Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever

Zhou, Shuli; Zhou, Suhong; Liu, Lin; Zhao, Meng; Kang, Min; Xiao, Jianpeng; Song, Tie

doi:10.3390/ijerph16245013

Cited by 7 publications

(4 citation statements)

References 47 publications

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“…Three significantly high-risk clusters were identified. The studies conducted in dengue non-endemic regions indicated that the core contributors to the spatial heterogeneity of dengue were: urban village; urban-rural fringe zone; dense population, human mobility, gross domestic product per capita; Normalized Difference Vegetation Index; number of imported cases; subway network; density of road networks ( 22 , 24 – 27 ). The three high-risk clusters we identified were characterized by a dense population, high human mobility, high incidence of imported cases, dense road networks, and advanced economy.…”

Section: Discussionmentioning

confidence: 99%

Epidemiology of Indigenous Dengue Cases in Zhejiang Province, Southeast China

Ren

Chen

et al. 2022

Front. Public Health

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ObjectiveAutochthonous transmission of the dengue virus (DENV) occurred each year from 2014 to 2018 in Zhejiang province, and became an emerging public health problem. We characterized the autochthonous transmission of the DENV and traced the source of infection for further control and prevention of dengue.MethodsDescriptive and spatiotemporal cluster analyses were conducted to characterize the epidemiology of autochthonous transmission of the DENV. Molecular epidemiology was used to identify the infection source.ResultsIn total, 1,654 indigenous cases and 12 outbreaks, with no deaths, were reported during 2004–2018. Before 2017, all outbreaks occurred in suburban areas. During 2017–2018, five out of eight outbreaks occurred in urban areas. The median duration of outbreaks (28 days) in 2017–2018 was shortened significantly (P = 0.028) in comparison with that in 2004–2016 (71 days). The median onset-visiting time, visiting-confirmation time, and onset-confirmation time was 1, 3, and 4 days, respectively. The DENV serotypes responsible for autochthonous transmission in Zhejiang Province were DENV 1, DENV 2, and DENV 3, with DENV 1 being the most frequently reported. Southeast Asia was the predominant source of indigenous infection.ConclusionsZhejiang Province witnessed an increase in the frequency, incidence, and geographic expansion of indigenous Dengue cases in recent years. The more developed coastal and central region of Zhejiang Province was impacted the most.

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Section: Discussionmentioning

confidence: 99%

Epidemiology of Indigenous Dengue Cases in Zhejiang Province, Southeast China

Ren

Chen

et al. 2022

Front. Public Health

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“…[ 19 ] The influence of climate change and travel to/from endemic countries are important factors leading to the disease outbreak. [ 20 ] An analysis of imported cases from 2014 to 2018 in China showed that the dengue patients were mainly aged between 21 and 50 years old made up the most farmers and unemployed people. [ 21 ] Among the 231 dengue patients admitted to our hospital, those in the < 60 years age group accounted for the largest proportion, followed by the 60 to 80 years age group, which may be attributed to the fact that more elderly patients come to see a doctor.…”

Section: Discussionmentioning

confidence: 99%

A survey of clinical and laboratory characteristics of the dengue fever epidemic from 2017 to 2019 in Zhejiang, China

et al. 2022

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To explore the epidemic, clinical, and laboratory characteristics of dengue patients in Zhejiang and the possible mechanism. Epidemic, clinical and laboratory data of 231 dengue patients admitted to the Second Affiliated Hospital of Zhejiang Traditional Chinese Medicine University between August 2017 and December 2019 were collected. GSE43777 dataset was downloaded from the Gene Expression Omnibus database and was used for the immune cell infiltration analysis, logistic regression analysis, and nomogram construction. Gene set enrichment analysis (GSEA) was performed to explore the possible regulatory pathways in dengue infection. Further, the receiver operating characteristic curve analysis and decision curve analysis were conducted to evaluate the value of related immune cells in predicting dengue severity. Among the 231 patients, the gender ratio was 1:1.1 (male/female). The patients in the <60 years age group, 60 to 80 years age group, and >80 years age group were 47.2%, 45.5%, and 7.3%, respectively. The major symptoms were fever (100%), weak (98.3%), anorexia (76.6%), muscle and joint pain (62.3%), and nausea (46.8%). In dengue patients, 98.7% of serum samples had decreased platelet levels, 96.5% of them had decreased white blood cell (WBC) levels, 97.8% had elevated aspartate aminotransferase levels, 82.3% had elevated lactate dehydrogenase levels, 49.4% had increased creatinine levels, and 35.5% had increased creatine kinase levels. Pneumonia, pleural effusion, and bilateral pleural reaction were observed in 16.5%, 8.2%, and 4.8%, respectively of dengue patients. Gallbladder wall roughness and splenomegaly accounted for 6.1% and 4.3% of all cases. Moreover, the levels of T cell, B cell, and dendritic cells were significantly higher in the convalescent group and they were involved in immune- and metabolism-related pathways. Of note, low levels of these 3 immune cells correlated with high dengue infection risk, while only dendritic cells exhibited satisfactory performance in predicting dengue severity. Dengue fever patients often onset with fever, accompanied by mild abnormalities of the blood system and other organ functions. Moreover, T cells, B cells, and dendritic cells might be involved in dengue infection and development.

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“…Kumar and Agrawal [140]; Sintayehu et al [141] These predictors included built-up area (explained by the Normalized Difference Builtup Index-NDBI), population, vegetation (explained by the Normalized Difference Vegetation Index-NDVI), land surface temperature (LST), water (explained by the Normalized Difference Water Index-NDWI), and moisture (explained by the Normalized Difference Moisture Index) [126,127,[140][141][142][143][144]. It is noted that the indices utilized to represent the environmental factors are well established in the literature and have been extensively used to study several environmental problems.…”

Section: Evaluating Different Spatial Socio-environmental Factors Of Df: a Multivariate Analysismentioning

confidence: 99%

Integrating Spatial Modelling and Space–Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan

Naqvi

Sajjad

Waseem

et al. 2021

IJERPH

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The spatial–temporal assessment of vector diseases is imperative to design effective action plans and establish preventive strategies. Therefore, such assessments have potential public health planning-related implications. In this context, we here propose an integrated spatial disease evaluation (I-SpaDE) framework. The I-SpaDE integrates various techniques such as the Kernel Density Estimation, the Optimized Hot Spot Analysis, space–time assessment and prediction, and the Geographically Weighted Regression (GWR). It makes it possible to systematically assess the disease concentrations, patterns/trends, clustering, prediction dynamics, and spatially varying relationships between disease and different associated factors. To demonstrate the applicability and effectiveness of the I-SpaDE, we apply it in the second largest city of Pakistan, namely Lahore, using Dengue Fever (DF) during 2007–2016 as an example vector disease. The most significant clustering is evident during the years 2007–2008, 2010–2011, 2013, and 2016. Mostly, the clusters are found within the city’s central functional area. The prediction analysis shows an inclination of DF distribution from less to more urbanized areas. The results from the GWR show that among various socio-ecological factors, the temperature is the most significantly associated with the DF followed by vegetation and built-up area. While the results are important to understand the DF situation in the study area and have useful implications for public health planning, the proposed framework is flexible, replicable, and robust to be utilized in other similar regions, particularly in developing countries in the tropics and sub-tropics.

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Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever

Cited by 7 publications

References 47 publications

Epidemiology of Indigenous Dengue Cases in Zhejiang Province, Southeast China

Epidemiology of Indigenous Dengue Cases in Zhejiang Province, Southeast China

A survey of clinical and laboratory characteristics of the dengue fever epidemic from 2017 to 2019 in Zhejiang, China

Integrating Spatial Modelling and Space–Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan

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