Evidence map›Paper›PMID 27453836›Full record

ReviewJournal of family medicine and primary care

Vaccine epidemiology: A review.

Chandrakant Lahariya

Abstract readReview
In one paragraph

Review in Journal of family medicine and primary care. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Observational
  4. How does geographical diversity shape vaccine efficacy?Clinical and experimental vaccine research · 2024
    Review
  5. Review
  6. Seroprevalence and Endemic Status ofJournal of arthropod-borne diseases · 2024
    Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Effect of vaccination against Covid-19 one year after its introduction in Brazil.Tropical diseases, travel medicine and vaccines · 2022
    Article
  16. Article
  17. Article
  18. Review
  19. Nasal vaccine as a booster shot: a viable solution to restrict pandemic?Clinical and experimental vaccine research · 2022
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Chandrakant Lahariya(Formerly at) Department of Community Medicine, Gajara Raja Medical College, Gwalior, Madhya Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review article outlines the key concepts in vaccine epidemiology, such as basic reproductive numbers, force of infection, vaccine efficacy and effectiveness, vaccine failure, herd immunity, herd effect, epidemiological shift, disease modeling, and describes the application of this knowledge both at program levels and in the practice by family physicians, epidemiologists, and pediatricians. A case has been made for increased knowledge and understanding of vaccine epidemiology among key stakeholders including policy makers, immunization program managers, public health experts, pediatricians, family physicians, and other experts/individuals involved in immunization service delivery. It has been argued that knowledge of vaccine epidemiology which is likely to benefit the society through contributions to the informed decision-making and improving vaccination coverage in the low and middle income countries (LMICs). The article ends with suggestions for the provision of systematic training and learning platforms in vaccine epidemiology to save millions of preventable deaths and improve health outcomes through life-course.

Indexed as

Child healthepidemiologylife coursevaccines

Identifiers

PMID27453836
PMCPMC4943153

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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.