household head is different than asking who makes decisions in a household (preferred approach).

• Based on question wording in the KII guide, there is a potential that respondents may have confused campaign-related factors with health system-related factors that would impede in vaccination.

Results

• It is unclear how the authors define “missed the opportunity of receiving measles vaccine.” The results should cite the total number of children considered “eligible” or in need of vaccination and clearly define the denominator used for coverage estimates.

• As described above, “MOV” should not be used to describe children that were not reached by the SIA campaign.

• The qualitative interviews could be more robustly and systematically analyzed. For example, issues with the health information system are cited in the discussion as a major finding. However, the quote used to support the health information system is about flawed use of population estimates – which is independent of the health information system. Was the health officer referring to DHIS2 or census estimates? I believe DHIS2 sits with the Ministry of Health in Malawi, not the National Statistical Office, so the respondent could have been referring to just census estimates (not the health information system).

Discussion

• As described above, “MOV” should not be used to describe children that were not reached by the SIA campaign.

**********

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PLoS One. 2021 Jan 11;16(1):e0243137. doi: 10.1371/journal.pone.0243137.r002

Author response to Decision Letter 0

18 Sep 2020

Manuscript: PONE-D-20-10234

Response to editor and reviewers

We are grateful to reviewers and editor for the time and effort they dedicated to providing feedback about our manuscript titled, “Proportion of children aged 9 – 59 months reached by the 2017 measles Supplementary Immunization Activity among the children with or without history of measles vaccination in Lilongwe district, Malawi”. Please see below our point-by-point response to the reviewers’ comments and queries. The page and line numbers indicated refer to the manuscript with tracked changes.

Editor’s comments

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

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We have made sure that our manuscript satisfies PLOS ONE’s style requirements. We have followed the formatting samples given above.

We gave this manuscript to Dr Alexander Kalimbira, head of Language Department at the University of Malawi. He copyedited the draft for language usage, spelling and grammar.

Upon resubmission, please provide the following:

• The name of the colleague or the details of the professional service that edited your manuscript

• A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file)

• A clean copy of the edited manuscript (uploaded as the new *manuscript* file)

We appreciate your comment. To address this and other comments from reviewers, we have added a sub-section of “the research team” (lines 183 – 189, pg 9); recruitment of household survey participants (lines 160 – 161 pg 8); recruitment of KII participants (line 213, pg 10)

4. Please ensure that you refer to Figures 1-3 in your text as, if accepted, production will need this reference to link the reader to the figure.

All figures used have been referred to in the text (Line 268, pg 12; Line 339, pg 16)

Table 2 has been referred to in the text (line 354, pg 18)

Additional Editor Comments (if provided):

Dear Author,

Please see the reviewer comments and in addition I have a few comments.

1) Introduction: Explain more about there is measles resurgence every three years.

We appreciate your comment. This has been well clarified in the text (lines 100 – 101)

Variable ‘marital status’ has been collapsed into two categories only (pg 16). For employment, categories “housewife” and “unemployed” have been combined (page 16)

Reviewers' comments

Reviewer #1:

This is an interesting study with potentially important implications for assessing the effectiveness of supplemental immunization activities. The manuscript is well written with coherent flow of information and argument. The conclusions may be of interest to countries working to reach children that are consistently missed in routine and supplemental immunization services. I have no major issues with the paper and offer the following minor recommendations for revision:

Abstract

1. On line 1, include the month along with year the SIA was conducted.

The month and the year the SIA was conducted has been indicated (line 21, pg 2)

2. The second sentence where the authors state "...20 households..." is inconsistent with the methods section and should be harmonized with the description in the methods.

This has been corrected, 20 replaced with 19 (line 28, pg 2)

Word “true” removed and sentence rephrased (line 30, pg 2)

4. Define MOV at first mention.

MOV as a primary outcome has been removed from the whole write up and replaced with “non-vaccination” of eligible children as primary outcome.

Background

We agree with the reviewer, and appreciate the resource shared. This statement has been edited to reflect the current WHO’s position (lines 63 – 67, pg 3)

Methods

This statement has been written again with simple and standard English for clarity (line 140 – 142, pg 7)

Respective targets of the quantitative and qualitative portions of the study clearly defined (lines 150 – 152, pg 7)

Corrected for consistency

9. Page 8, training of research assistants: indicate how many research assistants were trained.

We have added a sub section of the research team where the number and training of research assistants is indicated (line 182 – 189, pg 9)

The word “true” has been removed, and statement written again (line 201 – 202, pg 9)

11. First paragraph on page 9, a rationale for how the required number of KIIs was determined should be provided.

The rationally for how the number of KIIs was arrived at has been explicitly given in the text (lines 211 – 212, pg 10)

The word “any” deleted from the statement.The primary outcome for this research was non-vaccination of eligible children during the SIA. Therefore, the study identified associated factors, and reasons for non-vaccination for both household survey and KIIs

Results - from this point forward, for some reason, all pages are numbered "1" and should be fixed.

Correct page numbering has been done

13. Paragraph 1: "Only 16% were gainfully employed." Authors should clarify what "gainfully" means in this regard. Employed for payment in monetary terms, in-kind, self-employed, agricultural work?

The statement has been edited for clarity (lines 298 – 299, pg 14)

14. Table 1: In caretakers educational level, "no education is repeated.

One has been deleted

15. In the description of factors associated with MOVs and possible reasone for non-vaccination, define "APR" at first mention.

APR defined as Adjusted Prevalence Ratio at first mention just below table 2 (line 324, pg 17)

We appreciate you comment. However, footnotes are not permitted as per journal requirements (PLOS ONE).

Discussion

We appreciate the comment and thank the reviewer for the guidance. We have given a plausible explanation to balance the evidence in support and against this finding. (lines 417 – 421, pg 21)

We thank the reviewer for the comment. We also noted that this finding is counter-intuitive. However, we have explained this further for clarity and better understanding (lines 431 – 437, pg 20).

Citation provided (line 458, pg 23)

Conclusion

We have made a better conclusion this time as our focus is on non-vaccination of eligible children as primary outcome. However, we still note that many children were missed because the overall proportion left unvaccinated is slightly over 41%

22. The last statement in the conclusion appear out of place or does not flow coherently. I suggest it should be moved to just before the preceding statement ("And finally...").

We have made appropriate changes as advised by the reviewer (lines 499 – 502, pg 26 – 25)

Reviewer #2:

Summary

Specific edits

Background

We appreciate your comment, and to address this, we have removed MOV from the whole manuscript and replaced it with “non-vaccination” of eligible children as a primary outcome in this study.

• Revisit literature on gaps in reaching children during mass measles vaccination coverage. There is documentation on how SIAs miss marginalized populations/gaps in coverage.

Literature revisited and new information added (lines 80 – 89, pg 4 – 5)

• Revisit citations 4-10 – these primarily look at reasons for MOV in the context of regular vaccination not people being missed through SIA.

Citations 4 and 6 are specifically looking at reasons for non-vaccination in the context of SIAs. However, literature shows that associated factors for non-vaccination of eligible children under routine immunization services are the same even in the context of SIAs

• It’s especially surprising that SPA findings are omitted from the paper given SPA has indicators directly related to MOV.

We appreciate your comment. We have added a more robust information on measles vaccination coverage in Malawi, and Lilongwe District in particular by citing from DHIS2 (lines 101 – 107, pg 5)

Methods

We appreciate your comment, and we agree with the reviewer. However, we have given a plausible counter-argument guided by previous studies [1-3] to balance the evidence.

• Insufficient justification why only eight KIIs were conducted. Were KIIs all with public health facility providers or CHAM/NGOs as well?

The rationally for how the number of KIIs was arrived at has been explicitly given in the text (lines 207 – 211, pg 10)

• Asking about sex of household head is different than asking who makes decisions in a household (preferred approach).

• Based on question wording in the KII guide, there is a potential that respondents may have confused campaign-related factors with health system-related factors that would impede in vaccination.

We appreciate your comment. The questionnaire was primarily designed for this research. However, most of the questions were taken and adapted from the WHO’s reference manual for cluster surveys. The respondents understood the kind of information the interviewer sought from them because all interviews in the household survey were done in vernacular language. Nevertheless, we agree with the reviewer that some questions needed to be better rephrased.

Results

• As described above, “MOV” should not be used to describe children that were not reached by the SIA campaign.

Number of eligible children stated (line 293, pg 14). And this number was used as a denominator for proportion estimates. Once again, MOV has been removed and replaced with non-vaccination of eligible children as a primary outcome in the context of SIA.

We appreciate your comment, and agree with you. We have therefore edited the statement for clarity (lines 369 - 370, pg 19; lines 450 – 454, pg 22 - 23)

Discussion

• As described above, “MOV” should not be used to describe children that were not reached by the SIA campaign.

“MOV” removed and replaced with “non-vaccination” as a primary outcome

________________________________________

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Reviewer #1: No

Reviewer #2: No

1. Gareaballah, E. and B. Loevinsohn, The accuracy of mother's reports about their children's vaccination status. Bulletin of the World Health Organization, 1989. 67(6): p. 669.

2. Langsten, R. and K. Hill, The accuracy of mothers' reports of child vaccination: evidence from rural Egypt. Social science & medicine, 1998. 46(9): p. 1205-1212.

3. Valadez, J.J. and L.H. Weld, Maternal recall error of child vaccination status in a developing nation. American journal of public health, 1992. 82(1): p. 120-122.

Attachment

Submitted filename: Response letter to reviewers.docx

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PLoS One. doi: 10.1371/journal.pone.0243137.r003

Decision Letter 1

Kavita Singh Ongechi

5 Oct 2020

PONE-D-20-10234R1

PLOS ONE

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=============================

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PLoS One. 2021 Jan 11;16(1):e0243137. doi: 10.1371/journal.pone.0243137.r004

Author response to Decision Letter 1

17 Oct 2020

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PLoS One. doi: 10.1371/journal.pone.0243137.r005

Decision Letter 2

Kavita Singh Ongechi

17 Nov 2020

PONE-D-20-10234R2

Dear Dr. Kainga,

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.

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Academic Editor

PLOS ONE

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Reviewers' comments:

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PLoS One. doi: 10.1371/journal.pone.0243137.r006

Acceptance letter

Kavita Singh Ongechi

25 Nov 2020

PONE-D-20-10234R2

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Associated Data

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

Supplementary Materials

S1 File. Quantitative questionnaire.

An original interviewer-administered questionnaire which was later transferred to Open Data Kit (ODK) to be ectronically administered. These questions were developed specifically for this study.

(DOCX)

Click here for additional data file.^{(16.8KB, docx)}

S2 File. Key informant guide.

This guide was used to collect qualitative data through Key Informant Interviews.

(DOCX)

Click here for additional data file.^{(14.2KB, docx)}

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Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files.

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PERMALINK

Proportion of children aged 9–59 months reached by the 2017 measles supplementary immunization activity among the children with or without history of measles vaccination in Lilongwe district, Malawi

Hamilton Wales Kainga

Steven Ssendagire

Jacquellyn Nambi Ssanyu

Sarah Nabukeera

Noel Namuhani

Fred Wabwire Mangen

Roles

Abstract

Background

Methods

Results

Conclusion

Background

Materials and methods

Study setting

Target population

Study design

Sampling procedure

Eligibility criteria

Research team

Data collection and measurements

Pre-testing and field editing of data

Data management

Data entry and cleaning

Data analysis

Bivariate analysis

Multivariable analysis

Qualitative data analysis

Fig 1. Summarizing the mixed methods used in this study.

Ethical approval

Results

Table 1. Background characteristics of the study participants.

Proportion reached by the SIA among children with or without history of vaccination

Fig 2. Showing the overall proportion of eligible children that were left unvaccinated during the SIA in Lilongwe.

Fig 3. Showing the proportion of eligible without history of measles vaccination who were also missed during the SIA.

Factors associated with non-vaccination and possible reasons for non-vaccination

Table 2. Bivariate and multivariable analysis of factors associated with non-vaccination.

Discussion

Study limitations

Conclusions

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Kavita Singh Ongechi

Roles

Transfer Alert

Author response to Decision Letter 0

Decision Letter 1

Kavita Singh Ongechi

Roles

Author response to Decision Letter 1

Decision Letter 2

Kavita Singh Ongechi

Roles

Acceptance letter

Kavita Singh Ongechi

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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