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Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China

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Abstract The epidemic of tuberculosis has posed a serious burden in Qinghai province, it is necessary to clarify the epidemiological characteristics and spatial-temporal distribution of TB for future prevention and… Click to show full abstract

Abstract The epidemic of tuberculosis has posed a serious burden in Qinghai province, it is necessary to clarify the epidemiological characteristics and spatial-temporal distribution of TB for future prevention and control measures. We used descriptive epidemiological methods and spatial statistical analysis including spatial correlation and spatial-temporal analysis in this study. Furthermore, we applied an exponential smoothing model for TB epidemiological trend forecasting. Of 43 859 TB cases, the sex ratio was 1.27:1 (M:F), and the average annual TB registered incidence was 70.00/100 000 of 2009–2019. More cases were reported in March and April, and the worst TB stricken regions were the prefectures of Golog and Yushu. High TB registered incidences were seen in males, farmers and herdsmen, Tibetans, or elderly people. 7132 cases were intractable, which were recurrent, drug resistant, or co-infected with other infections. Three likely cases clusters with significant high risk were found by spatial-temporal scan on data of 2009–2019. The exponential smoothing winters' additive model was selected as the best-fitting model to forecast monthly TB cases in the future. This research indicated that TB in Qinghai is still a serious threaten to the local residents' health. Multi-departmental collaboration and funds special for TB treatments and control are still needed, and the exponential smoothing model is promising which could be applied for forecasting of TB epidemic trend in this high-altitude province.

Keywords: qinghai; epidemiological characteristics; exponential smoothing; tuberculosis; model; smoothing model

Journal Title: Epidemiology and Infection
Year Published: 2022

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