In this paper we propose the use of a random network model for simulating and understanding the epidemics of influenza A(H1N1). The proposed model is used to simulate the transmission process of influenza A(H1N1) in a community region of Venezuela using distributed computing in order to accomplish many realizations of the underlying random process. These large scale epidemic simulations have recently become an important application of high-performance computing. The network model proposed performs better than the traditional epidemic model based on ordinary differential equations since it adjusts better to the irregularity of the real world data. In addition, the network model allows the consideration of many possibilities regarding the spread of influenza at the population level. The results presented here show how well the SEIR model fits the data for the AH1N1 time series despite the irregularity of the data and returns parameter values that are in good agreement with the medical data regarding AH1N1 influenza virus. This versatile network model approach may be applied to the simulation of the transmission dynamics of several epidemics in human networks. In addition, the simulation can provide useful information for the understanding, prediction and control of the transmission of influenza A(H1N1) epidemics.
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http://dx.doi.org/10.1016/j.actatropica.2014.12.008 | DOI Listing |
Int J Infect Dis
December 2024
Instituto de Salud Pública de Navarra, Pamplona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.
Objective: We estimated the influenza vaccination effectiveness (IVE) in preventing medical consultations and hospitalizations due to influenza during the 2023/24 season.
Methods: Two test-negative case-control studies analyzed patients who consulted primary healthcare or were hospitalized for respiratory symptoms and were tested for influenza by PCR in the 2023/24 season in Navarre, Spain. Influenza vaccination status in the current and previous seasons was compared between confirmed influenza cases and test-negative controls.
Heliyon
December 2024
Virology Laboratory, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, (icddr,b), Bangladesh.
According to sparse information from various countries, the seasonal influenza virus circulation has drastically decreased during the COVID-19 pandemic. Here, we show the cross-reactivity of anti-SARS-CoV-2 antibodies against influenza viruses. Plasma samples were collected from 311 SARS-CoV-2 infected individuals.
View Article and Find Full Text PDFVaccine
January 2025
Center of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.
J Biomol Struct Dyn
December 2024
Department of Biological Sciences, Birla Institute of Technology and Science, Pilani, Hyderabad, India.
Influenza A (H1N1) virus has been one of the most common threats to humankind since 1918. The viral genome is frequently substituted, leading to new strains and recurrent pandemics. Despite knowing the effects of single amino acid substitutions on individual viral proteins, the effects of collective substitutions on viral infection remain elusive.
View Article and Find Full Text PDFLancet Infect Dis
November 2024
Moderna, Cambridge, MA, USA.
Background: Coadministration of a respiratory syncytial virus (RSV) vaccine with seasonal influenza or SARS-CoV-2 vaccines could reduce health-care visits and increase vaccination uptake in older adults who are at high risk for severe respiratory disease. The RSV mRNA-1345 vaccine demonstrated efficacy against RSV disease with acceptable safety in the ConquerRSV trial in adults aged 60 years and older. We aimed to evaluate the safety and immunogenicity of mRNA-1345 coadministered with a seasonal influenza vaccine or SARS-CoV-2 mRNA vaccine.
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