Dengue fever, the most common mosquito-borne viral disease globally, affects an estimated 60 million people annually across 130 countries. The disease burden has significantly increased in recent decades, with Southeast Asia, South America, and the Western Pacific bearing the brunt of reported cases. While dengue is endemic in many tropical and subtropical regions, its geographical range is expanding into more temperate climates, evidenced by epidemic activity in parts of North America and a rise in autochthonous transmission in southern Europe. This expansion is attributed to various factors, including changes in climate (temperature and humidity), land use, urbanization, and human movement, which increase the proximity between vectors and humans and favor the spread of vector species. The geographical range, timing, and intensity of dengue transmission are determined by the interplay of environmental factors (temperature, humidity, water sources) and anthropogenic factors (urbanization, population growth). Climate significantly impacts dengue transmission by influencing mosquito lifespan, aquatic developmental rates, viral incubation period, and biting rate. Previous studies have developed dengue transmission suitability measures, primarily using mechanistic models that quantify transmission potential based on temperature and humidity data. These models offer a higher spatial and temporal resolution compared to statistical approaches, accurately capturing the timing and spatial distribution of dengue infections across diverse climate conditions. However, less attention has been given to how past environmental changes may have influenced current geographical limits and epidemic activity. This study uses a mechanistic dengue suitability measure (Index P) to quantify local and global changes in climate suitability for dengue virus transmission over the last four decades, and analyzes how changes in climate and population growth have contributed to the global population living in areas with favorable environmental conditions for dengue virus transmission.

Numerous studies have investigated the impact of climate change and other factors on dengue virus transmission. Several studies have used mechanistic models to evaluate the relationship between climate variables and mosquito-borne virus transmission potential. These models consider factors such as temperature and humidity, which affect mosquito survival, reproduction, and viral incubation period. However, these studies often focus on specific regions or lack sufficient validation across diverse geographical areas. Statistical approaches like species distribution modeling have also been used, but these may have limitations in capturing non-linear interactions between climate variables and transmission dynamics and may struggle with limited reporting from low-transmission areas. Existing studies have made progress in estimating future dengue risk using modeling techniques but underemphasized the influence of past environmental changes on current dengue transmission patterns. This research builds on previous modeling efforts by employing a mechanistic dengue transmission suitability measure (Index P) to analyze changes in climate suitability at a higher spatial and temporal resolution over the past four decades, specifically addressing the impact of past environmental changes on the current geographic distribution and epidemic activity of dengue.

This study utilized a mechanistic dengue suitability measure called Index P, which is based on temperature and relative humidity data and accounts for their effects on mosquito-viral traits. Spatiotemporal Index P data for 186 countries and territories from 1979 to 2022 were obtained from previously published research. The data has a monthly time resolution and a spatial resolution of 360 arcseconds (approximately 11 km at the equator). The analysis focused on *Ae. aegypti* mosquitoes, the primary vector for dengue transmission, due to the availability of detailed empirical data on the relationship between meteorological variables and vector-viral traits. The average climate suitability per pixel from 1979 to 2022 was calculated to highlight areas suitable for transmission throughout the year. The relationship between estimated climate suitability and dengue incidence was characterized using reported dengue case counts from several countries with robust surveillance data (Brazil, Colombia, Costa Rica, Vietnam, Taiwan, and Thailand). A censored linear regression model was fitted for each country to quantify the effect of climate suitability on dengue incidence. The absolute change in climate suitability from 1979-1983 (past) to 2018-2022 (present) was estimated, identifying areas with increases or decreases in suitability. Long-term trends in monthly time series of suitability were quantified using a seasonal Mann-Kendall test. Areas that transitioned from low to high suitability (expansion) and high to low suitability (contraction) were identified. The analysis incorporated human population data to calculate the total population living in high-risk areas (climate suitability > 0.5) in 1979-1983 and 2018-2022. To estimate the independent contribution of climate change and population growth, hypothetical scenarios were considered where either climate or population effects were held constant. Finally, the study stratified climate suitability changes by population density, economic income group, and climate zone to investigate the influence of various factors on dengue risk.

Globally, the average climate suitability for dengue transmission, as measured by Index P, showed increases in several regions including the southern United States, northeastern Brazil, western and southern Africa, the Indian subcontinent, Southeast Asia, and coastal areas of Europe. Conversely, decreases were observed in northern Australia, parts of South America, and northeastern Africa. Approximately 28.5% of total land area exhibited long-term changes in climate suitability. The proportion of land area with high climate suitability increased globally from 38.4% to 39.5%, representing an expansion of about 1.5 million km². The most significant increase was observed in Asia (0.8 million km²) and North America (0.6 million km²). Africa showed both expansion and contraction, with net change minimal. The proportion of the global population living in high-risk areas (climate suitability > 0.5) increased from 48.8% to 60.0%, representing an increase of 2.5 billion people. Population growth was the primary driver of this increase in the Global South, while climate suitability expansion drove the change in the Global North. Independent analyses showed that population effects contributed 2.16 billion more people in high-risk areas globally, compared to 182 million for climate effects alone. The study also examined shifts in climate suitability stratified by population density, economic income group, and climate zone. High and very high density areas saw increases in high climate suitability across most regions except Africa. While lower-income economies had higher proportions of favorable climate conditions, upper-middle and high-income economies experienced larger relative increases in climate suitability. Temperate climate zones showed the largest increase in high climate suitability.

This study's findings provide valuable insights into the drivers of increased dengue risk globally. The expansion of climate suitability into previously unsuitable regions, particularly in the Global North, highlights the impact of climate change on dengue transmission. The significant population growth in historically high-suitability areas, especially in the Global South, further amplifies dengue risk. The interplay of climate change and population growth differentially impacts dengue risk across regions, with population growth being the dominant factor in the Global South, and climate suitability expansion playing a larger role in the Global North. The observed increases in climate suitability in some areas align with recent reports of increased local transmission or larger outbreaks. The relatively low and unchanged climate suitability across much of Europe contrasts with some future projections, suggesting that the risk of large-scale dengue outbreaks in Europe remains limited for now, even considering a recent rise in localized transmission events. The study’s findings highlight the importance of considering both climate change and population dynamics when assessing dengue risk and designing public health interventions. These factors should also inform resource allocation and vaccination strategies globally, prioritizing regions experiencing substantial population increases within areas of high climate suitability.

This study demonstrates a substantial increase in the global population residing in areas with high climate suitability for dengue virus transmission, driven by differing mechanisms in the Global South (population growth) and the Global North (climate suitability expansion). The findings highlight the crucial interplay between climate change and population dynamics in shaping dengue risk and underscore the need for region-specific strategies addressing this growing public health challenge. Future research should explore the influence of additional factors like precipitation, altitude, urbanization, and vegetation, and further investigate the interaction between long-term climate change trends, extreme climate events, and global teleconnection phenomena on dengue transmission.

The study's suitability index, while robust, relies on temperature and humidity data and does not account for the presence of the mosquito vector, human host, or virus. It primarily focuses on *Ae. aegypti*, neglecting the contribution of *Ae. albopictus*. Differences between estimated climate suitability and reported cases may arise in certain environments (e.g., arid regions, sparsely populated areas). The model doesn't incorporate other factors influencing transmission, such as precipitation, altitude, urbanization, and vegetation, and it doesn't account for cyclic climate phenomena or climate extremes. The estimates reflect the recent past and may not fully capture future trends due to accelerating global warming.