Researchers have developed a mathematical framework to estimate the value of investing in developing and conserving an antibiotic to mitigate the burden of bacterial infections caused by resistant Staphylococcus aureus during a pandemic influenza outbreak.
It’s not just H5N1 that has dissipated. The virus’s nearly-as-scary cousin, H7N9, emerged in China in 2013 and sickened more than 1,500 people in China over five years, killing roughly 40 percent of them.
The idea is to generate poultry that cannot get flu and would form a "buffer” between wild birds and humans.
As part of our nation’s overall pandemic preparedness strategy, the US Department of Health and Human Services (HHS) set a preparedness goal of establishing and maintaining a stockpile of bulk vaccine antigen and adjuvants for influenza viruses with pandemic potential to vaccinate 26 million people immediately after a pandemic is declared.
The US Biomedical Advanced Research and Development Authority (BARDA) conducted a randomized, double-blinded Phase 2 clinical study with the oldest stockpiled influenza A(H5N1) antigen, stored over the previous 10–12 years administered with or without MF59® adjuvant, stored over the previous 2–7 years at the time of vaccination.
Since 2013, the H7N9 avian influenza A virus (AIV) has caused human infections and to the extent of now surpassing H5N1.
The pandemic occurred before the age of molecular virology. Back then it wasn’t even known what caused influenza; influenza viruses were first detected in 1930. In the decades that followed, though, it was recognized that the pandemic was caused by an influenza A virus of the H1N1 subtype. In the late 1990s, U.S. army scientists found and deciphered the virus’s genetic code.
The idea that major cities and their airports are important drivers of worldwide contagion makes intuitive sense, and it’s supported by mathematical models. But models don’t always reflect reality.
This software allows laboratory directors and emergency planners to estimate the daily number of specimens expected to be received for testing and the laboratory’s testing capacity during each pandemic stage.
This software allows users to simulate the effects of various interventions – including vaccination, school closure, facemasks, and patient isolation – on the spread of an influenza pandemic.