  This study embarks on a comprehensive exploration of the decadal trends and
future trajectories of twenty distinct infectious diseases in China from 1998
to 2021. A refined Hybrid Bayesian Structural Time Series (BSTS)-Markov Chain
Monte Carlo (MCMC) model is employed, intertwining with Long Short-Term Memory
(LSTM) networks to dissect intricate relationships amidst population
demographics, economic indices, and the evolution of infectious diseases. The
findings reveal the persistent prevalence of high incidence diseases in future
10 years, like AIDS, Gonorrhea, and Syphilis, and stable occurrences of middle
incidence rate diseases such as Brucellosis and Scarlet Fever, while also
foretelling the potential disappearance of lower incidence rate diseases like
Cholera, Encephalitis B, and Measles. The study particularly underscores the
transformative impact of the COVID-19 pandemic, showcasing its extensive
implications on the incidences and management of a plethora of diseases, urging
a deeper probe into the nuanced alterations in disease transmission, testing,
and reporting modalities amidst global health crises. This research accentuates
the critical role of advanced predictive analytics in fostering global
preparedness and response mechanisms, and in fortifying the resilience and
adaptability of China public health framework against burgeoning infectious
disease threats.
