Climate and Dengue Transmission: Evidence and Implications

1Climate change is one of the most important environmental changes populations will face in the coming decades. Understanding how it may affect human health and disease is complex and requires a thorough understanding of links between present climate and disease. Links between climate and diseases with various modes of transmission (vector-, water-, food-, soil-, and airborne) have been identified, with the strongest associations being between climate and mosquito-borne diseases. Although widely held as the world’s most important arbovirus, only one review of potential climate change impacts on dengue virus (DENV) transmission has been published with a focus on tools currently used to establish climate–disease associations.

2DENV is transmitted by Aedes genus mosquitoes, primarily Aedes aegypti and Aedes albopictus. Recent analysis indicates the that numbers of dengue fever (DF) cases may be as high as 400 million/year. Climate affects the DENV and vector populations both directly and indirectly. Temperature influences vector development rates, mortality, and behavior and controls viral replication within the mosquito. Variability in precipitation influences habitat availability for Ae. aegypti and Ae. albopictus larvae and pupae. Temperature further interacts with rainfall as the chief regulator of evaporation, thereby also affecting the availability of water habitats. Indirectly, rainfall, temperature, and humidity influence land cover and land use, which can promote or impede the growth of vector populations. The incidence of DF has been associated with vegetation indices, tree cover, housing quality, and surrounding land cover. Climate change can also alter how humans interact with the land, altering its use and impacting mosquito population magnitude and species composition.

3Although empirical relationships have been identified between climate conditions, DF, and DENV vectors, causal relationships have not been firmly established, thus limiting our ability to assess intervention strategies. In order to evaluate the potential impacts of climate change and better prepare mitigation strategies, we examined the strength of the evidence supporting the complex relationships among Aedes mosquitoes, DENV, and weather and climate. We also explored the relative utility of statistical and process-based models and their ability to identify key associations between climate and disease and to predict and simulate DENV transmission under projected climate change conditions.

4We developed a framework of the hypothesized relationships between Aedes mosquitoes, DENV, and weather and climate (Figure 1). We reviewed evidence for each of the links illustrated in Figure 1 based on a) findings in published literature from laboratory and field studies conducted on the vector and virus, b) results of predictive models driven by weather and climate data, and c) investigations of DENV transmission in relation to climate. We assessed the relative strengths and limitations of empirical and process-based models and their use of established climate–transmission relationships. Last, we provide recommendations for future research to enhance model performance and improve our ability to forecast and prepare for the effects of climate change on DF.

5Temperature and virus replication and transmission. Temperature is a key component in the ecology of DENV as seen from its numerous interactions with other components of the disease system (Figure 1). Most directly, ambient temperature increases are associated with a faster rate of viral replication within the vector and with a shorter extrinsic incubation period (EIP; the time required for DENV to become transmissible to another host after initial infection of a mosquito). There are four major serotypes of DENV: DENV-1, DENV-2, DENV-3, and DENV-4. demonstrated that for both DENV-1 and DENV-4 the time between feeding and virus detection in the salivary glands of Ae. aegypti mosquitoes decreased from 9 days at 26°C and 28°C to 5 days at 30°C. more directly demonstrated that the EIP for DENV-2 virus in Ae. aegypti mosquitoes is temperature dependent by allowing infected mosquitoes to feed on monkeys. They reported that the EIP was as short as 7 days at temperatures of 32–35°C, and ≥ 12 days at 30°C, whereas no virus transmission occurred at 26°C within the 25-day period of the study. In addition, the EIP was dependent on the density of the virus in the ingested blood, such that higher densities were associated with shorter EIPs. Using censored Bayesian time-to-event models to analyze data collected from many studies, estimated the average EIP to be 15 days at 25°C, and 6.5 days at 30°C. estimated shorter incubation periods (5–9 days) but they defined the end of the EIP as the time when the virus was detected in the mosquito, whereas defined it as the time when the mosquito transmitted the virus. Because temperature varies throughout the day in nature, explored the susceptibility of Ae. aegypti to DENV infections under different diurnal temperature ranges (DTRs). They found that with the same mean temperature, mosquitoes exposed to a greater DTR were less likely to become infected than those exposed to a smaller DTR; however, the EIP was unchanged. Evidence suggests that even small increases in temperatures and narrower DTRs may facilitate DENV transmission by decreasing the EIP or by increasing the susceptibility of mosquitoes to infection.

6Temperature and vector ecology. Mosquitoes of the genus Aedes, primarily Ae. aegypti, are the vectors for DENV; therefore, the ecology of the virus is intrinsically tied to the ecology of these mosquitoes. Temperature can exert considerable influence on mosquito population dynamics. Egg and immature mosquito development, ovarian development, and survival at all stages of the mosquito life cycle are governed in part by temperature. In the laboratory setting, found that immature Ae. aegypti development rates generally increased with incubation temperatures to 34°C and then slowed. Survival through all developmental phases peaked at approximately 90% (27°C) with cooler temperatures being especially detrimental to survival. reported that Ae. aegypti egg, larvae, and pupae development rates increased at higher incubation temperatures and ceased at < 8.3°C. Their estimated survival rates were also similar to those reported by, with the ideal range for survival through all phases of development (88–93%) occurring between 20–30°C. The laboratory studies discussed above yielded consistent results with little variation between trials. In the field portion of their study, found that development rates accelerated in warmer water, but development was often slower and more variable in field trials than in their laboratory trials at comparative temperatures.

7Adult mosquito survival is important because only mosquitoes that live beyond the EIP can act as potential vectors. The first blood meal is generally taken 3 days post-eclosion (i.e., 3 days after emerging as an adult); therefore, assuming an EIP of 7–12 days (based on ), a minimum of 10–15 days is required for a newly emerged mosquito to become infectious. Mark–release–recapture studies have estimated that adult daily survival rates are between 86% and 91%. Although these studies did not examine climatic influences on survivability, has provided evidence of increased mortality with exposure to prolonged extreme heat (> 40°C) and cold (< 0°C) in a laboratory setting. Using the ranges of adult survival rates and the estimated minimum age to complete the EIP indicated above, 10.4% (86% daily survival with a 15-day EIP) to 38.9% (91% daily survival with a 10-day EIP) of mosquitoes will survive long enough to complete the EIP and become infectious to humans, assuming they are infected with DENV when they take their first blood meal. Larger DTRs result in a shorter mosquito life span than smaller DTRs around the same mean temperature; however, larger DTRs may concurrently shorten the duration of the EIP, demonstrating the complex nature of these relationships. recently reported that less thermal energy is required for pupation when temperatures fluctuate around a low mean value than when the temperature is constant at that value, whereas more thermal energy is required when temperatures fluctuate around a higher mean value than when the temperature is constant around that value. These results indicate that population models that assume the required thermal energy for pupation is constant could be over- or underestimating development times, leading to inaccurate simulations.

8The female mosquito’s reproductive cycle is also governed by ambient temperature. At < 20°C, fertilization decreases. established that increased minimum temperatures resulted in accelerated oviposition cycles and egg laying. Female Ae. aegypti require a blood meal for ovarian development, and feeding behavior is also influenced by temperature. Feeding activity is limited or ceases at temperatures < 15°C and can also be limited at temperatures > 36°C (CW Morin, unpublished data). Multiplicity of feeding, that is, the taking of blood meals from multiple hosts during a single gonotrophic cycle (blood feeding, ovarian development, and egg laying), has been associated with higher levels of DENV transmission. found that higher temperatures were associated with higher incidences of multiple blood feedings in Thailand but not in Puerto Rico. Female size was also negatively correlated with temperature, and smaller females exhibited increased multiplicity of feeding in Thailand.

9The effect of temperature on the ability of the mosquito to reproduce has consequences for population dynamics and range limits. There is evidence of selection of breeding containers based on temperature and sun exposure. found that Ae. aegypti preferred shaded containers and cooler water temperatures for egg laying in Puerto Rico. However, found that containers with more sun exposure were more likely to be inhabited in Iquitos, Peru. This may be because obtaining optimal water temperature for the mosquito required heating from direct sun exposure in one location and protection from the sun in another. In both cases, however, water temperature was important for mosquito reproduction. also found the presence of trees to be associated with Ae. aegypti pupal productivity; they suggested that although dense vegetation may promote growth by contributing organic material to the habitat, it can also influence water temperature and evaporation by creating shade. This highlights how land-cover and land-use characteristics can influence microclimates and, consequently, mosquito populations. Using a statistical population model with known temperature limits and ecological parameters of the mosquito, calculated the limits of Ae. aegypti habitat range to be along the 15°C average annual temperature isotherm. An examination of the spatial distribution of adult Ae. aegypti with remotely sensed land use and land cover indicated that Ae. aegypti were more likely to be present in areas with structures and medium height trees than in areas with bare earth.

10Although there are similarities in the thermal characteristics of many of the variables associated with vector and viral development, the critical limiting values are not the same. Integrating all these variables together in one temperature-driven model can enable simulation of very complex dynamics. Figure 2 shows the varying effects of temperature on many of the variables discussed above. There is often little correlation in the individual responses of these variables to temperature. This indicates that although increasing temperatures may accelerate parts of the viral transmission cycle, other components may become limited by high temperatures. Thus, the overall effect of warming on DENV ecology will be context dependent.

11Precipitation and vector ecology. Whereas temperature has a direct biophysical influence on viral replication and on vector development and survival, precipitation provides essential habitat for the aquatic stages of the mosquito life cycle. Containers, common in urban environments, are often an important habitat. studied vector abundances related to climate in Tucson, Arizona, an urban area inhabited by Ae. aegypti and in close proximity to DENV-endemic areas, but where DF does not occur. Not surprisingly, increased collections of Ae. aegypti eggs and adults coincided with the monsoon rains. In neighborhoods near San Juan, Puerto Rico, found that higher precipitation was associated with increased Ae. aegypti populations, and that man-made containers were the most important pupae habitat for producing adult mosquitoes. Intense rainfall, however, may wash out breeding sites and thus have a negative effect on vector populations.

12Precipitation is often required to create and maintain breeding sites and has a strong influence on vector distributions. estimated intraannual climate-induced range changes of Ae. albopictus in Hawaii using a geographic information system (GIS), climate data, and the known habitat of the mosquito. They concluded that mosquito ranges expand during La Niña conditions (generally wetter) and decrease during El Niño conditions (generally drier). This could increase future risk of DF given projected changes of El Niño Southern Oscillation (ENSO) cycles. Drier conditions, however, can indirectly expand a vector’s range. used a biophysical model in conjunction with an evolutionary response component to project alterations in the range of Ae. aegypti in Australia due to climate change and concluded that habitat for the mosquito will likely expand as individuals increase household water storage in response to a drier climate. Drier conditions could also cause selection pressure towards greater egg resistance to desiccation. posited that installing domestic water reservoirs to combat drying from warmer temperatures and decreased precipitation actually provides additional breeding grounds for Ae. aegypti mosquitoes, whose range is predicted to expand with increasing temperature. Australia’s risk of DF comes not only from the direct effects of climate change on mosquito population density, but also from the adaptive measures people take to mitigate its effects.

13Climate, habitat, and vector ecology. Precipitation and temperature work interdependently: Increased temperatures accelerate evaporation rates and limit standing water as a potential habitat source for immature mosquitoes, although the eggs are resistant to desiccation over extended time periods and thus climate effects on immature vector survival are a complex balance between precipitation and evaporation. Higher rates of precipitation combined with higher temperatures also result in increased humidity. Higher humidity is associated with increased Ae. aegypti feeding activity, survival, and egg development. For instance, reported that daily minimum temperature and an increase in precipitation from the previous month were both associated with increased larval abundances.

14Within water habitats, competition for space and nutrients is a key determinant of population levels. As the water in containers evaporates, the density of immature mosquitoes may increase, enhancing competition and deterring potential egg laying. raised immature Ae. aegypti at various densities in laboratory conditions and found that higher densities resulted in slower development, greater mortality, and a lower body mass. Field studies have supported these findings. demonstrated that mortality was density dependent for Ae. aegypti between the egg and second instar larval development stage. Similarly, found that when competition existed among larvae, the younger instars suffered the greatest delay in development. At the greatest extreme, complete evaporation will result in complete mortality of larvae and pupae.

15Much of the density dependence exhibited in these studies is the result of nutritional stress in the containers. This suggests that precipitation exerts less influence on density-dependent mortality than nutritional levels within the habitat. subjected laboratory-reared Ae. aegypti to varying levels of food rations and concluded that oviposition and pupation were delayed under food stress. reported that nutritional levels regulate production of growth retardant factor (GRF), which can limit population growth. However, a conflicting study by showed that the production of GRF is strain dependent, and it probably plays only a small role in population control. Still other studies have provided evidence that shows nutrition to be important for Ae. aegypti larval development and survival. discovered that containers with more organic matter resulted in larger mosquitoes, quicker development, and higher survival rates. Similarly, studied larvae-inhabited containers in Puerto Rico and their results indicate the existence of food competition in most containers, although containers with a larger water volume showed reduced competition-related effects (such as retarded development and increased mortality). This may be explained by larger water bodies being less affected by evaporation, resulting in lower larvae/pupae population densities. also showed that the body mass of individual mosquitoes was decreased among mosquitoes in more crowded containers. As noted previously by, smaller body size is associated with increased transmission potential because of the increased multiplicity of feeding in smaller mosquitoes compared with larger mosquitoes.

16In addition, reported that female preferences for oviposition sites were affected by larval density. Specifically, female Ae. aegypti were more attracted to sites with higher larval densities up to a threshold level, after which they were repelled. These results indicate that the effects of precipitation and evaporation on available water sources can regulate the size, population, and behavior of DENV vectors.

17Climate factors may also provoke competition between species of mosquitoes. Ae. aegypti and Ae. albopictus are two DENV vectors that often have overlapping habitat distributions. studied egg mortality rates of these two species in varying laboratory environments and reported that although Ae. aegypti eggs thrived across a wide range of humidity and temperature combinations, Ae. albopictus eggs experienced high mortality at conditions at < 95% humidity when temperatures were > 22°C. In their southern Florida cemetery survey of mosquito presence vs. absence, found a significantly lower Ae. albopictus presence after the dry season than during the wet season, whereas the Ae. aegypti presence was consistent.

18Vector population and DF incidence. Although often monitored to assess DENV transmission risk, vector abundances are not always associated with DF incidence. In a study in São Paulo, Brazil, reported that the average number of female mosquitoes was the best predictor of DF cases in humans and that numbers of female mosquitoes and eggs, and the presence of female mosquitoes were all positively correlated with DF cases. However, studies by and, using the Breteau index (number of containers inhabited by immature Ae. aegypti per 100 houses inspected), did not find statistically significant relationships between mosquito indices and DF cases, suggesting that the utility of surveying vector populations to evaluate DF risk may vary. Several factors may be responsible for this lack of association. posited that the development of herd immunity may explain the decrease in the incidence of DF observed over their 3-year study period despite a consistently high mosquito index. found temperature to be a significant predictor of DF incidence, and suggested that this relationship may exist because DENV replication within the mosquito is regulated by temperature and, therefore, so is the length of the EIP. It is possible that a given temperature may be sufficient to support vector populations but inadequate to support viral replication, or that once a certain threshold of mosquito density is met, a further increase in density will have only a minimal impact on DENV transmission.

19Climate and disease occurrence. Numerous methods of statistical analysis have been used to estimate associations between climate variables and DF incidence, including cross correlations; Poisson, logistic, and multivariate regression; autoregression; and wavelet analysis (Table 1). Many have been successful (e.g., Arcari et al. 2007; ) in identifying climate–DENV relationships and creating predictive models of DF incidence based on climate associations. Variables that predict the intensity and timing of outbreaks include minimum, maximum, and mean temperature as well as relative humidity and wind velocity, whereas the seasonal timing of epidemics is predicted by precipitation. Often these variables are predictive at specific time lags.

20The sign and strength of climate–DENV associations depend largely on local climate context. In a study by in southern Taiwan, mean and maximum temperature were negatively associated with DF cases, which seems counterintuitive until the generally high temperatures in this region [which can often reach levels that damage mosquitoes and thus limit virus transmission (> 30°C)] are considered. In contrast, in other regions low temperatures may be the limiting factor. Similarly, did not find a high correlation between precipitation and DF incidence in Singapore because rain occurs there throughout the year, and thus it is not a significant limiting factor for mosquitoes. In Taiwan, found relative humidity to be negatively associated with DF incidence. They hypothesized that although mosquitoes generally survive longer in humid conditions, they may bite more when water-stressed, thus increasing DENV transmission at lower humidity. These studies highlight the multiple avenues through which climate variables can influence DENV transmission.

21Because of their influence on weather patterns, ENSO indices and sea surface temperatures also have been analyzed in relation to DF incidence. and have both found ENSO to be a good predictor of DF cases in Mexico. ENSO associations with DENV transmission have also been identified in the Caribbean, Thailand, Costa Rica, Australia, and Vietnam. Studies in Noumea and Puerto Rico, however, have found little or only sporadic associations. The inconsistent nature of these associations may reflect regional variation in the effects of ENSO on precipitation and temperature.

22Unfortunately, because of data constraints, analyses are often performed using data aggregated over large spatial scales (e.g., country level) or long time periods (e.g., monthly or annually). found only weak associations between DF incidence, climate, and ENSO indices based on country-level analyses in Puerto Rico, Mexico, and Thailand. However, reported that several climate variables were associated with DF incidence when broken down by municipality in Puerto Rico. More important, the predictors and the strengths of their associations with DF varied among municipalities, highlighting the importance of local climate variation on DENV ecology. Other studies have also reported evidence of within-country or within-province variability in climate–dengue associations. In Indonesia, found that variation in rainfall patterns among provinces was a large determinant of the strength and direction of associations between climate variables and DF incidence. reported that lag times for associations between climate variables and DF incidence varied among locations along the Texas–Mexico border, and reported that the explanatory power of ENSO indices and climate on DF incidence varied by province in Thailand.

23Analyses based on long time scales and broad geographic areas may fail to identify the influence of processes that occur over daily or weekly time periods and geography and climate features that may vary substantially at the country and sub-country level. For instance, showed that timing of DF outbreaks in Peru varied considerably between the coastal, mountain, and jungle regions. In particular, because suitable climatic conditions for DENV transmission existed during most of the year in jungle regions, these regions were often the source of DF outbreaks in neighboring regions. analyzed a multiwave outbreak of DF cases in Taiwan in 2007 and noted that after the initial wave of infection there were fewer infections in mid-August after two typhoons lowered temperatures, but the resulting moisture and remerging high temperatures resulted in a second wave of DF cases in early fall. These patterns were evident because data were analyzed over weekly and daily time periods. Unfortunately, availability of data often forces researchers to scale up. For example, attempted to perform a study at the census-block level in San Juan, Puerto Rico; however, because of the small numbers of DF cases, they had to analyze data at the municipality level instead.

24The predictive power and robustness of predictive models would be improved with additional data over longer time periods.,, and created statistical predictive models that were trained on < 10 years of data and could only be tested over a 1-year period. This makes it difficult to assess whether the relationships they observed will hold in time. created a statistical model for Puerto Rico using data from 1988 through 2005, and found that validation statistics were reduced considerably when data for a single year (1990) were removed. In Mexico, Colón-Gonzáles et al. (2011) noted an association between ENSO and DF incidence that was no longer evident when one large spike in DF cases was excluded from the analysis.

25The reported incidence of DF is subject to substantial over- and underreporting, which may vary by geographic region and time. Changes in case definitions, health care availability, diagnostic capabilities, and subclinical cases all influence the number of cases reported. avoided some of these issues by studying factors associated with time periods classified as epidemics or nonepidemics. It is also difficult to know where DENV transmission occurs, especially given the 4- to 10-day incubation period between infection and the onset of symptoms. Introduction of new DENV serotypes into a population can also be a confounding factor because it will alter immunity and symptoms in response to an incident infection. Finally, efforts to control DENV transmission may also confound associations between climate variables and the incidence of DF. Therefore, it is important to account for confounding by these and other factors before attempting to find associations with weather and climate.

26Although the above mentioned studies suggest that climate strongly influences DENV transmission, some studies have found other factors to be of equal or greater importance. and found the level of urbanization and number of artificial containers to be associated with vector populations and DF cases. Other studies have concluded that herd immunity, introduction of new or recycling of old viral serotypes, and changing demographics are partially or largely responsible for the variability in DENV transmission. found evidence that when climate conditions are favorable, imported cases of DF can initiate local DF epidemics in Taiwan, thus suggesting a way in which climate and human behavior may interact to influence viral transmission.

27Climate change and DF incidence. The impact of climate change on DF has also been examined. The studies discussed above, concerning climate, vectors, and the virus, suggest that suitable climatic conditions are required for mosquito population development and subsequent infections. It follows, therefore, that changes in climate will alter the spatial and temporal dynamics of DENV ecology, potentially increasing vector ranges, lengthening the duration of vector activity, and increasing the mosquito’s infectious period by shortening the EIP. Conversely, increased temperatures in already warm locations may have negative effects on the range of virus transmission through decreased vector survival, reproduction, and immature habitat.

28published one of the earliest papers connecting climate and future DENV transmission risk. They used a modified vectorial capacity equation to estimate the vector population required to maintain DENV transmission. The equation included climate dependent variables such as the EIP, daily mosquito mortality, mosquito size, and the length of the gonotrophic cycle. The Intergovernmental Panel on Climate Change–projected temperature increases of 2–4°C were applied to weekly-averaged data from weather stations in cities across the tropics. suggested that climate change would lead to an increase in the latitudinal and elevational extent of the disease, and a longer season of viral transmission.

29used a similar vectorial capacity equation that was modified to estimate epidemic potential. The model used projected climate change data from a general circulation model (GCM) at 250 km × 250 km resolution to project future DF risk across the world, focusing on five climatologically contrasting cities. The model predicted large increases in the geographic extent of DF and a longer disease season, especially in temperate regions at the fringes of the virus’ range. and both provided a good framework for future research on climate and DF risk, but estimates should be updated based on current GCM projections with improved resolution that are based on standardized approaches.

30conducted an early study using logistic regression to model disease range based on the statistical association of DF presence with water vapor and other climate variables. Based on GCM projections and human population demographics, the authors predicted that the magnitude and distribution of DF would increase and encompass a larger total population and percent of the population. Caution should be used when modeling DF incidence using statistical relationships with climate variables because the statistical model is trained with present climate data that may differ greatly from projected future climate regimes. The boundaries of statistical model predictions are limited to climate variable combinations that have already been experienced, and extrapolating outside those bounds may lead to inaccuracies.

31Process-based models can be used to estimate the effects of climate change on DF incidence while avoiding some of the restrictions of statistical techniques. The container-inhabiting mosquito simulation model (CIMSiM) accomplishes this using a dynamic life-table model. CIMSiM estimates the combined effects of temperature, precipitation, container types, and predation on mosquito survival and development. This type of modeling has been applied using climate change scenarios to project changes in vector dynamics under future values of temperature and precipitation. paired CIMSiM with a DF simulation model (DENSiM) to simulate DENV transmission between mosquito and human populations. This work was the first to use a combined climate and epidemiological approach to study DENV ecology. The authors have conducted a preliminary validation of the model in Honduras but stress that, although initial results are promising, additional validation is needed. More recently, used a matrix model driven by climate fluctuations to simulate the populations of two mosquito species of the genus Aedes. Using daily precipitation data, were able to successfully replicate field populations of the mosquitoes over the first 2 years of the study period with relatively high accuracy. However, although the model replicated the general dynamics, it overestimated populations in the third year, possibly due to lower capture frequency or changing mortality rates. incorporated global average climate data that was linearly downscaled to 1° resolution into an Ae. aegypti population model. The authors reported that model-based estimates of mosquito density worldwide were in general agreement with the known mosquito range. In a follow-up study, used numeric modeling to simulate the response of Ae. aegypti mosquitoes to climate change. They correlated modeled mosquito populations with DF incidence and used this relationship to predict future DF incidence by modeling new mosquito populations using projected future climate data. Although these studies show progress in our understanding of DENV ecology, they are still limited by equating DF incidence with vector populations, which have been shown to be unrelated in some studies. Newer models and studies should build upon this framework to represent finer scales and better-detailed processes.

32Although process-based models can be used to consider the complex dynamics of DENV ecology, they possess important limitations as predictive tools. Detailed knowledge of the processes within the system is required to build dynamic models. This is not true of statistical models, which are capable of establishing relationships even if the mechanisms responsible for the relationships are not well understood. Indeed, associations identified based on statistical analyses can be used to inform the parameters used in process-based models, and process-based models can conversely identify field studies that might be useful. In addition, process-based models of well understood systems will not perform well without appropriate input data. Information on climate, land cover, and demographic data must be available and accurate to produce useful results. Lastly, certain relationships between components of the model may change over time in ways that are difficult to predict. This includes possible evolution of the virus and the vector, changes in the land use or land cover of an area, and the behavior of human populations. Evaluating model results can also be difficult. Factors that may confound the association between climate change and DF incidence include improvements in surveillance that increase the ascertainment of DF cases, making it difficult to determine if increased cases are related to improved surveillance or increases in regional or global temperatures. Therefore, although still an important and useful tool, the limitations of process-based models need to be considered, and despite the models described above having been successfully used to simulate past vector dynamics and DF epidemics, their utility for predicting future occurrences is untested.

33Some studies suggest that climate change will not necessarily result in significant changes in the range and incidence of DF, especially in developed countries. compared DF incidence levels on either side of the Texas–Mexico border and concluded that although mosquito levels were similar, the risk of DENV transmission was far lower in Texas than in Mexico because human–vector contact was reduced due to the prevalence of well-sealed air-conditioned buildings, less outdoor exposure, and socioeconomic factors. Although not the focus of this review, the potential importance of socioeconomic factors should not be underestimated; clearly, these factors can have significant effects. In addition, we recognize that both mosquitoes and DENV may adapt to climate change in ways we cannot currently predict. However, the literature from other disease models suggests that the magnitude of these influences may vary by the intensity and types of climatic changes that occur in a given location. These changes may occur due to direct influences on the evolution of the vector and infectious agent but may also be related to changes in viral diversity associated with increasing or decreasing levels of DENV transmission.

34Previous studies have shown that climate exerts a critical influence on the spatial and temporal extent of DF. However, future studies need to better capture the effects of environmental factors on the ecology of DENV. Here we briefly discuss two examples of environmental influences that need to be resolved in future studies of climate and DENV transmission risk.

35The assumption that a vector will always colonize new habitats if temperature tolerances allow is simplistic. Although mosquitoes transmitting disease are unlikely to be limited by host ranges (because they often feed primarily on humans), they may be limited by competition. For example in Florida, Ae. aegypti populations have been displaced spatially and/or temporally from some locations and replaced by Ae. albopictus, especially in rural settings, suggesting that Ae. albopictus may be a better competitor for larval habitat under certain conditions. Although both of these mosquitoes are DENV vectors, their competence is variable. Ae. albopictus tends to be a more generalist feeder, but it prefers human hosts for blood meals when available. Studies also suggest that Ae. albopictus is less susceptible to DENV infection and dissemination to the salivary glands. Physical barriers such as large water bodies, mountains, or deserts may also restrict species dispersion.

36The effect of climate on the virus itself also has received little attention in the literature. Vector abundance indices are generally taken as the only measure of DENV transmission potential. Because climate exerts a major influence on mosquito population dynamics, studies focusing on climate–disease associations often choose to model vectors. However, virus dynamics within the mosquito must also be considered., for example, used the temperature dependence of the EIP to project DENV transmission rates in Europe under various climate scenarios. Optimal temperatures for development of the vector are not necessarily the same as those for the virus (Figure 2). As a result, large vector populations may not be sufficient for transmitting DENV if viral replication is inhibited or if the lifespan of the mosquito is shorter than the EIP. Consequently, vector abundance/density may not always be appropriate proxy measurements of DENV transmission risk. The virus and vector may also adapt to changes in climate as they occur slowly over time, and thus, changes in the relationship between climate and DENV transmission may also occur.

37Future studies should focus on addressing these issues. DENV vector dispersal ability should be evaluated by inventorying the species currently inhabiting areas of concern and then assessing the likelihood of invasion by the new vector. Current mosquito population models can be made more sophisticated by including a viral component, as done by. This entails calculating viral development within mosquitoes and ensuring that models are sensitive to adult survival and biting behavior in relation to temperature and humidity. The resulting models would be capable of estimating populations of infectious mosquitoes, and not simply total mosquito populations. Lastly, climate data can be incorporated into vectorial capacity models, as was done in earlier studies.

38Many specific questions still need to be addressed. For instance: Do key processes identified in developing nations hold the same importance in developed nations? What is the best method of assessing climate effects on DENV transmission risk? Will human processes supersede environmental factors in dictating DF prevalence in some areas? And finally, can we enhance our understanding of DENV ecology by studying disease systems, and if so, how might we apply this knowledge to mitigate the effects of DENV on human populations?

39Although there has been much speculation on the connection between climate and DF occurrence, in the present review we have highlighted the need for research that produces more precise and stable results. Although climate variables strongly influence DENV and its vectors, caution must be taken when using only one element or connection to predict disease occurrence. Climate influences disease ecology at many levels, and the many nonlinearities and feedbacks present in the system create complex dynamics that are not easily modeled or understood. In addition, human factors, including behavior, immunity, and socioeconomic influences, also contribute to the complexity of these relations. Nonetheless, it may be possible to extract basic patterns and general predictions that could provide useful information for mitigating the effects of climate change on DF occurrences.

40Capturing all aspects of the disease is a daunting task, but newer techniques may help overcome the difficulties. Process-based models that incorporate a more holistic view of the viral ecology should be implemented as new information on the topic is obtained and computing power increases. The use of interdisciplinary approaches will ensure that studies focus on the interactions between the components of the disease system, in addition to studying each component in isolation. A better understanding of the influences of climate on disease ecology is needed to improve projections of future disease risk, thus enabling better preparation and improved strategies to limit DENV transmission.