Dataset Information

Epidemic dynamics and antigenic evolution in a single season of influenza A.

ABSTRACT: We use a mathematical model to study the evolution of influenza A during the epidemic dynamics of a single season. Classifying strains by their distance from the epidemic-originating strain, we show that neutral mutation yields a constant rate of antigenic evolution, even in the presence of epidemic dynamics. We introduce host immunity and viral immune escape to construct a non-neutral model. Our population dynamics can then be framed naturally in the context of population genetics, and we show that departure from neutrality is governed by the covariance between a strain's fitness and its distance from the original epidemic strain. We quantify the amount of antigenic evolution that takes place in excess of what is expected under neutrality and find that this excess amount is largest under strong host immunity and long epidemics.

SUBMITTER: Boni MF

PROVIDER: S-EPMC1560306 | biostudies-literature | 2006 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Epidemic dynamics and antigenic evolution in a single season of influenza A.

Boni Maciej F MF Gog Julia R JR Andreasen Viggo V Feldman Marcus W MW

Proceedings. Biological sciences 20060601 1592

We use a mathematical model to study the evolution of influenza A during the epidemic dynamics of a single season. Classifying strains by their distance from the epidemic-originating strain, we show that neutral mutation yields a constant rate of antigenic evolution, even in the presence of epidemic dynamics. We introduce host immunity and viral immune escape to construct a non-neutral model. Our population dynamics can then be framed naturally in the context of population genetics, and we show ...[more]

PMID: 16777717

Similar Datasets

Project description:BACKGROUND:Due to the high rate of antigenic variation of influenza virus, seasonal characterization of the virus is crucial to assess and monitor the emergence of new pathogenic variants and hence formulate effective control measures. However, no study has yet been conducted in Mozambique to assess genetic, antigenic and antiviral susceptibility profile of influenza virus. METHODS:A subset of samples (n = 20) from influenza positive children detected in two hospitals in Maputo city during 2015 season as part of the implementation of influenza surveillance system, were selected. The following assays were performed on these samples: antigenic characterization by hemagglutination inhibition assay, genetic characterization by Sanger sequencing of hemagglutinin (HA) and neuraminidase (NA) and susceptibility to oseltamivir and zanamivir (NA inhibitors) by enzymatic assay. RESULTS:The A(H1N1)pdm09 subtype viruses remained closely related antigenically and genetically to the 2016 vaccine virus A/California/7/2009 and other widely distributed viruses belonging to genetic group 6B. The majority of influenza A(H3N2) viruses studied were antigenically similar to the 2016-2017 vaccine virus, A/Hong Kong/4801/2014, and their HA and NA gene sequences fell into genetic subclade 3C.2a being closely related to viruses circulating in southern Africa. The influenza B viruses were antigenically similar to the 2016 season vaccine virus and HA sequences of all three fell into the B/Yamagata-lineage, clade 3, but contained NA genes of the B/Victoria-lineage. All tested viruses were sensitive to oseltamivir and zanamivir. CONCLUSION:Overall, all Mozambican influenza A and B viruses were most closely related to Southern African viruses and all were sensitive to oseltamivir and zanamivir. These findings suggest the existence of an ecological niche of influenza viruses within the region and hence highlighting the need for joint epidemiologic and virologic surveillance to monitor the evolution of influenza viruses.

Dataset Information

Epidemic dynamics and antigenic evolution in a single season of influenza A.

Publications

Epidemic dynamics and antigenic evolution in a single season of influenza A.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets