Publication date: Aug 16, 2024
Rifampicin resistant tuberculosis (RR-TB) poses a growing threat to individuals and communities. This study utilized a seasonal autoregressive integrated moving average (SARIMA) model to quantitatively predict the monthly incidence of RR-TB in Yunnan Province which could guide government health administration departments and the centers for disease control and prevention (CDC) in preventing and controlling the RR-TB epidemic. The study utilized routine surveillance reporting data from the infectious Disease Network Surveillance and Reporting System. Monthly incidence rates of RR-TB were collected from January 2019 to December 2022. A time series SARIMA model was used to predict the number of monthly RR-TB cases in Yunnan Province in 2023, and the model was validated using time series plots, seasonal and non-seasonal differencing, autocorrelation and partial autocorrelation analysis, and white noise tests. From 2019 to 2022, the incidence of RR-TB decreases as the incidence of all TB decreases (P 0. 05). The time series decomposition shows that it presented obvious seasonality, periodicity and randomness after being decomposed. Time series analysis was performed on the original series after 1 non-seasonal difference and 1 seasonal difference, the ADF test showed P
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Semantics
Type | Source | Name |
---|---|---|
drug | DRUGBANK | Rifampicin |
disease | MESH | tuberculosis |
pathway | KEGG | Tuberculosis |
disease | MESH | infectious Disease |
pathway | REACTOME | Infectious disease |
drug | DRUGBANK | Coenzyme M |
disease | MESH | pulmonary tuberculosis |
drug | DRUGBANK | L-Valine |
drug | DRUGBANK | Trestolone |
disease | MESH | COVID 19 pandemic |
drug | DRUGBANK | Tretamine |
disease | MESH | respiratory diseases |
disease | MESH | morbidity |
drug | DRUGBANK | Etoperidone |
disease | MESH | Emerging Infectious Diseases |
drug | DRUGBANK | Guanosine |
disease | MESH | Tuberculosis Multidrug-Resistant |