The Epidemiological Characteristics and Dynamic Transmission of Dengue in China, 2013

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

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

Dengue Incidence Trends and Its Burden in Major Endemic Regions from 1990 to 2019

BACKGROUND

Dengue has become one of the major vector-borne diseases, which has been an important public health concern. We aimed to estimate the disease burden of dengue in major endemic regions from 1990 to 2019, and explore the impact pattern of the socioeconomic factors on the burden of dengue based on the global burden of diseases, injuries, and risk factors study 2019 (GBD 2019).

METHODS

Using the analytical strategies and data from the GBD 2019, we described the incidence and disability-adjusted life years (DALYs) of dengue in major endemic regions from 1990 to 2019. Furthermore, we estimated the correlation between dengue burden and socioeconomic factors, and then established an autoregressive integrated moving average (ARIMA) model to predict the epidemic trends of dengue in endemic regions. All estimates were proposed as numbers and age-standardized rates (ASR) per 100,000 population, with uncertainty intervals (UIs). The ASRs of dengue incidence were compared geographically and five regions were stratified by a sociodemographic index (SDI).

RESULTS

A significant rise was observed on a global scale between 1990 and 2019, with the overall age-standardized rate (ASR) increasing from 557.15 (95% UI 243.32-1212.53) per 100,000 in 1990 to 740.4 (95% UI 478.2-1323.1) per 100,000 in 2019. In 2019, the Oceania region had the highest age-standardized incidence rates per 100,000 population (3173.48 (95% UI 762.33-6161.18)), followed by the South Asia region (1740.79 (95% UI 660.93-4287.12)), and then the Southeast Asia region (1153.57 (95% UI 1049.49-1281.59)). In Oceania, South Asia, and Southeast Asia, increase trends were found in the burden of dengue fever measured by ASRs of DALY which were consistent with ASRs of dengue incidence at the national level. Most of the countries with the heaviest burden of dengue fever occurred in areas with low and medium SDI regions. However, the burden in high-middle and high-SDI countries is relatively low, especially the Solomon Islands and Tonga in Oceania, the Maldives in South Asia and Indonesia in Southeast Asia. The age distribution results of the incidence rate and disease burden of dengue fever of major endemic regions showed that the higher risk and disease burden are mainly concentrated in people under 14 or over 70 years old. The prediction by ARIMA showed that the risk of dengue fever in South and Southeast Asia is on the rise, and further prevention and control is warranted.

CONCLUSIONS

In view of the rapid population growth and urbanization in many dengue-endemic countries, our research results are of great significance for presenting the future trend in dengue fever. It is recommended to policy makers that specific attention needs to be paid to the negative impact of urbanization on dengue incidence and allocate more resources to the low-SDI areas and people under 14 or over 70 years old to reduce the burden of dengue fever.

Etiology of acute febrile illnesses in Southern China: Findings from a two-year sentinel surveillance project, 2017–2019

Background

Southern China is at risk for arborvirus disease transmission, including Zika virus and dengue. Patients often present to clinical care with non-specific acute febrile illnesses (AFI). To better describe the etiology of AFI, we implemented a two-year AFI surveillance project at five sentinel hospitals in Yunnan and Guangdong Provinces.

Methods

Between June 2017 and August 2019, we enrolled patients between 2 and 65 years of age presenting at one sentinel hospital in Mengla County, Yunnan, and four in Jiangmen City, Guangdong, with symptoms of AFI (acute onset of fever ≥ 37.5°C within the past 7 days) without respiratory symptoms or diarrhea. Demographic, epidemiologic, and clinical information was obtained and entered into a web-based AFI surveillance database. A custom TaqMan Array card (TAC) was used to test patients’ whole blood specimens for 27 different pathogens using real-time polymerase chain reaction assays.

Results

During the two-year project period, 836 patients were enrolled; 443 patients from Mengla County and 393 patients from Jiangmen City. The median age was 33 years [range: 2–65], and most were hospitalized [641, 77%]. Of 796 patients with valid TAC results, 341 (43%) were positive for at least one of the 10 unique pathogens detected. This included 205 (26%) patients positive for dengue virus, 60 (8%) for Orientia tsutsugamushi, and 42 (5%) for Coxiella burnetii. Ten patients (1%) in Jiangmen City tested positive for malaria, 8 of whom reported recent travel outside of China. TAC results were negative for 455 (57%) patients. None of the patients had a positive TAC detection for Zika virus.

Conclusions

The project detected variability in the etiology of AFI in Southern China and highlighted the importance of differential diagnosis. Dengue, O. tsutsugamushi, and C. burnetii were the most frequently identified pathogens among enrolled AFI patients. As a non-notifiable disease, the frequent detection of C. burnetii is noteworthy and warrants additional investigation. The project provided a framework for routine surveillance for persons presenting with AFI.

Epidemiology of Indigenous Dengue Cases in Zhejiang Province, Southeast China

Objective

Autochthonous transmission of the dengue virus (DENV) occurred each year from 2014 to 2018 in Zhejiang province, and became an emerging public health problem. We characterized the autochthonous transmission of the DENV and traced the source of infection for further control and prevention of dengue.

Methods

Descriptive and spatiotemporal cluster analyses were conducted to characterize the epidemiology of autochthonous transmission of the DENV. Molecular epidemiology was used to identify the infection source.

Results

In total, 1,654 indigenous cases and 12 outbreaks, with no deaths, were reported during 2004–2018. Before 2017, all outbreaks occurred in suburban areas. During 2017–2018, five out of eight outbreaks occurred in urban areas. The median duration of outbreaks (28 days) in 2017–2018 was shortened significantly (P = 0.028) in comparison with that in 2004–2016 (71 days). The median onset-visiting time, visiting-confirmation time, and onset-confirmation time was 1, 3, and 4 days, respectively. The DENV serotypes responsible for autochthonous transmission in Zhejiang Province were DENV 1, DENV 2, and DENV 3, with DENV 1 being the most frequently reported. Southeast Asia was the predominant source of indigenous infection.

Conclusions

Zhejiang Province witnessed an increase in the frequency, incidence, and geographic expansion of indigenous Dengue cases in recent years. The more developed coastal and central region of Zhejiang Province was impacted the most.

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.

Land use and land cover change and its impacts on dengue dynamics in China: A systematic review

Background

Dengue is a prioritized public health concern in China. Because of the larger scale, more frequent and wider spatial distribution, the challenge for dengue prevention and control has increased in recent years. While land use and land cover (LULC) change was suggested to be associated with dengue, relevant research has been quite limited. The “Open Door” policy introduced in 1978 led to significant LULC change in China. This systematic review is the first to review the studies on the impacts of LULC change on dengue dynamics in China. This review aims at identifying the research evidence, research gaps and provide insights for future research.

Methods

A systematic literature review was conducted following the PRISMA protocol. The combinations of search terms on LULC, dengue and its vectors were searched in the databases PubMed, Web of Science, and Baidu Scholar. Research conducted on China published from 1978 to December 2019 and written in English or Chinese was selected for further screening. References listed in articles meeting the inclusion criteria were also reviewed and included if again inclusion criteria were met to minimize the probability of missing relevant research.

Results

28 studies published between 1978 and 2017 were included for the full review. Guangdong Province and southern Taiwan were the major regional foci in the literature. The majority of the reviewed studies observed associations between LULC change factors and dengue incidence and distribution. Conflictive evidence was shown in the studies about the impacts of green space and blue space on dengue in China. Transportation infrastructure and urbanization were repeatedly suggested to be positively associated with dengue incidence and spread. The majority of the studies reviewed considered meteorological and sociodemographic factors when they analyzed the effects of LULC change on dengue. Primary and secondary remote sensing (RS) data were the primary source for LULC variables. In 21 of 28 studies, a geographic information system (GIS) was used to process data of environmental variables and dengue cases and to perform spatial analysis of dengue.

Conclusions

The effects of LULC change on the dynamics of dengue in China varied in different periods and regions. The application of RS and GIS enriches the means and dimensions to explore the relations between LULC change and dengue. Further comprehensive regional research is necessary to assess the influence of LULC change on local dengue transmission to provide practical advice for dengue prevention and control.

Dengue is a major public health concern in China. The rapid development of urbanization along with climate change increases the challenge for dengue prevention and control. Previous research has mainly focused on the meteorological variables whereas land use and land cover (LULC) change received comparatively less attention. Our review identified that the regional research hotspots of dengue epidemics in China were Guangdong Province and southern Taiwan. Though inconsistent, most included studies somehow observed associations between at least one of the LULC change factors and dengue. A geographical information system (GIS) was widely used to perform spatial analysis in the selected literature. Its application provided a novel view to describe the relationships between environmental factors and the situation of dengue, which enabled scholars to explore more characteristics of dengue transmission. Meanwhile, the use of remote sensing (RS) enriched the means of environmental monitoring. However, there are research gaps in the area of dengue and LULC change, such as the less consideration of dengue vector study, the lack of interplays between factors, and the lack of considering interventions and policies. Furthermore, because of different research settings, results from these studies were difficult to compare. Thus, further comprehensive and comparable investigations are necessary to better understand the effects of LULC change on dengue in China. This review is the first to expound the studies on the associations between LULC change and dengue dynamics in China. It demonstrates the findings and methodologies and provided insights for future research.

Increasingly expanded future risk of dengue fever in the Pearl River Delta, China

BACKGROUND

In recent years, frequent outbreaks of dengue fever (DF) have become an increasingly serious public health issue in China, especially in the Pearl River Delta (PRD) with fast socioeconomic developments. Previous studies mainly focused on the historic DF epidemics, their influencing factors, and the prediction of DF risks. However, the future risks of this disease under both different socioeconomic development and representative concentration pathways (RCPs) scenarios remain little understood.

METHODOLOGY AND PRINCIPAL FINDINGS

In this study, a spatial dataset of gross domestic product (GDP), population density, and land use and land coverage (LULC) in 2050 and 2070 was obtained by simulation based on the different shared socioeconomic pathways (SSPs), and the future climatic data derived from the RCP scenarios were integrated into the Maxent models for predicting the future DF risk in the PRD region. Among all the variables included in this study, socioeconomics factors made the dominant contribution (83% or so) during simulating the current spatial distribution of the DF epidemics in the PRD region. Moreover, the spatial distribution of future DF risk identified by the climatic and socioeconomic (C&S) variables models was more detailed than that of the climatic variables models. Along with global warming and socioeconomic development, the zones with DF high and moderate risk will continue to increase, and the population at high and moderate risk will reach a maximum of 48.47 million (i.e., 63.78% of the whole PRD) under the RCP 4.5/SSP2 in 2070.

CONCLUSIONS

The increasing DF risk may be an inevitable public health threat in the PRD region with rapid socioeconomic developments and global warming in the future. Our results suggest that curbs in emissions and more sustainable socioeconomic growth targets offer hope for limiting the future impact of dengue, and effective prevention and control need to continue to be strengthened at the junction of Guangzhou-Foshan, north-central Zhongshan city, and central-western Dongguan city. Our study provides useful clues for relevant hygienic authorities making targeted adapting strategies for this disease.

The long-term changing dynamics of dengue infectivity in Guangdong, China, from 2008-2018: a modelling analysis

BACKGROUND

Dengue remains a severe threat to public health in tropical and subtropical regions. In China, over 85% of domestic dengue cases are in the Guangdong province and there were 53 139 reported cases during 2008-2018. In Guangdong, the 2014 dengue outbreak was the largest in the last 20 y and it was probably triggered by a new strain imported from other regions.

METHODS

We studied the long-term patterns of dengue infectivity in Guangdong from 2008-2018 and compared the infectivity estimates across different periods.

RESULTS

We found that the annual epidemics approximately followed exponential growth during 2011-2014. The transmission rates were at a low level during 2008-2012, significantly increased 1.43-fold [1.22, 1.69] during 2013-2014 and then decreased back to a low level after 2015. By using the mosquito index and the likelihood-inference approach, we found that the new strain most likely invaded Guangdong in April 2014.

CONCLUSIONS

The long-term changing dynamics of dengue infectivity are associated with the new dengue virus strain invasion and public health control programmes. The increase in infectiousness indicates the potential for dengue to go from being imported to becoming an endemic in Guangdong, China.

Spatial Dynamics of Dengue Fever in Mainland China, 2019

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

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.

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.

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.

Molecular characterization of the viral structural gene of the first dengue virus type 1 outbreak in Xishuangbanna: A border area of China, Burma and Laos

BACKGROUND

Xishuangbanna, a border area of China, Burma and Laos, had its first major DENV-1 outbreak in 2017. This study aims to explore the genetic characterization, potential source and evolution of the viruses in outbreak.

METHODS

The structural protein C/prM/E genes of viruses isolated from local residents or Burmese travelers were sequenced followed by mutation, phylogenetic, homologous recombination, molecular clock and demographic reconstruction analysis.

RESULTS

Phylogenetic analysis revealed that all of the strains were classified as three cluster of DENV-1. Cluster 1, 2 and 3 were most similar to China Guangzhou 2011, China Hubei 2014 and Laos 2008 strain, respectively. Among 236 base mutations, 31 caused nonsynonymous mutations when compared with the DENV-1SS. No homologous recombination signal was discovered. The structural protein of these strains had similar three-dimensional structure. Only site 434 showed differences among five predicted protein binding sites. Molecular clock phylogenetic and demographic reconstruction analysis showed that DENV-1 became highly diversified in 1972 followed by a slightly decreased period until 2017.

CONCLUSIONS

Dengue isolated strains show diversification between Burma and China. Amino acid substitution (I440T) may lead to weakened virulence of the epidemic strains. DENV-1 became highly diversified in 1972 followed by a slightly decreased period.

The non-canonical Notch signaling is essential for the control of fertility in Aedes aegypti

The Notch signaling pathway is a highly evolutionarily-conserved cell-cell signaling pathway that regulates many events during development. It plays a pivotal role in the regulation of fundamental cellular processes, such as cell proliferation, stem cell maintenance, and differentiation during embryonic and adult development. However, functions of Notch signaling in Aedes aegypti, the major mosquito vector for dengue, are largely unknown. In this study, we identified a unique feature of A. aegypti Notch (AaNotch) in the control of the sterile-like phenotype in female mosquitoes. Silencing AaNotch with a reverse genetic approach significantly reduced the fecundity and fertility of the mosquito. Silencing AaNotch also resulted in the prevention of micropyle formation, which led to impaired fertilization. In addition, JNK phosphorylation (a signaling molecule in the non-canonical Notch signaling pathway) was inhibited in the absence of AaNotch. Furthermore, treatment with a JNK inhibitor in the mosquito resulted in impaired fecundity and fertility. Taken together, our results demonstrate that non-canonical Notch signaling is essential for controlling fertility in the A. aegypti mosquito.

Exploring Determinants of Spatial Variations in the Dengue Fever Epidemic Using Geographically Weighted Regression Model: A Case Study in the Joint Guangzhou-Foshan Area, China, 2014

Dengue fever (DF) is a common and rapidly spreading vector-borne viral disease in tropical and subtropical regions. In recent years, this imported disease has posed an increasing threat to public health in China, especially in many southern cities. Although the severity of DF outbreaks in these cities is generally associated with known risk factors at various administrative levels, spatial heterogeneities of these associations remain little understood on a finer scale. In this study, the neighboring Guangzhou and Foshan (GF) cities were considered as a joint area for characterizing the spatial variations in the 2014 DF epidemic at various grid levels from 1 × 1 km² to 6 × 6 km². On an appropriate scale, geographically weighted regression (GWR) models were employed to interpret the influences of socioeconomic and environmental factors on this epidemic across the GF area. DF transmissions in Guangzhou and Foshan cities presented synchronous temporal changes and spatial expansions during the main epidemic months. Across the GF area, this epidemic was obviously spatially featured at various grid levels, especially on the 2 × 2 km² scale. Its spatial variations were relatively sufficiently explained by population size, road density, and economic status integrated in the GWR model with the lowest Akaike Information Criterion (AICc = 5227.97) and highest adjusted R square (0.732) values. These results indicated that these three socioeconomic factors acted as geographical determinants of spatial variability of the 2014 DF epidemic across the joint GF area, although some other potential factors should be added to improve the explaining the spatial variations in the central zones. This work improves our understanding of the effects of socioeconomic conditions on the spatial variations in this epidemic and helps local hygienic authorities to make targeted joint interventions for preventing and controlling this epidemic across the GF area.

Diversity of Mosquitoes (Diptera: Culicidae) Attracted to Human Subjects in Rubber Plantations, Secondary Forests, and Villages in Luang Prabang Province, Northern Lao PDR

The impact of the rapid expansion of rubber plantations in South-East Asia on mosquito populations is uncertain. We compared the abundance and diversity of adult mosquitoes using human-baited traps in four typical rural habitats in northern Lao PDR: secondary forests, immature rubber plantations, mature rubber plantations, and villages. Generalized estimating equations were used to explore differences in mosquito abundance between habitats, and Simpson's diversity index was used to measure species diversity. Over nine months, 24,927 female mosquitoes were collected, including 51 species newly recorded in Lao PDR. A list of the 114 mosquito species identified is included. More mosquitoes, including vector species, were collected in the secondary forest than immature rubber plantations (rainy season, odds ratio [OR] 0.33, 95% confidence interval [CI] 0.31-0.36; dry season, 0.46, 95% CI 0.41-0.51), mature rubber plantations (rainy season, OR 0.25, 95% CI 0.23-0.27; dry season, OR 0.25, 95% CI 0.22-0.28), and villages (rainy season, OR 0.13, 95% CI 0.12-0.14; dry season, 0.20, 95% CI 0.18-0.23). All habitats showed high species diversity (Simpson's indexes between 0.82-0.86) with vectors of dengue, Japanese encephalitis (JE), lymphatic filariasis, and malaria. In the secondary forests and rubber plantations, Aedes albopictus (Skuse), a dengue vector, was the dominant mosquito species, while in the villages, Culex vishnui (Theobald), a JE vector, was most common. This study has increased the overall knowledge of mosquito fauna in Lao PDR. The high abundance of Ae. albopictus in natural and man-made forests warrants concern, with vector control measures currently only implemented in cities and villages.

Age-associated differences in clinical manifestations and laboratory parameters during a dengue virus type 4 outbreak in Argentina

Infection by any of the four dengue virus (DENV) serotypes produces a wide spectrum of clinical illness in humans. Differences in clinical manifestation and severity have been associated with secondary heterologous infection, patient age, and virus serotype. In this context, this retrospective study sought to analyze the presentation of dengue in patients during the 2014 DENV-4 outbreak affecting the City of Orán, Salta Province, Argentina. Demographic data, clinical manifestations, and laboratory abnormalities of laboratory-confirmed dengue patients were compared between age groups and between patients with and without warning signs. Of 301 patients with laboratory-confirmed dengue, 37.9% presented dengue with warning signs. Although nearly half of all patients had secondary DENV infections, no severe dengue cases, or deaths were reported. Furthermore, no association was found between incidence of warning signs and pre-existing immunity to DENV. Pediatric patients were least likely to present warning signs and showed significantly decreased risk of fever, retro-orbital pain, arthalgia, diarrhea and thrombocytopenia, and higher risk of rash compared to older patients. Female patients of all ages were also at higher risk of developing several symptoms. The characterization of DENV-4 infection in humans, a DENV serotype recently reported in Argentina, revealed differences in clinical manifestations, laboratory parameters and the presence/absence of warning signs based on age group. Further investigation of these age-related differences should contribute to better assessment of dengue disease in at risk populations.

Closing the gap in travel medicine: reframing research questions for a new era

BACKGROUND

Travel medicine needs are changing. New patterns of travel, including greater travel by individuals from emerging economies with different values in costs, risks and benefits, must be considered. This review aims to (1) highlight selected studies that have been published that address previously identified gaps in knowledge; (2) propose possible ways to consider questions regarding travel medicine practice for travelers from emerging economies, underscoring priorities for research focusing on these important populations; (3) highlight potential deficiencies in relevance of current international guidelines as they pertain to travelers from emerging economies; (4) frame research questions for travelers from emerging economies and (5) consider roles for ISTM in closing the gap.

METHODS

We reviewed past travel medicine research priorities published in 2010 to identify publications that responded to some research questions posed. We also reviewed CDC and WHO recommendations and assessed their applicability to travelers from emerging economies.

RESULTS

Recent publications have responded to some research questions, but gaps remain and new questions have emerged. Re-framing of several key research questions is needed for travelers from emerging economies.

DISCUSSION

A new challenge looms for traditional travel medicine fields to identify and attend to knowledge and guideline gaps, particularly to rethink questions regarding travel medicine to make them relevant for travelers from emerging economies. The International Society of Travel Medicine is well positioned to assist emerging economies assess their resources and needs, formulate research priorities and tailor the development of travel medicine into a framework aligned to their requirements.

Ecological Niche Modeling Identifies Fine-Scale Areas at High Risk of Dengue Fever in the Pearl River Delta, China

Dengue fever (DF) is one of the most common and rapidly spreading mosquito-borne viral diseases in tropical and subtropical regions. In recent years, this imported disease has posed a serious threat to public health in China, especially in the Pearl River Delta (PRD). Although the severity of DF outbreaks in the PRD is generally associated with known risk factors, fine scale assessments of areas at high risk for DF outbreaks are limited. We built five ecological niche models to identify such areas including a variety of climatic, environmental, and socioeconomic variables, as well as, in some models, extracted principal components. All the models we tested accurately identified the risk of DF, the area under the receiver operating characteristic curve (AUC) were greater than 0.8, but the model using all original variables was the most accurate (AUC = 0.906). Socioeconomic variables had a greater impact on this model (total contribution 55.27%) than climatic and environmental variables (total contribution 44.93%). We found the highest risk of DF outbreaks on the border of Guangzhou and Foshan (in the central PRD), and in northern Zhongshan (in the southern PRD). Our fine-scale results may help health agencies to focus epidemic monitoring tightly on the areas at highest risk of DF outbreaks.