[RAPIDD SOW]{.underline}

In January 2008, the Fogarty International Center of the National
Institutes of Health, HHS, and the Chemical-Biological Division of the
Science and Technology Directorate, DHS, began a collaborative program,
"Research and Policy for Infectious Disease Dynamics" (RAPIDD), which
over the next several years will encompass an extensive series of
conferences, seminars, working groups and postdoctoral fellowships
designed to address critical challenges in the mathematical modeling of
infectious diseases. The formal starting point for the RAPIDD program
was a January 22-23 conference, on "Infectious disease modeling: lessons
learned and future prospects." which took place on the NIH main campus
in Bethesda, MD, and included approximately 40 US and international
participants.

The conference agreed on topics for two follow-up meetings -- one on
"model hierarchies," the other on "zoonoses" (see more detailed
descriptions below) -- to be held at Pennsylvania State University March
23-25 and April 9-11, 2008. Travel and meeting services arranged in
consultation with appropriate FIC and PSU staff. Coordinate with PSU
staff for formal scientific write-ups and related activities by
participant experts, for the two follow-up meetings, each of which will
include approximately 20 US and international participants.

Estimated arrangements and covered expenses (per meeting):

[Roundtrip Airfares]{.underline}

East Coast US at 8 participants

Other US at 7 participants

UK/Europe at 5 participants

[Ground transport (roundtrip)]{.underline}

For 20 participants

[Per Diem (\$123 per day for State College, PA; \$79 lodging and \$44
Meals and incidental expenses)]{.underline}

Per diem: (Lodging x 2 nights = \$158; M&IE x 2.5 days = \$110) x 20
participants = \$5360 - \$480 (for 2 catered lunches at \$12 each per
M&IE) \$4880

[Buffet lunch]{.underline} for 20 participants x 2 days

[Summary of proceedings]{.underline} and recommendations, with
references to relevant scientific literature, and related activities to
be completed by scientific staff,

Center for Infectious Disease Dynamics, Pennsylvania State University
\$8500

1\) "Model hierarchies" meeting, March 23-25

Multifaceted questions of infectious disease dynamics and control can
often benefit from a **\'hierarchy\'** **of models and their validation
against epidemiological data.** Models can be arranged in a hierarchy,
ranging from complex agent-based simulations to simple analytical
arguments. Rigorous theoretical work to assess how to \'nest\' models at
different levels of descriptive complexity is a crucial next step. In
particular, we need to address a central, difficult question: are there
generic rules for which model to use in what context, or is the best
balance of simple and complex approaches problem- and disease-specific?
What level of model complexity is necessary to explain observed
dynamics?; What additional understanding is gained by increasing model
complexity? A key issue in this process (and more generally in the
field) is model validation against data; specifically: what combination
of historical or real-time host network and epidemic data is needed to
validate the structure and results of a given model? How can models
shape the design of data collection to improve validation? In parallel,
there need to be further developments of statistical *parameter
estimation* methods, to characterize important (and often otherwise
unobtainable) parameters by fitting hierarchies of mechanistic models,
to parallel outbreak and host network data. A particular priority here
is developing Bayesian and other approaches to using \'mixed\' data
(e.g. disease incidence and serological survey data).

2\) "Zoonoses" meeting, April 9-11

**What makes a zoonosis "good" or "bad" in terms of our ability to model
dynamics and control?** What key data and novel modeling developments
will help us understand the emergence and onward spread of zoonoses? An
in-depth comparative study across zoonoses to estimate transmission
rates, relative importance of reservoirs, dynamic effects of life
history in reservoirs and humans, probabilities of species jumps,
potential for drug resistance, immune escape, etc., would inform
priorities for countermeasure development and response planning (e.g.
Rift Valley Fever vs. Nipah/Hendra virus vs. Venzulean Equine
Encephalitis), while cataloging parameter values/ranges and identifying
critical knowledge gaps.

No other services will be required for these two meetings.