MISMS: using data analysis to inform disease prevention
MISMS is an 18-year program with a mission to advance evidence-based policies for pandemic preparedness and influenza control strategies in the US and other countries. Originally called the Multinational Influenza Seasonal Mortality Study, MISMS began in 2001 with a focus on developing mathematical and statistical models of transmission dynamics and disease burden of influenza in varying climates. The program is led by a core team of scientists at the Division of International Epidemiology and Population Studies (DIEPS) at the Fogarty International Center (FIC), US National Institutes of Health.
Since its inception, MISMS has expanded to include (a) molecular epidemiology using genetic sequence data, (b) viral evolution at the human-animal interface, and (c) study of other important human respiratory pathogens, such as RSV. MISMS staff annually organize training workshops to teach methods of data analysis globally, with a focus on low- and middle-income countries, and lead global collaborations to facilitate data-sharing and large-scale studies of disease dynamics.
MISMS training workshop in South Africa, 2018
Examples of how MISMS research has impacted policy decision-making:
- Retargeting influenza vaccine campaigns towards children, who are key vectors of transmission in communities, providing indirect protection to seniors who typically have low immune responses to vaccination and high mortality.
- Advising individual countries in tropical and sub-tropical regions on whether to use the Northern hemisphere or Southern hemisphere formulation of the influenza vaccine, based on studies of the seasonal timing of their influenza epidemics, which tend to be more variable than the distinct winter epidemics experienced in temperate regions.
- Improving biosecurity in zoos and on farms targeting the role of humans in transmitting influenza viruses to animals, given studies showing how frequently humans spread pandemic H1N1 viruses to swine, in particular, but also zoo animals.