Dengue is still an imported disease in China: a case study in Guangzhou

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.

Shifting spatial, temporal and demographic patterns of dengue incidence and associated meteorological factors in Jazan Region of Saudi Arabia from 2015-2020

BACKGROUND OBJECTIVES

Dengue poses a considerable public health threat in Saudi Arabia, with escalating outbreaks in Jazan, where seasonal rains create ideal mosquito breeding conditions. Elucidating local epidemiological dynamics is imperative to strengthen evidence-based prevention policies. This study analyzed the spatiotemporal, demographic, and meteorological patterns of dengue in Jazan from 2015-2020.

METHODS

This retrospective cross-sectional study utilized surveillance records for 3427 confirmed dengue cases. Descriptive analyses characterized geographic, seasonal, age, gender, and nationality distributions. Forecasting models project expected epidemics through 2025. Regression analysis identified climate factors associated with monthly case counts.

RESULTS

Dengue exhibited shifting seasonal peaks, transitioning into year-round transmission by 2019, indicating endemic establishment. Cases clustered in different high-burden sectors annually, requiring localized vector control. The majority of affected individuals were young male adults, with gender gaps narrowing over time. Saudi nationals had an escalating incidence, but non-citizens showed a higher risk, signaling importation threats. Seasonal outbreaks were associated with temperature, wind speed, and direction.

INTERPRETATION CONCLUSION

Enhanced surveillance, outbreak forecasting, targeted control activities, and integrated prevention policies grounded in continuous evidence assessment can effectively address endemic dengue transmission in Jazan. This study provides key insights to optimize data-driven decision-making for dengue control in Saudi Arabia.

The molecular epidemiology of a dengue virus outbreak in Taiwan: population wide versus infrapopulation mutation analysis

Dengue virus (DENV) causes approximately 390 million dengue infections worldwide every year. There were 22,777 reported DENV infections in Tainan, Taiwan in 2015. In this study, we sequenced the C-prM-E genes from 45 DENV 2015 strains, and phylogenetic analysis based on C-prM-E genes revealed that all strains were classified as DENV serotype 2 Cosmopolitan genotype. Sequence analysis comparing different DENV-2 genotypes and Cosmopolitan DENV-2 sequences prior to 2015 showed a clade replacement event in the DENV-2 Cosmopolitan genotype. Additionally, a major substitution C-A314G (K73R) was found in the capsid region which may have contributed to the clade replacement event. Reverse genetics virus rgC-A314G (K73R) showed slower replication in BHK-21 and C6/36 cells compared to wildtype virus, as well as a decrease in NS1 production in BHK-21-infected cells. After a series of passaging, the C-A314G (K73R) mutation reverted to wildtype and was thus considered to be unstable. Next generation sequencing (NGS) of three sera collected from a single DENV2-infected patient at 1-, 2-, and 5-days post-admission was employed to examine the genetic diversity over-time and mutations that may work in conjunction with C-A314G (K73R). Results showed that the number of haplotypes decreased with time in the DENV-infected patient. On the fifth day after admission, two new haplotypes emerged, and a single non-synonymous NS4A-L115I mutation was identified. Therefore, we have identified a persistent mutation C-A314G (K73R) in all of the DENV-2 isolates, and during the course of an infection, a single new non-synonymous mutation in the NS4A region appears in the virus population within a single host. The C-A314G (K73R) thus may have played a role in the DENV-2 2015 outbreak while the NS4A-L115I may be advantageous during DENV infection within the host.

Long-term effects of climate factors on dengue fever over a 40-year period

BACKGROUND

Dengue fever stands as one of the most extensively disseminated mosquito-borne infectious diseases worldwide. While numerous studies have investigated its influencing factors, a gap remains in long-term analysis, impeding the identification of temporal patterns, periodicity in transmission, and the development of effective prevention and control strategies. Thus, we aim to analyze the periodicity of dengue fever incidence and explore the association between various climate factors and the disease over an extended time series.

METHODS

By utilizing monthly dengue fever cases and climate data spanning four decades (1978-2018) in Guangdong province, China, we employed wavelet analysis to detect dengue fever periodicity and analyze the time-lag relationship with climate factors. Additionally, Geodetector q statistic was employed to quantify the explanatory power of each climate factor and assess interaction effects.

RESULTS

Our findings revealed a prolonged transmission period of dengue fever over the 40-year period, transitioning from August to November in the 1970s to nearly year-round in the 2010s. Moreover, we observed lags of 1.5, 3.5, and 3 months between dengue fever and temperature, relative humidity, and precipitation, respectively. The explanatory power of precipitation, temperature, relative humidity, and the Oceanic Niño Index (ONI) on dengue fever was determined to be 18.19%, 12.04%, 11.37%, and 5.17%, respectively. Dengue fever exhibited susceptibility to various climate factors, with notable nonlinear enhancement arising from the interaction of any two variables. Notably, the interaction between precipitation and humidity yielded the most significant effect, accounting for an explanatory power of 75.32%.

CONCLUSIONS

Consequently, future prevention and control strategies for dengue fever should take into account these climate changes and formulate corresponding measures accordingly. In regions experiencing the onset of high temperatures, humidity, and precipitation, it is imperative to initiate mosquito prevention and control measures within a specific window period of 1.5 months.

Modelling the dynamic basic reproduction number of dengue based on MOI of Aedes albopictus derived from a multi-site field investigation in Guangzhou, a subtropical region

BACKGROUND

More than half of the global population lives in areas at risk of dengue (DENV) transmission. Developing an efficient risk prediction system can help curb dengue outbreaks, but multiple variables, including mosquito-based surveillance indicators, still constrain our understanding. Mosquito or oviposition positive index (MOI) has been utilized in field surveillance to monitor the wild population density of Aedes albopictus in Guangzhou since 2005.

METHODS

Based on the mosquito surveillance data using Mosq-ovitrap collection and human landing collection (HLC) launched at 12 sites in Guangzhou from 2015 to 2017, we established a MOI-based model of the basic dengue reproduction number (R0) using the classical Ross-Macdonald framework combined with a linear mixed-effects model.

RESULTS

During the survey period, the mean MOI and adult mosquito density index (ADI) using HLC for Ae. albopictus were 12.96 ± 17.78 and 16.79 ± 55.92, respectively. The R0 estimated from the daily ADI (ADID) showed a significant seasonal variation. A 10-unit increase in MOI was associated with 1.08-fold (95% CI 1.05, 1.11) ADID and an increase of 0.14 (95% CI 0.05, 0.23) in the logarithmic transformation of R0. MOI-based R0 of dengue varied by month and average monthly temperature. During the active period of Ae. albopictus from April to November in Guangzhou region, a high risk of dengue outbreak was predicted by the MOI-based R0 model, especially from August to October, with the predicted R0 > 1. Meanwhile, from December to March, the estimates of MOI-based R0 were < 1.

CONCLUSIONS

The present study enriched our knowledge about mosquito-based surveillance indicators and indicated that the MOI of Ae. albopictus could be valuable for application in estimating the R0 of dengue using a statistical model. The MOI-based R0 model prediction of the risk of dengue transmission varied by month and temperature in Guangzhou. Our findings lay a foundation for further development of a complex efficient dengue risk prediction system.

Prior water availability modifies the effect of heavy rainfall on dengue transmission: a time series analysis of passive surveillance data from southern China

Introduction

Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions, potentially due to the neglect of prior water availability in mosquito breeding sites as an effect modifier.

Methods

In this study, we addressed this research gap by considering the impact of prior water availability for the first time. We measured prior water availability as the cumulative precipitation over the preceding 8 weeks and utilized a distributed lag non-linear model stratified by the level of prior water availability to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China.

Results

Our findings suggest that the effects of heavy rainfall are likely to be modified by prior water availability. A 24-55 day lagged impact of heavy rainfall was associated with an increase in dengue risk when prior water availability was low, with the greatest incidence rate ratio (IRR) of 1.37 [95% credible interval (CI): 1.02-1.83] occurring at a lag of 27 days. In contrast, a heavy rainfall lag of 7-121 days decreased dengue risk when prior water availability was high, with the lowest IRR of 0.59 (95% CI: 0.43-0.79), occurring at a lag of 45 days.

Discussion

These findings may help to reconcile the inconsistent conclusions reached by previous studies and improve our understanding of the complex relationship between heavy rainfall and dengue infection risk.

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.

The epidemiology and evolutionary dynamics of massive dengue outbreak in China, 2019

Introduction

In 2019, China experienced massive dengue outbreaks with high incidence and expanded outbreak areas. The study aims to depict dengue's epidemiology and evolutionary dynamics in China and explore the possible origin of these outbreaks.

Methods

Records of confirmed dengue cases in 2019 were obtained from the China Notifiable Disease Surveillance System. The sequences of complete envelope gene detected from the outbreak provinces in China in 2019 were retrieved from GenBank. Maximum Likelihood trees were constructed to genotype the viruses. The median-joining network was used to visualize fine-scale genetic relationships. Four methods were used to estimate the selective pressure.

Results

A total of 22,688 dengue cases were reported, 71.4% of which were indigenous cases and 28.6% were imported cases (including from abroad and from other domestic provinces). The abroad cases were predominantly imported from Southeast Asia countries (94.6%), with Cambodia (3,234 cases, 58.9%), and Myanmar (1,097 cases, 20.0%) ranked as the top two. A total of 11 provinces with dengue outbreaks were identified in the central-south of China, of which Yunnan and Guangdong provinces had the highest number of imported and indigenous cases. The primary source of imported cases in Yunnan was from Myanmar, while in the other ten provinces, the majority of imported cases were from Cambodia. Guangdong, Yunnan and Guangxi provinces were China's primary sources of domestically imported cases. Phylogenetic analysis of the viruses in outbreak provinces revealed three genotypes: (I, IV, and V) in DENV 1, Cosmopolitan and Asian I genotypes in DENV 2, and two genotypes (I and III) in DENV 3. Some genotypes concurrently circulated in different outbreak provinces. Most of the viruses were clustered with those from Southeast Asia. Haplotype network analysis showed that Southeast Asia, possibly Cambodia and Thailand, was the respective origin of the viruses in clade 1 and 4 for DENV 1. Positive selection was detected at codon 386 in clade 1.

Conclusion

Dengue importation from abroad, especially from Southeast Asia, resulted in the dengue epidemic in China in 2019. Domestic transmission between provinces and positive selection on virus evolution may contribute to the massive dengue outbreaks.

Epidemiological characteristics of imported acute infectious diseases in Guangzhou, China, 2005-2019

BACKGROUND

The global spread of infectious diseases is currently a prominent threat to public health, with the accelerating pace of globalization and frequent international personnel intercourse. The present study examined the epidemiological characteristics of overseas imported cases of acute infectious diseases in Guangzhou, China.

METHODS

We retrospectively investigated the distribution of diseases, demographic characteristics, and temporal and spatial variations of imported cases of acute infectious diseases in Guangzhou based on the surveillance data of notifiable infectious diseases from 2005 to 2019, provided by Guangzhou center for Disease Control and Prevention. The Cochran-Armitage trend test was applied to examine the trend in the number of imported cases over time.

RESULTS

A total of 1,025 overseas imported cases of acute infectious diseases were identified during the study period. The top three diseases were dengue (67.12%), malaria (12.39%), and influenza A (H1N1) pdm09 (4.10%). Imported cases were predominantly males, with a sex ratio of 2.6: 1 and 75.22% of the cases were those aged 20-49 years. Businessmen, workers, students and unemployed persons accounted for a large proportion of the cases (68.49%) and many of the cases came from Southeast Asia (59.02%). The number of imported cases of acute infectious diseases increased during the study period and hit 318 in 2019. A clear seasonal pattern was observed in the number of imported cases with a peak period between June and November. Imported cases were reported in all of the 11 districts in Guangzhou and the central districts were more seriously affected compared with other districts.

CONCLUSIONS

The burden of dengue imported from overseas was substantial and increasing in Guangzhou, China, with the peak period from June to November. Dengue was the most common imported disease. Most imported cases were males aged 20-49 years and businessmen. Further efforts, such as strengthening surveillance of imported cases, paying close attention to the epidemics in hotspots, and improving the ability to detect the imported cases from overseas, are warranted to control infectious diseases especially in the center of the city with a higher population density highly affected by imported cases.

Spatiotemporal and Seasonal Trends of Class A and B Notifiable Infectious Diseases in China: A Retrospective Analysis (Preprint)

BACKGROUND

China is the most populous country globally and has made significant achievements in the control of infectious diseases over the last decades. The 2003 SARS epidemic triggered the initiation of the China Information System for Disease Control and Prevention (CISDCP). Since then, numerous studies have investigated the epidemiological features and trends of individual infectious diseases in China; however, few considered the changing spatiotemporal trends and seasonality of these infectious diseases over time.

OBJECTIVE

This study aims to systematically review the spatiotemporal trends and seasonal characteristics of class A and class B notifiable infectious diseases in China during 2005-2020.

METHODS

We extracted the incidence and mortality data of 8 types (27 diseases) of notifiable infectious diseases from the CISDCP. We used the Mann-Kendall and Sen's methods to investigate the diseases' temporal trends, Moran I statistic for their geographical distribution, and circular distribution analysis for their seasonality.

RESULTS

Between January 2005 and December 2020, 51,028,733 incident cases and 261,851 attributable deaths were recorded. Pertussis (P=.03), dengue fever (P=.01), brucellosis (P=.001), scarlet fever (P=.02), AIDS (P<.001), syphilis (P<.001), hepatitis C (P<.001) and hepatitis E (P=.04) exhibited significant upward trends. Furthermore, measles (P<.001), bacillary and amebic dysentery (P<.001), malaria (P=.04), dengue fever (P=.006), brucellosis (P=.03), and tuberculosis (P=.003) exhibited significant seasonal patterns. We observed marked disease burden-related geographic disparities and heterogeneities. Notably, high-risk areas for various infectious diseases have remained relatively unchanged since 2005. In particular, hemorrhagic fever and brucellosis were largely concentrated in Northeast China; neonatal tetanus, typhoid and paratyphoid, Japanese encephalitis, leptospirosis, and AIDS in Southwest China; BAD in North China; schistosomiasis in Central China; anthrax, tuberculosis, and hepatitis A in Northwest China; rabies in South China; and gonorrhea in East China. However, the geographical distribution of syphilis, scarlet fever, and hepatitis E drifted from coastal to inland provinces during 2005-2020.

CONCLUSIONS

The overall infectious disease burden in China is declining; however, hepatitis C and E, bacterial infections, and sexually transmitted infections continue to multiply, many of which have spread from coastal to inland provinces.

Temporal and spatial patterns of dengue geographical distribution in Jeddah, Saudi Arabia

INTRODUCTION

Dengue fever disease is affected by many scoioeconomic and enviromental factors throughout endemic areas globally. These factors contribute to increase the incidence of endemic dengue endemic in Jeddah, Saudi Arabia.

OBJECTIVES

This study aimed to investigate the distribution and spatial patterns of dengue fever cases in Jeddah, and to determine if there is an association between dengue fever and the following environmental factors: temperature, humidity, land cover, climate, rainfall, epicenter of reproduction, and socioeconomic factors.

METHODS

A descriptive and analytical cross-sectional study was conducted in Jeddah in 2020. The study included all reported suspected and confirmed dengue cases. The sample size was 1458 cases. Data were obtained from the Dengue Active Surveillance System and the confirmed cases were geo-distributed in areas by QGIS. All significant variables were included in the logistic regression table.

RESULTS

The majority (61.9 %) were suspected cases and 38.1 % confirmed cases. The majority of the cases were male. The highest spatial distribution was in the middle of Jeddah and the lowest in the south. The highest temporal distribution for confirmed cases was in June, and for suspected cases in December. Age, gender, occupation, and area were all significantly associated with the dengue reported cases. Most all the enviromental factors were not statistically significant.

CONCLUSION

The study showed three clusters of dengue fever and infection concentrated in the middle and east of Jeddah. The lack of investigation in the environmental factors regarding the dengue distribution and its impact on the population area has to be taken seriously and dengue intervention programs should be implemented to reduce the endemic dengue in Jeddah.

Epidemiological Characteristics and the Dynamic Transmission Model of Dengue Fever in Zhanjiang City, Guangdong Province in 2018

Background: With the progress of urbanization, the mobility of people has gradually increased, which has led to the further spread of dengue fever. This study evaluated the transmissibility of dengue fever within districts and between different districts in Zhanjiang City to provide corresponding advice for cross-regional prevention and control. Methods: A mathematical model of transmission dynamics was developed to explore the transmissibility of the disease and to compare that between different regions. Results: A total of 467 DF cases (6.38 per 100,000 people) were reported in Zhanjiang City in 2018. In the model, without any intervention, the number of simulated cases in this epidemic reached about 950. The dengue fever transmissions between districts varied within and between regions. When the spread of dengue fever from Chikan Districts to other districts was cut off, the number of cases in other districts dropped significantly or even to zero. When the density of mosquitoes in Xiashan District was controlled, the dengue fever epidemic in Xiashan District was found to be significantly alleviated. Conclusions: When there is a dengue outbreak, timely measures can effectively control it from developing into an epidemic. Different prevention and control measures in different districts could efficiently reduce the risk of disease transmission.

Dengue and Dengue Virus in Guangdong, China, 1978-2017: Epidemiology, Seroprevalence, Evolution, and Policies

Background

Guangdong is a hyperepidemic area of dengue, which has over 0.72 million cumulative cases within the last four decades, accounting for more than 90% of cases in China. The local epidemic of dengue in Guangdong is suspected to be triggered by imported cases and results in consequent seasonal transmission. However, the comprehensive epidemiological characteristics of dengue in Guangdong are still unclear.

Methods

The epidemiology, seroprevalence, molecular evolution of dengue virus, and the development of policies and strategies on the prevention and control of dengue were analyzed in Guangdong, China from 1978 to 2017.

Findings

Seasonal transmission of dengue virus in Guangdong, China was mainly sustained from July to October of each year. August to September was the highest risk period of local dengue outbreaks. Most of the dengue cases in Guangdong were young and middle-aged adults. Five hundred and three fatal cases were recorded, which declined within the last two decades (n = 10). The serological test of healthy donors' serum samples showed a positive rate of 5.77%. Dengue virus 1-4 (DENV 1-4) was detected in Guangdong from 1978 to 2017. DENV 1 was the dominant serotype of dengue outbreaks from 1978 to 2017, with an increasing tendency of DENV 2 since 2010. Local outbreaks of DENV 3 were rare. DENV 4 was only encountered in imported cases in Guangdong, China. The imported cases were the main source of outbreaks of DENV 1-2. Early detection, management of dengue cases, and precise vector control were the key strategies for local dengue prevention and control in Guangdong, China.

Interpretation

Dengue has not become an endemic arboviral disease in Guangdong, China. Early detection, case management, and implementation of precise control strategies are key findings for preventing local dengue transmission, which may serve for countries still struggling to combat imported dengue in the west pacific areas.

Dengue Fever in Mainland China, 2005-2020: A Descriptive Analysis of Dengue Cases and Aedes Data

Dengue fever occurs throughout mainland China, except in the Tibet Autonomous Region. During 2005–2020, there were 12,701 imported cases and 81,653 indigenous cases recorded. The indigenous cases were mainly clustered in Guangdong (74.0%) and Yunnan provinces (13.7%). Indigenous dengue fever is a seasonal illness in mainland China, manifesting predominantly in summer and autumn. Indigenous dengue fever cases tend to peak every 5years and have shown a substantial increase during the period 2005–2020. During the study period, indigenous dengue fever occurred more than ten times in each of the seven counties of Guangdong Province. Indigenous dengue fever has spread from low to high latitudes; that is, from the southwestern, southern, and southeastern areas to the central and northern regions, and from border ports and cities to rural areas. Aedes aegypti has become widespread in Yunnan Province but has diminished in Guangxi, Guangdong, and Hainan provinces in recent years. Aedes albopictus is distributed throughout mainland China, spanning 25 provinces and municipalities. To maintain effective public health prevention and control, it is important to monitor dengue occurrence, provide dengue classification guidance, and ensure sustainable vector management of Aedes.

Global burden for dengue and the evolving pattern in the past 30 years

BACKGROUND

Dengue is the most prevalent and rapidly spreading mosquito-borne viral disease. We present the global, regional and national burden of dengue from 1990 to 2019 based on the findings from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019).

METHODS

Based upon GBD 2019 dengue data on age-standardized incidence rate (ASIR), age-standardized death rate (ASDR) and age-standardized disability-adjusted life years (DALYs) rate, this study estimates and presents annual percentage change (EAPC) to quantify trends over time to assess potential correlates of increased dengue activity, such as global travel and warming.

RESULTS

Globally from 1990 to 2019, dengue incident cases, deaths and DALYs gradually increased. Those under 5 years of age, once accounting for the largest portion of deaths and DALYs in 1990, were eclipsed by those who were 15-49 years old in 2019. Age standardized incidence [ASIR: EAPC: 3.16, 95% confidence interval (CI): 2.90-3.43], death (ASDR: EAPC: 5.42, 95% CI: 2.64-8.28) and DALY rates (EAPC: 2.31, 95% CI: 2.00-2.62) accelerated most among high-middle and high sociodemographic index (SDI) regions. South-East Asia and South Asia had most of the dengue incident cases, deaths and DALYs, but East Asia had the fastest rise in ASIR (EAPC: 4.57, 95% CI: 4.31, 4.82), while Tropical Latin America led in ASDR (EAPC: 11.32, 95% CI: 9.11, 13.58) and age-standardized DALYs rate (EAPC: 4.13, 95% CI: 2.98, 5.29). SDI showed consistent bell-shaped relationship with ASIR, ASDR and age-standardized DALYs rate. Global land-ocean temperature index and air passenger travel metrics were found to be remarkably positively correlated with dengue burden.

CONCLUSIONS

The burden of dengue has become heavier from 1990 to 2019, amidst the three decades of urbanization, warming climates and increased human mobility in much of the world. South-East Asia and South Asia remain as regions of concern, especially in conjunction with the Americas' swift rise in dengue burden.

The epidemiological characteristics of dengue in high-risk areas of China, 2013-2016

Introduction

Dengue has become a more serious human health concern in China, with increased incidence and expanded outbreak regions. The knowledge of the cross-sectional and longitudinal epidemiological characteristics and the evolutionary dynamics of dengue in high-risk areas of China is limited.

Methods

Records of dengue cases from 2013 to 2016 were obtained from the China Notifiable Disease Surveillance System. Full envelope gene sequences of dengue viruses detected from the high-risk areas of China were collected. Maximum Likelihood tree and haplotype network analyses were conducted to explore the phylogenetic relationship of viruses from high-risk areas of China.

Results

A total of 56,520 cases was reported in China from 2013 to 2016. During this time, Yunnan, Guangdong and Fujian provinces were the high-risk areas. Imported cases occurred almost year-round, and were mainly introduced from Southeast Asia. The first indigenous case usually occurred in June to August, and the last one occurred before December in Yunnan and Fujian provinces but in December in Guangdong Province. Seven genotypes of DENV 1–3 were detected in the high-risk areas, with DENV 1-I the main genotype and DENV 2-Cosmopolitan the secondary one. The Maximum Likelihood trees show that almost all the indigenous viruses separated into different clusters. DENV 1-I viruses were found to be clustered in Guangdong Province, but not in Fujian and Yunnan, from 2013 to 2015. The ancestors of the Guangdong viruses in the cluster in 2013 and 2014 were most closely related to strains from Thailand or Singapore, and the Guangdong virus in 2015 was most closely related to the Guangdong virus of 2014. Based on closest phylogenetic relationships, viruses from Myanmar possibly initiated further indigenous cases in Yunnan, those from Indonesia in Fujian, while viruses from Thailand, Malaysia, Singapore and Indonesia were predominant in Guangdong Province.

Conclusions

Dengue is still an imported disease in China, although some genotypes continued to circulate in successive years. Viral phylogenies based on the envelope gene suggested periodic introductions of dengue strains into China, primarily from Southeast Asia, with occasional sustained, multi-year transmission in some regions of China.

Dengue is the most prevalent and rapidly spreading mosquito-borne viral disease globally. Because of the multiple introductions, dengue outbreaks occurred in epidemic seasons in Southern China, supported by suitable weather conditions. Surveillance data from 2013 to 2016 in China showed that Guangdong, Yunnan and Fujian provinces were the high-risk areas, with dengue outbreaks occurring almost every year. However, knowledge has been lacking of the epidemiological characteristics and the evolution pattern of dengue virus in these high-risk areas. This study shows a variety of epidemiological characteristics and sources of imported cases among the high-risk areas in China, with likely origins primarily from countries in Southeast Asia. Seven genotypes of the DENV 1–3 variety co-circulated with DENV1-I, the main genotype, and DENV 2-Cosmopolitan, the secondary. Genetic relationships among viral strains suggest that the indigenous viruses in the high-risk areas arose from imported viruses and sometimes persisted between years into the next epidemic season, especially in Guangdong Province. Population movement has played a vital role in dengue epidemics in China. This information may be useful in dengue control, especially during epidemic seasons and in the development of an early warning system within the region, in collaboration with bordering countries.

Assessment of the global circulation and endemicity of dengue

Dengue is a significant public health issue, affecting hundreds of millions of people worldwide. As it is spreading from tropical and subtropical zones, some regions previously recognised as non-endemic are at risk of becoming endemic. However, the global circulation of dengue is not fully understood and quantitative measurements of endemicity levels are lacking, posing an obstacle in the precise control of dengue spread. In this study, a sequence-based pipeline was designed based on random sampling to study the transmission of dengue. The limited intercontinental transmission was identified, while regional circulation of dengue was quantified in terms of importation, local circulation and exportation. Additionally, hypo- and hyper-endemic regions were identified using a new metric, with the former characterised by low local circulation and increased importation, whereas the latter by high local circulation and reduced importation. In this study, the global circulation pattern of dengue was examined and a sequence-based endemicity measurement was proposed, which will be helpful for future surveillance and targeted control of dengue.

Travel-related infection in Guangzhou, China,2009-2019

BACKGROUND

We analyzed the epidemiological characteristics of travel-related infectious diseases in reported Guangzhou between 2009 and 2019 to provide a scientific basis for prevention and control strategies.

METHOD

The infectious diseases report information system of China was mined for case reports, combined with clinical diagnosis records, and analyzed.

RESULTS

Between 2009 and 2019, 1478 cases of imported infectious diseases were reported in Guangzhou. Dengue fever accounted for 46.14%of cases and malaria accounted for 45.47% of cases. The patients with imported travel-related infection cases were mainly male (75.88%), Chinese (75.57%), and aged 20-45 years (83.01%). Cases increased from May each year, peaked between August and September, and declined rapidly after October. The main source areas of import were Africa and other countries in Asia.

CONCLUSIONS

Dengue fever and malaria are the main travel-related infection in Guangzhou, and are generally brought in by male Chinese workers. Intervention and health education in this population should be strengthened to prevent and control travel-related infection.

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.

Effects of Overwintering on the Survival and Vector Competence of Aedes albopictus in the Urban Life Cycle of Dengue Virus in Guangzhou, China

The Pearl River Delta, where Aedes albopictus (Ae. albopictus) is the only vector for dengue transmission, has exhibited one of the highest dengue burdens in southern China in recent decades. However, whether dengue virus (DENV) can overwinter in Ae. albopictus in the Pearl River Delta has not been determined to date. In this study, 300 field-derived Ae. albopictus mosquitoes from Guangzhou that were infected with the predominant endemic DENV-1 strain were investigated under simulated urban balcony environment from October 16, 2016, to June 16, 2017. The vertical transmission of DENV in the infected overwintering Ae. albopictus was analyzed. The DENV infected overwintering mosquitoes were evaluated for viral load at nine-time points using reverse transcription-quantitative PCR. The vector competence of the infected overwintering Ae. albopictus was also investigated by using suckling mice. Adult mosquitoes and larvae were found during the observation period. The vertical transmission of DENV-1 was documented. The DENV-1-positive rates between overwintering males and females had no difference. The proportion of DENV-1-positive overwintering mosquitoes decreased over time and had no difference beyond three months after the experiment. Overwintering mosquitoes can spread DENV-1 to hosts. No engorged mosquitoes at an ambient temperature below 15 °C were observed. The ratio of engorged mosquitoes was positively correlated with the ambient temperature ranging from 15 to 30 °C. Our results demonstrated that DENV can overwinter in Ae. albopictus in the Pearl River Delta, Ae. albopictus is the competent vector for DENV, and maintain autochthonous dengue outbreaks in the Pearl River Delta through vertical transmission.

New genotype invasion of dengue virus serotype 1 drove massive outbreak in Guangzhou, China

Background

Dengue fever is a mosquito-borne infectious disease that has caused major health problems. Variations in dengue virus (DENV) genes are important features of epidemic outbreaks. However, the associations of DENV genes with epidemic potential have not been extensively examined. Here, we assessed new genotype invasion of DENV-1 isolated from Guangzhou in China to evaluate associations with epidemic outbreaks.

Methodology/principal findings

We used DENV-1 strains isolated from sera of dengue cases from 2002 to 2016 in Guangzhou for complete genome sequencing. A neighbor-joining phylogenetic tree was constructed to elucidate the genotype characteristics and determine if new genotype invasion was correlated with major outbreaks. In our study, a new genotype invasion event was observed during each significant outbreak period in 2002–2003, 2006–2007, and 2013–2014. Genotype II was the main epidemic genotype in 2003 and before. Invasion of genotype I in 2006 caused an unusual outbreak with 765 cases (relative risk [RR] = 16.24, 95% confidence interval [CI] 12.41–21.25). At the middle and late stages of the 2013 outbreak, genotype III was introduced to Guangzhou as a new genotype invasion responsible for 37,340 cases with RR 541.73 (95% CI 417.78–702.45), after which genotypes I and III began co-circulating. Base mutations occurred after new genotype invasion, and the gene sequence of NS3 protein had the lowest average similarity ratio (99.82%), followed by the gene sequence of E protein (99.86%), as compared to the 2013 strain.

Conclusions/significance

Genotype replacement and co-circulation of multiple DENV-1 genotypes were observed. New genotype invasion was highly correlated with local unusual outbreaks. In addition to DENV-1 genotype I in the unprecedented outbreak in 2014, new genotype invasion by DENV-1 genotype III occurred in Guangzhou.

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.

Dengue fever transmission between a construction site and its surrounding communities in China

BACKGROUND

Due to an increase in mosquito habitats and the lack facilities to carry out basic mosquito control, construction sites in China are more likely to experience secondary dengue fever infection after importation of an initial infection, which may then increase the number of infections in the neighboring communities and the chance of community transmission. The aim of this study was to investigate how to effectively reduce the transmission of dengue fever at construction sites and the neighboring communities.

METHODS

The Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model of human and SEI model of mosquitoes were developed to estimate the transmission of dengue virus between humans and mosquitoes within the construction site and within a neighboring community, as well between each of these. With the calibrated model, we further estimated the effectiveness of different intervention scenarios targeting at reducing the transmissibility at different locations (i.e. construction sites and community) with the total attack rate (TAR) and the duration of the outbreak (DO).

RESULTS

A total of 102 construction site-related and 131 community-related cases of dengue fever were reported in our area of study. Without intervention, the number of cases related to the construction site and the community rose to 156 (TAR: 31.25%) and 10,796 (TAR: 21.59%), respectively. When the transmission route from mosquitoes to humans in the community was cut off, the number of community cases decreased to a minimum of 33 compared with other simulated scenarios (TAR: 0.068%, DO: 60 days). If the transmission route from infectious mosquitoes in the community and that from the construction site to susceptible people on the site were cut off at the same time, the number of cases on the construction site dropped to a minimum of 74 (TAR: 14.88%, DO: 66 days).

CONCLUSIONS

To control the outbreak of dengue fever effectively on both the construction site and in the community, interventions needed to be made both within the community and from the community to the construction site. If interventions only took place within the construction site, the number of cases on the construction site would not be reduced. Also, interventions implemented only within the construction site or between the construction site and the community would not lead to a reduction in the number of cases in the community.

Effects of natural and socioeconomic factors on dengue transmission in two cities of China from 2006 to 2017

Dengue fever (DF) is a common and rapidly spreading vector-borne viral disease in tropical and subtropical regions. In recent years, in China, DF still poses an increasing threat to public health in many cities; but the incidence shows significant spatiotemporal differences. The purpose of this study was to identify the key factors affecting the spatial and temporal distribution of DF. We collected natural environmental and socio-economic data for two adjacent cities, Guangzhou (73 variables) and Foshan (71 variables), with the most DF cases in China. We performed random forest modelling to rank the factors according to their level of importance, and used negative binomial regression analysis to compare the risk factors between outbreak years and non-outbreak years. The natural environmental factors contributing to DF incidence for Guangzhou were temperature (relative risk (RR) = 18.80, 95% confidence interval (CI) = 3.11-113.67), humidity (RR = 1.85, 95% CI = 1.17-2.90) and green area (RR = 12.11, 95% CI = 6.14-55.50), and for Foshan was forest coverage (RR = 5.83, 95% CI = 2.72-12.45). Socio-economic impact were shown in Guangzhou with foreign visitor (RR = 1.18, 95% CI = 1.05-1.34) and oversea air passenger transport (RR = 7.34, 95% CI = 2.26-23.86); in Foshan, with oversea tourism (RR = 1.65, 95% CI = 1.34-2.04); and in Guangzhou-Foshan, with the development of intercity metro (RR = 1.26, 95% CI = 1.10-1.44). The difference between the two cities was the greater impact of the foreign visitor, green spaces and climate factor on DF in Guangzhou; the impact of the construction of intercity metro; and the more significant impact of oversea tourism on DF in Foshan. Our results suggest meaningful clues to public health authorities implementing joint interventions on DF prevention and early warning, to increase health education on DF prevention for international visitors and oversea travelers, and cross-city metro passengers; using rapid body temperature detection in public places such as airports, metros and parks can help detect cases early.

Modeling the effect of temperature on dengue virus transmission with periodic delay differential equations

Dengue fever is a re-emergent mosquito-borne disease, which prevails in tropical and subtropical regions, mainly in urban and peri-urban areas. Its incidence has increased fourfold since 1970, and dengue fever has become the most prevalent mosquito-borne disease in humans now. In order to study the effect of temperature on the dengue virus transmission, we formulate a dengue virus transmission model with maturation delay for mosquito production and seasonality. The basic reproduction number $\mathbb{R}_0$ of the model is computed, and results suggest that the dengue fever will die out if $\mathbb{R}_0$ < 1, and there exists at least one positive periodic solution and the disease will persist if $\mathbb{R}_0$ > 1. Theoretical results are applied to the outbreak of dengue fever in Guangdong province, China. Simulations reveal that the temperature change causes the periodic oscillations of dengue fever cases, which is good accordance with the reported cases of dengue fever in Guangdong province. Our study contributes to a better understanding of dengue virus transmission dynamics and proves beneficial in preventing and controlling of dengue fever.

Increase in cases of dengue in China, 2004-2016: A retrospective observational study

BACKGROUND

Dengue fever (DF) is a vector-bore infectious disease that can infect humans, and has been recognized as a global public health threat, with significant morbidity and mortality rates.

METHOD

To describe the epidemiological profile of DF in China during 2004-2016, the morbidity data of DF by age-group, season (different months) and geographic location (different provinces) were obtained from the public health science data center of China for subsequent epidemiological analysis.

RESULTS

The results showed that the incidence of DF shows striking annual variations, and two large outbreaks occurred in 2006-2007 and during 2012-2015. The results of the average morbidity rates (cases/100,000 population) for human DF indicated that among all dengue fever cases, Guangdong in southern area of China had the highest rates (3.8160 cases/100,000 population), followed by Yunnan (0.6614 cases/100,000 population), Fujian (0.3463 cases/100,000 population) and Guangxi (0.1474 cases/100,000 population). Epidemic peaks occurred in late June and early November, and the incidence rate among middle-aged people (30-45 years old) was relatively high, followed by rates among 15-29 and 45-59 age groups.

CONCLUSION

In this study, we demonstrated the epidemiological profile of DF circulating in China and revealed the geographic distribution, dynamic transmission, seasonal asymmetries and age distribution, which will provide guidelines on the prevention and control of DF in China. The present investigation is useful in the risk assessment of DF transmission, to predict DF outbreaks and the prevention and control strategies should be used along with surveillance to reduce the spread of DF in China.

Development of a mechanistic dengue simulation model for Guangzhou

Dengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This study aimed to evaluate different dengue management strategies in a region where this disease is emerging. This work was done by establishing a dengue simulation model for Guangzhou to enable the testing of control strategies aimed at vector control and vaccination. For that purpose, the computer-based dengue simulation model (DENSiM) together with the Container-Inhabiting Mosquito Simulation Model (CIMSiM) has been used to create a working dengue simulation model for the city of Guangzhou. In order to achieve the best model fit against historical surveillance data, virus introduction scenarios were run and then matched against the actual dengue surveillance data. The simulation model was able to predict retrospective outbreaks with a sensitivity of 0.18 and a specificity of 0.98. This new parameterisation can now be used to evaluate the potential impact of different control strategies on dengue transmission in Guangzhou. The knowledge generated from this research would provide useful information for authorities regarding the historic patterns of dengue outbreaks, as well as the effectiveness of different disease management strategies.

Bionomics and insecticide resistance of Aedes albopictus in Shandong, a high latitude and high-risk dengue transmission area in China

BACKGROUND

Dengue fever outbreaks tend to spread northward in China, and Jining is the northernmost region where local dengue fever cases have been detected. Therefore, it is important to investigate the density of Aedes albopictus and its resistance to deltamethrin.

METHODS

The Breteau index (BI) and container index (CI) were calculated to assess the larval density of Ae. albopictus and human-baited double net trap (HDN) surveillance was performed in six subordinate counties (Rencheng, Yanzhou, Sishui, Liangshan, Zoucheng and Jiaxiang) of Jining City in 2017 and 2018. The resistance of Ae. albopictus adults to deltamethrin was evaluated using the World Health Organization (WHO) standard resistance bioassay. The mutations at Vgsc codons 1532 and 1534 were also analysed to determine the association between kdr mutations and phenotypic resistance in adult mosquitoes.

RESULTS

The average BI, CI and biting rate at Jining were 45.30, 16.02 and 1.97 (female /man/hour) in 2017 and 15.95, 7.86 and 0.59 f/m/h in 2018, respectively. In August 26, 2017, when the first dengue fever case was diagnosed, the BI at Qianli village in Jiaxiang County was 107.27. The application of prevention and control measures by the government sharply decreased the BI to a value of 4.95 in September 3, 2017. The mortality of field-collected Ae. albopictus females from Jiaxiang was 41.98%. I1532T, F1534L and F1534S mutations were found in domain III of the Vgsc gene. This study provides the first demonstration that both I1532T and F1534S mutations are positively correlated with the deltamethrin-resistant phenotype.

CONCLUSIONS

Mosquito density surveillance, resistance monitoring and risk assessment should be strengthened in areas at risk for dengue to ensure the sustainable control of Ae. albopictus and thus the prevention and control of dengue transmission.

The driver of dengue fever incidence in two high-risk areas of China: A comparative study

In China, the knowledge of the underlying causes of heterogeneous distribution pattern of dengue fever in different high-risk areas is limited. A comparative study will help us understand the influencing factors of dengue in different high-risk areas. In the study, we compared the effects of climate, mosquito density and imported cases on dengue fever in two high-risk areas using Generalized Additive Model (GAM), random forests and Structural Equation Model (SEM). GAM analysis identified a similar positive correlation between imported cases, density of Aedes larvae, climate variables and dengue fever occurrence in the studied high-risk areas of both Guangdong and Yunnan provinces. Random forests showed that the most important factors affecting dengue fever occurrence were the number of imported cases, BI and the monthly average minimum temperature in Guangdong province; whereas the imported cases, the monthly average temperature and monthly relative humidity in Yunnan province. We found the rainfall had the indirect effect on dengue fever occurrence in both areas mediated by mosquito density; while the direct effect in high-risk areas of Guangdong was dominated by temperature and no obvious effect in Yunnan province by SEM. In total, climate factors and mosquito density are the key drivers on dengue fever incidence in different high-risk areas of China. These findings could provide scientific evidence for early warning and the scientific control of dengue fever in high-risk areas.

Neglected Urban Villages in Current Vector Surveillance System: Evidences in Guangzhou, China

Numerous urban villages (UVs) with substandard living conditions that cause people to live there with vulnerability to health impacts, including vector-borne diseases such as dengue fever (DF), are major environmental and public health concerns in highly urbanized regions, especially in developing countries. It is necessary to explore the relationship between UVs and vector for effectively dealing with these problems. In this study, land-use types, including UVs, normal construction land (NCL), unused land (UL), vegetation, and water, were retrieved from the high-resolution remotely sensed imagery in the central area of Guangzhou in 2017. The vector density from May to October in 2017, including Aedes. albopictus (Ae. albopictus)’s Breteau index (BI), standard space index (SSI), and adult density index (ADI) were obtained from the vector surveillance system implemented by the Guangzhou Center for Disease Control and Prevention (CDC). Furthermore, the spatial and temporal patterns of vector monitoring sites and vector density were analyzed on a fine scale, and then the Geodetector tool was further employed to explore the relationships between vector density and land-use types. The monitoring sites were mainly located in NCL (55.70%–56.44%) and UV (13.14%–13.92%). Among the total monitoring sites of BI (79), SSI (312), and ADI (326), the random sites accounted for about 88.61%, 97.12%, and 98.47%, respectively. The density of Ae. albopictus was temporally related to rainfall and temperature and was obviously differentiated among different land-use types. Meanwhile, the grids with higher density, which were mostly concentrated in the Pearl River fork zone that collects a large number of UVs, showed that the density of Ae. albopictus was spatially associated with the UVs. Next, the results of the Geodetector illustrated that UVs posed great impact on the density of Ae. albopictus across the central region of Guangzhou. We suggest that the number of monitoring sites in the UVs should be appropriately increased to strengthen the current vector surveillance system in Guangzhou. This study will provide targeted guidance for local authorities, making more effective control and prevention measures on the DF epidemics.

Prediction model for dengue fever based on interactive effects between multiple meteorological factors in Guangdong, China (2008-2016)

Introduction

In order to improve the prediction accuracy of dengue fever incidence, we constructed a prediction model with interactive effects between meteorological factors, based on weekly dengue fever cases in Guangdong, China from 2008 to 2016.

Methods

Dengue fever data were derived from statistical data from the China National Notifiable Infectious Disease Reporting Information System. Daily meteorological data were obtained from the China Integrated Meteorological Information Sharing System. The minimum temperature for transmission was identified using data fitting and the Ross-Macdonald model. Correlations and interactive effects were examined using Spearman’s rank correlation and multivariate analysis of variance. A probit regression model to describe the incidence of dengue fever from 2008 to 2016 and forecast the 2017 incidence was constructed, based on key meteorological factors, interactive effects, mosquito-vector factors, and other important factors.

Results

We found the minimum temperature suitable for dengue transmission was ≥18°C, and as 97.91% of cases occurred when the minimum temperature was above 18 °C, the data were used for model training and construction. Epidemics of dengue are related to mean temperature, maximum/minimum and mean atmospheric pressure, and mean relative humidity. Moreover, interactions occur between mean temperature, minimum atmospheric pressure, and mean relative humidity. Our weekly probit regression prediction model is 0.72. Prediction of dengue cases for the first 41 weeks of 2017 exhibited goodness of fit of 0.60.

Conclusion

Our model was accurate and timely, with consideration of interactive effects between meteorological factors.

The increasing menace of dengue in Guangzhou, 2001-2016: the most important epicenter in mainland China

Background

Dengue is the most prevalent mosquito-borne disease in the world, with China affected seriously in recent years. 65.8% of dengue cases identified in mainland China since 2005 were reported from the city of Guangzhou.

Methods

In this study, we described the incidence rate and distribution of dengue cases using data collected form National Notifiable Infectious Disease Reporting Information System data in Guangzhou for 2001 to 2016. All dengue cases were investigated using standardized questionnaire.

Results

A total of 42,469 dengue cases were reported, with an average annual incidence rate of 20.99 per 100,000 resident population. Over this time period, the incidence rate of indigenous cases increased. Dengue affected areas also expanded sharply geographically from 58.1% of communities affected during 2001–2005 to 96.4% of communities affected in 2011–2016. Overall 95.30% of the overseas imported cases were reported during March and December, while 99.79% of indigenous cases were reported during July and November. All four dengue virus serotypes were identified both in imported cases and indigenous cases. The Aedes albopictus mosquito was the only vector for dengue transmission in the area.

Conclusions

Guangzhou has become the dengue epicenter in mainland China. Control strategies for dengue should be adjusted to the epidemiological characteristics above and intensive study need to be conducted to explore the factors that driving the rapid increase of dengue.

The expanding pattern of Aedes aegypti in southern Yunnan, China: insights from microsatellite and mitochondrial DNA markers

BACKGROUND

Aedes aegypti, the vector of dengue fever, was first reported in Yunnan in 2002. Now, this species is found in nine counties in border areas of south-west Yunnan. Related dengue fever outbreaks have been reported since 2013. The population genetics of Ae. aegypti in these areas were studied to explain the expansion history of this species.

METHODS

Fifteen natural populations of Ae. aegypti were sampled from six counties of Yunnan, and two laboratory populations from Guangdong and Hainan were also included in this study. A total of 12 microsatellite loci and three mitochondrial genes were analysed.

RESULTS

The results indicate that Ae. aegypti populations from Yunnan show similar genetic diversity. The 17 populations could be divided into three groups: the first group included populations from Longchuan, Ruili and Gengma, which are located in the southwest of Yunnan; the second group included populations from Jinghong and Menghai, in the south of Yunnan; and the third group included populations from Mengla and the two laboratory populations from Guangdong and Hainan. Both microsatellite and mtDNA data revealed that the genetic relationships of the populations corresponded to their geographic relationships.

CONCLUSIONS

The results suggested that the expansion of Ae. aegypti from northern Myanmar and Laos to southern and southwestern Yunnan was a natural process. The effect of human activity on expansion was not obvious. Surveillance efforts should still be focused on border areas where Ae. aegypti does not occur, and a powerful control strategy should be applied to prevent outbreaks of dengue fever.

Molecular epidemiological characteristics of dengue virus carried by 34 patients in Guangzhou in 2018

Dengue fever is a major worldwide public health problem that, as estimated by the WHO, causes epidemics in over 100 countries, resulting in hundreds of millions of dengue virus (DENV) infections every year. In China, dengue fever mainly occurs in coastal areas. Recurring dengue outbreaks were reported by Guangdong Province almost every year since the first epidemic in 1978. DENV infections persisted in Guangzhou in consecutive years since 2000, with the dengue epidemic reaching a historical peak in 2014. Because Guangzhou is one of the largest cities for opening up in China, understanding the epidemiological characteristics of dengue fever in the city can hopefully provide a significant basis for developing effective dengue prevention strategies. In this study, a total of 34 DENV strains, including 29 DENV-1 strains and 5 DENV-2 strains, were isolated from a blood samples drawn from patients who were diagnosed with dengue fever by hospitals in Guangzhou during 2018. To explore the epidemiological characteristics of dengue fever, the envelope (E) gene obtained from the isolates was amplified for phylogenetic analysis. The results from the phylogenetic analysis showed that DENV in Guangzhou was mainly imported from Southeast Asian countries. Additionally, propagation paths based on phylogeographical analysis suggested potential local dengue transmission in Guangzhou.

The evolutionary dynamics of DENV 4 genotype I over a 60-year period

Dengue virus serotype 4 (DENV 4) has had a relatively low prevalence worldwide for decades; however, likely due to data paucity, no study has investigated the epidemiology and evolutionary dynamics of DENV 4 genotype I (DENV 4-I). This study aims to understand the diversity, epidemiology and dynamics of DENV 4-I. We collected 404 full length DENV4-1 envelope (E) gene sequences from 14 countries using two sources: Yunnan Province in China (15 strains during 2013–2016) and GenBank (489 strains up to 2018-01-11). Conducting phylogenetic and phylogeographical analyses, we estimated the virus spread, population dynamics, and selection pressures using different statistical analysis methods (substitution saturation, likelihood mapping, Bayesian coalescent inference, and maximum likelihood estimation). Our results show that during the last 60 years (1956–2016), DENV 4-I was present in mainland and maritime Southeast Asia, the Indian subcontinent, the southern provinces of China, parts of Brazil and Australia. The recent spread of DENV 4-I likely originated in the Philippines and later spread to Thailand. From Thailand, it spread to adjacent countries and eventually the Indian subcontinent. Apparently diverging around years 1957, 1963, 1976 and 1990, the different Clades (Clade I-V) were defined. The mean overall evolution rate of DENV 4-I was 9.74 (95% HPD: 8.68–10.82) × 10⁻⁴ nucleotide substitutions/site/year. The most recent common ancestor for DENV 4-I traces back to 1956. While the demographic history of DENV 4-I fluctuated, peaks appeared around 1982 and 2006. While purifying selection dominated the majority of E-gene evolution of DENV 4-I, positive selection characterized Clade III (Vietnam). DENV 4-I evolved in situ in Southeast Asia and the Indian subcontinent. Thailand and Indian acted as the main and secondary virus distribution hubs globally and regionally. Our phylogenetic analysis highlights the need for strengthened regional cooperation on surveillance and sharing of sample sequences to improve global dengue control and cross-border transmission prevention efforts.

Dengue virus (DENV) can be classified into four serotypes, DENV 1, 2, 3 and 4. Although DENV 4 is the first dengue serotype to diverge in phylogenetic analyses of the genus Flavivirus, this serotype occurs at a low prevalence worldwide and spreads the least rapidly. Similar to other serotypes, DENV 4 can also cause severe dengue (SD) disease manifestations, such as dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS). To date, no study has investigated the epidemiology and dynamics of DENV 4 genotype I comprehensively. In this study, we seek to address this gap. Our study shows that the distribution of DENV 4-I is mainly restricted to Southeast Asia and the Indian subcontinent. The most recent spread of DENV 4-I likely originated from Southeast Asia–initially circulating in the Philippines, then Thailand and later on the Indian subcontinent. Viruses evolved in situ in Southeast Asia and the Indian subcontinent, respectively. Although DENV 4-I occasionally spread elsewhere, this genotype did not become widely established. The overall evolution rate of DENV 4-I was comparable with that of DENV 2–4. The nucleotide sequences indicates that the demographic history of DENV 4-I fluctuated with peaks apparent during parts of the 1980s and 2000s. Although a weak positive selection existed in Clade III -predominately in Vietnam, purifying selection dominated the E-gene evolution of DENV 4-I.

Spatiotemporal characteristics and primary influencing factors of typical dengue fever epidemics in China

BACKGROUND

Dengue fever (DF) is a common mosquito-borne viral infectious disease in the world, and increasingly severe DF epidemics in China have seriously affected people's health in recent years. Thus, investigating spatiotemporal patterns and potential influencing factors of DF epidemics in typical regions is critical to consolidate effective prevention and control measures for these regional epidemics.

METHODS

A generalized additive model (GAM) was used to identify potential contributing factors that influence spatiotemporal epidemic patterns in typical DF epidemic regions of China (e.g., the Pearl River Delta [PRD] and the Border of Yunnan and Myanmar [BYM]). In terms of influencing factors, environmental factors including the normalized difference vegetation index (NDVI), temperature, precipitation, and humidity, in conjunction with socioeconomic factors, such as population density (Pop), road density, land-use, and gross domestic product, were employed.

RESULTS

DF epidemics in the PRD and BYM exhibit prominent spatial variations at 4 km and 3 km grid scales, characterized by significant spatial clustering over the Guangzhou-Foshan, Dehong, and Xishuangbanna areas. The GAM that integrated the Pop-urban land ratio (ULR)-NDVI-humidity-temperature factors for the PRD and the ULR-Road density-NDVI-temperature-water land ratio-precipitation factors for the BYM performed well in terms of overall accuracy, with Akaike Information Criterion values of 61 859.89 and 826.65, explaining a total variance of 83.4 and 97.3%, respectively. As indicated, socioeconomic factors have a stronger influence on DF epidemics than environmental factors in the study area. Among these factors, Pop (PRD) and ULR (BYM) were the socioeconomic factors explaining the largest variance in regional epidemics, whereas NDVI was the environmental factor explaining the largest variance in both regions. In addition, the common factors (ULR, NDVI, and temperature) in these two regions exhibited different effects on regional epidemics.

CONCLUSIONS

The spatiotemporal patterns of DF in the PRD and BYM are influenced by environmental and socioeconomic factors, the socioeconomic factors may play a significant role in DF epidemics in cases where environmental factors are suitable and differ only slightly throughout an area. Thus, prevention and control resources should be fully allocated by referring to the spatial patterns of primary influencing factors to better consolidate the prevention and control measures for DF epidemics.

Epidemiological and clinical characteristics of Dengue virus outbreaks in two regions of China, 2014 - 2015

Dengue virus (DENV), a single-stranded RNA virus and Flaviviridae family member, is transmitted by Aedes aegypti and Aedes albopictus mosquitoes. DENV causes dengue fever, which may progress to severe dengue. Hospital-based surveillance was performed in two Chinese regions, Guangzhou and Xishuangbanna, during the dengue epidemics in 2014 and 2015, respectively. Acute-phase serum was obtained from 133 patients with suspected dengue infections during the peak season for dengue cases. Viremia levels, virus sero-positivity, serotype distribution, infection type, clinical manifestations and virus phylogenetics were investigated. Of the 112 DENV-confirmed cases, 92(82.14%) were IgM antibody-positive for DENV, and 69(51.88%) were positive for DENV RNA. From these cases, 47(41.96%) were classified as primary infections, 39(34.82%) as secondary infections and 26 (23.21%) as undetermined infections. The viremia levels were negatively correlated with IgM presence, but had no relationship with the infection type. DENV-1 genotype V dominated in Guangzhou, whereas the DENV-2 Cosmopolitan genotype dominated in Xishuangbanna, where fewer DENV-1 genotype I cases occurred. DENV-2 is associated with severe dengue illness with more serious clinical issues. The strains isolated during 2014–2015 are closely related to the isolates obtained from other Chinese regions and to those isolated recently in Southeast Asian countries. Our results indicate that DENV is no longer an imported virus and is now endemic in China. An extensive seroepidemiological study of DENV and the implementation of vector control measures against it are now warranted in China.

Virulence difference of five type I dengue viruses and the intrinsic molecular mechanism

Dengue virus (DENV) is the most important vector-borne virus globally. The safe and effective vaccines are still under development and there are no antiviral drugs for DENV induced diseases. In this study, we obtained five DENV1 isolates (DENV1 A to E) from the outbreak of dengue fever in 2014 of Guangzhou, China, and analyzed their replication efficiency and virulence in vitro and in vivo. The results suggested that among the five DENV1 strains, DENV1 B has the highest replication efficiency in both human and mosquito cells in vitro, also causes the highest mortality to suckling mice. Further study suggested that nonstructural proteins from DENV1B have higher capacity to suppress host interferon signaling. In addition, the NS2B3 protease from DENV1B has higher enzymatic activity compared with that from DENV1 E. Finally, we identified that the 64^th amino acid of NS2A and the 55^th amino acid of NS2B were two virulence determining sites for DENV1. This study provided new evidences of the molecular mechanisms of DENV virulence.

Dengue is the most important vector-borne viral infection that endangers an estimated 2.5 billion people globally. The recently licensed dengue vaccine has major weaknesses and there are no antiviral drugs for the treatment of dengue related diseases. Identifying the virulence determinants is important for understanding the molecule bases of viral life cycle, also contributing to vaccine design and development. In this study, we analyzed the virulence differences among five DENV1 strains that obtained from the 2014 DENV outbreak in Guangzhou, China, and identified two novel virulence determining sites for DENV1. This study provides new ideas for investigation of DENV protein function, pathogenic mechanism and novel attenuated vaccine.

Effects of human mobility, temperature and mosquito control on the spatiotemporal transmission of dengue

Dengue transmission exhibits evident geographic variations and seasonal differences. Such heterogeneity is caused by various impact factors, in which temperature and host/vector behaviors could drive its spatiotemporal transmission, but mosquito control could stop its progression. These factors together contribute to the observed distributions of dengue incidence from surveillance systems. To effectively and efficiently monitor and response to dengue outbreak, it would be necessary to systematically model these factors and their impacts on dengue transmission. This paper introduces a new modeling framework with consideration of multi-scale factors and surveillance data to clarify the hidden dynamics accounting for dengue spatiotemporal transmission. The model is based on compartmental system which takes into account the biting-based interactions among humans, viruses and mosquitoes, as well as the essential impacts of human mobility, temperature and mosquito control. This framework was validated with real epidemic data by applying retrospectively to the 2014 dengue epidemic in the Pearl River Delta (PRD) in southern China. The results indicated that suitable condition of temperature could be responsible for the explosive dengue outbreak in the PRD, and human mobility could be the causal factor leading to its spatial transmission across different cities. It was further found that mosquito intervention has significantly reduced dengue incidence, where a total of 52,770 (95% confidence interval [CI]: 29,231-76,308) dengue cases were prevented in the PRD in 2014. The findings can offer new insights for improving the predictability and risk assessment of dengue epidemics. The model also can be readily extended to investigate the transmission dynamics of other mosquito-borne diseases.

Dengue control in the context of climate change: Views from health professionals in different geographic regions of China

BACKGROUND

Dengue is a significant climate-sensitive disease. Public health professionals play an important role in prevention and control of the disease. This study aimed to explore dengue control and prevention in the context of climate change in China.

METHODS

A cross-sectional survey was conducted among 630 public health professionals in 2015. Descriptive analysis and logistic regression were performed.

RESULTS

More than 80% of participants from southwest and central China believed climate change would affect dengue. However, participants from northeast China were less likely to believe so (65%). Sixty-nine percent of participants in Yunnan perceived that dengue had emerged/re-emerged in recent years, compared with 40.6% in Henan and 23.8% in Liaoning. Less than 60% of participants thought current prevention and control programs had been effective. Participants believed mosquitoes in high abundance, imported cases and climate change were main risk factors for dengue in China.

CONCLUSION

There were varying views of dengue in China. Professionals in areas susceptible to dengue were more likely to be concerned about climate change and dengue. Current prevention and control strategies need to be improved. Providing more information for staff in lower levels of Centers for Disease Control and Prevention may help in containing a possible increase of dengue.

Seasonal and interannual risks of dengue introduction from South-East Asia into China, 2005-2015

Due to worldwide increased human mobility, air-transportation data and mathematical models have been widely used to measure risks of global dispersal of pathogens. However, the seasonal and interannual risks of pathogens importation and onward transmission from endemic countries have rarely been quantified and validated. We constructed a modelling framework, integrating air travel, epidemiological, demographical, entomological and meteorological data, to measure the seasonal probability of dengue introduction from endemic countries. This framework has been applied retrospectively to elucidate spatiotemporal patterns and increasing seasonal risk of dengue importation from South-East Asia into China via air travel in multiple populations, Chinese travelers and local residents, over a decade of 2005-15. We found that the volume of airline travelers from South-East Asia into China has quadrupled from 2005 to 2015 with Chinese travelers increased rapidly. Following the growth of air traffic, the probability of dengue importation from South-East Asia into China has increased dramatically from 2005 to 2015. This study also revealed seasonal asymmetries of transmission routes: Sri Lanka and Maldives have emerged as origins; neglected cities at central and coastal China have been increasingly vulnerable to dengue importation and onward transmission. Compared to the monthly occurrence of dengue reported in China, our model performed robustly for importation and onward transmission risk estimates. The approach and evidence could facilitate to understand and mitigate the changing seasonal threat of arbovirus from endemic regions.

Risk factors spatial-temporal detection for dengue fever in Guangzhou

Dengue fever (DF) has been a growing public-health concern in China since its emergence in Guangdong Province in 1978. Of all the regions that have experienced dengue outbreaks in mainland China, the city of Guangzhou is the most affected. This study aims to investigate the potential risk factors for dengue virus (DENV) transmission in Guangzhou, China, from 2006 to 2014. The impact of risk factors on DENV transmission was qualified by the q-values calculated using a novel spatial-temporal method, the GeoDetector model. Both climatic and socioeconomic factors were considered. The impacts on DF incidence of each single factor and the interaction of two factors were analysed. The results show that the number of days with rainfall of the month before last has the highest determinant power, with a q-value of 0.898 (P < 0.01); the q-values of the other factors related to temperature and precipitation were around 0.38–0.50. Integrating a Pearson correlation analysis, nonlinear associations were found between the DF incidence in Guangzhou and the climatic factors considered. The coupled impact of the different variables considered was enhanced compared with their individual effects. In addition, an increased number of tourists in the city were associated with a high incidence of DF. This study demonstrates that the number of rain days in a month has great influence on the DF incidence of the month after next; the temperature and precipitation have nonlinear impacts on the DF incidence in Guangzhou; both the domestic and overseas tourists coming to the city increase the risk of DENV transmission. These findings are useful in the risk assessment of DENV transmission, to predict DF outbreaks and to implement preventive DF reduction strategies.

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

OBJECTIVE

To identify the high risk spatiotemporal clusters of dengue cases and explore the associated risk factors.

METHODS

Monthly indigenous dengue cases in 2005-2017 were aggregated at county level. Spatiotemporal cluster analysis was used to explore dengue distribution features using SaTScan9.4.4 and Arcgis10.3.0. In addition, the influential factors and potential high risk areas of dengue outbreaks were analyzed using ecological niche models in Maxent 3.3.1 software.

RESULTS

We found a heterogeneous spatial and temporal distribution pattern of dengue cases. The identified high risk region in the primary cluster covered 13 counties in Guangdong Province and in the secondary clusters included 14 counties in Yunnan Province. Additionally, there was a nonlinear association between meteorological and environmental factors and dengue outbreaks, with 8.5%-57.1%, 6.7%-38.3% and 3.2%-40.4% contribution from annual average minimum temperature, land cover and annual average precipitation, respectively.

CONCLUSIONS

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.

Full-length genome and molecular characterization of dengue virus serotype 2 isolated from an imported patient from Myanmar

BACKGROUND

Dengue is the most common mosquito-borne infection worldwide and a serious threat to global public health. Sporadic dengue virus serotype 2 (DENV-2) imported cases from Myanmar have been documented almost every year in Yunnan Province of China since 2005. However, the complete genome sequences of DENV-2 isolates imported from Myanmar are not available.

METHODS

The full-length genome of the DENV-2 strain (YNPE2), isolated from an imported case from Myanmar in 2013, was identified by the next-generation sequencing. The extreme ends of the viral genome were validated by 5'/3' RACE and Sanger sequencing. Furthermore, phylogenetic, recombination and selection pressure analyses were conducted for the molecular characterization of YNPE2 strain.

RESULTS

Whole-genome sequencing revealed that the full-length sequence of YNPE2 strain was 10,724 bases, with an open reading frame encoding for 3391 amino acids. The YNPE2 strain had 99.0% nucleotide identity and 99.8% amino acid identity with two closely related strains, ThD2_0078_01 strain (DQ181797) and DENV-2/TH/BID-V2157/200 strain (FJ639832). The phylogenetic analysis suggested that the YNPE2 strain belonged to Asian I genotype and was likely derived from Thailand strain (DQ181797). Moreover, selection pressure analysis revealed two amino acid sites of the NS4B and NS5 proteins, with important evidence of positive selection.

CONCLUSION

This study revealed the first complete genome sequence and molecular characterization of a DENV-2 strain (YNPE2) isolated from an imported case from Myanmar, thus providing a valuable reference genome source for future surveillance, epidemiology and vaccine development of DENV-2 virus in Yunnan, China.

Complete Genome Sequence Analysis of an Imported Dengue Virus Serotype 1 Strain from Myanmar

It has been determined that recent dengue virus epidemics in Yunnan, China, originated from Southeast Asian strains. Here, we report the first complete genome sequence and molecular characterization of the imported dengue virus serotype 1 strain YNPE1.

It has been determined that recent dengue virus epidemics in Yunnan, China, originated from Southeast Asian strains. Here, we report the first complete genome sequence and molecular characterization of the imported dengue virus serotype 1 strain YNPE1. Phylogenetic analysis revealed that strain YNPE1 belonged to genotype I.

The epidemiological characteristics and molecular phylogeny of the dengue virus in Guangdong, China, 2015

In 2015, an unexpected multiple outbreak of dengue occurred in Guangdong, China. In total, 1,699 cases were reported, of which 1,627 cases were verified to have DENV infections by nucleic acid or NS1 protein, including 44 DENV-1, 1126 DENV-2, 18 DENV-3 and 6 DENV-4, and the other cases were confirmed by NS1 ELISA. Phylogenetic analyses of DENV-1 isolates identified two genotypes (I and V). The predominant DENV-2 outbreak isolates were the Cosmopolitan genotypes, which likely originated from Malaysia. The DENV-3 isolates were assigned into genotype I and genotype III. All 6 DENV-4 isolates from imported cases were likely originally from Cambodia, Thailand and the Philippines. The entomological surveillance showed a moderate risk for the BI index in Chaozhou and Foshan and a low risk in Guangzhou. The imported cases were mostly detected in Guangzhou and Foshan. Surprisingly, the most serious outbreak occurred in Chaozhou, but not in Guangzhou or Foshan. A combined analyses demonstrated the multiple geographical origins of this outbreak, and highlight the detection of suspected cases after the alerting of imported cases, early implementation of control policies and reinforce the vector surveillance strategies were the key points in the chain of prevention and control of dengue epidemics.

Non-linear effects of mean temperature and relative humidity on dengue incidence in Guangzhou, China

BACKGROUND

Dengue fever is an important infectious disease in Guangzhou, China; previous studies on the effects of weather factors on the incidence of dengue fever did not consider the linearity of the associations.

METHODS

This study evaluated the effects of daily mean temperature, relative humidity and rainfall on the incidence of dengue fever. A generalized additive model with splines smoothing function was performed to examine the effects of daily mean, minimum and maximum temperatures, relative humidity and rainfall on incidence of dengue fever during 2006-2014.

RESULTS

Our analysis detected a non-linear effect of mean, minimum and maximum temperatures and relative humidity on dengue fever with the thresholds at 28°C, 23°C and 32°C for daily mean, minimum and maximum temperatures, 76% for relative humidity, respectively. Below the thresholds, there was a significant positive effect, the excess risk in dengue fever for each 1°C in the mean temperature at lag7-14days was 10.21%, (95% CI: 6.62% to 13.92%), 7.10% (95% CI: 4.99%, 9.26%) for 1°C increase in daily minimum temperature in lag 11days, and 2.27% (95% CI: 0.84%, 3.72%) for 1°C increase in daily maximum temperature in lag 10days; and each 1% increase in relative humidity of lag7-14days was associated with 1.95% (95% CI: 1.21% to 2.69%) in risk of dengue fever.

CONCLUSIONS

Future prevention and control measures and epidemiology studies on dengue fever should consider these weather factors based on their exposure-response relationship.

China's capacity of hospitals to deal with infectious diseases in the context of climate change

OBJECTIVES

Infectious diseases are a major cause of morbidity and mortality in China. The capacity of hospitals to deal with the challenge from emerging and re-emerging infectious diseases due to climate change is of great importance to population health. This study aimed to explore the capacity of hospitals in China to deal with such challenges.

METHODS

A cross-sectional questionnaire survey was utilized to gauge information regarding capacity of hospitals to deal with infectious diseases in the context of climate change among 611 clinical professionals whose roles pertained to infectious disease diagnosis, treatment and management in Anhui Province of China. Descriptive analysis and logistic regression analysis were performed on the data.

RESULTS

More than 90% of participants believed climate change would have an adverse influence on population health and infectious disease control in China. Most indicated that their hospitals were well prepared for emerging infectious diseases at present, and they considered that logistical support in hospitals (e.g. administrative and maintenance services) should be strengthened for future capacity building. The majority of participants suggested that effective prevention and control measures, more interdisciplinary collaborations, more funding in rural areas for health care, and improved access to facilities enabling online reporting of infectious diseases, were extremely important strategies in building capacity to curb the population health impact of emerging and re-emerging infectious diseases due to climate change in China.

CONCLUSIONS

Clinical professionals recognized that climate change will likely increase the transmission of infectious diseases. Although rural health care and hospitals' logistical support need to be improved, most professionals believed their hospitals to be capable of dealing with emerging diseases. They thought that interdisciplinary and cross-regional collaborations, together with necessary resource support (e.g. improved facilities for rural health care) would be important control strategies.

Weather variables and the El Niño Southern Oscillation may drive the epidemics of dengue in Guangdong Province, China

OBJECTIVE

To investigate the periodicity of dengue and the relationship between weather variables, El Niño Southern Oscillation (ENSO) and dengue incidence in Guangdong Province, China.

METHODS

Guangdong monthly dengue incidence and weather data and El Niño index information for 1988 to 2015 were collected. Wavelet analysis was used to investigate the periodicity of dengue, and the coherence and time-lag phases between dengue and weather variables and ENSO. The Generalized Additive Model (GAM) approach was further employed to explore the dose-response relationship of those variables on dengue. Finally, random forest analysis was applied to measure the relative importance of the climate predictors.

RESULTS

Dengue in Guangdong has a dominant annual periodicity over the period 1988-2015. Mean minimum temperature, total precipitation, and mean relative humidity are positively related to dengue incidence for 2, 3, and 4months lag, respectively. ENSO in the previous 12months may have driven the dengue epidemics in 1995, 2002, 2006 and 2010 in Guangdong. GAM analysis indicates an approximate linear association for the temperature-dengue relationship, approximate logarithm curve for the humidity-dengue relationship, and an inverted U-shape association for the precipitation-dengue (the threshold of precipitation is 348mm per month) and ENSO-dengue relationships (the threshold of ENSO index is 0.6°C). The monthly mean minimum temperature in the previous two months was identified as the most important climate variable associated with dengue epidemics in Guangdong Province.

CONCLUSION

Our study suggests weather factors and ENSO are important predictors of dengue incidence. These findings provide useful evidence for early warning systems to help to respond to the global expansion of dengue fever.