ArticleVaccines2023
Harnessing the Power of Collaboration to Expand the Coverage and Equity of COVID-19 Vaccinations in India: A Community Collaboration Model.
Article in Vaccines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Life Course Vaccination Continuum (LCVAC): An Expert Consensus on Life Course Vaccination in India.Cureus · 2026Review
- Building trust during crises by engaging with existing distrust.Frontiers in public health · 2025Article
- Mapping knowledge landscapes and emerging trends of Marburg virus: A text-mining study.Heliyon · 2024Article
- Public health partnerships with faith-based organizations to support vaccination uptake among minoritized communities: A scoping review.PLOS global public health · 2024Article
- Partnership coordination for optimized COVID-19 vaccination: a case study of Benue and Niger states.Frontiers in public health · 2024Article
- Future Prospects, Approaches, and the Government's Role in the Development of a Hepatitis C Virus Vaccine.Pathogens (Basel, Switzerland) · 2023Review
- Influenza immunization of healthcare personnel in the post-COVID-19 pandemic era: Still a lot to do!Vaccine: X · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
Early in 2021, India embarked on the uphill journey of the COVID-19 vaccination of the largest population group in the world in a prioritized manner and in the shortest possible time. Considering the endless variety of geography and diverse socio-economic demographic, religious, and community contexts, there was a high likelihood of certain population subgroups with known vulnerabilities facing inequities, which were anticipated to be further accentuated by a digital divide. This necessitated devising solutions for such communities in a localized manner to aid the local government in breaking the service access and uptake barriers with an inclusive approach. To bridge this vital gap, the Momentum Routine Immunization Transformation and Equity project implemented a three-tiered collaboration, viz., government, non-governmental organizations (NGOs), and a wide range of vulnerable and at-risk communities, utilizing knowledge exchange and use of data. The project implemented localization strategies through the NGOs for community engagement in conjunction with government vaccination teams to universalize COVID-19 vaccination uptake up to the last mile. The collaboration resulted in reaching close to 50 million beneficiaries through messaging and facilitated the administration of more than 14 million vaccine doses, including 6.1 million doses for vulnerable and marginalized communities in 18 States and Union territories in India, along with suggesting implications for public health practice and research.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.