Evidence map›Paper›PMID 35914832›Full record

ArticleBMJ global health2022

Epidemiological impact and cost-effectiveness analysis of COVID-19 vaccination in Kenya.

Stacey Orangi, John Ojal, Samuel Pc Brand, Cameline Orlendo, Angela Kairu, Rabia Aziza, Morris Ogero, Ambrose Agweyu, George M Warimwe, Sophie Uyoga and 15 more

Abstract read
In one paragraph

Article in BMJ global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
–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

22 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
  5. Article
  6. Rethinking the evidence on COVID-19 in Africa.The Lancet. Infectious diseases · 2025
    Review
  7. Article
  8. Article
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  11. How does geographical diversity shape vaccine efficacy?Clinical and experimental vaccine research · 2024
    Review
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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

25 authors.

Stacey Orangi *Health Economics Research Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya sorangi@kemri-wellcome.org jojal@kemri-wellcome.org.ORCID 0000-0002-3236-5229
John Ojal *Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya sorangi@kemri-wellcome.org jojal@kemri-wellcome.org.
Samuel Pc BrandThe Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, UK.
Cameline OrlendoKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Angela KairuHealth Economics Research Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.ORCID 0000-0002-0965-4460
Rabia AzizaThe Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, UK.
Morris OgeroKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Ambrose AgweyuKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.ORCID 0000-0001-8760-1279
George M WarimweKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Sophie UyogaKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Edward OtienoKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Lynette I Ochola-OyierKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Charles N AgotiKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Kadondi KaseraMinistry of Health, Government of Kenya, Nairobi, Kenya.
Patrick AmothMinistry of Health, Government of Kenya, Nairobi, Kenya.
Mercy MwangangiMinistry of Health, Government of Kenya, Nairobi, Kenya.
Rashid AmanMinistry of Health, Government of Kenya, Nairobi, Kenya.
Wangari Ng'ang'aPresidential Policy & Strategy Unit, The Presidency, Government of Kenya, Nairobi, Kenya.
Ifedayo Mo AdetifaKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
J Anthony G ScottKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Philip BejonKenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Matt J KeelingThe Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, UK.
Stefan FlascheThe Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.
D James Nokes *Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, Kenya.
Edwine Barasa *Health Economics Research Unit, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya.ORCID 0000-0001-5793-7177

Funding

Department of HealthWellcome Trust 208812/Z/17/Z
6 · The paper itself

Abstract

backgroundA few studies have assessed the epidemiological impact and the cost-effectiveness of COVID-19 vaccines in settings where most of the population had been exposed to SARS-CoV-2 infection.

methodsWe conducted a cost-effectiveness analysis of COVID-19 vaccine in Kenya from a societal perspective over a 1.5-year time frame. An age-structured transmission model assumed at least 80% of the population to have prior natural immunity when an immune escape variant was introduced. We examine the effect of slow (18 months) or rapid (6 months) vaccine roll-out with vaccine coverage of 30%, 50% or 70% of the adult (>18 years) population prioritising roll-out in those over 50-years (80% uptake in all scenarios). Cost data were obtained from primary analyses. We assumed vaccine procurement at US$7 per dose and vaccine delivery costs of US$3.90-US$6.11 per dose. The cost-effectiveness threshold was US$919.11.

findingsSlow roll-out at 30% coverage largely targets those over 50 years and resulted in 54% fewer deaths (8132 (7914-8373)) than no vaccination and was cost saving (incremental cost-effectiveness ratio, ICER=US$-1343 (US$-1345 to US$-1341) per disability-adjusted life-year, DALY averted). Increasing coverage to 50% and 70%, further reduced deaths by 12% (810 (757-872) and 5% (282 (251-317) but was not cost-effective, using Kenya's cost-effectiveness threshold (US$919.11). Rapid roll-out with 30% coverage averted 63% more deaths and was more cost-saving (ICER=US$-1607 (US$-1609 to US$-1604) per DALY averted) compared with slow roll-out at the same coverage level, but 50% and 70% coverage scenarios were not cost-effective.

interpretationWith prior exposure partially protecting much of the Kenyan population, vaccination of young adults may no longer be cost-effective.

Indexed as

COVID-19COVID-19 VaccinesCost-Benefit AnalysisHumansKenyaSARS-CoV-2Young AdultCOVID-19 VaccinesCOVID-19EpidemiologyHealth economicsVaccines

Identifiers

PMID35914832
PMCPMC9344598

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Registered trials

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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.