Engineering Effective Responses to Influenza Outbreaks
We present a policy-oriented summary of our six-year "service-systems-focused" research into pandemic influenza. We cover three topics: (1) R[subscript 0], the basic reproductive number for the flu; (2) NPIs, non-pharmaceutical inventions to reduce the chance of becoming infected; and (3)...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute for Operations Research and the Management Sciences (INFORMS)
2017
|
| Online Access: | http://hdl.handle.net/1721.1/106894 https://orcid.org/0000-0003-2776-4900 |
| Summary: | We present a policy-oriented summary of our six-year "service-systems-focused" research into pandemic influenza. We cover three topics: (1) R[subscript 0], the basic reproductive number for the flu; (2) NPIs, non-pharmaceutical inventions to reduce the chance of becoming infected; and (3) flu vaccine allocations. We use a service-systems framing and mathematical modeling approach incorporating theories and data on the spread and control of influenza. We examine how behavioral actions and governmental policies, thoughtfully derived, can minimize influenza’s societal impact. There is widespread misinterpretation that R0 is a numerical constant of a given virus. We argue that it is not, but rather that its value is largely determined by local conditions and actions, many under our individual and collective control. This control is, in the absence of vaccine, intelligent use of NPIs—highly effective in reducing the spread of influenza. Our vaccine analysis relies on government data depicting flu-like cases and vaccines administered during the 2009 H1N1 outbreak. During that outbreak, barely half of all states received allotments of vaccine in time to protect any citizens. The method of vaccine deployment—in proportion to census population—ignored the temporally uneven flu wave progression across the United States. |
|---|