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The patterns and driving forces of dengue invasions in China.
Zhao, Zhe; Yue, Yujuan; Liu, Xiaobo; Li, Chuanxi; Ma, Wei; Liu, Qiyong.
  • Zhao Z; Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhua Road, Lixia District, Jinan, 250012, People's Republic of China.
  • Yue Y; State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing, 102206, People's Republic of China.
  • Liu X; Department of Vector Control, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhua Road, Lixia District, Jinan, 250012, People's Republic of China.
  • Li C; Shandong University Climate Change and Health Center, Jinan, 250012, People's Republic of China.
  • Ma W; State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing, 102206, People's Republic of China.
  • Liu Q; Department of Vector Control, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhua Road, Lixia District, Jinan, 250012, People's Republic of China.
Infect Dis Poverty ; 12(1): 42, 2023 Apr 21.
Article in English | MEDLINE | ID: covidwho-2327417
ABSTRACT

BACKGROUND:

Global connectivity and environmental change pose continuous threats to dengue invasions from worldwide to China. However, the intrinsic relationship on introduction and outbreak risks of dengue driven by the landscape features are still unknown. This study aimed to map the patterns on source-sink relation of dengue cases and assess the driving forces for dengue invasions in China.

METHODS:

We identified the local and imported cases (2006-2020) and assembled the datasets on environmental conditions. The vector auto-regression model was applied to detect the cross-relations of source-sink patterns. We selected the major environmental drivers via the Boruta algorithm to assess the driving forces in dengue outbreak dynamics by applying generalized additive models. We reconstructed the internal connections among imported cases, local cases, and external environmental drivers using the structural equation modeling.

RESULTS:

From 2006 to 2020, 81,652 local dengue cases and 12,701 imported dengue cases in China were reported. The hotspots of dengue introductions and outbreaks were in southeast and southwest China, originating from South and Southeast Asia. Oversea-imported dengue cases, as the Granger-cause, were the initial driver of the dengue dynamic; the suitable local bio-socioecological environment is the fundamental factor for dengue epidemics. The Bio8 [odds ratio (OR) = 2.11, 95% confidence interval (CI) 1.67-2.68], Bio9 (OR = 291.62, 95% CI 125.63-676.89), Bio15 (OR = 4.15, 95% CI 3.30-5.24), normalized difference vegetation index in March (OR = 1.27, 95% CI 1.06-1.51) and July (OR = 1.04, 95% CI 1.00-1.07), and the imported cases are the major drivers of dengue local transmissions (OR = 4.79, 95% CI 4.34-5.28). The intermediary effect of an index on population and economic development to local cases via the path of imported cases was detected in the dengue dynamic system.

CONCLUSIONS:

Dengue outbreaks in China are triggered by introductions of imported cases and boosted by landscape features and connectivity. Our research will contribute to developing nature-based solutions for dengue surveillance, mitigation, and control from a socio-ecological perspective based on invasion ecology theories to control and prevent future dengue invasion and localization.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Dengue / Epidemics Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Asia Language: English Journal: Infect Dis Poverty Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Dengue / Epidemics Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Asia Language: English Journal: Infect Dis Poverty Year: 2023 Document Type: Article