Evidence map›Paper›PMID 31036657›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Ebola vaccination in the Democratic Republic of the Congo.

Chad R Wells, Abhishek Pandey, Alyssa S Parpia, Meagan C Fitzpatrick, Lauren A Meyers, Burton H Singer, Alison P Galvani

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

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  7. Toward optimal disease surveillance with graph-based active learning.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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

7 authors.

Chad R WellsCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.
Abhishek PandeyCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.
Alyssa S ParpiaCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.ORCID 0000-0002-9083-1929
Meagan C FitzpatrickCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.
Lauren A MeyersDepartment of Integrative Biology, University of Texas, Austin TX, 78712.
Burton H SingerEmerging Pathogens Institute, University of Florida, Gainesville, FL 32610 bhsinger@epi.ufl.edu.
Alison P GalvaniCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.

Funding

Impacts of Individual and Social Behavior on Influenza Dynamics and ControlU01GM087719 · NIGMS · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2009 to 2018
$6.3M
NIGMS NIH HHS U01 GM087719
6 · The paper itself

Abstract

Following the April 2018 reemergence of Ebola in a rural region of the Democratic Republic of the Congo (DRC), the virus spread to an urban center by early May. Within 2 wk of the first case confirmation, a vaccination campaign was initiated in which 3,017 doses were administered to contacts of cases and frontline healthcare workers. To evaluate the spatial dynamics of Ebola transmission and quantify the impact of vaccination, we developed a geographically explicit model that incorporates high-resolution data on poverty and population density. We found that while Ebola risk was concentrated around sites initially reporting infections, longer-range dissemination also posed a risk to areas with high population density and poverty. We estimate that the vaccination program contracted the geographical area at risk for Ebola by up to 70.4% and reduced the level of risk within that region by up to 70.1%. The early implementation of vaccination was critical. A delay of even 1 wk would have reduced these effects to 33.3 and 44.8%, respectively. These results underscore the importance of the rapid deployment of Ebola vaccines during emerging outbreaks to containing transmission and preventing global spread. The spatiotemporal framework developed here provides a tool for identifying high-risk regions, in which surveillance can be intensified and preemptive control can be implemented during future outbreaks.

Indexed as

Ebola VaccinesDemocratic Republic of the CongoHemorrhagic Fever, EbolaHumansTime FactorsVaccinationEbola VaccinesEbolavirusspatial analysisspatial interaction modelvaccine

Identifiers

PMID31036657
PMCPMC6525480

What OpenQuestion holds

Textmetadata
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.