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

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...

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Autores principales: Shang, Y., Zhang, T. T., Wang, Z. F., Ma, B. Z., Yang, N., Qiu, Y. T., Li, B., Zhang, Q., Huang, Q. L., Liu, K. Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888277/
https://www.ncbi.nlm.nih.gov/pubmed/35225193
http://dx.doi.org/10.1017/S0950268822000036
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author Shang, Y.
Zhang, T. T.
Wang, Z. F.
Ma, B. Z.
Yang, N.
Qiu, Y. T.
Li, B.
Zhang, Q.
Huang, Q. L.
Liu, K. Y.
author_facet Shang, Y.
Zhang, T. T.
Wang, Z. F.
Ma, B. Z.
Yang, N.
Qiu, Y. T.
Li, B.
Zhang, Q.
Huang, Q. L.
Liu, K. Y.
author_sort Shang, Y.
collection PubMed
description 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.
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spelling pubmed-88882772022-03-14 Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China Shang, Y. Zhang, T. T. Wang, Z. F. Ma, B. Z. Yang, N. Qiu, Y. T. Li, B. Zhang, Q. Huang, Q. L. Liu, K. Y. Epidemiol Infect Original Paper 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. Cambridge University Press 2022-01-12 /pmc/articles/PMC8888277/ /pubmed/35225193 http://dx.doi.org/10.1017/S0950268822000036 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
spellingShingle Original Paper
Shang, Y.
Zhang, T. T.
Wang, Z. F.
Ma, B. Z.
Yang, N.
Qiu, Y. T.
Li, B.
Zhang, Q.
Huang, Q. L.
Liu, K. Y.
Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China
title Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China
title_full Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China
title_fullStr Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China
title_full_unstemmed Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China
title_short Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China
title_sort spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in qinghai plateau, china
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888277/
https://www.ncbi.nlm.nih.gov/pubmed/35225193
http://dx.doi.org/10.1017/S0950268822000036
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