# "Chanjo Kwa Wakati" - Leveraging community health workers and a responsive digital health system to improve vaccination coverage and timeliness in rural settings

> **NIH NIH R01** · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · 2022 · $638,030

## Abstract

Ensuring equitable vaccinations is critical for protecting all children against preventable and potentially
dangerous infections such as polio, diphtheria, and measles. Yet, numerous studies have highlighted low
vaccination coverage and timeliness, particularly among children from resource-limited settings. For example, in
Tanzania, only 68% of children receive all basic vaccines that are recommended in the first year of life. Reasons
for vaccination inequities are multifaceted; they include low caregiver knowledge about vaccines, and challenges
with health service delivery and access. Health service interruptions during the global COVID-19 pandemic have
further restricted opportunities for caregiver education, impacted vaccine access, and exacerbated vaccination
inequities. Approaches that optimally utilize limited health workforce capacity and rapidly evolving digital health
capacity for remote healthcare in resource-limited settings hold great potential for mitigating childhood
vaccination inequities. We recently completed (1) a Fogarty-funded study (R21TW010262) that demonstrated
the feasibility and efficacy of mobile phone-based reminders and conditional financial incentives for improving
the coverage and timeliness of childhood vaccinations, and (2) a community health worker (CHW) intervention
that was shown to be acceptable for mitigating caregiver knowledge gaps about childhood vaccines. Building on
this prior work and with support from Tanzania’s National Immunization and Vaccine Development program, we
propose to evaluate an integrated, community-based, digital intervention for promoting equity in childhood
vaccinations. The outreach and educational intervention, called ”Chanjo Kwa Wakati” (“timely vaccination”), is
targeted toward recent mothers and comprises a combination of CHW outreach and low-cost digital strategies
(autonomous mobile phone-based vaccination promotion messages, reminders, stockout notifications, and
incentive offers for timely vaccinations). In Aim 1, we will evaluate the effectiveness of Chanjo Kwa Wakati in
promoting the coverage and timeliness of childhood vaccinations in a Type I effectiveness implementation hybrid
trial. The trial will involve the staggered implementation of the intervention across catchment areas of 40 rural
health facilities in two predominantly rural regions of Tanzania with large numbers of un- or under-vaccinated
children. Vaccination outcomes will be analyzed for children born to 1200 women participating in the trial. In Aim
2, we will evaluate implementation factors associated with variations in intervention effectiveness, analyze the
cost effectiveness of the intervention, and develop an implementation blueprint to guide scale-up to other
settings. In Aim 3, we will evaluate the feasibility and potential efficacy of a machine learning approach for
proactively identifying children at risk of non- or delayed vaccinations and validate predictive models using
vaccination data gathered in A...

## Key facts

- **NIH application ID:** 10502467
- **Project number:** 1R01HD110844-01
- **Recipient organization:** UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
- **Principal Investigator:** Esther Stanslaus Ngadaya
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $638,030
- **Award type:** 1
- **Project period:** 2022-09-18 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10502467

## Citation

> US National Institutes of Health, RePORTER application 10502467, "Chanjo Kwa Wakati" - Leveraging community health workers and a responsive digital health system to improve vaccination coverage and timeliness in rural settings (1R01HD110844-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10502467. Licensed CC0.

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