Evidence map›Paper›PMID 38726228›Full record

ArticleFrontiers in public health2024

Clinical trial capacity building in a pandemic-outcome of a rapid site readiness project in Latin America.

Sue Ann Costa Clemens, Isabela Gonzalez, Daniele Sereni, Ralf Clemens

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Sue Ann Costa ClemensInstitute for Global Health, University of Siena, Siena, Italy.
Isabela GonzalezInstitute for Global Health, University of Siena, Siena, Italy.
Daniele SereniWit I.C.T. Consulting, Siena, Italy.
Ralf ClemensInternational Vaccine Institute IVI BOT, Seoul, Republic of Korea.

Funding

Gates Foundation INV-021464
6 · The paper itself

Abstract

Background: Latin America (Latam) has a tradition of large-scale vaccine trials. Because of fluctuating demand, many sites have downsized their infrastructure. Therefore, BMGF launched a clinical trial site-readiness initiative early in the coronavirus-2019 (COVID-19) pandemic including Latam countries between August and September 2020. This survey evaluated clinical development performance measures pre/post initiative (September 2022). Results: 20/21 prequalified sites participated in COVID-19 vaccine/drug development trials. 156 clinical trials (140 COVID-19 vaccine/drug trials) were initiated in the 2 years since prequalification, compared to 176 in the 5 years before. 33,428/37,810 participants were included in COVID-19 programs. The number of enrolled subjects/day across sites quadrupled from 15 (1-35) to 63 (5-300). The dropout rate was 6.8%. Study approval timelines were reduced from 60 (12-120) to 35 (5-90) days. Mean qualified staff was increased from 24 (6-80) to 88 (22-180). Conclusion: Clinical trial sites across Latam were successfully prequalified to participate in COVID-19 developments. For the 100 days mission of vaccine availability in a new pandemic sufficient and well-trained clinical trial sites readily available are essential. This is only achievable if sites-especially in low/middle-income countries-are maintained active through a constant flow of vaccine studies.

Indexed as

Capacity BuildingClinical Trials as TopicCOVID-19COVID-19 VaccinesHumansLatin AmericaPandemicsSARS-CoV-2Surveys and QuestionnairesCOVID-19 Vaccinesclinical developmentclinical trial siteCOVID-19Latin Americasite capacity building initiativesuccess metrics

Identifiers

PMID38726228
PMCPMC11079433

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.