Introduction: Influenza virus infections cause significant morbidity, and the unique ability of these viruses to undergo antigenic drift and shift means that it is critical for current laboratory assays to keep pace with these changes for accurate diagnosis. New subtypes have the potential to evolve into pandemics hence accurate virus subtyping is also essential.
Areas Covered: In this article, the authors review the current techniques available to detect influenza virus.
Expert Opinion: The biggest gains in improving on influenza diagnostics may lie in reappraising our current approach and optimizing all existing steps in influenza detection: pre-analytical, analytical, post-analytical. In addition, we must foster close collaboration between governments, surveillance networks and frontline diagnostic laboratories, and utilize advances in information technology to facilitate these interactions and to disseminate crucial information.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1517/17530059.2012.642860 | DOI Listing |
Open Forum Infect Dis
January 2025
Harvard Medical School, Boston, Massachusetts, USA.
Background: Infections by and influenza viruses are vaccine-preventable diseases causing great morbidity and mortality. We evaluated pneumococcal and influenza vaccination practices during pre-international travel health consultations.
Methods: We evaluated data on pretravel visits over a 10-year period (1 July 2012 through 31 June 2022) from 31 sites in Global TravEpiNet (GTEN), a consortium of US healthcare facilities providing pretravel health consultations.
Sci Rep
January 2025
Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
A dynamics informed neural networks (DINNs) incorporating the susceptible-exposed-infectious-recovered-vaccinated (SEIRV) model was developed to enhance the understanding of the temporal evolution dynamics of infectious diseases. This work integrates differential equations with deep neural networks to predict time-varying parameters in the SEIRV model. Experimental results based on reported data from China between January 1, and December 1, 2022, demonstrate that the proposed dynamics informed neural networks (DINNs) method can accurately learn the dynamics and predict future states.
View Article and Find Full Text PDFHealth Secur
January 2025
Robert A. Johnson, PhD, is Director, Medical Countermeasures Programs, and Gary L. Disbrow, PhD, is Director, Center for Biomedical Advanced Research and Development Authority (BARDA), Washington, DC. Terence M. Barnhart, PhD, is Senior Strategy Implementation Leader, Tunnell Government Services, Inc. (Contractor Supporting BARDA), Washington, DC.
From influenza to COVID-19, emerging infectious diseases have taken a heavy toll on lives and resources. Emerging infectious diseases represent one of the largest threats to national security. The primary mission of the Center for Biomedical Advanced Research and Development Authority (BARDA), within the US Administration for Strategic Preparedness and Response, is to support the advanced development of medical countermeasures (MCMs) for public health security threats, including select infectious diseases.
View Article and Find Full Text PDFRev Panam Salud Publica
January 2025
Ministry of Health Brasília Brazil Ministry of Health, Brasília, Brazil.
Objective: To describe the Brazilian experience of responding to public health emergencies in 2023, the organizational structure, and epidemiological characteristics.
Methods: Three emergencies (case studies) that occurred during the study year were analyzed according to the actions implemented during the response and the impacts on the population. The public health emergencies were summarized and analyzed through research on official documents and websites of the Ministry of Health and local health authorities.
J R Soc Interface
January 2025
Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
Influenza forecasts could aid public health response as shown for temperate regions, but such efforts are more challenging in the tropics and subtropics due to more irregular influenza activities. Here, we built six forecast approaches for influenza in the (sub)tropics, with six model forms designed to model seasonal infection risk (i.e.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!