Finding patient zero in susceptible-infectious-susceptible epidemic processes

Finding the source of an epidemic is important, because correct source identification can help to stop a budding epidemic or prevent new ones. We investigate the backward equations of the N-intertwined mean-field approximation susceptible-infectious-susceptible (SIS) process. The backward equations allow us to trace the epidemic back to its source on networks of sizes up to at least N=1500. Additionally, we show that the source of the "more realistic" Markovian SIS model cannot feasibly be found, even in a "best-case scenario," where the infinitesimal generator Q, which completely describes the epidemic process and the underlying contact network, is known. The Markovian initial condition s(0), which reveals the epidemic source, can be found analytically when the viral state vector s(t) is known at some time t as s(0)=s(t)e^{-Qt}. However, s(0) can hardly be computed, except for small times t. The numerical errors are largely due to the matrix exponential e^{-Qt}, which is severely ill-behaved.

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Publication Details

Journal
Physical review. E
Published
2024-10-18
DOI
https://doi.org/10.1103/physreve.110.044308
Citations
2
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.79

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article

Finding patient zero in susceptible-infectious-susceptible epidemic processes

Piet Van Mieghem, Robin Persoons
2 citations
Physical review. E
COVID-19 epidemiological studies
0.79
article

Finding patient zero in susceptible-infectious-susceptible epidemic processes

Piet Van Mieghem, Robin Persoons
article en
2 citations

Abstract

Finding the source of an epidemic is important, because correct source identification can help to stop a budding epidemic or prevent new ones. We investigate the backward equations of the N-intertwined mean-field approximation susceptible-infectious-susceptible (SIS) process. The backward equations allow us to trace the epidemic back to its source on networks of sizes up to at least N=1500. Additionally, we show that the source of the "more realistic" Markovian SIS model cannot feasibly be found, even in a "best-case scenario," where the infinitesimal generator Q, which completely describes the epidemic process and the underlying contact network, is known. The Markovian initial condition s(0), which reveals the epidemic source, can be found analytically when the viral state vector s(t) is known at some time t as s(0)=s(t)e^{-Qt}. However, s(0) can hardly be computed, except for small times t. The numerical errors are largely due to the matrix exponential e^{-Qt}, which is severely ill-behaved.

Physical review. EVol. 110(4)
Delft University of Technology (NL)
European Research Council, Horizon 2020
Good health and well-being
Openalex Percentile: Top 30%
COVID-19 epidemiological studies
0.79
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Finding patient zero in susceptible-infectious-susceptible epidemic processes — Piet Van Mieghem, Robin Persoons · Physical review. E (2024) | TGRS Research Map | TGRS