ArticlePLOS global public health2025
Use of the Chainchecker application: Uganda's experience during the 2022 Sudan Virus Disease outbreak.
Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
On September 20, 2022, the Uganda Ministry of Health declared an outbreak of Sudan Virus Disease (SVD). As the outbreak grew, it became imperative to quickly visualize and analyze chains of disease transmission. Determining epidemiological links between cases is critical for outbreak control as incorrect linkages may result in missed case detection and undetected disease transmission. We describe the Uganda Ministry of Health's experience using Chainchecker, a computer application designed to visualize and verify transmission chain data. To use Chainchecker, a line list documenting the epidemiological details associated with individual cases is uploaded to the application. To verify epidemiologic linkages, the application calculates the exposure windows for each case based on user-defined incubation periods and dates of symptom onset. If genetic sequencing data is available, Chainchecker can overlay genetic distance data on top of the epidemiologic data. Chainchecker can also provide visualizations of hospitalization data, which can highlight potential instances of nosocomial disease transmission. Using the Chainchecker application, the case investigation team was able to connect 11 previously unlinked cases to the larger chain of disease transmission. The use of the application also led to the identification and correction of transmission chain errors for 13 SVD cases and the identification of 5 potential instances of nosocomial transmission. The use of the Chainchecker application in Uganda during the 2022 SVD outbreak allowed the response teams to rectify critical errors in transmission chains. Countries prone to Ebola Disease (EBOD) outbreaks should consider incorporating Chainchecker as an element of EBOD preparedness and response.
Identifiers
What OpenQuestion holds
Registered trials
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.