Using conservation of pattern to estimate spatial parameters from a
single snapshot (2004)
Keeling, Brooks and Gilligan. P.N.A.S.
101 9155-9160
ABSTRACT
Rapid reaction in the face of an epidemic is a key element in effective
and efficient control; this is especially important when the disease
has severe public health or economic consequences. Determining an
appropriate level of response requires rapid estimation of the rate of
spread of infection from limited disease distribution data. Generally,
the techniques used to estimate such spatial parameters require
detailed spatial data at multiple time points; such data are often
time-consuming and expensive to collect. Here we present an alternative
approach that is computationally efficient and only requires spatial
data from a single time point, hence saving valuable time at the start
of the epidemic. By assuming that fundamental spatial statistics are
near equilibrium, parameters can be estimated by minimizing the
expected rate of change of these statistics, hence conserving the
general spatial pattern. Although applicable to both ecological and
epidemiological data, here we focus on disease data from computer
simulations and real epidemics to show that this method produces
reliable results that could be used in practical situations.
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