Increasing Dengue Incidence in Singapore over the Past 40 Years: Population Growth,Climate and Mobility

In Singapore, the frequency and magnitude of dengue epidemics have increased significantly over the past 40 years. It is important to understand the main drivers for the rapid increase in dengue incidence. We studied the relative contributions of putative drivers for the rise of dengue in Singapore: population growth, climate parameters and international air passenger arrivals from dengue endemic countries, for the time period of 1974 until 2011. We used multivariable Poisson regression models with the following predictors: Annual Population Size; Aedes Premises Index; Mean Annual Temperature; Minimum and Maximum Temperature Recorded in each year; Annual Precipitation and Annual Number of Air Passengers arriving from dengue-endemic South-East Asia to Singapore. The relative risk (RR) of the increase in dengue incidence due to population growth over the study period was 42.7, while the climate variables (mean and minimum temperature) together explained an RR of 7.1 (RR defined as risk at the end of the time period relative to the beginning and goodness of fit associated with the model leading to these estimates assessed by pseudo-R2 equal to 0.83). Estimating the extent of the contribution of these individual factors on the increasing dengue incidence, we found that population growth contributed to 86% while the residual 14% was explained by increase in temperature. We found no correlation with incoming air passenger arrivals into Singapore from dengue endemic countries. Our findings have significant implications for predicting future trends of the dengue epidemics given the rapid urbanization with population growth in many dengue endemic countries. It is time for policy-makers and the scientific community alike to pay more attention to the negative impact of urbanization and urban climate on diseases such as dengue.     

The Effects of Weather and Climate Change on Dengue

Background

There is much uncertainty about the future impact of climate change on vector-borne diseases. Such uncertainty reflects the difficulties in modelling the complex interactions between disease, climatic and socioeconomic determinants. We used a comprehensive panel dataset from Mexico covering 23 years of province-specific dengue reports across nine climatic regions to estimate the impact of weather on dengue, accounting for the effects of non-climatic factors.

Methods and Findings

Using a Generalized Additive Model, we estimated statistically significant effects of weather and access to piped water on dengue. The effects of weather were highly nonlinear. Minimum temperature (Tmin) had almost no effect on dengue incidence below 5°C, but Tmin values above 18°C showed a rapidly increasing effect. Maximum temperature above 20°C also showed an increasing effect on dengue incidence with a peak around 32°C, after which the effect declined. There is also an increasing effect of precipitation as it rose to about 550 mm, beyond which such effect declines. Rising access to piped water was related to increasing dengue incidence. We used our model estimations to project the potential impact of climate change on dengue incidence under three emission scenarios by 2030, 2050, and 2080. An increase of up to 40% in dengue incidence by 2080 was estimated under climate change while holding the other driving factors constant.

Conclusions

Our results indicate that weather significantly influences dengue incidence in Mexico and that such relationships are highly nonlinear. These findings highlight the importance of using flexible model specifications when analysing weather–health interactions. Climate change may contribute to an increase in dengue incidence. Rising access to piped water may aggravate dengue incidence if it leads to increased domestic water storage. Climate change may therefore influence the success or failure of future efforts against dengue.     

An accurate mathematical model predicting number of dengue cases in tropics

Dengue fever is a systemic viral infection of epidemic proportions in tropical countries. The incidence of dengue fever is ever increasing and has doubled over the last few decades. Estimated 50million new cases are detected each year and close to 10000 deaths occur each year. Epidemics are unpredictable and unprecedented. When epidemics occur, health services are over whelmed leading to overcrowding of hospitals. At present there is no evidence that dengue epidemics can be predicted. Since the breeding of the dengue mosquito is directly influenced by environmental factors, it is plausible that epidemics could be predicted using weather data. We hypothesized that there is a mathematical relationship between incidence of dengue fever and environmental factors and if such relationship exists, new cases of dengue fever in the succeeding months can be predicted using weather data of the current month. We developed a mathematical model using machine learning technique. We used Island wide dengue epidemiology data, weather data and population density in developing the model. We used incidence of dengue fever, average rain fall, humidity, wind speed, temperature and population density of each district in the model. We found that the model is able to predict the incidence of dengue fever of a given month in a given district with precision (RMSE between 18- 35.3). Further, using weather data of a given month, the number of cases of dengue in succeeding months too can be predicted with precision (RMSE 10.4—30). Health authorities can use existing weather data in predicting epidemics in the immediate future and therefore measures to prevent new cases can be taken and more importantly the authorities can prepare local authorities for outbreaks.     

Epidemiology of Dengue Disease in Malaysia (2000–2012): A Systematic Literature Review

A literature survey and analysis was conducted to describe the epidemiology of dengue disease in Malaysia between 2000 and 2012. Published literature was searched for epidemiological studies of dengue disease, using specific search strategies for each electronic database; 237 relevant data sources were identified, 28 of which fulfilled the inclusion criteria. The epidemiology of dengue disease in Malaysia was characterized by a non-linear increase in the number of reported cases from 7,103 in 2000 to 46,171 in 2010, and a shift in the age range predominance from children toward adults. The overall increase in dengue disease was accompanied by a rise in the number, but not the proportion, of severe cases. The dominant circulating dengue virus serotypes changed continually over the decade and differed between states. Several gaps in epidemiological knowledge were identified; in particular, studies of regional differences, age-stratified seroprevalence, and hospital admissions.

Protocol registration

PROSPERO #CRD42012002293

Author summary

Dengue disease is a tropical and subtropical mosquito-borne viral illness, and is a major health concern in Malaysia. We conducted this literature analysis and review to describe the epidemiology of dengue disease in Malaysia between 2000 and 2012, to determine the impact of dengue disease on the Malaysian population, and to identify future research priorities. We used well-defined methods to search and identify relevant research, and data were selected according to predetermined inclusion criteria. This long-term review highlights the changing epidemiology of dengue fever in Malaysia. Although the overall incidence has stabilized in recent years, dengue disease remains a public health burden. Our review demonstrates an increased incidence of all forms of dengue disease and a predominantly adult age distribution. Changes in circulating dengue virus serotypes may have implications for the incidence and severity of dengue disease. Increasing levels of rainfall, humidity, temperature, and urbanization have been identified as risk factors for dengue disease outbreak. We believe that the recent improvements to the surveillance system in Malaysia should, if pursued over the next few years, greatly improve our understanding of the burden of dengue fever and enable us to monitor the impact of disease control measures in the future.     

Prediction of dengue incidence using search query surveillance

Background

The use of internet search data has been demonstrated to be effective at predicting influenza incidence. This approach may be more successful for dengue which has large variation in annual incidence and a more distinctive clinical presentation and mode of transmission.

Methods

We gathered freely-available dengue incidence data from Singapore (weekly incidence, 2004–2011) and Bangkok (monthly incidence, 2004–2011). Internet search data for the same period were downloaded from Google Insights for Search. Search terms were chosen to reflect three categories of dengue-related search: nomenclature, signs/symptoms, and treatment. We compared three models to predict incidence: a step-down linear regression, generalized boosted regression, and negative binomial regression. Logistic regression and Support Vector Machine (SVM) models were used to predict a binary outcome defined by whether dengue incidence exceeded a chosen threshold. Incidence prediction models were assessed using and Pearson correlation between predicted and observed dengue incidence. Logistic and SVM model performance were assessed by the area under the receiver operating characteristic curve. Models were validated using multiple cross-validation techniques.

Results

The linear model selected by AIC step-down was found to be superior to other models considered. In Bangkok, the model has an , and a correlation of 0.869 between fitted and observed. In Singapore, the model has an , and a correlation of 0.931. In both Singapore and Bangkok, SVM models outperformed logistic regression in predicting periods of high incidence. The AUC for the SVM models using the 75th percentile cutoff is 0.906 in Singapore and 0.960 in Bangkok.

Conclusions

Internet search terms predict incidence and periods of large incidence of dengue with high accuracy and may prove useful in areas with underdeveloped surveillance systems. The methods presented here use freely available data and analysis tools and can be readily adapted to other settings.     

Interaction of climate and socio-ecological environment drives the dengue outbreak in epidemic region of China

Transmission of dengue virus is a complex process with interactions between virus, mosquitoes and humans, influenced by multiple factors simultaneously. Studies have examined the impact of climate or socio-ecological factors on dengue, or only analyzed the individual effects of each single factor on dengue transmission. However, little research has addressed the interactive effects by multiple factors on dengue incidence. This study uses the geographical detector method to investigate the interactive effect of climate and socio-ecological factors on dengue incidence from two perspectives: over a long-time series and during outbreak periods; and surmised on the possibility of dengue outbreaks in the future. Results suggest that the temperature plays a dominant role in the long-time series of dengue transmission, while socio-ecological factors have great explanatory power for dengue outbreaks. The interactive effect of any two factors is greater than the impact of single factor on dengue transmission, and the interactions of pairs of climate and socio-ecological factors have more significant impact on dengue. Increasing temperature and surge in travel could cause dengue outbreaks in the future. Based on these results, three recommendations are offered regarding the prevention of dengue outbreaks: mitigating the urban heat island effect, adjusting the time and frequency of vector control intervention, and providing targeted health education to travelers at the border points. This study hopes to provide meaningful clues and a scientific basis for policymakers regarding effective interventions against dengue transmission, even during outbreaks.     

Yellow fever and dengue—the interactions of virus,vector and host in the re-emergence of epidemic disease

The incidence of the mosquito-borne flavivirus diseases, yellow fever, dengue and dengue hemorrhagic fever has increased dramatically in recent years. Both diseases are characterized by the emergence of explosive epidemics. Yellow fever outbreaks appear to have a periodicity dependent upon fluctuations in sylvatic (enzootic) transmission cycles and the ecological factors that influence these cycles. Spread of the virus from the sylvatic cycle to human settlements, ultimately with interhuman transmission by domestic Aedes aegypti is a repeating event in Africa, and presents a renewed threat in the Americas, where effective Ae. aegypti control collapsed in the 1970s. The incidence of dengue has also increased dramatically in recent years, with up to 80 million persons living in tropical regions of the world now affected annually—an attack rate of 4%. The severe form, dengue hemorrhagic fever (DHF) has become a leading health problem throughout Asia in the last 20 years and is emerging as an epidemic disease in the Americas. Unlike yellow fever, sylvatic dengue transmission cycles are not responsible for disease emergence. The major factors underlying dengue epidemics are changes in human ecology, increasing contact with Ae. aegypti, the co-circulation of multiple dengue serotypes, and a rising prevalence of immunity and immunopathological events that underlie the pathogenesis of DHF. In this review, the complex interplay of virus, host, vector, environment and weather in the ecology of yellow fever and dengue are explored.     

Interaction of Mean Temperature and Daily Fluctuation Influences Dengue Incidence in Dhaka,Bangladesh

Local weather influences the transmission of the dengue virus. Most studies analyzing the relationship between dengue and climate are based on relatively coarse aggregate measures such as mean temperature. Here, we include both mean temperature and daily fluctuations in temperature in modelling dengue transmission in Dhaka, the capital of Bangladesh. We used a negative binomial generalized linear model, adjusted for rainfall, anomalies in sea surface temperature (an index for El Niño-Southern Oscillation), population density, the number of dengue cases in the previous month, and the long term temporal trend in dengue incidence. In addition to the significant associations of mean temperature and temperature fluctuation with dengue incidence, we found interaction of mean and temperature fluctuation significantly influences disease transmission at a lag of one month. High mean temperature with low fluctuation increases dengue incidence one month later. Besides temperature, dengue incidence was also influenced by sea surface temperature anomalies in the current and previous month, presumably as a consequence of concomitant anomalies in the annual rainfall cycle. Population density exerted a significant positive influence on dengue incidence indicating increasing risk of dengue in over-populated Dhaka. Understanding these complex relationships between climate, population, and dengue incidence will help inform outbreak prediction and control.     

Epidemiology of Infant Dengue Cases Illuminates Serotype-Specificity in the Interaction between Immunity and Disease,and Changes in Transmission Dynamics

Background

Infants born to dengue immune mothers acquire maternal antibodies to dengue. These antibodies, though initially protective, decline during the first year of life to levels thought to be disease enhancing, before reaching undetectable levels. Infants have long been studied to understand the interaction between infection and disease on an individual level.

Methods/Findings

Considering infants (cases <1 year old) as a unique group, we analyzed serotype specific dengue case data from patients admitted to a pediatric hospital in Bangkok, Thailand. We show differences in the propensity of serotypes to cause disease in individuals with dengue antibodies (infants and post-primary cases) and in individuals without dengue antibodies (primary cases). The mean age of infant cases differed among serotypes, consistent with previously observed differential waning of maternal antibody titers by serotype. We show that trends over time in epidemiology of infant cases are consistent with those observed in the whole population, and therefore with trends in the force of infection.

Conclusions/Significance

Infants with dengue are informative about the interaction between antibody and the dengue serotypes, confirming that in this population DENV-2 and DENV-4 almost exclusively cause disease in the presence of dengue antibody despite infections occurring in others. We also observe differences between the serotypes in the mean age in infant cases, informative about the interaction between waning immunity and disease for the different serotypes in infants. In addition, we show that the mean age of infant cases over time is informative about transmission in the whole population. Therefore, ongoing surveillance for dengue in infants could provide useful insights into dengue epidemiology, particularly after the introduction of a dengue vaccine targeting adults and older children.     

Multiyear Climate Variability and Dengue—El Ni?o Southern Oscillation,Weather, and Dengue Incidence in Puerto Rico,Mexico, and Thailand: A Longitudinal Data Analysis

Background

The mosquito-borne dengue viruses are a major public health problem throughout the tropical and subtropical regions of the world. Changes in temperature and precipitation have well-defined roles in the transmission cycle and may thus play a role in changing incidence levels. The El Niño Southern Oscillation (ENSO) is a multiyear climate driver of local temperature and precipitation worldwide. Previous studies have reported varying degrees of association between ENSO and dengue incidence.

Methods and Findings

We analyzed the relationship between ENSO, local weather, and dengue incidence in Puerto Rico, Mexico, and Thailand using wavelet analysis to identify time- and frequency-specific association. In Puerto Rico, ENSO was transiently associated with temperature and dengue incidence on multiyear scales. However, only local precipitation and not temperature was associated with dengue on multiyear scales. In Thailand, ENSO was associated with both temperature and precipitation. Although precipitation was associated with dengue incidence, the association was nonstationary and likely spurious. In Mexico, no association between any of the variables was observed on the multiyear scale.

Conclusions

The evidence for a relationship between ENSO, climate, and dengue incidence presented here is weak. While multiyear climate variability may play a role in endemic interannual dengue dynamics, we did not find evidence of a strong, consistent relationship in any of the study areas. The role of ENSO may be obscured by local climate heterogeneity, insufficient data, randomly coincident outbreaks, and other, potentially stronger, intrinsic factors regulating transmission dynamics. Please see later in the article for the Editors'' Summary     

The Nicaraguan Pediatric Dengue Cohort Study: Incidence of Inapparent and Symptomatic Dengue Virus Infections, 2004–2010

Dengue, caused by the four serotypes of dengue virus (DENV), is the most prevalent mosquito-borne viral disease of humans. To examine the incidence and transmission of dengue, the authors performed a prospective community-based cohort study in 5,545 children aged 2–14 years in Managua, Nicaragua, between 2004 and 2010. Children were provided with medical care through study physicians who systematically recorded medical consult data, and yearly blood samples were collected to evaluate DENV infection incidence. The incidence of dengue cases observed was 16.1 cases (range 3.4–43.5) per 1,000 person-years (95% CI: 14.5, 17.8), and a pattern of high dengue case incidence every other year was observed. The incidence of DENV infections was 90.2 infections (range 45.2–105.3) per 1,000 person-years (95% CI: 86.1, 94.5). The majority of DENV infections in young children (<6 years old) were primary (60%) and the majority of infections in older children (≥9 years of age) were secondary (82%), as expected. The incidence rate of second DENV infections (121.3 per 1,000 person-years; 95% CI: 102.7, 143.4) was significantly higher than the incidence rate of primary DENV infections (78.8 per 1,000 person-years; 95% CI: 73.2, 84.9). The rigorous analytic methodology used in this study, including incidence reporting in person-years, allows comparison across studies and across different infectious diseases. This study provides important information for understanding dengue epidemiology and informing dengue vaccine policy.     

Dengue infection in children in ratchaburi, Thailand: a cohort study. I. Epidemiology of symptomatic acute dengue infection in children, 2006-2009

Background

There is an urgent need to field test dengue vaccines to determine their role in the control of the disease. Our aims were to study dengue epidemiology and prepare the site for a dengue vaccine efficacy trial.

Methods and Findings

We performed a prospective cohort study of children in primary schools in central Thailand from 2006 through 2009. We assessed the epidemiology of dengue by active fever surveillance for acute febrile illness as detected by school absenteeism and telephone contact of parents, and dengue diagnostic testing. Dengue accounted for 394 (6.74%) of the 5,842 febrile cases identified in 2882, 3104, 2717 and 2312 student person-years over the four years, respectively. Dengue incidence was 1.77% in 2006, 3.58% in 2007, 5.74% in 2008 and 3.29% in 2009. Mean dengue incidence over the 4 years was 3.6%. Dengue virus (DENV) types were determined in 333 (84.5%) of positive specimens; DENV serotype 1 (DENV-1) was the most common (43%), followed by DENV-2 (29%), DENV-3 (20%) and DENV-4 (8%). Disease severity ranged from dengue hemorrhagic fever (DHF) in 42 (10.5%) cases, dengue fever (DF) in 142 (35.5%) cases and undifferentiated fever (UF) in 210 (52.5%) cases. All four DENV serotypes were involved in all disease severity. A majority of cases had secondary DENV infection, 95% in DHF, 88.7% in DF and 81.9% in UF. Two DHF (0.5%) cases had primary DENV-3 infection.

Conclusion

The results illustrate the high incidence of dengue with all four DENV serotypes in primary school children, with approximately 50% of disease manifesting as mild clinical symptoms of UF, not meeting the 1997 WHO criteria for dengue. Severe disease (DHF) occurred in one tenth of cases. Data of this type are required for clinical trials to evaluate the efficacy of dengue vaccines in large scale clinical trials.     

Epidemiology of Dengue Disease in the Philippines (2000–2011): A Systematic Literature Review

This literature analysis describes the available dengue epidemiology data in the Philippines between 2000 and 2011. Of 253 relevant data sources identified, 34, including additional epidemiology data provided by the National Epidemiology Center, Department of Health, Philippines, were reviewed. There were 14 publications in peer reviewed journals, and 17 surveillance reports/sources, which provided variable information from the passive reporting system and show broad trends in dengue incidence, including age group predominance and disease severity. The peer reviewed studies focused on clinical severity of cases, some revealed data on circulating serotypes and genotypes and on the seroepidemiology of dengue including incidence rates for infection and apparent disease. Gaps in the data were identified, and include the absence incidence rates stratified by age, dengue serotype and genotype distribution, disease severity data, sex distribution data, and seroprevalence data.

Protocol registration

PROSPERO CRD42012002292     

Economic impact of dengue illness and the cost-effectiveness of future vaccination programs in Singapore

Background

Dengue illness causes 50–100 million infections worldwide and threatens 2.5 billion people in the tropical and subtropical regions. Little is known about the disease burden and economic impact of dengue in higher resourced countries or the cost-effectiveness of potential dengue vaccines in such settings.

Methods and Findings

We estimate the direct and indirect costs of dengue from hospitalized and ambulatory cases in Singapore. We consider inter alia the impacts of dengue on the economy using the human-capital and the friction cost methods. Disease burden was estimated using disability-adjusted life years (DALYs) and the cost-effectiveness of a potential vaccine program was evaluated. The average economic impact of dengue illness in Singapore from 2000 to 2009 in constant 2010 US$ ranged between $0.85 billion and $1.15 billion, of which control costs constitute 42%–59%. Using empirically derived disability weights, we estimated an annual average disease burden of 9–14 DALYs per 100 000 habitants, making it comparable to diseases such as hepatitis B or syphilis. The proportion of symptomatic dengue cases detected by the national surveillance system was estimated to be low, and to decrease with age. Under population projections by the United Nations, the price per dose threshold for which vaccines stop being more cost-effective than the current vector control program ranged from $50 for mass vaccination requiring 3 doses and only conferring 10 years of immunity to $300 for vaccination requiring 2 doses and conferring lifetime immunity. The thresholds for these vaccine programs to not be cost-effective for Singapore were $100 and $500 per dose respectively.

Conclusions

Dengue illness presents a serious economic and disease burden in Singapore. Dengue vaccines are expected to be cost-effective if reasonably low prices are adopted and will help to reduce the economic and disease burden of dengue in Singapore substantially.     

Epidemiological Trends of Dengue Disease in Mexico (2000–2011): A Systematic Literature Search and Analysis

This systematic literature review describes the epidemiology of dengue disease in Mexico (2000–2011). The annual number of uncomplicated dengue cases reported increased from 1,714 in 2000 to 15,424 in 2011 (incidence rates of 1.72 and 14.12 per 100,000 population, respectively). Peaks were observed in 2002, 2007, and 2009. Coastal states were most affected by dengue disease. The age distribution pattern showed an increasing number of cases during childhood, a peak at 10–20 years, and a gradual decline during adulthood. All four dengue virus serotypes were detected. Although national surveillance is in place, there are knowledge gaps relating to asymptomatic cases, primary/secondary infections, and seroprevalence rates of infection in all age strata. Under-reporting of the clinical spectrum of the disease is also problematic. Dengue disease remains a serious public health problem in Mexico.     

Barriers and Bridges to Prevention and Control of Dengue: The Need for a Social–Ecological Approach

This article critically examines how programs for the prevention and control of dengue fever have been conducted in the absence of an integrated approach, and considers the social and ecological factors influencing their effectiveness. Despite recognition of dengue fever as the most important arboviral disease affecting humans, and in spite of a greater emphasis on community-based control approaches, the burden placed on the communities, countries, and regions affected by this disease continues to rise. In considering historical experience in the Americas and the Asia-Pacific region, as well as the global forces that are exerting new pressures, the important elements of successful control programs are identified as community ownership, partnership with government, leadership, scalability, and control of immature mosquitoes. The key barriers to the exchange of knowledge and the transdisciplinary cooperation necessary for sustainable dengue control are rooted in differences in values among policy-makers, citizens, and scientists and are repeatedly expressed in technical, economic, cultural, geographic, and political dimensions. Through consideration of case studies in Cuba, Guatemala, Singapore, Thailand, Indonesia, and Vietnam, the limitations of control approaches that fail to take into account the complexities of ecological and social systems are presented. Bridges to effective control are identified as the basis for adaptability, both of control programs to the mosquito vector’s changing behavior and of education programs to public, regional and local particularities, as well as transdisciplinarity, community empowerment, the ability to scale local experiences up to the macro-level, and the capacity to learn from experience to achieve sustainability.     

Developing a Time Series Predictive Model for Dengue in Zhongshan,China Based on Weather and Guangzhou Dengue Surveillance Data

Background

Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information.

Methods

We obtained weekly dengue case data from 1^st January, 2005 to 31^st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation.

Results

Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845–2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938–0.967). The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case. The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance.

Conclusion

Our study findings suggest that the occurrence of dengue outbreaks in Guangzhou could impact dengue outbreaks in Zhongshan under suitable weather conditions. Future studies should focus on developing integrated early warning systems for dengue transmission including local weather and human movement.     

Interacting Virus Abundance and Transmission Intensity Underlie Tomato Spotted Wilt Virus Incidence: An Example Weather-Based Model for Cultivated Tobacco

Through a modeling approach, we investigated weather factors that affect the summer incidence of Tomato spotted wilt virus (TSWV), a virus vectored exclusively by thrips, in cultivated tobacco. Aspects of thrips and plant biology that affect disease spread were treated as functions of weather, leading to a model of disease incidence informed by thrips and plant biology, and dependent on weather input variables. We found that disease incidence during the summer was influenced by weather affecting thrips activity during the preceding year, especially during a time when thrips transmit TSWV to and from the plant hosts that constitute the virus’ natural reservoir. We identified an interaction between spring precipitation and earlier weather affecting thrips, relating this to virus abundance and transmission intensity as interacting factors affecting disease incidence. Throughout, weather is the basic driver of epidemiology in the system, and our findings allowed us to detect associations between atypically high- or low-incidence years and the local climatic deviations from normal weather patterns, brought about by El Niño Southern Oscillation transitions.     

Climate change impacts on West Nile virus transmission in a global context

West Nile virus (WNV), the most widely distributed virus of the encephalitic flaviviruses, is a vector-borne pathogen of global importance. The transmission cycle exists in rural and urban areas where the virus infects birds, humans, horses and other mammals. Multiple factors impact the transmission and distribution of WNV, related to the dynamics and interactions between pathogen, vector, vertebrate hosts and environment. Hence, among other drivers, weather conditions have direct and indirect influences on vector competence (the ability to acquire, maintain and transmit the virus), on the vector population dynamic and on the virus replication rate within the mosquito, which are mostly weather dependent. The importance of climatic factors (temperature, precipitation, relative humidity and winds) as drivers in WNV epidemiology is increasing under conditions of climate change. Indeed, recent changes in climatic conditions, particularly increased ambient temperature and fluctuations in rainfall amounts, contributed to the maintenance (endemization process) of WNV in various locations in southern Europe, western Asia, the eastern Mediterranean, the Canadian Prairies, parts of the USA and Australia. As predictions show that the current trends are expected to continue, for better preparedness, any assessment of future transmission of WNV should take into consideration the impacts of climate change.     

Dengue epidemiology and pathogenesis:images of the future viewed through a mirror of the past

Every year, millions of individuals throughout the world are seriously affected by dengue virus. The unavailability of a vaccine and of anti-viral drugs has made this mosquito-borne disease a serious health concern. Not only does dengue cause fatalities but it also has a profoundly negative economic impact. In recent decades, extensive research has been performed on epidemiology, vector biology, life cycle, pathogenesis, vaccine development and prevention. Although dengue research is still not at a stage to suggest definite hopes of a cure, encouraging significant advances have provided remarkable progress in the fight against infection. Recent developments indicate that both anti-viral drug and vaccine research should be pursued, in parallel with vector control programs.