Spatiotemporal dynamics of dengue epidemics, southern Vietnam

Household immunity and individual risk of infection with dengue virus in a prospective, longitudinal cohort study

Although it is known that household infections drive the transmission of dengue virus (DENV), it is unclear how household composition and the immune status of inhabitants affect the individual risk of infection. Most population-based studies to date have focused on paediatric cohorts because more severe forms of dengue mainly occur in children, and the role of adults in dengue transmission is understudied. Here we analysed data from a multigenerational cohort study of 470 households, comprising 2,860 individuals, in Kamphaeng Phet, Thailand, to evaluate risk factors for DENV infection. Using a gradient-boosted regression model trained on annual haemagglutination inhibition antibody titre inputs, we identified 1,049 infections, 90% of which were subclinical. By analysing imputed infections, we found that individual antibody titres, household composition and antibody titres of other members in the same household affect an individual's risk of DENV infection. Those individuals living in households with high average antibody titres, or households with more adults, had a reduced risk of infection. We propose that herd immunity to dengue acts at the household level and may provide insight into the drivers of the recent change in the shifting age distribution of dengue cases in Thailand.

Common patterns between dengue cases, climate, and local environmental variables in Costa Rica: A wavelet approach

Dengue transmission poses significant challenges for public health authorities worldwide due to its susceptibility to various factors, including environmental and climate variability, affecting its incidence and geographic spread. This study focuses on Costa Rica, a country characterized by diverse microclimates nearby, where dengue has been endemic since its introduction in 1993. Using wavelet coherence and clustering analysis, we performed a time-series analysis to uncover the intricate connections between climate, local environmental factors, and dengue occurrences. The findings indicate that multiannual dengue frequency (3 yr) is correlated with the Oceanic Niño Index and the Tropical North Atlantic Index. This association is particularly prominent in cantons located along the North and South Pacific Coast, as well as in the Central cantons of the country. Furthermore, the time series of these climate indices exhibit a leading phase of approximately nine months ahead of dengue cases. Additionally, the clustering analysis uncovers non-contiguous groups of cantons that exhibit similar correlation patterns, irrespective of their proximity or adjacency. This highlights the significance of climate factors in influencing dengue dynamics across diverse regions, regardless of spatial closeness or distance between them. On the other hand, the annual dengue frequency was correlated with local environmental indices. A persistent correlation between dengue cases and local environmental variables is observed over time in the North Pacific and the Central Region of the country's Northwest, with environmental factors leading by less than three months. These findings contribute to understanding dengue transmission's spatial and temporal dynamics in Costa Rica, highlighting the importance of climate and local environmental factors in dengue surveillance and control efforts.

Disentangling local and global climate drivers in the population dynamics of mosquito-borne infections

Identifying climate drivers is essential to understand and predict epidemics of mosquito-borne infections whose population dynamics typically exhibit seasonality and multiannual cycles. Which climate covariates to consider varies across studies, from local factors such as temperature to remote drivers such as the El Niño-Southern Oscillation. With partial wavelet coherence, we present a systematic investigation of nonstationary associations between mosquito-borne disease incidence and a given climate factor while controlling for another. Analysis of almost 200 time series of dengue and malaria around the globe at different geographical scales shows a systematic effect of global climate drivers on interannual variability and of local ones on seasonality. This clear separation of time scales of action enhances detection of climate drivers and indicates those best suited for building early-warning systems.

Characterizing dengue transmission in rural areas: A systematic review

Dengue has historically been considered an urban disease associated with dense human populations and the built environment. Recently, studies suggest increasing dengue virus (DENV) transmission in rural populations. It is unclear whether these reports reflect recent spread into rural areas or ongoing transmission that was previously unnoticed, and what mechanisms are driving this rural transmission. We conducted a systematic review to synthesize research on dengue in rural areas and apply this knowledge to summarize aspects of rurality used in current epidemiological studies of DENV transmission given changing and mixed environments. We described how authors defined rurality and how they defined mechanisms for rural dengue transmission. We systematically searched PubMed, Web of Science, and Embase for articles evaluating dengue prevalence or cumulative incidence in rural areas. A total of 106 articles published between 1958 and 2021 met our inclusion criteria. Overall, 56% (n = 22) of the 48 estimates that compared urban and rural settings reported rural dengue incidence as being as high or higher than in urban locations. In some rural areas, the force of infection appears to be increasing over time, as measured by increasing seroprevalence in children and thus likely decreasing age of first infection, suggesting that rural dengue transmission may be a relatively recent phenomenon. Authors characterized rural locations by many different factors, including population density and size, environmental and land use characteristics, and by comparing their context to urban areas. Hypothesized mechanisms for rural dengue transmission included travel, population size, urban infrastructure, vector and environmental factors, among other mechanisms. Strengthening our understanding of the relationship between rurality and dengue will require a more nuanced definition of rurality from the perspective of DENV transmission. Future studies should focus on characterizing details of study locations based on their environmental features, exposure histories, and movement dynamics to identify characteristics that may influence dengue transmission.

Effectiveness of dengue training programmes on prevention and control among high school students in the Yangon region, Myanmar

Background

Dengue is one of the health problems in Myanmar. Thus, health promotion in schools is considered a key approach for reducing risk-taking behaviours related to dengue.

Objectives

The study aimed to evaluate a dengue training programme for high school students to measure changes in knowledge, attitude and practices (KAP) towards dengue; evaluate the effectiveness of the programme in improving prevention and control practices among families and determining changes in larval indices in their dwelling places.

Methodology

The dengue school training programme was conducted for Grades 9 and 10 students in Yangon. In total, 300 students in the intervention school received training and were compared with 300 students as control. KAP was assessed using a self-administered questionnaire, whereas larval and control practice surveys were conducted at the homes of both groups 3 months before and after the programme.

Results

The KAP scores of the intervention group increased after the programme. Moreover, the programme improved prevention and control practices and decreased the larval indices in the intervention group. Students from the same group with high scores in knowledge and self-reported practices were less likely to exhibit Aedes larval positivity in their residential areas.

Conclusion

This study demonstrated the impact of the dengue training programme on the KAP of students and short-term family larval control practices, which influenced household larval indices.

Molecular Characterization of Dengue Virus Strains from the 2019-2020 Epidemic in Hanoi, Vietnam

Dengue virus (DENV), which has circulated in Vietnam for several decades, has multiple serotypes and genotypes. A 2019 dengue outbreak resulted in a larger number of cases than any other outbreak. We conducted a molecular characterization using samples collected in 2019-2020 from dengue patients in Hanoi and nearby cities located in northern Vietnam. The circulating serotypes were DENV-1 (25%, n = 22) and DENV-2 (73%, n = 64). Phylogenetic analyses revealed that all DENV-1 (n = 13) were genotype I and clustered to local strains circulating during the previous outbreak in the 2017, whereas DENV-2 consisted of two genotypes: Asian-I (n = 5), related to local strains from 2006-2022, and cosmopolitan (n = 18), the predominant genotype in this epidemic. The current cosmopolitan virus was identified as having an Asian-Pacific lineage. The virus was closely related to strains in other recent outbreaks in Southeast Asian countries and China. Multiple introductions occurred in 2016-2017, which were possibly from maritime Southeast Asia (Indonesia, Singapore, and Malaysia), mainland Southeast Asia (Cambodia and Thailand), or China, rather than from an expansion of localized Vietnamese cosmopolitan strains that were previously detected in the 2000s. We also analyzed the genetic relationship between Vietnam's cosmopolitan strain and recent global strains reported from Asia, Oceania, Africa, and South America. This analysis revealed that viruses of Asian-Pacific lineage are not restricted to Asia but have spread to Peru and Brazil in South America.

A phylogenetic study of dengue virus in urban Vietnam shows long-term persistence of endemic strains

Dengue virus (DENV) causes repeated outbreaks of disease in endemic areas, with patterns of local transmission strongly influenced by seasonality, importation via human movement, immunity, and vector control efforts. An understanding of how each of these interacts to enable endemic transmission (continual circulation of local virus strains) is largely unknown. There are times of the year when no cases are reported, often for extended periods of time, perhaps wrongly implying the successful eradication of a local strain from that area. Individuals who presented at a clinic or hospital in four communes in Nha Trang, Vietnam, were initially tested for DENV antigen presence. Enrolled positive individuals then had their corresponding household members invited to participate, and those who enrolled were tested for DENV. The presence of viral nucleic acid in all samples was confirmed using quantitative polymerase chain reaction, and positive samples were then whole-genome sequenced using an amplicon and target enrichment library preparation techniques and Illumina MiSeq sequencing technology. Generated consensus genome sequences were then analysed using phylogenetic tree reconstruction to categorise sequences into clades with a common ancestor, enabling investigations of both viral clade persistence and introductions. Hypothetical introduction dates were additionally assessed using a molecular clock model that calculated the time to the most recent common ancestor (TMRCA). We obtained 511 DENV whole-genome sequences covering four serotypes and more than ten distinct viral clades. For five of these clades, we had sufficient data to show that the same viral lineage persisted for at least several months. We noted that some clades persisted longer than others during the sampling time, and by comparison with other published sequences from elsewhere in Vietnam and around the world, we saw that at least two different viral lineages were introduced into the population during the study period (April 2017-2019). Next, by inferring the TMRCA from the construction of molecular clock phylogenies, we predicted that two of the viral lineages had been present in the study population for over a decade. We observed five viral lineages co-circulating in Nha Trang from three DENV serotypes, with two likely to have remained as uninterrupted transmission chains for a decade. This suggests clade cryptic persistence in the area, even during periods of low reported incidence.

The imported infections among foreign travelers in China: an observational study

BACKGROUND

In the past few decades, globalization has rendered more frequent and intensive population movement between countries, which has changed the original disease spectrum and brought a huge health impact on the global population including China. This study aims to describe the spectrum and epidemiological characteristics of imported infections among foreign travelers travelling to China.

METHODS

The data on imported infections among foreign travelers were obtained from Custom Inbound Screening System (CISS) and the National Notifiable Infectious Disease Reporting System (NNIDRS). All the infections were classified into respiratory, gastrointestinal, vector-borne, blood/sex-transmitted and mucocutaneous diseases, of which case numbers and incidences were calculated and the proportions were compared among subgroups.

RESULTS

In total, 17,189 travelers diagnosed with 58 imported infectious diseases were reported from 2014 to 2018, with an overall incidence of 122.59 per million. Respiratory infection (7,351 cases, mainly influenza) and blood/sex-transmitted diseases (6,114 cases mainly Hepatitis B and HIV infection) were the most frequently diagnosed diseases, followed by vector-borne infections (3,128 cases, mainly dengue fever and malaria). The highest case number was from Asia and Europe, while the highest incidence rate was from Africa (296.00 per million). When specific diagnosis was compared, both the highest absolute case number and incidence were observed for influenza. An obvious seasonal pattern was observed for vector-borne diseases, with the annual epidemic spanning from July to November. The origin-destination matrices disclosed the movement of imported infection followed specific routes.

CONCLUSIONS

Our study provided a profile of infectious diseases among foreign travelers travelling to China and pinpointed the target regions, seasons and populations for prevention and control, to attain an informed control of imported infections in China.

Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis

Background

Scrub Typhus (ST) is a rickettsial disease caused by Orientia tsutsugamushi. The number of ST cases has been increasing in China during the past decades, which attracts great concerns of the public health.

Methods

We obtained monthly documented ST cases greater than 54 cases in 434 counties of China during 2012-2020. Spatiotemporal wavelet analysis was conducted to identify the ST clusters with similar pattern of the temporal variation and explore the association between ST variation and El Niño and La Niña events. Wavelet coherency analysis and partial wavelet coherency analysis was employed to further explore the co-effects of global and local climatic factors on ST.

Results

Wavelet cluster analysis detected seven clusters in China, three of which are mainly distributed in Eastern China, while the other four clusters are located in the Southern China. Among the seven clusters, summer and autumn-winter peak of ST are the two main outbreak periods; while stable and fluctuated periodic feature of ST series was found at 12-month and 4-(or 6-) month according to the wavelet power spectra. Similarly, the three-character bands were also found in the associations between ST and El Niño and La Niña events, among which the 12-month period band showed weakest climate-ST association and the other two bands owned stronger association, indicating that the global climate dynamics may have short-term effects on the ST variations. Meanwhile, 12-month period band with strong association was found between the four local climatic factors (precipitation, pressure, relative humidity and temperature) and the ST variations. Further, partial wavelet coherency analysis suggested that global climatic dynamics dominate annual ST variations, while local climatic factors dominate the small periods.

Conclusion

The ST variations are not directly attributable to the change in large-scale climate. The existence of these plausible climatic determinants stimulates the interests for more insights into the epidemiology of ST, which is important for devising prevention and early warning strategies.

Global Change and Emerging Infectious Diseases

Our world is undergoing rapid planetary changes driven by human activities, often mediated by economic incentives and resource management, affecting all life on Earth. Concurrently, many infectious diseases have recently emerged or spread into new populations. Mounting evidence suggests that global change-including climate change, land-use change, urbanization, and global movement of individuals, species, and goods-may be accelerating disease emergence by reshaping ecological systems in concert with socioeconomic factors. Here, we review insights, approaches, and mechanisms by which global change drives disease emergence from a disease ecology perspective. We aim to spur more interdisciplinary collaboration with economists and identification of more effective and sustainable interventions to prevent disease emergence. While almost all infectious diseases change in response to global change, the mechanisms and directions of these effects are system specific, requiring new, integrated approaches to disease control that recognize linkages between environmental and economic sustainability and human and planetary health.

Importance of Public Transport Networks for Reconciling the Spatial Distribution of Dengue and the Association of Socio-Economic Factors with Dengue Risk in Bangkok, Thailand

Dengue is the most widespread mosquito-borne viral disease of man and spreading at an alarming rate. Socio-economic inequality has long been thought to contribute to providing an environment for viral propagation. However, identifying socio-economic (SE) risk factors is confounded by intra-urban daily human mobility, with virus being ferried across cities. This study aimed to identify SE variables associated with dengue at a subdistrict level in Bangkok, analyse how they explain observed dengue hotspots and assess the impact of mobility networks on such associations. Using meteorological, dengue case, national statistics, and transport databases from the Bangkok authorities, we applied statistical association and spatial analyses to identify SE variables associated with dengue and spatial hotspots and the extent to which incorporating transport data impacts the observed associations. We identified three SE risk factors at the subdistrict level: lack of education, % of houses being cement/brick, and number of houses as being associated with increased risk of dengue. Spatial hotspots of dengue were found to occur consistently in the centre of the city, but which did not entirely have the socio-economic risk factor characteristics. Incorporation of the intra-urban transport network, however, much improved the overall statistical association of the socio-economic variables with dengue incidence and reconciled the incongruous difference between the spatial hotspots and the SE risk factors. Our study suggests that incorporating transport networks enables a more real-world analysis within urban areas and should enable improvements in the identification of risk factors.

Periodic synchronisation of dengue epidemics in Thailand over the last 5 decades driven by temperature and immunity

The spatial distribution of dengue and its vectors (spp. Aedes) may be the widest it has ever been, and projections suggest that climate change may allow the expansion to continue. However, less work has been done to understand how climate variability and change affects dengue in regions where the pathogen is already endemic. In these areas, the waxing and waning of immunity has a large impact on temporal dynamics of cases of dengue haemorrhagic fever. Here, we use 51 years of data across 72 provinces and characterise spatiotemporal patterns of dengue in Thailand, where dengue has caused almost 1.5 million cases over the last 30 years, and examine the roles played by temperature and dynamics of immunity in giving rise to those patterns. We find that timescales of multiannual oscillations in dengue vary in space and time and uncover an interesting spatial phenomenon: Thailand has experienced multiple, periodic synchronisation events. We show that although patterns in synchrony of dengue are similar to those observed in temperature, the relationship between the two is most consistent during synchronous periods, while during asynchronous periods, temperature plays a less prominent role. With simulations from temperature-driven models, we explore how dynamics of immunity interact with temperature to produce the observed patterns in synchrony. The simulations produced patterns in synchrony that were similar to observations, supporting an important role of immunity. We demonstrate that multiannual oscillations produced by immunity can lead to asynchronous dynamics and that synchrony in temperature can then synchronise these dengue dynamics. At higher mean temperatures, immune dynamics can be more predominant, and dengue dynamics more insensitive to multiannual fluctuations in temperature, suggesting that with rising mean temperatures, dengue dynamics may become increasingly asynchronous. These findings can help underpin predictions of disease patterns as global temperatures rise.

This study shows that spatially large-scale shifts in temperature can synchronize dengue dynamics across Thailand; however, as average temperatures rise, dengue dynamics may increasingly be dictated by dynamics of immunity, which may in turn mean fewer synchronous outbreaks in the future.

Modeling the Cost-Effectiveness of Interventions to Prevent Plague in Madagascar

Plague (Yersinia pestis) remains endemic in certain parts of the world. We assessed the cost-effectiveness of plague control interventions recommended by the World Health Organization with particular consideration to intervention coverage and timing. We developed a dynamic model of the spread of plague between interacting populations of humans, rats, and fleas and performed a cost-effectiveness analysis calibrated to a 2017 Madagascar outbreak. We assessed three interventions alone and in combination: expanded access to antibiotic treatment with doxycycline, mass distribution of doxycycline prophylaxis, and mass distribution of malathion. We varied intervention timing and coverage levels. We calculated costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios from a healthcare perspective. The preferred intervention, using a cost-effectiveness threshold of $1350/QALY (GDP per capita in Madagascar), was expanded access to antibiotic treatment with doxycycline with 100% coverage starting immediately after the first reported case, gaining 543 QALYs at an incremental cost of $1023/QALY gained. Sensitivity analyses support expanded access to antibiotic treatment and leave open the possibility that mass distribution of doxycycline prophylaxis or mass distribution of malathion could be cost-effective. Our analysis highlights the potential for rapid expansion of access to doxycycline upon recognition of plague outbreaks to cost-effectively prevent future large-scale plague outbreaks and highlights the importance of intervention timing.

Determine neighboring region spatial effect on dengue cases using ensemble ARIMA models

The state of Selangor, in Malaysia consist of urban and peri-urban centres with good transportation system, and suitable temperature levels with high precipitations and humidity which make the state ideal for high number of dengue cases, annually. This study investigates if districts within the Selangor state do influence each other in determining pattern of dengue cases. Study compares two different models; the Autoregressive Integrated Moving Average (ARIMA) and Ensemble ARIMA models, using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) measurement to gauge their performance tools. ARIMA model is developed using the epidemiological data of dengue cases, whereas ensemble ARIMA incorporates the neighbouring regions' dengue models as the exogenous variable (X), into traditional ARIMA model. Ensemble ARIMA models have better model fit compared to the basic ARIMA models by incorporating neighbuoring effects of seven districts which made of state of Selangor. The AIC and BIC values of ensemble ARIMA models to be smaller compared to traditional ARIMA counterpart models. Thus, study concludes that pattern of dengue cases for a district is subject to spatial effects of its neighbouring districts and number of dengue cases in the surrounding areas.

Probabilistic seasonal dengue forecasting in Vietnam: A modelling study using superensembles

BACKGROUND

With enough advanced notice, dengue outbreaks can be mitigated. As a climate-sensitive disease, environmental conditions and past patterns of dengue can be used to make predictions about future outbreak risk. These predictions improve public health planning and decision-making to ultimately reduce the burden of disease. Past approaches to dengue forecasting have used seasonal climate forecasts, but the predictive ability of a system using different lead times in a year-round prediction system has been seldom explored. Moreover, the transition from theoretical to operational systems integrated with disease control activities is rare.

METHODS AND FINDINGS

We introduce an operational seasonal dengue forecasting system for Vietnam where Earth observations, seasonal climate forecasts, and lagged dengue cases are used to drive a superensemble of probabilistic dengue models to predict dengue risk up to 6 months ahead. Bayesian spatiotemporal models were fit to 19 years (2002-2020) of dengue data at the province level across Vietnam. A superensemble of these models then makes probabilistic predictions of dengue incidence at various future time points aligned with key Vietnamese decision and planning deadlines. We demonstrate that the superensemble generates more accurate predictions of dengue incidence than the individual models it incorporates across a suite of time horizons and transmission settings. Using historical data, the superensemble made slightly more accurate predictions (continuous rank probability score [CRPS] = 66.8, 95% CI 60.6-148.0) than a baseline model which forecasts the same incidence rate every month (CRPS = 79.4, 95% CI 78.5-80.5) at lead times of 1 to 3 months, albeit with larger uncertainty. The outbreak detection capability of the superensemble was considerably larger (69%) than that of the baseline model (54.5%). Predictions were most accurate in southern Vietnam, an area that experiences semi-regular seasonal dengue transmission. The system also demonstrated added value across multiple areas compared to previous practice of not using a forecast. We use the system to make a prospective prediction for dengue incidence in Vietnam for the period May to October 2020. Prospective predictions made with the superensemble were slightly more accurate (CRPS = 110, 95% CI 102-575) than those made with the baseline model (CRPS = 125, 95% CI 120-168) but had larger uncertainty. Finally, we propose a framework for the evaluation of probabilistic predictions. Despite the demonstrated value of our forecasting system, the approach is limited by the consistency of the dengue case data, as well as the lack of publicly available, continuous, and long-term data sets on mosquito control efforts and serotype-specific case data.

CONCLUSIONS

This study shows that by combining detailed Earth observation data, seasonal climate forecasts, and state-of-the-art models, dengue outbreaks can be predicted across a broad range of settings, with enough lead time to meaningfully inform dengue control. While our system omits some important variables not currently available at a subnational scale, the majority of past outbreaks could be predicted up to 3 months ahead. Over the next 2 years, the system will be prospectively evaluated and, if successful, potentially extended to other areas and other climate-sensitive disease systems.

Analysis of COVID-19 Cases' Spatial Dependence in US Counties Reveals Health Inequalities

On March 13, 2020, the World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) caused by the novel coronavirus SARS-CoV2 a pandemic. Since then the virus has infected over 9.1 million individuals and resulted in over 470,000 deaths worldwide (as of June 24, 2020). Here, we discuss the spatial correlation between county population health rankings and the incidence of COVID-19 cases and COVID-19 related deaths in the United States. We analyzed the spread of the disease based on multiple variables at the county level, using publicly available data on the numbers of confirmed cases and deaths, intensive care unit beds and socio-demographic, and healthcare resources in the U.S. Our results indicate substantial geographical variations in the distribution of COVID-19 cases and deaths across the US counties. There was significant positive global spatial correlation between the percentage of Black Americans and cases of COVID-19 (Moran I = 0.174 and 0.264, p < 0.0001). A similar result was found for the global spatial correlation between the percentage of Black American and deaths due to COVID-19 at the county level in the U.S. (Moran I = 0.264, p < 0.0001). There was no significant spatial correlation between the Hispanic population and COVID-19 cases and deaths; however, a higher percentage of non-Hispanic white was significantly negatively spatially correlated with cases (Moran I = -0.203, p < 0.0001) and deaths (Moran I = -0.137, p < 0.0001) from the disease. This study showed significant but weak spatial autocorrelation between the number of intensive care unit beds and COVID-19 cases (Moran I = 0.08, p < 0.0001) and deaths (Moran I = 0.15, p < 0.0001), respectively. These findings provide more detail into the interplay between the infectious disease and healthcare-related characteristics of the population. Only by understanding these relationships will it be possible to mitigate the rate of spread and severity of the disease.

Impact of sars-cov-2 interventions on dengue transmission

An estimated 105 million dengue infections occur per year across 120 countries, where traditional vector control is the primary control strategy to reduce contact between mosquito vectors and people. The ongoing sars-cov-2 pandemic has resulted in dramatic reductions in human mobility due to social distancing measures; the effects on vector-borne illnesses are not known. Here we examine the pre and post differences of dengue case counts in Malaysia, Singapore and Thailand, and estimate the effects of social distancing as a treatment effect whilst adjusting for temporal confounders. We found that social distancing is expected to lead to 4.32 additional cases per 100,000 individuals in Thailand per month, which equates to 170 more cases per month in the Bangkok province (95% CI: 100-242) and 2008 cases in the country as a whole (95% CI: 1170-2846). Social distancing policy estimates for Thailand were also found to be robust to model misspecification, and variable addition and omission. Conversely, no significant impact on dengue transmission was found in Singapore or Malaysia. Across country disparities in social distancing policy effects on reported dengue cases are reasoned to be driven by differences in workplace-residence structure, with an increase in transmission risk of arboviruses from social distancing primarily through heightened exposure to vectors in elevated time spent at residences, demonstrating the need to understand the effects of location on dengue transmission risk under novel population mixing conditions such as those under social distancing policies.

Time-series modelling of dengue incidence in the Mekong Delta region of Viet Nam using remote sensing data

Objective

This study aims to enhance the capacity of dengue prediction by investigating the relationship of dengue incidence with climate and environmental factors in the Mekong Delta region (MDR) of Viet Nam by using remote sensing data.

Methods

To produce monthly data sets for each province, we extracted and aggregated precipitation data from the Global Satellite Mapping of Precipitation project and land surface temperatures and normalized difference vegetation indexes from the Moderate Resolution Imaging Spectroradiometer satellite observations. Monthly data sets from 2000 to 2016 were used to construct autoregressive integrated moving average (ARIMA) models to predict dengue incidence for 12 provinces across the study region.

Results

The final models were able to predict dengue incidence from January to December 2016 that concurred with the observation that dengue epidemics occur mostly in rainy seasons. As a result, the obtained model presents a good fit at a regional level with the correlation value of 0.65 between predicted and reported dengue cases; nevertheless, its performance declines at the subregional scale.

Conclusion

We demonstrated the use of remote sensing data in time-series to develop a model of dengue incidence in the MDR of Viet Nam. Results indicated that this approach could be an effective method to predict regional dengue incidence and its trends.

Assessing and modelling vulnerability to dengue in the Mekong Delta of Vietnam by geospatial and time-series approaches

Dengue fever has continuously been a disease burden in Vietnam during the last 20 years, particularly in the Mekong Delta region (MDR), which is one of the most vulnerable to climate change. Variations in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue. This study focuses on assessing dengue risk via the vulnerability concept, which is composed of exposure and susceptibility using a combined approach of mapping and modelling for the MDR of Vietnam during the period between 2001 and 2016. Multisource remote sensing data from Global Satellite Mapping of Precipitation (GSMaP) and Moderate Resolution Imaging Spectrophotometer (MODIS) was used for presenting climate and environment variables in mapping and modelling vulnerability. Monthly and yearly maps of vulnerability to dengue in the MDR, produced for 15-year period, aided analysis of the temporal and spatial patterns of vulnerability to dengue in the study region and were used for constructing time-series modelling of vulnerability for the following year. The results showed that there is a clear seasonal variation in the vulnerability due to variability of the climate factor and its strong dispersion across the study region, with higher vulnerability in the scattered areas of urban and mixed horticulture land and lower vulnerability in areas covered by forest and bare soil lands. The Pearson's correlation was applied to evaluate the association between dengue rates and vulnerability values aggregated at the provincial level. Reasonable linear association, with correlation coefficients of 0.41-0.63, was found in two-thirds of the provinces. The predicted vulnerabilities to dengue during 2016 were comparable with the estimated values and trends for most provinces of the MDR. Our demonstrated approach with integrated geospatial data seems to be a promising tool in supporting the public health sector in assessing potential space and time of a subsequent increase in vulnerability to dengue, particularly in the context of climate change.

Implementation of geographical information systems for the study of diseases caused by vector-borne arboviruses in Southeast Asia: A review based on the publication record

The spread of mosquito-borne diseases in Southeast Asia has dramatically increased in the latest decades. These infections include dengue, chikungunya and Japanese Encephalitis (JE), high-burden viruses sharing overlapping disease manifestation and vector distribution. The use of Geographical Information Systems (GIS) to monitor the dynamics of disease and vector distribution can assist in disease epidemic prediction and public health interventions, particularly in Southeast Asia where sustained high temperatures drive the epidemic spread of these mosquito-borne viruses. Due to lack of accurate data, the spatial and temporal dynamics of these mosquito-borne viral disease transmission countries are poorly understood, which has limited disease control effort. By following studies carried out on these three viruses across the region in a specific time period revealing general patterns of research activities and characteristics, this review finds the need to improve decision-support by disease mapping and management. The results presented, based on a publication search with respect to diseases due to arboviruses, specifically dengue, chikungunya and Japanese encephalitis, should improve opportunities for future studies on the implementation of GIS in the control of mosquito-borne viral diseases in Southeast Asia.

Spatiotemporal and Socioeconomic Risk Factors for Dengue at the Province Level in Vietnam, 2013-2015: Clustering Analysis and Regression Model

Dengue is a serious infectious disease threat in Vietnam, but its spatiotemporal and socioeconomic risk factors are not currently well understood at the province level across the country and on a multiannual scale. We explore spatial trends, clusters and outliers in dengue case counts at the province level from 2011–2015 and use this to extract spatiotemporal variables for regression analysis of the association between dengue case counts and selected spatiotemporal and socioeconomic variables from 2013–2015. Dengue in Vietnam follows anticipated spatial trends, with a potential two-year cycle of high-high clusters in some southern provinces. Small but significant associations are observed between dengue case counts and mobility, population density, a province’s dengue rates the previous year, and average dengue rates two years previous in first and second order contiguous neighbours. Significant associations were not found between dengue case counts and housing pressure, access to electricity, clinician density, province-adjusted poverty rate, percentage of children below one vaccinated, or percentage of population in urban settings. These findings challenge assumptions about socioeconomic and spatiotemporal risk factors for dengue, and support national prevention targeting in Vietnam at the province level. They may also be of wider relevance for the study of other arboviruses, including Japanese encephalitis, Zika, and Chikungunya.

Impact of Climate Variability and Abundance of Mosquitoes on Dengue Transmission in Central Vietnam

Dengue fever is an important arboviral disease in many countries. Its incidence has increased during the last decade in central Vietnam. Most dengue studies in Vietnam focused on the northern area (Hanoi) and southern regions but not on central Vietnam. Dengue transmission dynamics and relevant environmental risk factors in central Vietnam are not understood. This study aimed to evaluate spatiotemporal patterns of dengue fever in central Vietnam and effects of climatic factors and abundance of mosquitoes on its transmission. Dengue and mosquito surveillance data were obtained from the Department of Vector Control and Border Quarantine at Nha Trang Pasteur Institute. Geographic Information System and satellite remote sensing techniques were used to perform spatiotemporal analyses and to develop climate models using generalized additive models. During 2005-2018, 230,458 dengue cases were reported in central Vietnam. Da Nang and Khanh Hoa were two major hotspots in the study area. The final models indicated the important role of Indian Ocean Dipole, multivariate El Niño-Southern Oscillation index, and vector index in dengue transmission in both regions. Regional climatic variables and mosquito population may drive dengue transmission in central Vietnam. These findings provide important information for developing an early dengue warning system in central Vietnam.

RC, Perkins TA. Optimizing the deployment of ultra-low volume and targeted indoor residual spraying for dengue outbreak response

Recent years have seen rising incidence of dengue and large outbreaks of Zika and chikungunya, which are all caused by viruses transmitted by Aedes aegypti mosquitoes. In most settings, the primary intervention against Aedes-transmitted viruses is vector control, such as indoor, ultra-low volume (ULV) spraying. Targeted indoor residual spraying (TIRS) has the potential to more effectively impact Aedes-borne diseases, but its implementation requires careful planning and evaluation. The optimal time to deploy these interventions and their relative epidemiological effects are, however, not well understood. We used an agent-based model of dengue virus transmission calibrated to data from Iquitos, Peru to assess the epidemiological effects of these interventions under differing strategies for deploying them. Specifically, we compared strategies where spray application was initiated when incidence rose above a threshold based on incidence in recent years to strategies where spraying occurred at the same time(s) each year. In the absence of spraying, the model predicted 361,000 infections [inter-quartile range (IQR): 347,000-383,000] in the period 2000-2010. The ULV strategy with the fewest median infections was spraying twice yearly, in March and October, which led to a median of 172,000 infections [IQR: 158,000-183,000], a 52% reduction from baseline. Compared to spraying once yearly in September, the best threshold-based strategy utilizing ULV had fewer median infections (254,000 vs. 261,000), but required more spraying (351 vs. 274 days). For TIRS, the best strategy was threshold-based, which led to the fewest infections of all strategies tested (9,900; [IQR: 8,720-11,400], a 94% reduction), and required fewer days spraying than the equivalent ULV strategy (280). Although spraying twice each year is likely to avert the most infections, our results indicate that a threshold-based strategy can become an alternative to better balance the translation of spraying effort into impact, particularly if used with a residual insecticide.

Long-term persistence of monotypic dengue transmission in small size isolated populations, French Polynesia, 1978-2014

Understanding the transition of epidemic to endemic dengue transmission remains a challenge in regions where serotypes co-circulate and there is extensive human mobility. French Polynesia, an isolated group of 117 islands of which 72 are inhabited, distributed among five geographically separated subdivisions, has recorded mono-serotype epidemics since 1944, with long inter-epidemic periods of circulation. Laboratory confirmed cases have been recorded since 1978, enabling exploration of dengue epidemiology under monotypic conditions in an isolated, spatially structured geographical location. A database was constructed of confirmed dengue cases, geolocated to island for a 35-year period. Statistical analyses of viral establishment, persistence and fade-out as well as synchrony among subdivisions were performed. Seven monotypic and one heterotypic dengue epidemic occurred, followed by low-level viral circulation with a recrudescent epidemic occurring on one occasion. Incidence was asynchronous among the subdivisions. Complete viral die-out occurred on several occasions with invasion of a new serotype. Competitive serotype replacement has been observed previously and seems to be characteristic of the South Pacific. Island population size had a strong impact on the establishment, persistence and fade-out of dengue cases and endemicity was estimated achievable only at a population size in excess of 175 000. Despite island remoteness and low population size, dengue cases were observed somewhere in French Polynesia almost constantly, in part due to the spatial structuration generating asynchrony among subdivisions. Long-term persistence of dengue virus in this group of island populations may be enabled by island hopping, although could equally be explained by a reservoir of sub-clinical infections on the most populated island, Tahiti.

Dengue virus is the most significant arthropod-borne virus infecting man. Understanding how long dengue virus can persist in populations of varying size is key to understanding its epidemiology. This is, however, impossible to achieve in settings where dengue is endemic, because of continued human movement and is further complexified by the occurrence of several co-circulating serotypes. By contrast, French Polynesia, an isolated group of 72 inhabited islands in the South Pacific, has had intermittent majoritarily monotypic dengue epidemics since the 1940s and offers a unique opportunity to address questions of viral persistence, turnover and the importance of spatial sub-structure in determining dengue epidemiology. Collating and analyzing a database of laboratory-confirmed dengue cases from across French Polynesia over a 35 year period we were able to show that dengue virus die-out can occur with or without replacement by a new serotype, monotypic transmission of dengue viruses fails to be maintained within small island populations but can persist for years among isolated islands connected via air and sea links. This remarkable long-term persistence of dengue virus in French Polynesia could be maintained by asynchronous viral transmission among connected islands and/or by repeated seeding from a reservoir of sub-clinical infections in the most populated island, Tahiti.

Whole genome sequencing and genetic variations in several dengue virus type 1 strains from unusual dengue epidemic of 2017 in Vietnam

Background

Dengue hemorrhagic fever is an acute viral infection transmitted by mosquitoes. In the 2017, a dengue epidemic occurred in Hanoi in a short time interval and many cases were serious with associated mortality. This was the largest and unusual dengue fever outbreak in the North of Vietnam over the past 20 years. The objective of the present study was to understand the genetic characteristics of the DENV-1 strain in the 2017 epidemic and its relationship with previous viruses in Vietnam and the rest of the world.

Methods

Complete genomes of 72 DENV-1 from patients in the 2017 epidemic were sequenced using NGS. The full genome sequences were then analyzed to find out the genetic variants in the groups of 72 strains, followed by their comparison with other strains that caused disease in Vietnam previously and several other regions of the world, revealing a genetic relationship between them.

Results

The complete genome sequence of 72 DENV-1 strains comprised 10,697 nucleotides with an open reading frame coding for 3392 amino acids. The genomic analysis revealed different amino acid substitutions in all genes, especially varying at position S75 (Capsid), M125 (PrM), D54 (E), T147, V180 (NS1), G45, Y126, I154 (NS2A), A94 (NS2B), M298 (NS3), K47, V68 (NS4A), I29 (NS4B), and R166, E536, G614, T821 (NS5). The genetic analysis suggested that the viruses were most closely related to the causative virus of the dengue outbreak in Vietnam and Cambodia from 2006 to 2008. These results indicated that DENV-1 from the dengue epidemic 2017 in Northern Vietnam originated from the virus that caused the dengue outbreak during the 2007 to 2008 period in Vietnam.

Conclusion

The present study is the first of its kind to describe complete genome sequence as well as genetic variants and phylogenetic analysis of DENV-1 associated with the unusual dengue epidemic of 2017 in northern Vietnam. These results provide detailed evidence to elucidate the origin, circulation, and genetic evolution of DENV in Vietnam.

Dengue in northeastern Brazil: a spatial and temporal perspective

INTRODUCTION:

The state of Ceará (Brazilian Northeast) has a high incidence of dengue. Therefore, we aimed to characterize the temporal patterns and spatial distribution of dengue cases in Ceará during 2001-2019.

METHODS:

A spatiotemporal ecological study was performed with secondary data. Time-trend analysis was performed using a segmented log-linear regression model to estimate the average annual percentage change (AAPC) and the annual percentage change (APC) in incidence of dengue. We also performed spatiotemporal analysis to identify the place, time, and relative risk (RR) of dengue clusters.

RESULTS:

There were 539,653 dengue cases. The AAPC reduced over time (-9.5%; 95% confidance interval [CI]: -18.3; -0.3). Three trends were identified-2001-2004: APC=-20.9% (95% CI: -65.1 to 44.8), 2005-2015: APC=7.9% (95% CI: -6.0 to 98.9), and 2016-2019: APC=-48.8% (95% CI: -83.0 to -6.1). During 2001-2007, 10 significant clusters were identified (RR=3.57-14.38: n=4 and RR=0.05-0.39: n=6). During 2008-2013, there was 1 cluster in the western region (RR= 3.40) and four other clusters (RR=0.02-0.15). The last period presented 5 high-RR clusters (RR=2.95-9.24). The low-RR clusters were located in the central-north, central-south, south, and northwest regions. However, the central-west region remained a high-RR cluster region throughout the study period.

CONCLUSIONS:

Dengue showed a decreasing incidence. During the epidemic years, the southern, eastern, and western regions presented high-risk clusters. Introduction of a new dengue serotype in a low-RR area can cause explosive outbreaks due to population susceptibility.

Baseline Characterization of Dengue Epidemiology in Yogyakarta City, Indonesia, before a Randomized Controlled Trial of Wolbachia for Arboviral Disease Control

Dengue is endemic in Indonesia. Here, we describe the epidemiology of dengue in the city of Yogyakarta, Central Java, as a prelude to implementation of a cluster-randomized trial of Wolbachia for the biocontrol of arboviral transmission. Surveillance records from 2006 to 2016 demonstrate seasonal oscillations of dengue incidence with varying magnitude. Two lines of evidence demonstrate a high force of infection; the hospitalized case burden of patients diagnosed with dengue hemorrhagic fever or dengue shock syndrome over the last decade consisted predominantly of children/adolescents, and a serosurvey of 314 healthy children aged 1–10 years found 68% possessed dengue virus–neutralizing antibodies. Finally, a mobility survey indicated children aged 1–10 years, and particularly 1–5 year-olds, spent most of their daytime hours at home. These findings inform the design of clinical trials to measure the impact of novel vector control methods such as Wolbachia introgression into Aedes aegypti mosquitoes, by providing baseline data on disease incidence and identifying subpopulations for recruitment into prospective studies of dengue virus infection and disease. The mobility survey findings indicate that in cluster trials of interventions applied at the community level, young children can reasonably be expected to spend most of their exposure time, in epidemiological terms, within the treatment arm to which they were randomized.

Serological inference of past primary and secondary dengue infection: implications for vaccination

Owing to the finding that Dengvaxia^® (the only licensed dengue vaccine to date) increases the risk of severe illness among seronegative recipients, the World Health Organization has recommended screening individuals for their serostatus prior to vaccination. To decide whether and how to carry out screening, it is necessary to estimate the transmission intensity of dengue and to understand the performance of the screening method. In this study, we inferred the annual force of infection (FOI; a measurement of transmission intensity) of dengue virus in three locations in Vietnam: An Giang (FOI = 0.04 for the below 10 years age group and FOI = 0.20 for the above 10 years age group), Ho Chi Minh City (FOI = 0.12) and Quang Ngai (FOI = 0.05). In addition, we show that using a quantitative approach to immunoglobulin G (IgG) levels (measured by indirect enzyme-linked immunosorbent assays) can help to distinguish individuals with primary exposures (primary seropositive) from those with secondary exposures (secondary seropositive). We found that primary-seropositive individuals—the main targets of the vaccine—tend to have a lower IgG level, and, thus, they have a higher chance of being misclassified as seronegative than secondary-seropositive cases. However, screening performance can be improved by incorporating patient age and transmission intensity into the interpretation of IgG levels.

Stochastic and spatio-temporal analysis of the Middle East Respiratory Syndrome outbreak in South Korea, 2015

South Korea was free of the Middle East Respiratory Syndrome (MERS) until 2015. The MERS outbreak in South Korea during 2015 was the largest outbreak of the Coronavirus outside the Middle East. The major characteristic of this outbreak is inter- or intra-hospital transmission. This recent MERS outbreak in South Korea is examined and assessed in this paper. The main objectives of the study is to characterize the pattern of the MERS outbreak in South Korea based on a basic reproductive ratio, the probability of ultimate extinction of the disease, and the spatio-temporal proximity of occurrence between patients. The survival function method and stochastic branching process model are adapted to calculate the basic reproductive ratio and the probability of ultimate extinction of the disease. We further investigate the occurrence pattern of the outbreak using a spatio-temporal autocorrelation function.

Spatio-temporal dynamics of dengue in Brazil: Seasonal travelling waves and determinants of regional synchrony

Dengue continues to be the most important vector-borne viral disease globally and in Brazil, where more than 1.4 million cases and over 500 deaths were reported in 2016. Mosquito control programmes and other interventions have not stopped the alarming trend of increasingly large epidemics in the past few years. Here, we analyzed monthly dengue cases reported in Brazil between 2001 and 2016 to better characterise the key drivers of dengue epidemics. Spatio-temporal analysis revealed recurring travelling waves of disease occurrence. Using wavelet methods, we characterised the average seasonal pattern of dengue in Brazil, which starts in the western states of Acre and Rondônia, then travels eastward to the coast before reaching the northeast of the country. Only two states in the north of Brazil (Roraima and Amapá) did not follow the countrywide pattern and had inconsistent timing of dengue epidemics throughout the study period. We also explored epidemic synchrony and timing of annual dengue cycles in Brazilian regions. Using gravity style models combined with climate factors, we showed that both human mobility and vector ecology contribute to spatial patterns of dengue occurrence. This study offers a characterization of the spatial dynamics of dengue in Brazil and its drivers, which could inform intervention strategies against dengue and other arboviruses.

Comparison of stochastic and deterministic frameworks in dengue modelling

We perform estimations of compartment models for dengue transmission in rural Cambodia with increasing complexity regarding both model structure and the account for stochasticity. On the one hand, we successively account for three embedded sources of stochasticity: observation noise, demographic variability and environmental hazard. On the other hand, complexity in the model structure is increased by introducing vector-borne transmission, explicit asymptomatic infections and interacting virus serotypes. Using two sources of case data from dengue epidemics in Kampong Cham (Cambodia), models are estimated in the bayesian framework, with Markov Chain Monte Carlo and Particle Markov Chain Monte Carlo. We highlight the advantages and drawbacks of the different formulations in a practical setting. Although in this case the deterministic models provide a good approximation of the mean trajectory for a low computational cost, the stochastic frameworks better reflect and account for parameter and simulation uncertainty.

The Estimates of the Health and Economic Burden of Dengue in Vietnam

Dengue has been estimated to cause a substantial health and economic burden in Vietnam. The most recent studies have estimated that it is responsible for 39884 disability-adjusted life years (DALYs) annually, representing an economic burden of US$94.87 million per year (in 2016 prices). However, there are alternative burden estimates that are notably lower. This variation is predominantly due to differences in how the number of symptomatic dengue cases is estimated. Understanding the methodology of these burden calculations is vital when interpreting health economic analyses of dengue. This review aims to provide an overview of the health and economic burden estimates of dengue in Vietnam. We also highlight important research gaps for future studies.

Hendra Virus Spillover is a Bimodal System Driven by Climatic Factors

Understanding environmental factors driving spatiotemporal patterns of disease can improve risk mitigation strategies. Hendra virus (HeV), discovered in Australia in 1994, spills over from bats (Pteropus sp.) to horses and thence to humans. Below latitude - 22°, almost all spillover events to horses occur during winter, and above this latitude spillover is aseasonal. We generated a statistical model of environmental drivers of HeV spillover per month. The model reproduced the spatiotemporal pattern of spillover risk between 1994 and 2015. The model was generated with an ensemble of methods for presence-absence data (boosted regression trees, random forests and logistic regression). Presences were the locations of horse cases, and absences per spatial unit (2.7 × 2.7 km pixels without spillover) were sampled with the horse census of Queensland and New South Wales. The most influential factors indicate that spillover is associated with both cold-dry and wet conditions. Bimodal responses to several variables suggest spillover involves two systems: one above and one below a latitudinal area close to - 22°. Northern spillovers are associated with cold-dry and wet conditions, and southern with cold-dry conditions. Biologically, these patterns could be driven by immune or behavioural changes in response to food shortage in bats and horse husbandry. Future research should look for differences in these traits between seasons in the two latitudinal regions. Based on the predicted risk patterns by latitude, we recommend enhanced preventive management for horses from March to November below latitude 22° south.

Cluster-Randomized Test-Negative Design Trials: A Novel and Efficient Method to Assess the Efficacy of Community-Level Dengue Interventions

Cluster-randomized controlled trials are the gold standard for assessing efficacy of community-level interventions, such as vector-control strategies against dengue. We describe a novel cluster-randomized trial methodology with a test-negative design (CR-TND), which offers advantages over traditional approaches. This method uses outcome-based sampling of patients presenting with a syndrome consistent with the disease of interest, who are subsequently classified as test-positive cases or test-negative controls on the basis of diagnostic testing. We used simulations of a cluster trial to demonstrate validity of efficacy estimates under the test-negative approach. We demonstrated that, provided study arms are balanced for both test-negative and test-positive illness at baseline and that other test-negative design assumptions are met, the efficacy estimates closely match true efficacy. Analytical considerations for an odds ratio-based effect estimate arising from clustered data and potential approaches to analysis are also discussed briefly. We concluded that application of the test-negative design to certain cluster-randomized trials could increase their efficiency and ease of implementation.

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.

Mosquito-borne transmission in urban landscapes: the missing link between vector abundance and human density

With escalating urbanization, the environmental, demographic, and socio-economic heterogeneity of urban landscapes poses a challenge to mathematical models for the transmission of vector-borne infections. Classical coupled vector–human models typically assume that mosquito abundance is either independent from, or proportional to, human population density, implying a decreasing force of infection, or per capita infection rate with host number. We question these assumptions by introducing an explicit dependence between host and vector densities through different recruitment functions, whose dynamical consequences we examine in a modified model formulation. Contrasting patterns in the force of infection are demonstrated, including in particular increasing trends when recruitment grows sufficiently fast with human density. Interaction of these patterns with seasonality in temperature can give rise to pronounced differences in timing, relative peak sizes, and duration of epidemics. These proposed dependencies explain empirical dengue risk patterns observed in the city of Delhi where socio-economic status has an impact on both human and mosquito densities. These observed risk trends with host density are inconsistent with current standard models. A better understanding of the connection between vector recruitment and host density is needed to address the population dynamics of mosquito-transmitted infections in urban landscapes.

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.

ENSO-driven climate variability promotes periodic major outbreaks of dengue in Venezuela

Dengue is a mosquito-borne viral disease of global impact. In Venezuela, dengue has emerged as one of the most important public health problems of urban areas with frequent epidemics since 2001. The long-term pattern of this disease has involved not only a general upward trend in cases but also a dramatic increase in the size and frequency of epidemic outbreaks. By assuming that climate variability has a relevant influence on these changes in time, we quantified the periodicity of dengue incidence in time-series of data from two northern regions of Venezuela. Disease cycles of 1 and 3-4 years (p < 0.05) were detected. We determined that dengue cycles corresponded with local climate and the El Niño Southern Oscillation (ENSO) variation at both seasonal and inter-annual scales (every 2-3 years). Dengue incidence peaks were more prevalent during the warmer and dryer years of El Niño confirming that ENSO is a regional climatic driver of such long-term periodicity through local changes in temperature and rainfall. Our findings support the evidence of the effect of climate on dengue dynamics and advocate the incorporation of climate information in the surveillance and prediction of this arboviral disease in Venezuela.

Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan

The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover.

Evidence of previous but not current transmission of chikungunya virus in southern and central Vietnam: Results from a systematic review and a seroprevalence study in four locations

BACKGROUND

Arbovirus infections are a serious concern in tropical countries due to their high levels of transmission and morbidity. With the outbreaks of chikungunya (CHIKV) in surrounding regions in recent years and the fact that the environment in Vietnam is suitable for the vectors of CHIKV, the possibility of transmission of CHIKV in Vietnam is of great interest. However, information about CHIKV activity in Vietnam remains limited.

METHODOLOGY

In order to address this question, we performed a systematic review of CHIKV in Vietnam and a CHIKV seroprevalence survey. The seroprevalence survey tested for CHIKV IgG in population serum samples from individuals of all ages in 2015 from four locations in Vietnam.

PRINCIPAL FINDINGS

The four locations were An Giang province (n = 137), Ho Chi Minh City (n = 136), Dak Lak province (n = 137), and Hue City (n = 136). The findings give us evidence of some CHIKV activity: 73/546 of overall samples were seropositive (13.4%). The age-adjusted seroprevalences were 12.30% (6.58-18.02), 13.42% (7.16-19.68), 7.97% (3.56-12.38), and 3.72% (1.75-5.69) in An Giang province, Ho Chi Minh City, Dak Lak province, and Hue City respectively. However, the age-stratified seroprevalence suggests that the last transmission ended around 30 years ago, consistent with results from the systematic review. We see no evidence for on-going transmission in three of the locations, though with some evidence of recent exposure in Dak Lak, most likely due to transmission in neighbouring countries. Before the 1980s, when transmission was occurring, we estimate on average 2-4% of the population were infected each year in HCMC and An Giang and Hue (though transmision ended earlier in Hue). We estimate lower transmission in Dak Lak, with around 1% of the population infected each year.

CONCLUSION

In conclusion, we find evidence of past CHIKV transmission in central and southern Vietnam, but no evidence of recent sustained transmission. When transmission of CHIKV did occur, it appeared to be widespread and affect a geographically diverse population. The estimated susceptibility of the population to chikungunya is continually increasing, therefore the possibility of future CHIKV transmission in Vietnam remains.

Epidemiological, Serological, and Virological Features of Dengue in Nha Trang City, Vietnam

Vietnam is endemic for dengue. We conducted a series of retrospective and prospective studies to characterize the epidemiology of dengue and population mobility patterns in Nha Trang city, Vietnam, with a view to rational design of trials of community-level interventions. A 10-year time series of dengue case notifications showed pronounced interannual variability, as well as spatial heterogeneity in ward-level dengue incidence (median annual coefficient of variation k = 0.47). Of 451 children aged 1-10 years enrolled in a cross-sectional serosurvey, almost one-third had evidence of a past dengue virus (DENV) infection, with older children more likely to have a multitypic response indicative of past exposure to ≥ 1 serotype. All four DENV serotypes were detected in hospitalized patients during 8 months of sampling in 2015. Mobility data collected from 1,000 children and young adults via prospective travel diaries showed that, although all ages spent approximately half of their daytime hours (5:00 am-9:00 pm) at home, younger age groups (≤ 14 years) spent a significantly greater proportion of their time within 500 m of home than older respondents. Together these findings inform the rational design of future trials of dengue preventive interventions in this setting by identifying 1) children < 7 years as an optimal target group for a flavivirus-naive serological cohort, 2) children and young adults as the predominant patient population for a study with a clinical end point of symptomatic dengue, and 3) substantial spatial and temporal variations in DENV transmission, with a consequent requirement for a trial to be large enough and of long enough duration to overcome this heterogeneity.

Spatial and temporal patterns of dengue infections in Timor-Leste, 2005-2013

Background

Dengue remains an important public health problem in Timor-Leste, with several major epidemics occurring over the last 10 years. The aim of this study was to identify dengue clusters at high geographical resolution and to determine the association between local environmental characteristics and the distribution and transmission of the disease.

Methods

Notifications of dengue cases that occurred from January 2005 to December 2013 were obtained from the Ministry of Health, Timor-Leste. The population of each suco (the third-level administrative subdivision) was obtained from the Population and Housing Census 2010. Spatial autocorrelation in dengue incidence was explored using Moran’s I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate, Zero-Inflated, Poisson (ZIP) regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling.

Results

The analysis used data from 3206 cases. Dengue incidence was highly seasonal with a large peak in January. Patients ≥ 14 years were found to be 74% [95% credible interval (CrI): 72–76%] less likely to be infected than those < 14 years, and females were 12% (95% CrI: 4–21%) more likely to suffer from dengue as compared to males. Dengue incidence increased by 0.7% (95% CrI: 0.6–0.8%) for a 1 °C increase in mean temperature; and 47% (95% CrI: 29–59%) for a 1 mm increase in precipitation. There was no significant residual spatial clustering after accounting for climate and demographic variables.

Conclusions

Dengue incidence was highly seasonal and spatially clustered, with positive associations with temperature, precipitation and demographic factors. These factors explained the observed spatial heterogeneity of infection.

Electronic supplementary material

The online version of this article (10.1186/s13071-017-2588-4) contains supplementary material, which is available to authorized users.

Direct Medical Costs of Dengue Fever in Vietnam: A Retrospective Study in a Tertiary Hospital

BACKGROUND

In Vietnam, dengue fever is a major health concern, yet comprehensive information on its economic costs is lacking. The present study investigated treatment costs associated with dengue fever from the perspective of health care provision.

METHODS

This retrospective study was conducted between January 2013 and December 2015 in Cu Chi General Hospital. The following dengue-related treatment costs were calculated: hospitalisation, diagnosis, specialised services, drug usage and medical supplies. Average cost per case and treatment cost across different age was calculated.

RESULTS

In the study period, 1672 patients with dengue fever were hospitalised. The average age was 24.98 (SD = 14.10) years, and 47.5% were males (795 patients). Across age groups, the average cost per episode was USD 48.10 (SD = 3.22). The highest costs (USD 56.61, SD = 48.84) were incurred in the adult age group (> 15 years), and the lowest costs (USD 30.10, SD = 17.27) were incurred in the paediatric age group (< 15 years).

CONCLUSION

The direct medical costs of dengue-related hospitalisation place a severe economic burden on patients and their families. The probable economic value of dengue management in Vietnam is significant.

An ecological and digital epidemiology analysis on the role of human behavior on the 2014 Chikungunya outbreak in Martinique

Understanding the spatio-temporal dynamics of endemic infections is of critical importance for a deeper understanding of pathogen transmission, and for the design of more efficient public health strategies. However, very few studies in this domain have focused on emerging infections, generating a gap of knowledge that hampers epidemiological response planning. Here, we analyze the case of a Chikungunya outbreak that occurred in Martinique in 2014. Using time series estimates from a network of sentinel practitioners covering the entire island, we first analyze the spatio-temporal dynamics and show that the largest city has served as the epicenter of this epidemic. We further show that the epidemic spread from there through two different propagation waves moving northwards and southwards, probably by individuals moving along the road network. We then develop a mathematical model to explore the drivers of the temporal dynamics of this mosquito-borne virus. Finally, we show that human behavior, inferred by a textual analysis of messages published on the social network Twitter, is required to explain the epidemiological dynamics over time. Overall, our results suggest that human behavior has been a key component of the outbreak propagation, and we argue that such results can lead to more efficient public health strategies specifically targeting the propagation process.

Identification of sympatric cryptic species of Aedes albopictus subgroup in Vietnam: new perspectives in phylosymbiosis of insect vector

Background

The Aedes (Stegomyia) albopictus subgroup includes 11 cryptic species of which Ae. albopictus is the most widely distributed. Its global expansion associated with a documented vector competence for several emerging arboviruses raise obvious concerns in the recently colonized regions. While several studies have provided important insights regarding medical importance of Ae. albopicus, the investigations of the other sibling species are scarce. In Asia, indigenous populations within the Ae. albopictus subgroup can be found in sympatry. In the present study, we aimed to describe and compare molecular, morphological and bacterial symbionts composition among sympatric individuals from the Ae. albopictus subgroup inhabiting a Vietnamese protected area.

Results

Based on morphological structure of the cibarial armarture, we identified a cryptic species in the forest park at Bù Gia Mập in the south-eastern region of Vietnam. Analysis of nuclear (ITS1-5.8S-ITS2) and mitochondrial (cox1, nad5) markers confirmed the divergence between the cryptic species and Ae. albopictus. Analysis of midgut bacterial microbiota revealed a strong similarity among the two species with a notable difference; contrary to Ae. albopictus, the cryptic species did not harbour any Wolbachia infection.

Conclusions

These results could reflect either a recent invasion of Wolbachia in Ae. albopictus or alternatively a loss of this symbiont in the cryptic species. We argue that neglected species of the Ae. albopictus subgroup are of main importance in order to estimate variation of host-symbionts interactions across evolution.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-017-2202-9) contains supplementary material, which is available to authorized users.

Changing paradigms in Aedes control: considering the spatial heterogeneity of dengue transmission

Current dengue vector control strategies, focusing on reactive implementation of insecticide-based interventions in response to clinically apparent disease manifestations, tend to be inefficient, short-lived, and unsustainable within the worldwide epidemiological scenario of virus epidemic recrudescence. As a result of a series of expert meetings and deliberations, a paradigm shift is occurring and a new strategy, using risk stratification at the city level in order to concentrate proactive, sustained efforts in areas at high risk for transmission, has emerged. In this article, the authors 1) outline this targeted, proactive intervention strategy, within the context of dengue epidemiology, the dynamics of its transmission, and current Aedes control strategies, and 2) provide support from published literature for the need to empirically test its impact on dengue transmission as well as on the size of disease outbreaks. As chikungunya and Zika viruses continue to expand their range, the need for a science-based, proactive approach for control of urban Aedes spp. mosquitoes will become a central focus of integrated disease management planning.

Synchrony of Dengue Incidence in Ho Chi Minh City and Bangkok

Background

Ho Chi Minh City and Bangkok are highly dengue endemic. The extent to which disease patterns are attributable to local versus regional dynamics remains unclear. To address this gap we compared key transmission parameters across the locations.

Methods and Principal Findings

We used 2003–2009 age-stratified case data to inform catalytic transmission models. Further, we compared the spatial clustering of serotypes within each city. We found that annual case numbers were highly consistent across the two cities (correlation of 0.77, 95% CI: 0.74–0.79) as was the annual force of infection (correlation of 0.57, 95% CI: 0.46–0.68). Serotypes were less similar with serotype-specific correlations ranging from 0.65 for DENV1 to -0.14 for DENV4. Significant spatial clustering of serotypes was observed in HCMC at distances <500m, similar to previous observations from Bangkok.

Discussions

Dengue dynamics are comparable across these two hubs. Low correlation in serotype distribution suggests that similar built environments, vector populations and climate, rather than viral flow drives these observations.

All four serotypes of dengue have circulated endemically throughout Southeast Asia for decades. However, despite the enormous burden of disease, there remains poor understanding of the similarity in disease patterns across the region. We analyzed data from over 100,000 cases of dengue from two of the largest cities in the region, Bangkok and Ho Chi Minh City between 2001 and 2009. We use basic statistical methods to reconstruct the annual probability of infection in the two cities during this time period using methods that are robust to differences in reporting mechanisms. We find that both the epidemic curves and annual probabilities of infection were highly correlated across the cities, however, serotype-specific correlations were far more variable. Finally, we used geocoded case homes from Ho Chi Minh to demonstrate that cases in the city clustered at spatial scales (<500m) similar to that previously observed in Bangkok. These findings show that dengue dynamics are highly comparable across these two urban hubs; however, the low correlation in serotype distribution suggests that similar built environments and climate, rather than viral flow drives these observations.

Dengue Sentinel Traveler Surveillance: Monthly and Yearly Notification Trends among Japanese Travelers, 2006-2014

Background

Dengue is becoming an increasing threat to non-endemic countries. In Japan, the reported number of imported cases has been rising, and the first domestic dengue outbreak in nearly 70 years was confirmed in 2014, highlighting the need for greater situational awareness and better-informed risk assessment.

Methods

Using national disease surveillance data and publically available traveler statistics, we compared monthly and yearly trends in the destination country-specific dengue notification rate per 100,000 Japanese travelers with those of domestic dengue cases in the respective country visited during 2006–2014. Comparisons were made for countries accounting for the majority of importations; yearly comparisons were restricted to countries where respective national surveillance data were publicly available.

Results

There were 1007 imported Japanese dengue cases (Bali, Indonesia (n = 202), the Philippines (n = 230), Thailand (n = 160), and India (n = 152)). Consistent with historic local dengue seasonality, monthly notification rate among travelers peaked in August in Thailand, September in the Philippines, and in Bali during April with a smaller peak in August. While the number of travelers to Bali was greatest in August, the notification rate was highest in April. Annually, trends in the notification rate among travelers to the Philippines and Thailand also closely reflected local notification trends.

Conclusion

Travelers to dengue-endemic countries appear to serve as reliable “sentinels”, with the trends in estimated risk of dengue infection among Japanese travelers closely reflecting local dengue trends, both seasonally and annually. Sentinel traveler surveillance can contribute to evidence-based pretravel advice, and help inform risk assessments and decision-making for importation and potentially for subsequent secondary transmission. As our approach takes advantage of traveler data that are readily available as a proxy denominator, sentinel traveler surveillance can be a practical surveillance tool that other countries could consider for implementation.

With increasing globalization, the threat of dengue is rising in areas that were previously unaffected. Japan has been experiencing a rise in notifications of imported cases, and in 2014 confirmed the first domestic outbreak in nearly 70 years. Such events prompted the country to more actively utilize existing imported dengue case data among travelers to inform situational awareness, risk assessment, and evidence-based decision-making. Using both national disease surveillance data and publically available traveler statistics, we compared monthly and yearly trends between reported numbers of dengue cases among Japanese travelers and those of domestic dengue cases in the countries visited. By using the number of Japanese travelers to a dengue-endemic country as an approximate denominator, we estimated the risk of dengue infection among travelers to the country. This method is more appropriate than simply monitoring the number of reported imported cases because it accounts for fluctuating numbers of travelers, such as during vacation periods. This study demonstrated that the trends in dengue notifications among travelers were consistent with local dengue trends, both yearly and seasonally. Our simple approach, which takes advantage of existing data, may be readily adopted elsewhere to help inform risk of importation and potential subsequent domestic transmission.