Spatiotemporal patterns and determinants of dengue at county level in China from 2005–2017

Liu, Keke; Sun, Jimin; Liu, Xiaobo; Li, Ruiyun; Wang, Yiguan; Lu, Liang; Wu, Haixia; Gao, Yuan; Xu, Lei

doi:10.1016/j.ijid.2018.09.003

Cited by 30 publications

(47 citation statements)

References 32 publications

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“…Many studies have been conducted to explore the characteristics of dengue fever in mainland China. including the overall demographic features, geographical distribution, temporal distribution, spatio-temporal characteristics and seasonal distribution (Bhatt et al, 2013;Castro et al, 2018;Chen and Liu, 2015;Corner et al, 2013;Dewan et al, 2017;Fan et al, 2014;Hashizume et al, 2012;Lai, 2011;Lippi et al, 2018;Liu et al, 2014;Liu et al, 2018a;Liu et al, 2018b;Sun et al, 2017;Wang et al, 2013aWang et al, , 2013bYue et al, 2018). However, most of the research is focused on indigenous dengue fever.…”

Section: Introductionmentioning

confidence: 99%

Epidemiological dynamics of dengue fever in mainland China, 2014–2018

Yue

Ren

et al. 2019

International Journal of Infectious Diseases

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To explore the epidemiological dynamics of dengue fever. Methods: Epidemiological dynamics of imported and indigenous dengue cases during 2014-2018, including demographic, time-series, spatial and spatio-temporal features, were analyzed. Results: There were 5 458 imported dengue cases and 59 183 indigenous dengue cases during 2014-2018. Both imported and indigenous dengue cases show seasonal patterns from August to November. 12.9% (12.9/100) of dengue cases were from businessmen. 58.2% (58.2/100) of dengue cases were from individuals between 21-50 years old. Imported dengue cases, mainly from Southeastern Asia, had doubled, and were distributed in 734 counties, 29 provinces, with 50% (50/100) in Yunnan. Except in 2014, indigenous dengue cases were under 5 000 every year, but the number in counties increased dramatically from 51 to 127. The total cases were distributed in 314 districts, 13 provinces. They were clustered in Yunnan border and southern Guangdong. They emerged gradually from southwestern and southern provinces to southeastern coastal provinces, and then to central and northern provinces every year. They spread from the southern regions to the central and northern regions in 2014-2018. Conclusions: The findings of epidemiological dynamics of dengue fever are helpful to formulate targeted, strategic plans and implement effective public health prevention and control measures.

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Section: Introductionmentioning

confidence: 99%

Epidemiological dynamics of dengue fever in mainland China, 2014–2018

Yue

Ren

et al. 2019

International Journal of Infectious Diseases

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“…Spatial scan statistics, when considering both spatial and temporal features, have been widely applied to explore the abnormal patterns of temporal and spatial clusters in epidemiological studies and the results have good statistical power (Sun et al, 2018;Liu et al, 2018;Wu et al, 2016). The TGR spatiotemporal patterns have never before been investigated in China.…”

Section: Discussionmentioning

confidence: 99%

Epidemiological characteristics and spatiotemporal patterns of typhus group rickettsiosis at the county level in China, 2005–2017

Gao

Yan

Liu

et al. 2020

International Journal of Infectious Diseases

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To explore the epidemiological characteristics and spatiotemporal patterns of typhus group rickettsiosis (TGR) in mainland China. Methods: A chi-squared test was used to compare the differences in the age and occupation distributions across the different years. Time-series analyses, spatial clustering analyses, and spatiotemporal scan statistics were used to detect the spatiotemporal patterns of the TGR incidence. Results: A total of 29,211 TGR cases were collected. Of these cases, 63.1% occurred from May to October, and 88.4% occurred in individuals between 0 and 59 years old. There was a significant spatial TGR heterogeneity from 2005 to 2017. The hotspots were located mainly in the southwestern, southern, and circum-Bohai Sea regions of northern China. Eighteen spatiotemporal clusters were observed using Kulldorff's space-time scan statistic, and the primary cluster included three counties, Jinghong city, Menghai county, and Mengla county. Conclusions: TGR is widely distributed in China, and it is a serious threat to public health. The hotspots were located mainly in the southwestern, southern, and circum-Bohai Sea regions of northern China, and the primary spatiotemporal cluster showed a trend shifting from circum-Bohai Sea regions to the southwestern regions. Targeted interventions should be executed in high-risk regions for precise prevention and control.

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“…Furthermore, dengue fever occurred more widely in space in GD. Dengue fever is closely related with population density and mobility, economic development, tra c development, etc [12][13][14][15]. GD has a much smaller area but a great larger population (Table 1).…”

Section: Discussionmentioning

confidence: 99%

“…They had similar seasonal characteristics for temperature and rainfall too ( Figure 6). Dengue fever is closely related with climate factors such as temperature and rainfall [8,[14][15]. Yunnan border belongs to the torrid zone, with annual rainfall of 800-1,600 mm.…”

Section: Discussionmentioning

confidence: 99%

Comparative analyses on epidemiological characteristics of dengue fever in Guangdong and Yunnan, China, 2004-2018

Yue

Liu

et al. 2020

Preprint

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Background Guangdong and Yunnan were the two provinces with the toughest dengue epidemic in China. It was to compare epidemiological characteristics of dengue fever there, 2004-2018. Methods Epidemiological method and spatial-temporal analysis were used to explore time-series, spatial and demographic features of dengue fever.Results 93.7% of indigenous cases and 65.9 % of imported cases in mainland China, 2004-2018 occurred in Guangdong and Yunnan. 55,970 and 5,938 indigenous cases occurred in 108 counties of Guangdong and 8 counties of Yunnan, respectively. 1,146 and 3,050 imported cases occurred in 84 counties of Guangdong and 72 counties of Yunnan, respectively. Guangdong and Yunnan had similar seasonal characteristics for dengue fever, and Guangdong had a longer peak period. 85.1% of indigenous cases in Yunnan were located in Ruili City and Jinghong City along the southwestern border. Most dengue cases in Guangdong occurred in the Pearl River Delta region, and especially more than 70.0% of dengue cases in Guangdong occurred in Guangzhou City. 93.9% of imported cases in Guangdong and Yunnan were imported from 9 countries of Southeast Asia. Thailand, Cambodia and Malaysia were the main imported origins in Guangdong. Myanmar and Laos were the main imported origins in Yunnan. There was a strong male predominance among imported cases and an almost equal gender distribution among indigenous cases. Most dengue cases were from individuals in 21-50 years old, accounting for 57.3% and 62.8% of indigenous cases and 83.2% and 62.6% of imported cases in Guangdong and Yunnan, respectively. There were similar major occupations as housework or unemployment, retiree and businessman for indigenous cases, and businessman for imported cases. However, farmers accounted for a larger proportion of dengue cases in Yunnan.Conclusions The findings of epidemiological characteristics and differences of dengue fever in Guangdong and Yunnan are helpful to formulate targeted, strategic plans and implement effective public health prevention measures in China.

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Spatiotemporal patterns and determinants of dengue at county level in China from 2005–2017

Abstract: The high risk areas of dengue outbreaks mainly are located in Guangdong and Yunnan Provinces, which are significantly shaped by environmental and meteorological factors, such as temperature, precipitation and land cover.

Cited by 30 publications

References 32 publications

Epidemiological dynamics of dengue fever in mainland China, 2014–2018

Epidemiological dynamics of dengue fever in mainland China, 2014–2018

Epidemiological characteristics and spatiotemporal patterns of typhus group rickettsiosis at the county level in China, 2005–2017

Comparative analyses on epidemiological characteristics of dengue fever in Guangdong and Yunnan, China, 2004-2018

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