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Improving the timeliness of administering birth dose vaccines using a digital platform in Nairobi slums., ChanjoBora

KENYA, 2019
Health and Well-Being (HaW)
Gershim Asiki, Ph.D., Hermann Pythagore Pierre Donfouet, PhD
Last modified June 25, 2025 Page views 2223 Metadata DDI/XML JSON

Identification

IDNO
DDI-KEN-APHRC-GBV-2018-V1.0
Title
Improving the timeliness of administering birth dose vaccines using a digital platform in Nairobi slums., ChanjoBora
Subtitle
ChanjoBora
Country
Name Country code
KENYA KEN
Abstract
Background: Vaccine preventable diseases still contribute substantially to child mortality in sub-Saharan Africa. Delays in administering vaccines within the recommended age group increase the risk of infection because of a prolonged potential exposure to vaccine-preventable diseases. Birth dose vaccines are administered late, due to fragmented systems of delivery, recording and communication between maternal health and child health services. Understanding these deficiencies presents opportunities for improving timely vaccinations at birth.
Objective: The main aim of this study was to assess the effectiveness of community health volunteers (CHVs) and healthcare workers using an electronic immunization registry consisting of a digital platform, web-based database and health text messages to improve timeliness of administering birth dose vaccines such as Bacille Calmette Guerin (BCG) and Oral Polio Vaccine (OPV) in Nairobi slums.

Methodology: Through a cross-sectional stepped wedge design, the intervention consisting of interaction between CHVs, pregnant women and healthcare workers using a digital platform linked to a central registry was implemented in eight villages in Viwandani (a site for the Nairobi Health and Demographic Surveillance System). CHVs or healthcare workers were to register pregnant women at home or health facility and automatically send tailored text messages from a central server, encouraging timely vaccination uptake. The project tested the feasibility of CHVs or healthcare workers using the platform and the effectiveness including cost-effectiveness of the intervention. Interviews were conducted with women with infants at baseline and the introduction of the intervention into clusters (villages) to measure the effect of the intervention on timeliness of birth dose vaccines.
Duration and budget: The duration of the project was 18 months and the total budget will be USD 100,000.
Conclusion: The expected findings generated from this study included the feasibility and effectiveness of using the digital platform for improving timely vaccinations and these was used to inform the design of a large trial in other settings. Within the larger trial we had hoped to also measure the impact of the intervention on infant survival. The digital platform was customized based on recommendations from this study to include additional features such as health sensitization videos.

Version

Version Date
2024-09-20
Version Notes
N/A

Coverage

Geographic Coverage
County Coverage (Nairobi County/Informal settlements of Viwandani)
Unit of Analysis
Community Health volunteers (CHVs),Pregnant Women, Health Workers and women with infants
Universe
The survey covered sampled Community Health volunteers (CHVs),Pregnant Women, Health Workers and women with infants

Producers and sponsors

Authoring entity/Primary investigators
Agency Name Affiliation
Gershim Asiki, Ph.D. APHRC
Hermann Pythagore Pierre Donfouet, PhD APHRC
Producers
Name Affiliation Role
Martin Kavao Mutua, Ph.D African Population and Health Research Center Co-Investigator
Elizabeth Kimani, Ph.D. African Population and Health Research Center Co-Investigator
Peter Otieno, MPH African Population and Health Research Center Co-Investigator
Kumar Abhishek Khamrai, MBA VAL partners Co-Investigator
Dominic Muindi, M.A (management VAL partners Co-Investigator
Funding Agency/Sponsor
Name Abbreviation Role
Bill and Melinda Gates Foundation: Grand Challenges Explorations Round 20 BMGF Funder
Other Identifications/Acknowledgments
Name Affiliation Role
Joy Chepkemboi African Population and Health Research Center Data Documentation Officer
Bonface Ingumba African Population and Health Research Center Data Governance Officer

Sampling

Sampling Procedure
Study design
We used a cross-sectional stepped wedge design which involved a sequential roll-out the intervention to clusters (defined as a village with one CHV selected for this study) over a number of time periods. A stepped wedge design allows the intervention to be staggered until all clusters receive the intervention in a determined random order. The two key reasons for choosing this design were: first, the intervention is likely to do more good than harm and would therefore be unethical to withhold the intervention from some participants of the study [35], secondly for logistical reasons, the intervention can only be implemented in stages [36].
Baseline measurements of timely vaccination was taken in all study villages at month 0 followed by introduction of the intervention sequentially in three time points 2 months apart. Initially three villages received the intervention followed by six after four months and finally all eight villages at six months were included in the intervention. Timeliness of vaccination was estimated at each point.
Study site (geographical)
The study was conducted in Viwandani, a Nairobi Urban Health and Demographic Surveillance System (NUHDSS) site [37], which had a population of 49,000 people, birth rate of 16 per 1000 per year, infant mortality rate of 34.7/1000 and timely vaccination coverage of 22% [10]. Viwandani is well characterized as a mobile population, with challenges of health services uptake, therefore suitable for testing this intervention.
Study populations
Pregnant women will be recruited in their second or last trimester, followed to birth and infant-mother pair followed two months after birth.
Inclusion criteria
The following criteria wias used to enroll women in the study:
1. Pregnant women living in Viwandani and in their second or third trimester (5-9 months of pregnancy)
2. Pregnant women resident in Viwandani and not intending to leave the study village in the next six months.
3. Pregnant women willing to be enrolled and followed until two months after birth.
Exclusion criteria
1. Pregnant women with complications of pregnancy as documented by health workers.
2. Pregnant women planning to vaccinate their baby outside Viwandani clinics.
3. Women with adverse pregnancy outcome during follow up (abortion, stillbirth, and early neonatal death).
4. Women diagnosed with multiple pregnancies.

Sample size and Sampling
Our sample size estimates were done following Hooper et al. [38]. First, a recent study on vaccination in the slums suggested that the percentage of timely vaccination is 22% [10]. We hypothesized that the intervention will increase that percentage of timely vaccination to 45% (significant difference of 23%), implying an effect size of 0.5. Based on the study by Russo et al. [39] on the vaccine coverage in Cameroon, we assumed an intra-cluster correlation (similarity of outcomes from individuals within a cluster at the same time point) of 0.04. Furthermore, we assumed a cluster autocorrelation (similarity of outcomes from individuals within a cluster taken at different times) of 0.8. We also assumed a cluster size of 12 neonates specified in advance, three steps and four time points (one baseline and three follow-up time points) are expected during recruitment and follow up. We further conjecture a confidence interval of 95%, a margin-of-error of 5% and a power of 80%. Based on these assumptions, the sample size required was 383 neonates and 8 clusters (villages). If we assumed a dropout rate to be 20%, our final sample size was 479 neonates.
Twelve neonates were consecutively selected in each cluster. In other words, during the time of the study CHVs were consecutively enrolled the neonates in each cluster until the targeted number was reached. At each step a new cohort was recruited and followed-up till 2 months after birth. At each step our primary outcomes wiere measured.
Deviations from the Sample Design
N/A
Response Rate
N/A
Weighting
N/A

Data Collection

Dates of Data Collection (YYYY/MM/DD)
Start date End date
2019-12-06 2019-10-06
Mode of data collection
Face-to-face [f2f]
Supervision
Enumerators were organized into teams that included a controller and a supervisor. Each team typically consisted of 3-4 interviewers, one controller, and one supervisor. The supervisor’s main role was to manage field data collection activities, oversee the interviewers, ensure proper handling of supplies and equipment, and liaise with local authorities. They were also responsible for assigning work to interviewers, performing spot checks, maintaining field control documents, and sending completed questionnaires and progress reports to the central office. Controllers assisted in overseeing data quality, ensuring consistency, and providing support to interviewers. Field visits were made periodically by senior management to monitor progress and provide additional support, ensuring smooth data collection and addressing any issues as they arose.
Type of Research Instrument
The questionnaires used in this study were developed in English and Swahili, based on standard models for health and vaccination surveys. They include a baseline questionnaire for mothers, a follow-up questionnaire, a mobile-based data entry form for Community Health Volunteers (CHVs), and a vaccination update form for health facilities. These were reviewed by healthcare professionals, CHVs, and mothers during focus groups. After translation into Swahili, a back-translation process ensured accuracy. Pretesting and feedback helped refine the questionnaires for clarity and usability. All documents and feedback from stakeholders was provided as external resources.

Data Processing

Cleaning Operations
he data management process involved uploading interview data from tablets into an interim database, with regular quality control checks performed by the Data Manager and Research Officer. The cleaned data was then uploaded into a secure master study database, which was regularly backed up in a secure location, with a password-protected copy maintained by the Data Manager. A detailed data dictionary was created for curation. For the electronic pregnancy and immunization registry, data was submitted directly from smart devices to a secure database with stringent privacy and security measures. Data was backed up, and validation rules ensured accuracy. Data sharing followed a pre-approved role-based access control system, with anonymized data shared with APHRC by VAL partners for analysis and reporting. In terms of data analysis, vaccination timeliness and effectiveness of interventions were assessed, using linked data to identify missing vaccinations and generate summaries for health
Other Processing
N/A

Data Appraisal

Estimates of Sampling Error
N/A

Data access

Contact
Name Affiliation Email URI
African Population and Health Research Center APHRC datarequests@aphrc.org http://www.aphrc.org/
Conditions
Conditions
APHRC data access condition
All non-APHRC staff seeking to use data generated at the Center must obtain written approval to use the data from the Director of Research. This form is developed to assess applications for data use and facilitate responsible sharing of data with external partners/ collaborators/researchers. By entering into this agreement, the undersigned agrees to use these data only for the purpose for which they were obtained and to abide by the conditions outlined below:

1.Data Ownership:
The data remain the property of APHRC; any unauthorized reproduction and sharing of the data is strictly prohibited. The user will, therefore, not release nor permit others to use or release the data to any other person without the written authorization from the Center.

2.Purpose:
The provided data must be used for the purpose specified in the Data Request Form; any other use not specified in the form must receive additional or separate authorization.

3.Respondent Identifiers:
The Center is committed to protecting the identity of the respondents who provide information in its research. All analytical data sets (both qualitative and quantitative) released by the Data Unit MUST are stripped of respondent identifiers to protect the identity of the respondents. By accepting to use APHRC data, the user is pledging that he/she will not, under any circumstance, regenerate the identifiers or permit others to use the data to learn the identity of any individual, household or community included in any data set.

4.Confidentiality pledge:
The user will not use nor permit others to use the data to report any information in the data sets that could identify, directly or by inference, individuals or households.

5.Reporting of errors or inconsistencies:
The user will promptly notify the Head of the Statistics and Survey Unit any errors discovered in the data as soon as the errors are discovered.

6.Publications resulting from APHRC data:
The Center requires external collaborators to work with APHRC staff on all publications resulting from its data. In order to facilitate this, lead authors should send a detailed concept note of the paper (including the background, rationale, data, analytical methods, and preliminary findings) to the Principle Investigator (or Theme Leader) for the project (with a copy to the Director of Research), who will circulate the abstract to concerned researchers for possible expression of interest in participating in the publication as co-authors. Any exception to the involvement of APHRC staff should be approved by the Director of Research, APHRC.

7.Security:
The user will take responsibility for the security of the data by ensuring that the data are used and stored in a secure environment where access is password protected. This will ensure that non-authorized people should not have access to the data.

8.Loss of privilege to use data:
In the event that APHRC determines that the data user is in violation of the conditions for using the data, or if the user wishes to cancel this agreement, the user will destroy the data files provided to him/her. APHRC retains the right to revoke this agreement or informs publishers to withhold publication of any work based wholly or in part on its data if the conditions for using the data are violated.

9.Acknowledgement:
Any work/reports from this data must acknowledge APHRC as the source of these data. For example, the suggested acknowledgement for NUHDSS data is: "This research uses livelihoods data collected under the longitudinal Nairobi Urban Health and Demographic Surveillance System (NUHDSS) since 2006. The NUHDSS is carried out by the African Population and Health Research Center in two slums settlements (Korogocho and Viwandani) in Nairobi City."Additionally all funders, the study communities that provided the data, and staff who collected and analyzed or processed the data should be acknowledged.

10.Deposit of Reports/Papers:
The user should submit electronic and paper copies of all publications generated using APHRC data to the Policy Engagement and Communications Department, with copies to the Director of Research.

11.Change of contact details:
The user will promptly inform the Director of Research of any change in your personal details as contained on this data request form.
Citation requirement
Citation requirement
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download

Metadata production

Document ID
DDI-KEN-APHRC-GBV-2018-V1.0
Producers
Name Abbreviation Role
African Population and Health Research Center APHRC Documentation of the DDI
Date of Production
2024-09-20
Document version
Version 1.0 (September 2024)