AI-Based Decadal Predictive Analysis of Twenty Infectious Diseases in China with an Improved BSTS-MCMC Model
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.
Code (0)
등록된 구현이 없습니다.
Tasks
ManagementTime SeriesMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Modern Machine-Learning Predictive Models for Diagnosing Infectious Diseases
Controlling infectious diseases is a major health priority because they can spread and infect humans, thus evolving into epidemics or pandemics. Therefore, early detection of infectious diseases is a significant need, an…
ArticlesBIG-bench Machine LearningA Fourfold Pathogen Reference Ontology Suite
Infectious diseases remain a critical global health challenge, and the integration of standardized ontologies plays a vital role in managing related data. The Infectious Disease Ontology (IDO) and its extensions, such as…
Leveraging Foundation Models for Clinical Text Analysis
Infectious diseases are a significant public health concern globally, and extracting relevant information from scientific literature can facilitate the development of effective prevention and treatment strategies. Howeve…
Using runs of homozygosity to detect genomic regions associated with susceptibility to infectious and metabolic diseases in dairy cows under intensive farming conditions
Runs of homozygosity (ROH) are contiguous stretches of homozygous genome which likely reflect transmission from common ances- tors and can be used to track the inheritance of haplotypes of interest. In the present paper,…
Quantifying the spread of communicable diseases with immigration of infectious individuals
We construct a set of new epidemiological thresholds to address the general problem of spreading and containment of a disease with influx of infected individuals when the classic $\mathcal R_0$ is no longer meaningful. W…