PLOS Medicine recently published an open-access article on incorporating decision analysis into infectious disease planning and response. Below is the introduction to the article, which can be viewed in full here.
Planning is critical to mitigating the sudden and potentially catastrophic impact of an infectious disease pandemic on society, but it is far from straightforward [1]. During a pandemic, decisions will be made under rapidly changing, uncertain conditions, with limited (if any) prior experience.
The 1918 H1N1 pandemic was estimated to have caused the death of tens of millions of people worldwide. It is encouraging that antivirals and vaccines available to us today would help to reduce the impact of a similar pandemic event, yet with cities and countries increasingly connected by air travel, we will likely be faced with a pathogen capable of spreading rapidly across the globe. The 2009 pandemic H1N1 (A(H1N1)pdm09), a virus estimated to be less transmissible than the 1918 strain [2], spread to 74 countries within just 4 months [3].
Mathematical and statistical models are important tools for pandemic planning and response. Although it is unlikely that we will ever be able to predict precisely where or when the next pandemic will occur [4], once an outbreak of pandemic potential has been identified, models have enormous potential to improve the effectiveness of our response. They can be used to synthesize the available data to provide enhanced situational awareness, to predict the future course of the pandemic and likely associated social and economic costs, and to plan mitigation strategies [5, 6].
Read the full article to learn more.
