Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimating a novel stochastic model for within-field disease dynamics of
  banana bunchy top virus via approximate Bayesian computation   The Banana Bunchy Top Virus (BBTV) is one of the most economically important
vector-borne banana diseases throughout the Asia-Pacific Basin and presents a
significant challenge to the agricultural sector. Current models of BBTV are
largely deterministic, limited by an incomplete understanding of interactions
in complex natural systems, and the appropriate identification of parameters. A
stochastic network-based Susceptible-Infected model has been created which
simulates the spread of BBTV across the subsections of a banana plantation,
parameterising nodal recovery, neighbouring and distant infectivity across
summer and winter. Findings from posterior results achieved through Markov
Chain Monte Carlo approach to approximate Bayesian computation suggest
seasonality in all parameters, which are influenced by correlated changes in
inspection accuracy, temperatures and aphid activity. This paper demonstrates
how the model may be used for monitoring and forecasting of various disease
management strategies to support policy-level decision making.

21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
1
The categories of this paper are: cs
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
13
The categories of this paper are: quant-ph
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
9
The categories of this paper are: nlin