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Modeling lesion transition dynamics to clinically characterize mpox patients with clade I MPXV in the Democratic Republic of the Congo

Abstract:

Coinciding with the global outbreak of clade IIb mpox virus (MPXV), the Democratic Republic of the Congo (DRC) recently experienced a rapid surge in mpox cases with clade I MPXV. On August 14, 2024, the WHO declared the continued cross-border spread of this clade in Africa a Public Health Emergency of International Concern (PHEIC). Clade I MPXV is known to be more fatal than clade IIb, but its clinical characteristics and prognosis differ between patients. Here, we used mathematical modelling to quantify temporal changes in total lesion counts during clade I MPXV infections, using data from a large cohort of patients with mpox in the DRC from 2007-2011. We further analyzed individuals’ clinical data to explore predictive biomarkers of high lesion counts. Our analysis indicates that patients with mpox can be stratified into two groups according to lesion severity, and that viral load in peripheral blood at symptom onset may serve as a predictor for this classification (AUC=0.70). Our estimates also suggest substantial individual heterogeneity in the time period for which patients have lesions, ranging from 20 to 65 days. Understanding the severity and duration of lesions in different patients, as characterized by our approach, may contribute to more tailored treatment strategies and control measures in ongoing clade I mpox outbreaks. 

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1126/scitranslmed.ads4773

Authors


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Funder identifier:
https://ror.org/03wnrjx87
Grant:
IES\R3\193037


Publisher:
American Association for the Advancement of Science
Journal:
Science Translational Medicine More from this journal
Volume:
17
Issue:
805
Article number:
eads4773
Publication date:
2025-07-02
Acceptance date:
2025-06-03
DOI:
EISSN:
1946-6242
ISSN:
1946-6234


Language:
English
Pubs id:
2127863
Local pid:
pubs:2127863
Deposit date:
2025-06-03
ARK identifier:

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