Association between meteorological factors and the prevalence dynamics of Japanese encephalitis

Tu, Taotian; Xu, Kai; Xu, Lei; Gao, Yuan; Zhou, Ying; He, Yaming; Liu, Yang; Liu, Qiyong; HengQing, Ji; Tang, Wenge

doi:10.1371/journal.pone.0247980

Cited by 20 publications

(16 citation statements)

References 36 publications

(20 reference statements)

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“…Japanese encephalitis (JE), a serious vector-borne viral infection caused by the Japanese encephalitis virus (JEV), is responsible for causing Epidemic encephalitis B—an acute infectious disease of the central nervous system, in 24 countries of Southeast Asia and the Western Pacific 1 – 3 . As the transmission of JE is highly dynamic, several studies have reported substantial variation in the estimation of its global impact.…”

Section: Introductionmentioning

confidence: 99%

Mechanistic insights into the Japanese encephalitis virus RNA dependent RNA polymerase protein inhibition by bioflavonoids from Azadirachta indica

Dwivedi¹,

Singh

El-Kafraway

et al. 2021

Sci Rep

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Japanese encephalitis (JE) virus is a flavivirus causing encephalitis causing neurological damage. RNA-dependent-RNA-polymerase (RdRp) is responsible for genome replication making it excellent anti-viral target. In this study, the crystal structure of JE RdRp (jRdRp) and bioflavonoids reported in Azadirachta indica were retrieved from specific databases. Structure-based virtual screening was employed using MTiOpenScreen server and top four compounds selected with the most negative docking scores. Conformations were redocked using AutoDock Vina; these complexes showed mechanistic interactions with Arg474, Gly605, Asp668, and Trp800 residues in the active site of jRdRp, i.e., guanosine-5′-triphosphate. Furthermore, 100 ns classical molecular dynamics simulation and binding free energy calculation showed stability of docked bioflavonoids in the active jRdRp pocket and significant contribution of van-der-Waals interactions for docked complex stability during simulation. Therefore, this study predicted the anti-viral activity of Gedunin, Nimbolide, Ohchinin acetate, and Kulactone against jRdRp and can be considered for further antiviral drug development.

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Section: Introductionmentioning

confidence: 99%

Mechanistic insights into the Japanese encephalitis virus RNA dependent RNA polymerase protein inhibition by bioflavonoids from Azadirachta indica

Dwivedi¹,

Singh

El-Kafraway

et al. 2021

Sci Rep

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“…Then, we applied the Dropout method to examine the uncertainty of 1- to 12-week ahead LSTM models, which has been used in estimating the uncertainty of LSTM-based disease risk prediction [ 38 ]. Specifically, based on the fixed parameters of LSTM and the testing set, we outputted 50 predictions by dropping a fixed percent of units randomly and computed the maximum, minimum, and mean of 50 predicted values for each epi week to generate the predicted interval.…”

Section: Methodsmentioning

confidence: 99%

Improving Dengue Forecasts by Using Geospatial Big Data Analysis in Google Earth Engine and the Historical Dengue Information-Aided Long Short Term Memory Modeling

Gurgel

et al. 2022

Biology

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Timely and accurate forecasts of dengue cases are of great importance for guiding disease prevention strategies, but still face challenges from (1) time-effectiveness due to time-consuming satellite data downloading and processing, (2) weak spatial representation capability due to data dependence on administrative unit-based statistics or weather station-based observations, and (3) stagnant accuracy without the application of historical case information. Geospatial big data, cloud computing platforms (e.g., Google Earth Engine, GEE), and emerging deep learning algorithms (e.g., long short term memory, LSTM) provide new opportunities for advancing these efforts. Here, we focused on the dengue epidemics in the urban agglomeration of the Federal District of Brazil (FDB) during 2007–2019. A new framework was proposed using geospatial big data analysis in the Google Earth Engine (GEE) platform and long short term memory (LSTM) modeling for dengue case forecasts over an epidemiological week basis. We first defined a buffer zone around an impervious area as the main area of dengue transmission by considering the impervious area as a human-dominated area and used the maximum distance of the flight range of Aedes aegypti and Aedes albopictus as a buffer distance. Those zones were used as units for further attribution analyses of dengue epidemics by aggregating the pixel values into the zones. The near weekly composite of potential driving factors was generated in GEE using the epidemiological weeks during 2007–2019, from the relevant geospatial data with daily or sub-daily temporal resolution. A multi-step-ahead LSTM model was used, and the time-differenced natural log-transformed dengue cases were used as outcomes. Two modeling scenarios (with and without historical dengue cases) were set to examine the potential of historical information on dengue forecasts. The results indicate that the performance was better when historical dengue cases were used and the 5-weeks-ahead forecast had the best performance, and the peak of a large outbreak in 2019 was accurately forecasted. The proposed framework in this study suggests the potential of the GEE platform, the LSTM algorithm, as well as historical information for dengue risk forecasting, which can easily be extensively applied to other regions or globally for timely and practical dengue forecasts.

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“…Twenty years ago, approximately 75% of JE patients were children aged 0-14 years, whereas adults were generally considered immune because they had experienced at least one natural infection [2]. The JE fatality rate is 20-30%, and 30-50% of survivors suffer from permanent and irreversible neuropsychiatric sequelae, which have placed a heavy burden on the public health system and society [3]. Therefore, JE has become a public health issue of international concern [4].…”

Section: Introductionmentioning

confidence: 99%

The epidemiology and disease burden of children hospitalized for viral infections within the family Flaviviridae in China: A national cross-sectional study

Wang

Zhang

et al. 2022

PLoS Negl Trop Dis

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Background Viruses of the family Flaviviridae, including Japanese encephalitis virus (JEV), dengue virus (DENV), yellow fever virus (YFV) and hepatitis C virus (HCV), are widely distributed worldwide. JEV, DENV and YFV belong to the genus Flavivirus, whereas HCV belongs to the genus Hepacivirus. Children’s symptoms are usually severe. As a result, rates of hospitalization due to infection with these viruses are high. The epidemiology and disease burden of hospitalized children have rarely been described in detail to date. The objective of this study was to report the general epidemiological characteristics, clinical phenotype, length of stay (LOS), burden of disease, and potential risk factors for hospitalized children infected with JEV, DENV, YFV, or HCV in Chinese pediatric hospitals. Methodology A cross-sectional study of epidemiology and disease burden of children hospitalized for Flaviviridae virus infections between December 2015 and December 2020 in China was performed. Face sheets of discharge medical records (FSMRs) were collected from 27 tertiary children’s hospitals in the Futang Research Center of Pediatric Development and aggregated into FUTang Update medical REcords (FUTURE). Information on sociodemographic variables, clinical phenotype, and LOS as well as economic burden was included in FSMRs and compared using appropriate statistical tests. Findings The study described 490 children aged 0–15 years hospitalized for infections with Flaviviridae viruses. Japanese encephalitis (JE) cases are the highest, accounting for 92.65% of the total hospitalization cases caused by Flaviviridae virus infection. The incidence of JE peaked from July to October with a profile of a high proportion of severe cases (68.06%) and low mortality (0.44%). Rural children had a significantly higher incidence than urban children (91.63%). Most hospitalized dengue cases were reported in 2019 when dengue outbreaks occurred in many provinces of China, although only 14 dengue cases were collected during the study period. Yellow fever (YF) is still an imported disease in China. The hospitalizations for children with hepatitis C (HC) were not high, and mild chronic HC was the main clinical phenotype of patients. Among the four viral infections, JE had the highest disease burden (LOS and expenditure) for hospitalized children. Conclusion First, the present study reveals that JE remains the most serious disease due to Flaviviridae virus infection and threatens children’s health in China. Many pediatric patients have severe illnesses, but their mortality rate is lower, suggesting that existing treatment is effective. Both JEV vaccination and infection control of rural children should represent a focus of study. Second, although the dual risks of indigenous epidemics and imports of DENV still exist, the prevalence of DENV in children is generally manageable. Third, YFV currently shows no evidence of an epidemic in China. Finally, the proportion of children with chronic hepatitis C (CHC) is relatively large among hospitalized children diagnosed with HCV. Thus, early and effective intervention should be offered to children infected with HCV to ease the burden of CHC on public health.

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Association between meteorological factors and the prevalence dynamics of Japanese encephalitis

Cited by 20 publications

References 36 publications

Mechanistic insights into the Japanese encephalitis virus RNA dependent RNA polymerase protein inhibition by bioflavonoids from Azadirachta indica

Mechanistic insights into the Japanese encephalitis virus RNA dependent RNA polymerase protein inhibition by bioflavonoids from Azadirachta indica

Improving Dengue Forecasts by Using Geospatial Big Data Analysis in Google Earth Engine and the Historical Dengue Information-Aided Long Short Term Memory Modeling

The epidemiology and disease burden of children hospitalized for viral infections within the family Flaviviridae in China: A national cross-sectional study

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