Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Investigation of COVID-19 Spreading Factors with Explainable AI
  Techniques   Since COVID-19 was first identified in December 2019, various public health
interventions have been implemented across the world. As different measures are
implemented at different countries at different times, we conduct an assessment
of the relative effectiveness of the measures implemented in 18 countries and
regions using data from 22/01/2020 to 02/04/2020. We compute the top one and
two measures that are most effective for the countries and regions studied
during the period. Two Explainable AI techniques, SHAP and ECPI, are used in
our study; such that we construct (machine learning) models for predicting the
instantaneous reproduction number ($R_t$) and use the models as surrogates to
the real world and inputs that the greatest influence to our models are seen as
measures that are most effective. Across-the-board, city lockdown and contact
tracing are the two most effective measures. For ensuring $R_t<1$, public
wearing face masks is also important. Mass testing alone is not the most
effective measure although when paired with other measures, it can be
effective. Warm temperature helps for reducing the transmission.

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The categories of this paper are: atom-ph
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The categories of this paper are: chem-ph
13
The categories of this paper are: quant-ph
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The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
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The categories of this paper are: funct-an
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The categories of this paper are: mtrl-th
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The categories of this paper are: comp-gas
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The categories of this paper are: q-fin
6
The categories of this paper are: astro-ph
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The categories of this paper are: solv-int
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The categories of this paper are: alg-geom
2
The categories of this paper are: math
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The categories of this paper are: ao-sci
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-lat