Exploring Epidemiological Characteristics of Domestic Imported Dengue Fever in Mainland China, 2014-2018

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

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.

Influences of Differentiated Residence and Workplace Location on the Identification of Spatiotemporal Patterns of Dengue Epidemics: A Case Study in Guangzhou, China

The location of the infections is the basic data for precise prevention and control of dengue fever (DF). However, most studies default to residence address as the place of infection, ignoring the possibility that cases are infected at other places (e.g., workplace address). This study aimed to explore the spatiotemporal patterns of DF in Guangzhou from 2016 to 2018, differentiating workplace and residence. In terms of temporal and spatial dimensions, a case weight assignment method that differentiates workplace and residence location was proposed, taking into account the onset of cases around their workplace and residence. Logistic modeling was used to classify the epidemic phases. Spatial autocorrelation analysis was used to reveal the high and early incidence areas of DF in Guangzhou from 2016 to 2018. At high temporal resolution, the DF in Guangzhou has apparent phase characteristics and is consistent with logistic growth. The local epidemic is clustered in terms of the number of cases and the time of onset and outbreak. High and early epidemic areas are mainly distributed in the central urban areas of Baiyun, Yuexiu, Liwan and Haizhu districts. The high epidemic areas due to commuting cases can be further identified after considering the workplaces of cases. Improving the temporal resolution and differentiating the workplace and residence address of cases could help to improve the identification of early and high epidemic areas in analyzing the spatiotemporal patterns of dengue fever in Guangzhou, which could more reasonably reflect the spatiotemporal patterns of DF in the study area.

Infectious diseases prevention and control using an integrated health big data system in China

BACKGROUND

The Yinzhou Center for Disease Prevention and Control (CDC) in China implemented an integrated health big data platform (IHBDP) that pooled health data from healthcare providers to combat the spread of infectious diseases, such as dengue fever and pulmonary tuberculosis (TB), and to identify gaps in vaccination uptake among migrant children.

METHODS

IHBDP is composed of medical data from clinics, electronic health records, residents' annual medical checkup and immunization records, as well as administrative data, such as student registries. We programmed IHBDP to automatically scan for and detect dengue and TB carriers, as well as identify migrant children with incomplete immunization according to a comprehensive set of screening criteria developed by public health and medical experts. We compared the effectiveness of the big data screening with existing traditional screening methods.

RESULTS

IHBDP successfully identified six cases of dengue out of a pool of 3972 suspected cases, whereas the traditional method only identified four cases (which were also detected by IHBDP). For TB, IHBDP identified 288 suspected cases from a total of 43,521 university students, in which three cases were eventually confirmed to be TB carriers through subsequent follow up CT or T-SPOT.TB tests. As for immunization screenings, IHBDP identified 240 migrant children with incomplete immunization, but the traditional door-to-door screening method only identified 20 ones.

CONCLUSIONS

Our study has demonstrated the effectiveness of using IHBDP to detect both acute and chronic infectious disease patients and identify children with incomplete immunization as compared to traditional screening methods.

Dengue fever and dengue virus in the People's Republic of China

Infection with dengue virus (DENV) leads to symptoms variable from dengue fever to severe dengue, which has posed a huge socioeconomic and disease burden to the world population, particularly in tropical and subtropical regions. To date, four serotypes of DENV (DENV-1 to DENV-4) have been identified to sustain the transmission cycle in humans. In the past decades, dengue incidences have become more frequent, and four serotypes and various genotypes have been identified in PR China. Several large-scale dengue outbreaks and frequent local endemics occurred in the southern and coastal provinces, and the imported dengue cases accounted primarily for the initiation of the epidemics. No antiviral drug exists for dengue, and no vaccine has been approved to use in PR China, however strategies including public awareness, national reporting system of infectious diseases and public health emergencies, vector mosquito control, personal protection, and improved environmental sanitation have greatly reduced dengue prevalence. Some new technologies in vector mosquito control are emerging and being applied for dengue control. China's territory spans tropical, subtropical, and temperate climates, hence understanding the dengue status in China will be of beneficial for the global prevention and control of dengue. Here, we review the dengue status in PR China for the past decades and the strategies emerging for dengue control.

Spatial Dynamics of Dengue Fever in Mainland China, 2019

New spatial characteristics of dengue fever in mainland China during 2019 were analyzed. There was a dengue fever outbreak in mainland China in 2019, with 15,187 indigenous cases in 13 provinces, 1281 domestic imported cases from 12 provinces and 5778 overseas imported cases from 47 countries, more than the previous cases during the period 2005–2018, except for in 2014. Indigenous cases occurred in Sichuan, Hubei and Chongqing in 2019. There have been big changes in the spatial distribution and proportion of dengue cases. Indigenous cases were not only located in the southwestern border and southeastern coastal provinces of Yunnan, Guangdong, Guangxi and Fujian but also in the central provinces of Jiangxi and Chongqing. Domestic imported cases were not only from Guangdong, but also from Yunnan. There were five new sources of importation of cases. Overseas imported cases were mainly from Cambodia and Myanmar in 2019. Understanding the new spatial characteristics of dengue fever in China helps to formulate targeted, strategic plans and implement effective public health prevention and control measures.

Determination of Factors Affecting Dengue Occurrence in Representative Areas of China: A Principal Component Regression Analysis

Background: Determination of the key factors affecting dengue occurrence is of significant importance for the successful response to its outbreak. Yunnan and Guangdong Provinces in China are hotspots of dengue outbreak during recent years. However, few studies focused on the drive of multi-dimensional factors on dengue occurrence failing to consider the possible multicollinearity of the studied factors, which may bias the results.

Methods: In this study, multiple linear regression analysis was utilized to explore the effect of multicollinearity among dengue occurrences and related natural and social factors. A principal component regression (PCR) analysis was utilized to determine the key dengue-driven factors in Guangzhou city of Guangdong Province and Xishuangbanna prefecture of Yunnan Province, respectively.

Results: The effect of multicollinearity existed in both Guangzhou city and Xishuangbanna prefecture, respectively. PCR model revealed that the top three contributing factors to dengue occurrence in Guangzhou were Breteau Index (BI) (positive correlation), the number of imported dengue cases lagged by 1 month (positive correlation), and monthly average of maximum temperature lagged by 1 month (negative correlation). In contrast, the top three factors contributing to dengue occurrence in Xishuangbanna included monthly average of minimum temperature lagged by 1 month (positive correlation), monthly average of maximum temperature (positive correlation), monthly average of relative humidity (positive correlation), respectively.

Conclusion: Meteorological factors presented stronger impacts on dengue occurrence in Xishuangbanna, Yunnan, while BI and the number of imported cases lagged by 1 month played important roles on dengue transmission in Guangzhou, Guangdong. Our findings could help to facilitate the formulation of tailored dengue response mechanism in representative areas of China in the future.

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

Environment and human mobility have been considered as two important factors that drive the outbreak and transmission of dengue fever (DF). Most studies focus on the local environment while neglecting environment of the places, especially epidemic areas that people came from or traveled to. Commuting is a major form of interactions between places. Therefore, this research generates commuting flows from mobile phone tracked data. Geographically weighted Poisson regression (GWPR) and analysis of variance (ANOVA) are used to examine the effect of commuting flows, especially those from/to epidemic areas, on DF in 2014 at the Jiedao level in Guangzhou. The results suggest that (1) commuting flows from/to epidemic areas affect the transmission of DF; (2) such effects vary in space; and (3) the spatial variation of the effects can be explained by the environment of the epidemic areas that commuters commuted from/to. These findings have important policy implications for making effective intervention strategies, especially when resources are limited.