Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022.
<h4>Background</h4>During the coronavirus disease 2019 (COVID-19) pandemic, the implementation of public health intervention measures have reshaped the transmission patterns of other infectious diseases. We aimed to analyze the epidemiological characteristics of dengue in Guangdong Provi...
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Public Library of Science (PLoS)
2025-02-01
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Online Access: | https://doi.org/10.1371/journal.pntd.0012832 |
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author | Jiaqing Xu Xiaohua Tan Yi Quan Dexin Gong Hui Deng Jianguo Zhao Xing Huang Yingtao Zhang Zhoupeng Ren Zuhua Rong Weilin Zeng Xing Li Wenyuan Zheng Shu Xiao Jianpeng Xiao Meng Zhang |
author_facet | Jiaqing Xu Xiaohua Tan Yi Quan Dexin Gong Hui Deng Jianguo Zhao Xing Huang Yingtao Zhang Zhoupeng Ren Zuhua Rong Weilin Zeng Xing Li Wenyuan Zheng Shu Xiao Jianpeng Xiao Meng Zhang |
author_sort | Jiaqing Xu |
collection | DOAJ |
description | <h4>Background</h4>During the coronavirus disease 2019 (COVID-19) pandemic, the implementation of public health intervention measures have reshaped the transmission patterns of other infectious diseases. We aimed to analyze the epidemiological characteristics of dengue in Guangdong Province, China, and to investigate the temporal shifts in dengue epidemic in Guangdong Province during the COVID-19 pandemic.<h4>Methods</h4>Based on the data of dengue reported cases, meteorological factors, and mosquito vector density in Guangdong Province from 2012 to 2022, wavelet analysis was applied to investigate the relationship between the dengue incidence in Southeast Asian (SEA) countries and the local dengue incidence in Guangdong Province. We constructed the dengue importation risk index to assess the monthly risk of dengue importation. Based on the counterfactual framework, we constructed the Bayesian structural time series (BSTS) model to capture the epidemic trends of dengue.<h4>Results</h4>Wavelet analysis showed that the local dengue incidence in Guangdong Province was in phase correlation with the dengue incidence of the prior month in relative SEA countries. The dengue importation risk index showed an increasing trend from 2012 to 2019, then decreased to a low level during the COVID-19 pandemic. From 2020 to 2022, the average annual number of reported imported cases and local cases of dengue in Guangdong Province were 26 and 2, respectively, with a decrease of 95.62% and 99.94% compared to the average during 2017-2019 (594 imported cases and 3,118 local cases). According to BSTS model estimates, 6557 local dengue cases may have been reduced in Guangdong Province from 2020 to 2022, with a relative reduction of 99.91% (95%CI: 98.85-99.99%).<h4>Conclusion</h4>The incidence of dengue in Guangdong notably declined from 2020 to 2022, which may be related to the co-benefits of COVID-19 intervention measures and the intensified interventions against dengue during that period. Furthermore, our findings further supported that dengue is not currently endemic in Guangdong. |
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institution | Kabale University |
issn | 1935-2727 1935-2735 |
language | English |
publishDate | 2025-02-01 |
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spelling | doaj-art-d44394b145284b6e96ead5ced58010742025-02-12T05:31:22ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352025-02-01192e001283210.1371/journal.pntd.0012832Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022.Jiaqing XuXiaohua TanYi QuanDexin GongHui DengJianguo ZhaoXing HuangYingtao ZhangZhoupeng RenZuhua RongWeilin ZengXing LiWenyuan ZhengShu XiaoJianpeng XiaoMeng Zhang<h4>Background</h4>During the coronavirus disease 2019 (COVID-19) pandemic, the implementation of public health intervention measures have reshaped the transmission patterns of other infectious diseases. We aimed to analyze the epidemiological characteristics of dengue in Guangdong Province, China, and to investigate the temporal shifts in dengue epidemic in Guangdong Province during the COVID-19 pandemic.<h4>Methods</h4>Based on the data of dengue reported cases, meteorological factors, and mosquito vector density in Guangdong Province from 2012 to 2022, wavelet analysis was applied to investigate the relationship between the dengue incidence in Southeast Asian (SEA) countries and the local dengue incidence in Guangdong Province. We constructed the dengue importation risk index to assess the monthly risk of dengue importation. Based on the counterfactual framework, we constructed the Bayesian structural time series (BSTS) model to capture the epidemic trends of dengue.<h4>Results</h4>Wavelet analysis showed that the local dengue incidence in Guangdong Province was in phase correlation with the dengue incidence of the prior month in relative SEA countries. The dengue importation risk index showed an increasing trend from 2012 to 2019, then decreased to a low level during the COVID-19 pandemic. From 2020 to 2022, the average annual number of reported imported cases and local cases of dengue in Guangdong Province were 26 and 2, respectively, with a decrease of 95.62% and 99.94% compared to the average during 2017-2019 (594 imported cases and 3,118 local cases). According to BSTS model estimates, 6557 local dengue cases may have been reduced in Guangdong Province from 2020 to 2022, with a relative reduction of 99.91% (95%CI: 98.85-99.99%).<h4>Conclusion</h4>The incidence of dengue in Guangdong notably declined from 2020 to 2022, which may be related to the co-benefits of COVID-19 intervention measures and the intensified interventions against dengue during that period. Furthermore, our findings further supported that dengue is not currently endemic in Guangdong.https://doi.org/10.1371/journal.pntd.0012832 |
spellingShingle | Jiaqing Xu Xiaohua Tan Yi Quan Dexin Gong Hui Deng Jianguo Zhao Xing Huang Yingtao Zhang Zhoupeng Ren Zuhua Rong Weilin Zeng Xing Li Wenyuan Zheng Shu Xiao Jianpeng Xiao Meng Zhang Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022. PLoS Neglected Tropical Diseases |
title | Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022. |
title_full | Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022. |
title_fullStr | Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022. |
title_full_unstemmed | Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022. |
title_short | Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022. |
title_sort | temporal shifts in dengue epidemic in guangdong province before and during the covid 19 pandemic a bayesian model study from 2012 to 2022 |
url | https://doi.org/10.1371/journal.pntd.0012832 |
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