ArticleMicroorganisms2026
Infection History Shapes Co-Epidemic Dynamics: A Transmission Source-Pathway Decomposition for COVID-19 and Influenza.
Article in Microorganisms, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Who cites it
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The concurrent circulation of SARS-CoV-2 and influenza presents a complex immunological landscape. While biological evidence suggests that prior or current infection with one virus can alter susceptibility to the other, conventional epidemiological models often obscure these effects by aggregating co-infected populations into a single compartment. This structural simplification limits our ability to quantify how infection history shapes population-level transmission dynamics. We developed a stratified, deterministic co-infection model that explicitly distinguishes between single, concurrent, and sequential infections by accounting for sequence-dependent heterogeneity in susceptibility and transmissibility. Our primary innovation is a transmission source-pathway decomposition framework that mathematically attributes the rate of new infections to its specific transmission source (i.e., which infectious subpopulation is generating the transmission: the singly-infected, co-infected, or sequentially-infected class) and transmission pathway (i.e., which susceptibility class is receiving new infections: fully susceptible individuals, or those with prior immunity, or those with active co-infection). This framework accounts for altered susceptibility and transmissibility dependent on infection history. Our model-based analysis reveals a profound, sequence-driven asymmetry in transmission. In a baseline co-epidemic scenario, COVID-19 is predominantly driven by a sequential source: individuals who contracted COVID-19
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