Dataset Information

Untangling the Interplay between Epidemic Spread and Transmission Network Dynamics.

ABSTRACT: The epidemic spread of infectious diseases is ubiquitous and often has a considerable impact on public health and economic wealth. The large variability in the spatio-temporal patterns of epidemics prohibits simple interventions and requires a detailed analysis of each epidemic with respect to its infectious agent and the corresponding routes of transmission. To facilitate this analysis, we introduce a mathematical framework which links epidemic patterns to the topology and dynamics of the underlying transmission network. The evolution, both in disease prevalence and transmission network topology, is derived from a closed set of partial differential equations for infections without allowing for recovery. The predictions are in excellent agreement with complementarily conducted agent-based simulations. The capacity of this new method is demonstrated in several case studies on HIV epidemics in synthetic populations: it allows us to monitor the evolution of contact behavior among healthy and infected individuals and the contributions of different disease stages to the spreading of the epidemic. This gives both direction to and a test bed for targeted intervention strategies for epidemic control. In conclusion, this mathematical framework provides a capable toolbox for the analysis of epidemics from first principles. This allows for fast, in silico modeling--and manipulation--of epidemics and is especially powerful if complemented with adequate empirical data for parameterization.

SUBMITTER: Kamp C

PROVIDER: S-EPMC2987842 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Untangling the Interplay between Epidemic Spread and Transmission Network Dynamics.

Kamp Christel C

PLoS computational biology 20101118 11

The epidemic spread of infectious diseases is ubiquitous and often has a considerable impact on public health and economic wealth. The large variability in the spatio-temporal patterns of epidemics prohibits simple interventions and requires a detailed analysis of each epidemic with respect to its infectious agent and the corresponding routes of transmission. To facilitate this analysis, we introduce a mathematical framework which links epidemic patterns to the topology and dynamics of the under ...[more]

PMID: 21124951

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Project description:UnlabelledNext-generation sequencing technology is now being increasingly applied to study the within- and between-host population dynamics of viruses. However, information on avian influenza virus evolution and transmission during a naturally occurring epidemic is still limited. Here, we use deep-sequencing data obtained from clinical samples collected from five industrial holdings and a backyard farm infected during the 2013 highly pathogenic avian influenza (HPAI) H7N7 epidemic in Italy to unravel (i) the epidemic virus population diversity, (ii) the evolution of virus pathogenicity, and (iii) the pathways of viral transmission between different holdings and sheds. We show a high level of genetic diversity of the HPAI H7N7 viruses within a single farm as a consequence of separate bottlenecks and founder effects. In particular, we identified the cocirculation in the index case of two viral strains showing a different insertion at the hemagglutinin cleavage site, as well as nine nucleotide differences at the consensus level and 92 minority variants. To assess interfarm transmission, we combined epidemiological and genetic data and identified the index case as the major source of the virus, suggesting the spread of different viral haplotypes from the index farm to the other industrial holdings, probably at different time points. Our results revealed interfarm transmission dynamics that the epidemiological data alone could not unravel and demonstrated that delay in the disease detection and stamping out was the major cause of the emergence and the spread of the HPAI strain.ImportanceThe within- and between-host evolutionary dynamics of a highly pathogenic avian influenza (HPAI) strain during a naturally occurring epidemic is currently poorly understood. Here, we perform for the first time an in-depth sequence analysis of all the samples collected during a HPAI epidemic and demonstrate the importance to complement outbreak investigations with genetic data to reconstruct the transmission dynamics of the viruses and to evaluate the within- and between-farm genetic diversity of the viral population. We show that the evolutionary transition from the low pathogenic form to the highly pathogenic form occurred within the first infected flock, where we identified haplotypes with hemagglutinin cleavage site of different lengths. We also identify the index case as the major source of virus, indicating that prompt application of depopulation measures is essential to limit virus spread to other farms.

Dataset Information

Untangling the Interplay between Epidemic Spread and Transmission Network Dynamics.

Publications

Untangling the Interplay between Epidemic Spread and Transmission Network Dynamics.

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