1. Aksarben Room – 2nd Floor
Pandemic Planning Communities Gauging Benefits of Combined Emphasis in Planning Focus: Infection Rate, Death Rate and Speed of Spread
Global Studies Conference (Latin America, Africa, Asia, and the Middle East)
October 1-3, 2009 University of Nebraska Omaha
Aksarben Room – 2nd Floor
“Three Response Communities’ Abilities to Respond to Pandemic Influenza”
Presenter: E. Hughes Shanks, Health Data and Evaluation Division, Lincoln-Lancaster County Health Dept.
Panelist: Nkemjika Kalu, University of Nebraska-Lincoln
Panelist: Yue Zou, University of Nebraska-Lincoln
Title of Working Paper: H5N1 Mutability: Three Response Communities by E. Hughes Shanks, MPA

2. What can Science and Policy Do Together?
Can Science Help These Activities?
Community Planning
Public Health Funding
Public Health Education
Scarce Resource Distribution

3. The Science Policy Interface
Definition: The Science Policy Interface is a public good that resides where elements of traditional “hard science” interact with elements of public policy.

4. What can the Science Policy Interface do in a pandemic?
Can the Interface create a greater likelihood of equitable resource distribution patterns?
Can the Interface improve government and/or industry capacities to provide adequate public health resources?

5. Why Consider the Science Policy Interface
This research shows evidence that certain combinations of science and public policy could help reduce excess mortality rates during a pandemic event.

6. Epistemic Communities Concerned with Pandemic Influenza
Planning (Community & Government)
Statistic-Centered (Epidemiology/Demographic)
Pharmacological/Pharmaceutical (Research, Marketing & Distribution)

7. Planning Communities UASI Cities (Omaha, KCMO, NYC)
MMRS Regions (Lincoln, Wichita KS)
MRS Districts (SE Neb., Central Neb.)
Statutory Bureau/Agencies (Nebraska DHHS)
Federal Bureaus (Office of Health Affairs, FEMA)

8. Statistics-Centered/Epidemiological Demographic Communities
Public (State/Local) Health Infection Control
WHO
CDC
State Agency (Bio-terrorism Divisions)

9. Pharmacological/Pharmaceutical Communities
Drug Manufacturers (Research, Testing, Marketing & Distribution)

10. Pandemic Scenario
Spitzer (1984) characterized the Spanish Flu pandemic as “lightning-fast” adding that the disease crossed “the entire country in the space of a few weeks.”
Source: Spitzer, Robert J., (1984) Review [Untitled] by Arthur M. Silverstein, The Swine Flu Affair, Administrative Science Quarterly. Volume 29, Number 2 (June), pp

11. Related Communities Public Education Scientific Institutions
Private Education Scientific Institutions
Government Sponsored Institutions
Government (Epidemiology) Bureaus
Public Science Industries
Private Science Industries

12. Threats to World Health
Excess Mortality
Scarce Resources
Science Policy Ambiguation

13. Excess Mortality
The Pandemic killed at least 450,000 Americans.

14. Policy Ambiguation Absence of Clarity in Planning Emphases
Medical Readiness v. Hospital Preparedness v. Disaster Preparedness v. Emergency Mgmt.
Public Health v. Private Enterprise v. Government Bureau v. Education/Research
Which Aspect of Planning Should Lead?

15. Research Methods and Design
Literature review and archival search
Content Analysis
Coding of select elements based on the threats to world health.
Data analyses of Inferential and Descriptive Statistics Tabulations

16. Finding
Type of funding seems to play a role in those Response Groups which perform their own research and are oriented toward prediction.
Based on an ANOVA Test the probability of this result , is p<0.050 Significant.

17. Finding
Planning centered communities exhibit the least concern for “speed of spread” when compared to Statistics-centered communities and Pharmacological/Pharmaceutical Interests

18. Finding
The compositional capacities (disciplinary make-up) of Planning centered communities and statistics centered groups is approximately 1/3 that of the pharmacological/pharmaceutical community group.

19. Use of Math Models Matters
Response groups that used math modeling while focusing on trans-national issues do so at predictably similar rates of occurrence between Groups.
Based a cross tabulation of Chi Square Tests = Significance .051, p<.050, result is barely statistically significant.

20. Finding
Internationally focused planning groups utilize math-based and perhaps other scientific resources in importantly different ways.
Based on an ANOVA Test the probability of this result is p< .050 Significant statistical result.

21. The Science and Policy Interface in Action
What Can Public Health Policy do in Combination with Science to save Lives?

22. Other Conclusions/Anecdotes?
Discussion?
Anecdotes?

23. Complete Paper and PowerPoint available.
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