Epidemiological characteristics and temporal-spatial analysis of overseas imported dengue fever cases in outbreak provinces of China, 2005–2019

Role of vector phenotypic plasticity in disease transmission as illustrated by the spread of dengue virus by Aedes albopictus

The incidence of vector-borne disease is on the rise globally, with burdens increasing in endemic countries and outbreaks occurring in new locations. Effective mitigation and intervention strategies require models that accurately predict both spatial and temporal changes in disease dynamics, but this remains challenging due to the complex and interactive relationships between environmental variation and the vector traits that govern the transmission of vector-borne diseases. Predictions of disease risk in the literature typically assume that vector traits vary instantaneously and independently of population density, and therefore do not capture the delayed response of these same traits to past biotic and abiotic environments. We argue here that to produce accurate predictions of disease risk it is necessary to account for environmentally driven and delayed instances of phenotypic plasticity. To show this, we develop a stage and phenotypically structured model for the invasive mosquito vector, Aedes albopictus, and dengue, the second most prevalent human vector-borne disease worldwide. We find that environmental variation drives a dynamic phenotypic structure in the mosquito population, which accurately predicts global patterns of mosquito trait-abundance dynamics. In turn, this interacts with disease transmission to capture historic dengue outbreaks. By comparing the model to a suite of simpler models, we reveal that it is the delayed phenotypic structure that is critical for accurate prediction. Consequently, the incorporation of vector trait relationships into transmission models is critical to improvement of early warning systems that inform mitigation and control strategies.

Spatiotemporal analysis of imported and local dengue virus and cases in a metropolis in Southwestern China, 2013-2022

Dengue fever is a viral illness, mainly transmitted by Aedes aegypti and Aedes albopictus. With climate change and urbanisation, more urbanised areas are becoming suitable for the survival and reproduction of dengue vector, consequently are becoming suitable for dengue transmission in China. Chongqing, a metropolis in southwestern China, has recently been hit by imported and local dengue fever, experiencing its first local outbreak in 2019. However, the genetic evolution dynamics of dengue viruses and the spatiotemporal patterns of imported and local dengue cases have not yet been elucidated. Hence, this study implemented phylogenetic analyses using genomic data of dengue viruses in 2019 and 2023 and a spatiotemporal analysis of dengue cases collected from 2013 to 2022. We sequenced a total of 15 nucleotide sequences of E genes. The dengue viruses formed separate clusters and were genetically related to those from Guangdong Province, China, and countries in Southeast Asia, including Laos, Thailand, Myanmar and Cambodia. Chongqing experienced a dengue outbreak in 2019 when 168 imported and 1,243 local cases were reported, mainly in September and October. Few cases were reported in 2013-2018, and only six were imported from 2020 to 2022 due to the COVID-19 lockdowns. Our findings suggest that dengue prevention in Chongqing should focus on domestic and overseas population mobility, especially in the Yubei and Wanzhou districts, where airports and railway stations are located, and the period between August and October when dengue outbreaks occur in endemic regions. Moreover, continuous vector monitoring should be implemented, especially during August-October, which would be useful for controlling the Aedes mosquitoes. This study is significant for defining Chongqing's appropriate dengue prevention and control strategies.

Dynamics and Efficacy: A Comprehensive Evaluation of the Advanced Dengue Fever Surveillance and Early Warning System in Ningbo City, 2023

Objective

To conduct a comprehensive evaluation of the Dengue Fever Surveillance and Early Warning System deployed in Ningbo City during 2023, focusing on its capacity for timely identification and reporting of dengue fever cases, particularly imported cases from endemic regions.

Methods

A detailed data of patient clinical features and blood profile trends was collected from clinical records and surveillance reports, focusing on the rapid diagnostic processes and surveillance rigor. This study assessed the effectiveness of the system in identifying and reporting dengue cases and identified the limitations of the existing framework through a basic statistical approach.

Results

The system demonstrated timely identification and reporting of dengue fever cases, with a particular emphasis on imported cases. However, several limitations were identified, including the need for more precise monitoring criteria and improved coordination with medical entities.

Conclusion

The study underscores the critical role of public health bodies in managing disease outbreaks and advocates for enhanced methodologies to refine epidemic control efforts. The findings contribute to the advancement of early warning mechanisms and the improvement of proactive infectious disease monitoring in metropolitan environments, providing valuable insights for fortifying the Dengue Fever Surveillance and Early Warning System in Ningbo City.

The timeline of overseas imported cases acts as a strong indicator of dengue outbreak in mainland China

The emergence of dengue viruses in new, susceptible human populations worldwide is increasingly influenced by a combination of local and global human movements and favorable environmental conditions. While various mathematical models have explored the impact of environmental factors on dengue outbreaks, the significant role of human mobility both internationally and domestically in transmitting the disease has been less frequently addressed. In this context, we introduce a modeling framework that integrates the effects of international travel-induced imported cases, climatic conditions, and local human movements to assess the spatiotemporal dynamics of dengue transmission. Utilizing the generation matrix method, we calculate the basic reproduction number and its sensitivity to various model parameters. Through numerical simulations using data on climate, human mobility, and reported dengue cases in mainland China, our model demonstrates a good agreement with observed data upon validation. Our findings reveal that while climatic conditions are a key driver for the rapid dengue transmission, human mobility plays a crucial role in its local spread. Importantly, the model highlights the significant impact of imported cases from overseas on the initiation of dengue outbreaks and their contribution to increasing the disease incidence rate by 34.6%. Furthermore, the analysis identifies that dengue cases originating from regions, such as Cambodia and Myanmar internationally, and Guangzhou and Xishuangbanna domestically, have the potential to significantly increase the disease burden in mainland China. These insights emphasize the critical need to include data on imported cases and domestic travel patterns in disease outbreak models to improve the precision of predictions, thereby enhancing dengue prevention, surveillance, and response strategies.

Forecasting and mapping dengue fever epidemics in China: a spatiotemporal analysis

BACKGROUND

Dengue fever (DF) has emerged as a significant public health concern in China. The spatiotemporal patterns and underlying influencing its spread, however, remain elusive. This study aims to identify the factors driving these variations and to assess the city-level risk of DF epidemics in China.

METHODS

We analyzed the frequency, intensity, and distribution of DF cases in China from 2003 to 2022 and evaluated 11 natural and socioeconomic factors as potential drivers. Using the random forest (RF) model, we assessed the contributions of these factors to local DF epidemics and predicted the corresponding city-level risk.

RESULTS

Between 2003 and 2022, there was a notable correlation between local and imported DF epidemics in case numbers (r = 0.41, P < 0.01) and affected cities (r = 0.79, P < 0.01). With the increase in the frequency and intensity of imported epidemics, local epidemics have become more severe. Their occurrence has increased from five to eight months per year, with case numbers spanning from 14 to 6641 per month. The spatial distribution of city-level DF epidemics aligns with the geographical divisions defined by the Huhuanyong Line (Hu Line) and Qin Mountain-Huai River Line (Q-H Line) and matched well with the city-level time windows for either mosquito vector activity (83.59%) or DF transmission (95.74%). The RF models achieved a high performance (AUC = 0.92) when considering the time windows. Importantly, they identified imported cases as the primary influencing factor, contributing significantly (24.82%) to local DF epidemics at the city level in the eastern region of the Hu Line (E-H region). Moreover, imported cases were found to have a linear promoting impact on local epidemics, while five climatic and six socioeconomic factors exhibited nonlinear effects (promoting or inhibiting) with varying inflection values. Additionally, this model demonstrated outstanding accuracy (hitting ratio = 95.56%) in predicting the city-level risks of local epidemics in China.

CONCLUSIONS

China is experiencing an increasing occurrence of sporadic local DF epidemics driven by an unavoidably higher frequency and intensity of imported DF epidemics. This research offers valuable insights for health authorities to strengthen their intervention capabilities against this disease.

Epidemiological Characteristics of Overseas-Imported Infectious Diseases Identified through Airport Health-Screening Measures: A Case Study on Fuzhou, China

BACKGROUND

This study aimed to examine the epidemiological characteristics of imported infections and assess the effectiveness of border health screening in detecting imported diseases.

METHODS

We obtained infection data for 2016 to 2019 from the Fuzhou Changle International Airport Infection Reporting System. The demographic, temporal, and spatial characteristics of travel-related infections were analyzed using r×c contingency tables, the Cochran-Armitage trend test, and seasonal-trend decomposition using LOESS (STL). Detection rates were used as a proxy for the effectiveness of border health-screening measures.

RESULTS

Overall, 559 travel-related infections were identified during the study period, with 94.3% being imported infections. Airport health screening demonstrated an overall effectiveness of 23.7% in identifying travel-associated infections. Imported infections were predominantly identified in males, with 55.8% of cases occurring in individuals aged 20-49. The peak periods of infection importation were from January to February and from May to August. The infectious diseases identified were imported from 25 different countries and regions. All dengue fever cases were imported from Southeast Asia. Most notifiable infections (76.0%) were identified through fever screening at the airport.

CONCLUSION

The increasing number of imported infections poses a growing challenge for public health systems. Multifaceted efforts including surveillance, vaccination, international collaboration, and public awareness are required to mitigate the importation and spread of infectious diseases from overseas sources.

Phylodynamics unveils invading and diffusing patterns of dengue virus serotype-1 in Guangdong, China from 1990 to 2019 under a global genotyping framework

BACKGROUND

The strong invasiveness and rapid expansion of dengue virus (DENV) pose a great challenge to global public health. However, dengue epidemic patterns and mechanisms at a genetic scale, particularly in term of cross-border transmissions, remain poorly understood. Importation is considered as the primary driver of dengue outbreaks in China, and since 1990 a frequent occurrence of large outbreaks has been triggered by the imported cases and subsequently spread to the western and northern parts of China. Therefore, this study aims to systematically reveal the invasion and diffusion patterns of DENV-1 in Guangdong, China from 1990 to 2019.

METHODS

These analyses were performed on 179 newly assembled genomes from indigenous dengue cases in Guangdong, China and 5152 E gene complete sequences recorded in Chinese mainland. The genetic population structure and epidemic patterns of DENV-1 circulating in Chinese mainland were characterized by phylogenetics, phylogeography, phylodynamics based on DENV-1 E-gene-based globally unified genotyping framework.

RESULTS

Multiple serotypes of DENV were co-circulating in Chinese mainland, particularly in Guangdong and Yunnan provinces. A total of 189 transmission clusters in 38 clades belonging to 22 subgenotypes of genotype I, IV and V of DENV-1 were identified, with 7 Clades of Concern (COCs) responsible for the large outbreaks since 1990. The epidemic periodicity was inferred from the data to be approximately 3 years. Dengue transmission events mainly occurred from Great Mekong Subregion-China (GMS-China), Southeast Asia (SEA), South Asia Subcontinent (SASC), and Oceania (OCE) to coastal and land border cities respectively in southeastern and southwestern China. Specially, Guangzhou was found to be the most dominant receipting hub, where DENV-1 diffused to other cities within the province and even other parts of the country. Genome phylogeny combined with epidemiological investigation demonstrated a clear local consecutive transmission process of a 5C1 transmission cluster (5C1-CN4) of DENV-1 in Guangzhou from 2013 to 2015, while the two provinces of Guangdong and Yunnan played key roles in ongoing transition of dengue epidemic patterns. In contextualizing within Invasion Biology theories, we have proposed a derived three-stage model encompassing the stages of invasion, colonization, and dissemination, which is supposed to enhance our understanding of dengue spreading patterns.

CONCLUSIONS

This study demonstrates the invasion and diffusion process of DENV-1 in Chinese mainland within a global genotyping framework, characterizing the genetic diversities of viral populations, multiple sources of importation, and periodic dynamics of the epidemic. These findings highlight the potential ongoing transition trends from epidemic to endemic status offering a valuable insight into early warning, prevention and control of rapid spreading of dengue both in China and worldwide.

Transcription factor B-H2 regulates CYP9J34 expression conveying deltamethrin resistance in Culex pipiens pallens

BACKGROUND

Mosquitoes are vectors of various diseases, posing significant health threats worldwide. Chemical pesticides, particularly pyrethroids like deltamethrin, are commonly used for mosquito control, but the emergence of resistant mosquito populations has become a concern. In the deltamethrin-resistant (DR) strain of Culex pipiens pallens, the highly expressed cytochrome P450 9 J34 (CYP9J34) gene is believed to play a role in resistance, yet the underlying mechanism remains unclear.

RESULTS

Quantitative polymerase chain reaction with reverse transcription (qRT-PCR) analysis revealed that the expression of CYP9J34 was 14.6-fold higher in DR strains than in deltamethrin-susceptible (DS) strains. The recombinant production of CYP9J34 protein of Cx. pipiens pallens showed that the protein could directly metabolize deltamethrin, yielding the major metabolite 4'-OH deltamethrin. Through dual luciferase reporter assays and RNA interference, the transcription factor homeobox protein B-H2-like (B-H2) was identified to modulate the expression of the CYP9J34 gene, contributing to mosquito resistance to deltamethrin.

CONCLUSIONS

Our findings demonstrate that the CYP9J34 protein could directly degrade deltamethrin, and the transcription factor B-H2 could regulate CYP9J34 expression, influencing the resistance of mosquitoes to deltamethrin. © 2023 Society of Chemical Industry.

Comparative whole-genome analysis of China and global epidemic Pseudomonas aeruginosa high-risk clones

OBJECTIVES

The various sequence types (STs) of Pseudomonas aeruginosa (P. aeruginosa) high-risk clones (HiRiCs) have been sporadically reported in China, but the systematic analysis of genomes for these STs remains limited. This study aimed to address the evolutionary pathways underlying the emergence of HiRiCs and their routes of dissemination from Chinese and global perspectives.

METHODS

The phylogenetic analysis was performed based on 416 newly sequenced clinical P. aeruginosa strains from Guangdong (GD), published genome sequences of 282 Chinese isolates, and 868 HiRiCs isolates from other countries. The genomic comparison study of global HiRiC ST244 was conducted to detect the model of global dissemination and local separation driven by association regional-specific antibiotic resistance genes. Furthermore, the evolutionary route of the emerging, China-specific HiRiC ST1971 was explored using Most Recent Common Ancestor (MRCA) analysis.

RESULTS

Based on comparative genomics analysis, we found a clear geographical separation of ST244 isolates, yet with an association between ST244 isolates from GD and America. We identified a set of 38 AMR genes that contribute to the geographical separation in ST244, and we identified genetic determinants either positively (MexB) and negatively (opmD) associated with GD ST244. For the China-unique HiRiC ST1971, its evolutionary history across different continents before emerging as ST1971 in China was also deduced.

CONCLUSION

This study provides insight into the specific genetics underlying regional differences among globally disseminated P. aeruginosa HiRiCs (ST244) as well as new understanding of the dissemination and evolution of a regional HiRiC (ST1971). Understanding the genetics of these and other HiRiCs may assist in controlling their emergence and further spread.

Detrended seasonal relationships and impact of climatic factors combined with spatiotemporal effect on the prevalence of human brucellosis

Human brucellosis (HB) is a seasonal and climate-affected infectious disease that is posing an increasing threat to public health and economy. However, most of the research on the seasonal relationships and impact of climatic factors on HB did not consider the secular trend and spatiotemporal effect related to the disease. We herein utilized long-term surveillance data on HB from 2008 to 2020 using sinusoidal models to explore detrended relationships between climatic factors and HB. In addition, we assessed the impact of such climatic factors on HB using a spatial panel data model combined with the spatiotemporal effect. HB peaked around mid-May. HB was significantly correlated with climatic factors with 1-5-month lag when the respective correlations reached the maximum across the different lag periods. Each 0.1 °C increase in temperature led to 0.5% decrease in the 5-month lag incidence of HB. We also observed a positive spatiotemporal effect on the disease. Our study provides a detailed and in-depth overview of seasonal relationships and impact of climatic factors on HB. In addition, it proposes a novel approach for exploring the seasonal relationships and quantifying the impacts of climatic factors on various infectious diseases.

Effects of the source of information and knowledge of dengue fever on the mosquito control behavior of residents of border areas of Yunnan, China

BACKGROUND

Strengthening the mosquito control measures undertaken by residents of an area where dengue fever is present can significantly decrease the spread of this disease. The aim of this study was to explore the effects of the source of information and knowledge of dengue fever on the mosquito control behavior of residents of areas at high risk of this disease to determine effective ways of enhancing this behavior.

METHODS

A survey was conducted via face-to-face interviews or questionnaires between March and May 2021 in three regions of the province of Yunnan, China. The survey included basic information about the respondents, the source(s) of their dengue fever information, the level of their dengue fever knowledge, and the measures they had implemented to control mosquitoes. Principal component analysis was used to extract the main components of the sources of information. Correlation analysis and structural equation analysis were used to explore the impact of the sources of information and residents' dengue fever knowledge on their mosquito control behavior.

RESULTS

Publicity achieved through mass media, including official WeChat accounts, magazines/newspapers, poster leaflets, television/radio and the Internet, had a direct effect on dengue fever knowledge and mosquito control behavior, and indirectly affected mosquito control behavior through dengue fever knowledge. Organized publicity campaigns, including information provided by medical staff and through community publicity, had a direct effect on dengue fever knowledge and indirectly affected mosquito control behavior through dengue fever knowledge. The residents' level of dengue fever knowledge had a significant, positive, direct effect on their mosquito control behavior.

CONCLUSIONS

Mosquito control is an important measure for the prevention and control of outbreaks of dengue fever. An effective source of information can improve the level of dengue fever knowledge among residents and thus enhance their mosquito control behavior.

Epidemiological Characteristics and Economic Burden of Dengue in Zhejiang Province, China

Dengue imposes a heavy economic burden on families and society. We used surveillance data reported in 2019 to characterize the dengue epidemic in Zhejiang Province, China, which provided guidance for dengue prevention and control. Dengue epidemics mostly occurred in July to October. People aged 30-44 years, males, and commercial service workers were more likely to suffer from dengue. The epidemic areas were mainly in Hangzhou and Wenzhou. Meanwhile, we assessed the economic cost of dengue in the province from both family and organizational perspectives. The direct economic burden of dengue patients was estimated to be USD 405,038.25, and the indirect economic burden was USD 140,364.90, for a total economic burden of USD 543,213.00. The direct economic burden of dengue patients should be reduced by increasing the coverage and reimbursement of health insurance. Additionally, the total annual cost of dengue prevention and control for the government and organizational sectors was estimated to be USD 7075,654.83. Quantifying the dengue burden is critical for developing disease control strategies, allocating public health resources, and setting health policy priorities.

The patterns and driving forces of dengue invasions in China

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.

Climate change and Aedes albopictus risks in China: current impact and future projection

BACKGROUND

Future distribution of dengue risk is usually predicted based on predicted climate changes using general circulation models (GCMs). However, it is difficult to validate the GCM results and assess the uncertainty of the predictions. The observed changes in climate may be very different from the GCM results. We aim to utilize trends in observed climate dynamics to predict future risks of Aedes albopictus in China.

METHODS

We collected Ae. albopictus surveillance data and observed climate records from 80 meteorological stations from 1970 to 2021. We analyzed the trends in climate change in China and made predictions on future climate for the years 2050 and 2080 based on trend analyses. We analyzed the relationship between climatic variables and the prevalence of Ae. albopictus in different months/seasons. We built a classification tree model (based on the average of 999 runs of classification and regression tree analyses) to predict the monthly/seasonal Ae. albopictus distribution based on the average climate from 1970 to 2000 and assessed the contributions of different climatic variables to the Ae. albopictus distribution. Using these models, we projected the future distributions of Ae. albopictus for 2050 and 2080.

RESULTS

The study included Ae. albopictus surveillance from 259 sites in China found that winter to early spring (November-February) temperatures were strongly correlated with Ae. albopictus prevalence (prediction accuracy ranges 93.0-98.8%)-the higher the temperature the higher the prevalence, while precipitation in summer (June-September) was important predictor for Ae. albopictus prevalence. The machine learning tree models predicted the current prevalence of Ae. albopictus with high levels of agreement (accuracy > 90% and Kappa agreement > 80% for all 12 months). Overall, winter temperature contributed the most to Ae. albopictus distribution, followed by summer precipitation. An increase in temperature was observed from 1970 to 2021 in most places in China, and annual change rates varied substantially from -0.22 ºC/year to 0.58 ºC/year among sites, with the largest increase in temperature occurring from February to April (an annual increase of 1.4-4.7 ºC in monthly mean, 0.6-4.0 ºC in monthly minimum, and 1.3-4.3 ºC in monthly maximum temperature) and the smallest in November and December. Temperature increases were lower in the tropics/subtropics (1.5-2.3 ºC from February-April) compared to the high-latitude areas (2.6-4.6 ºC from February-April). The projected temperatures in 2050 and 2080 by this study were approximately 1-1.5 °C higher than those projected by GCMs. The estimated current Ae. albopictus risk distribution had a northern boundary of north-central China and the southern edge of northeastern China, with a risk period of June-September. The projected future Ae. albopictus risks in 2050 and 2080 cover nearly all of China, with an expanded risk period of April-October. The current at-risk population was estimated to be 960 million and the future at-risk population was projected to be 1.2 billion.

CONCLUSIONS

The magnitude of climate change in China is likely to surpass GCM predictions. Future dengue risks will expand to cover nearly all of China if current climate trends continue.

Knockdown resistance mutations distribution and characteristics of Aedes albopictus field populations within eleven dengue local epidemic provinces in China

Background

Aedes albopictus, commonly known as the tiger mosquito, has attracted global attention because its bite can transmit several viruses, such as dengue virus. With the absence of an effective therapy and vaccine, mosquito control is the sole method for dengue fever control. However, Ae. albopictus has developed resistance to most insecticides, especially pyrethroids. Many scholars have conducted thorough research for the target-site of pyrethroids. The main target-site is the voltage-gated sodium channel gene (VGSC) whose mutation causes knockdown resistance (kdr). The spatial distribution of three locus kdr mutations in Ae. albopictus has not been comprehensively analyzed nationwide in China. In addition, the relationship between the frequency of kdr mutations and dengue fever has not yet been explored.

Methods

A total of 2,241 Ae. albopictus samples from 49 populations from 11 provinces of mainland China were collected in 2020 and analyzed for mutations in the VGSC gene. DNAstar 7.1. Seqman and Mega-X were used to compare the sequences and read the peak map to confirm the genotypes and alleles of each mutation. ArcGIS 10.6 software was used to make interpolation and extract meteorological data of collection sites and to conduct spatial autocorrelation analysis. R 4.1.2 software was used to conduct a chi-square test for kdr mutations and dengue area and to analyze the correlation between meteorological factors and kdr mutations.

Results

The overall frequencies of mutant alleles at 1016G, 1532T, and 1534S/C/L were 13.19%, 4.89%, and 46.90%, respectively. Mutations at the three loci were found at 89.80% (44/49), 44.90% (22/49), and 97.96% (48/49) of the field populations. At each of the loci V1016 and I1532, only one allele was detected, which was GGA(G) and ACC(T), respectively. Five mutant alleles were found at codon 1534: TCC/S (33.49%), TGC/C (11.96%), TTG/L (0.60%), CTC/L (0.49%), and TTA/L (0.58%). In total, 31 triple-locus genotype combinations were found, and the single locus mutation was the most common. We also found firstly triple-locus mutant individuals, whose genotypes were V/G+I/T+F/S and V/G+I/T+S/S. The 1016 and 1532 mutation rates were significantly negatively related to the annual average temperature (AAT), but the 1534 mutation rate was significantly positively related to AAT. The 1532 mutation rate was significantly positively related to the 1016 mutation rate but negatively related to the 1534 mutation rate. A relationship was observed between the 1534 codon mutation rate and dengue epidemic areas in this study. Furthermore, spatial autocorrelation analysis results showed that the mutation rates of different codons in different geographical areas had spatial aggregation and positive spatial correlation.

Conclusion

This study showed that the multiple kdr mutations at codon 1016, 1532 and 1534 of Ae. albopictus were found in most areas of China. Two novel triple-locus genotype combinations, V/G+I/T+F/S and V/G+I/T+S/S, were detected in this study. In addition, the relationship between mosquito resistance and dengue fever outbreak should be further explored, especially considering the insecticide-usage history in different areas. The characteristic of spatial aggregation of VGSC gene mutation rates reminds us to notice the gene exchange and similarity of insecticide usage in the adjacent areas. The use of pyrethroids should be restricted to delay resistance development. New-type insecticides should be developed to adjust the changes in the resistance spectrum. Our study provides abundant data on the Ae. albopictus kdr gene mutation in China; these findings will be useful for the correlation analysis of molecular mechanism of insecticide resistance.

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.

Spatial Heterogeneity and Its Influencing Factors of Syphilis in Ningxia, Northwest China, from 2004 to 2017: A Spatial Analysis

Syphilis remains a growing and resurging infectious disease in China. However, exploring the influence of environmental factors on the spatiotemporal distribution of syphilis remains under explore. This study aims to analyze the spatiotemporal distribution characteristics of syphilis in Ningxia, Northwest China, and its potential environmental influencing factors. Based on the standardized incidence ratio of syphilis for 22 administrative areas in Ningxia from 2004 to 2017, spatiotemporal autocorrelation and scan analyses were employed to analyze the spatial and temporal distribution characteristics of syphilis incidence, while a fixed-effect spatial panel regression model identified the potential factors affecting syphilis incidence. Syphilis incidence increased from 3.78/100,000 in 2004 to 54.69/100,000 in 2017 with significant spatial clustering in 2007 and 2009-2013. The "high-high" and "low-low" clusters were mainly distributed in northern and southern Ningxia, respectively. The spatial error panel model demonstrated that the syphilis incidence may be positively correlated with the per capita GDP and tertiary industry GDP and negatively correlated with the number of health facilities and healthcare personnel. Sex ratio and meteorological factors were not significantly associated with syphilis incidence. These results show that the syphilis incidence in Ningxia is still increasing and has significant spatial distribution differences and clustering. Socio-economic and health-resource factors could affect the incidence; therefore, strengthening syphilis surveillance of migrants in the economically developed region and allocating health resources to economically underdeveloped areas may effectively help prevent and control syphilis outbreaks in high-risk cluster areas of Ningxia.

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

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.

We performed a general epidemiological and disease burden assessment of 490 hospitalized children infected with any virus from the family Flaviviridae [Japanese encephalitis virus (JEV), dengue virus (DENV), yellow fever virus (YFV) and hepatitis C virus (HCV)] from December 2015 to December 2020 with confirmed clinical presentation and laboratory results. Our study found that hospitalization for Japanese encephalitis (JE) predominated in children who lived in rural areas, and the infection was rate was considerably higher in summer and autumn (July–October) compared with other months. In addition, children hospitalized with JE have the largest share of disease burden. However, the overall low rate of hospitalization and mortality of children shows that China’s JE prevention and control policies remain effective. However, the prevention, control and surveillance of JEV in rural areas should not be neglected. Dengue and yellow fever have not yet caused serious public health concerns among children in China, but the spatial and temporal distributions of viral infection must be assessed to be alert to the indigenous spread of imported cases. CHC is a refractory phenotype of HCV infection in children; thus, early screening and intervention are encouraged given the insidious appearance of symptoms in the early stages after HCV infection. These findings can help to understand the epidemic status of viruses classified in the family Flaviviridae in children and the disease burden of hospitalized children, which is conducive to precise prevention and control, optimization of the allocation of resources, and the formulation of more reasonable and effective policies.

Spatial Analysis of Inequality in Thailand: Applications of Satellite Data and Spatial Statistics/Econometrics

To formulate and monitor the progress of development policies, acquiring data with sufficient spatiotemporal details is inevitable. With the increasing availability of open remote-sensing data and open-source software packages, this research suggested the novelty integration of satellite data and spatial analytical methods, enabling a timely and costless framework for assessing the nationwide socioeconomic condition. Specifically, the spatial statistical and spatial econometrical methods were applied to geospatial data to identify the clustering patterns and the localized associations of inequality in Thailand. The spatial statistical results showed that Bangkok and its vicinity had been a cluster of high socioeconomic conditions, representing the spatial inequality of development. In addition, results of the spatial econometrical models showed that the satellite-based indicators could identify the socioeconomic condition (with p-value < 0.010 and R-squared ranging between 0.345 and 0.657). Inequality indicators (i.e., Gini, Thiel and Atkinson) were then constructed by using survey-based and satellite-based data, informing that spatial inequality has been slowly declining. These findings recommended the new establishment of polycentric growth poles that offer economic opportunities and reduce spatial inequality. In addition, in accordance with Sustainable Development Goal 10 (reduced inequalities), this analytical framework can be applied to country-specific implications along with the global scale extensions.