Weisent, J.

International Journal of Infectious Diseases

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Comparison of three time series models for predicting campylobacteriosis risk in Georgia, Minnesota and Oregon 

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omparison of three time series models for predicting
ampylobacteriosis risk in Georgia, Minnesota and Oregon
. Weisent
University of Tennessee, Knoxville, TN, USA
Background: Three time series models (regression,
ecomposition, and Box-Jenkins Autoregressive Integrated
oving Averages) were applied to national surveillance data
or campylobacteriosis with the goal of disease forecasting
n three U.S. states.
Methods: Data sets spanned 1998 to 2007 for Minnesota
nd Oregon, 1999 to 2007 for Georgia. Year 2008 was used to
alidate model results. Mean absolute percent error, mean
quare error and coefﬁcient of determination (R2) were the
valuation ﬁt statistics.
Results: Results showed that decomposition best cap-
ured the temporal patterns in disease risk. Training dataset
2 values were 72.2, 76.3 and 89.9% and validation year R2
alues were 66.2, 52.6 and 79.9% respectively for Georgia,
regon and Minnesota. All three techniques could be uti-
ized to predict monthly risk of infection for Campylobacter
p. However, the decomposition model provided the fastest,
ost accurate, user-friendly method.
Conclusion: Use of this model can assist public health
ersonnel in predicting epidemics and developing disease
ntervention strategies.
oi:10.1016/j.ijid.2010.02.2111
7.029
nticipating the species jump: Surveillance for emerging
iral threats
. Flanagan
Penn State University, State College, PA, USA
Emerging infectious diseases (EID) may pose new inter-
ational security threats because of their potential to inﬂict
arm upon humans, crops, livestock, health infrastruc-
ure, and economies. Some viruses pose unique challenges
ecause of their high mutation rates, which enable them
o evade host immunity, persist in the environment, and
nfect new host species. For example, inﬂuenza and human
mmunodeﬁciency viruses originally infected animals, but
ubsequent mutations enabled these viruses to ‘‘jump’’ to
ew human hosts. Current disease surveillance efforts rely
pon data from clinical specimens — that is, from individuals
ho are already sick. As a result, little is known about the
bundance of viruses that exist in nature but do not (yet)
ause human disease. Human populations could be preemp-
ively protected if researchers can learn what events lead to
iral species jumping. If researchers can discover common
enetic and ecological determinants that precede species
umping, then these determinants may be used to detect
iruses teetering on the threshold of human pathogenicity.
nowledge of such determinants may ultimately prove use-
ul to threat analysts and others charged with anticipating
he genetically engineered viruses of the future, be they
atural or man-made. This paper will report the ﬁndings of
thought leaders workshop convened to debate the fea-ternational Congress on Infectious Diseases (ICID) Abstracts
ibility of identifying determinants and hypothesize what
nformation and technologies might be needed to make such
urveillance possible.
oi:10.1016/j.ijid.2010.02.2112
7.030
he making of a world atlas of infectious diseases
.F. Wertheim1, P. Horby1, T.L. Viet1, T.N.T. Tanh1, J.
oodall 2,∗
Oxford University, Hanoi, Viet Nam
ProMED-mail, Brookline, MA, USA
Background: Many infectious diseases are restricted in
heir geographical range due to climatic conditions, pres-
nce of vectors or speciﬁc reservoir hosts, local food
ustoms, hygiene, antibiotic use, among others. Currently
here is no comprehensive illustrated overview of the
eographic spread of infectious diseases and their determi-
ants. Such a compendium of world infectious disease maps
s crucial for teaching, research and creating awareness of
isk.
Methods: With the collaboration of experts from around
he globe we are collecting and making updated maps of
ore than 100 infectious diseases and their preferred con-
itions. We do extensive data searches to arrive at the best
eospatial data available. Each map will be accompanied by
n explanatory text. All our maps are sent out for indepen-
ent peer review to ensure their quality and accuracy.
Results: The atlas will be published by Wiley-Blackwell,
nd at a later stage the maps will be updated and made
vailable online under open access.
Streptococcus suis, Human Cases and Pig Density
Conclusion: The printed atlas will be followed up with
web-portal for global infectious disease mapping activi-
ies, where all the data will be bundled, visualised and made
vailable to anyone interested, and updated regularly.


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Comparison of three time series models for predicting campylobacteriosis risk in Georgia, Minnesota and Oregon

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