Evidence map›Paper›PMID 38352600›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Yellow fever in Ghana: Predicting emergence and ecology from historical outbreaks.

Seth D Judson, Ernest Kenu, Trevon Fuller, Franklin Asiedu-Bekoe, Alberta Biritwum-Nyarko, Lee F Schroeder, David W Dowdy

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 2 countries.

Seth D JudsonDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID 0000-0001-9911-7839
Ernest KenuDepartment of Epidemiology, University of Ghana School of Public Health, Accra, Ghana.
Trevon FullerInstitute of the Environment and Sustainability, University of California Los Angeles, USA.
Franklin Asiedu-BekoeDisease Surveillance Department, Ghana Health Service, Accra, Ghana.
Alberta Biritwum-NyarkoPolicy, Planning, Monitoring & Evaluation Division, Ghana Health Service, Accra, Ghana.
Lee F SchroederDepartment of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
David W DowdyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Ghana Health Service · GHJohns Hopkins University · USUniversity of California, Los Angeles · USUniversity of Ghana · GHUniversity of Michigan · US

Funding

RESEARCH TRAINING IN MICROBIAL DISEASEST32AI007291 · NIAID · JOHNS HOPKINS UNIVERSITY · PI JOEL N BLANKSON, Sara Elizabeth Cosgrove · 1986 to 2026
$9.1M
Understanding and Improving the Effectiveness of Public Health Laboratory Networks for Infectious Diseases in GhanaR01AI136977 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DOWDY, DAVID WESLEY, SCHROEDER, LEE FREDERICK · 2019 to 2023
$3.4M
NIAID NIH HHS R01 AI136977NIAID NIH HHS T32 AI007291
6 · The paper itself

Abstract

Understanding the epidemiology and ecology of yellow fever in endemic regions is critical for preventing future outbreaks. Ghana is a high-risk country for yellow fever. In this study we estimate the epidemiology, ecological cycles, and areas at risk for yellow fever in Ghana based on historical outbreaks. We identify 2371 cases and 887 deaths (case fatality rate 37.4%) from yellow fever reported in Ghana from 1910 to 2022. Since implementation of routine childhood vaccination in 1992, the estimated mean annual number of cases decreased by 81% and the geographic distribution of yellow fever cases also changed. While there have been multiple large historical outbreaks of yellow fever in Ghana from the urban cycle, recent outbreaks have originated among unvaccinated nomadic groups in rural areas with the sylvatic/savanna cycles. Using machine learning and an ecological niche modeling framework, we predict areas in Ghana that are similar to where prior yellow fever outbreaks have originated based on temperature, precipitation, landcover, elevation, and human population density. We find differences in predictions depending on the ecological cycles of outbreaks. Ultimately, these findings and methods could be used to inform further subnational risk assessments for yellow fever in Ghana and other high-risk countries.

Identifiers

PMID38352600
PMCPMC10862978
OpenAlexW4391343708

What Socratic 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 Socratic graph.