The impact of climate suitability, urbanisation, and connectivity on the expansion of dengue in 21st century Brazil

Space-time dynamics of the dengue epidemic in Brazil, 2024: an insight for decision making

BACKGROUND

Dengue is a vector-borne viral infection caused by the dengue virus transmitted to humans primarily by Aedes aegypti. The year 2024 has been a historic year for dengue in Brazil, with the highest number of probable cases ever registered. Herein, we analyze the temporal trend and spatio-temporal dynamics of dengue cases in Brazil during the first nine epidemiological weeks (EW) of 2024.

METHODS

This is an ecological study, including all probable cases of dengue in Brazil during the period, carried out in two steps: time series analysis to assess the temporal trend and spatial analysis to identify high-risk clusters.

RESULTS

1,345,801 probable cases of dengue were reported. The regions with the highest increasing trend were the Northeast with an average epidemiologic week percent change (AEPC) of 52.4 (95% CI: 45.5-59.7; p < 0.001) and the South with 35.9 (95% CI: 27.7-44.5; p < 0.001). There was a statistically significant increasing trend in all states, except Acre (AEPC = -4.1; 95% CI: -16.3-10; p = 0.55), Amapá (AEPC = 1.3; 95% CI: -16.2-22.3; p = 0.9) and Espírito Santo (AEPC = 8.9; 95% CI: -15.7-40.6; p = 0.5). The retrospective space-time analysis showed a cluster within the Northeast, Central-West and Southeast regions, with a radius of 515.3 km, in which 1,267 municipalities and 525,324 of the cases were concentrated (RR = 6.3; p < 0.001). Regarding the spatial variation of the temporal trend, 21 risk areas were found, all of them located in Southeast or Central-West states. The area with the highest relative risk was Minas Gerais state, where 5,748 cases were concentrated (RR = 8.1; p < 0.001). Finally, a purely spatial analysis revealed 25 clusters, the one with the highest relative risk being composed of two municipalities in Acre (RR = 6.9; p < 0.001).

CONCLUSIONS

We described a detailed temporal-spatial analysis of dengue cases in the first EWs of 2024 in Brazil, which were mainly concentrated in the Southeast and Central-West regions. Overall, it is recommended that governments adopt public policies to control the the vector population in high-risk areas, as well as to prevent the spread of dengue fever to other areas of Brazil.

Demographic-environmental effect on dengue outbreaks in 11 countries

BACKGROUND

Dengue outbreaks are common in tropical or temperate countries, and climate change can exacerbate the problem by creating conditions conducive to the spread of mosquitoes and prolonging the transmission season. Warmer temperatures can allow mosquitoes to mature faster and increase their ability to spread disease. Additionally, changes in rainfall patterns can create more standing water, providing a breeding ground for mosquitoes.

OBJECTIVE

The objective of this study is to investigate the correlation between environmental and demographic factors and the dissemination of dengue fever. The study will use yearly data from 2000 to 2021 from 11 countries highly affected by dengue, considering multiple factors such as dengue cases, temperatures, precipitation, and population to better understand the impact of these variables on dengue transmission.

METHODS

In this research, Poisson regression (PR) and negative binomial regression (NBR) models are used to model count data and estimate the effect of different predictor variables on the outcome. Also, histogram plots and pairwise correlation plots are used to provide an initial overview of the distribution and relationship between the variables. Moreover, Goodness-of-fit tests, t-test analysis, diagnostic plots, influence plots, and residual vs. leverage plots are used to check the assumptions and validity of the models and identify any outliers or influential observations that may be affecting the results.

RESULTS

The findings indicate that mean temperature and log(Urban) had a positive impact on dengue infection rates, while maximum temperature, log(Precipitation), and population density had a negative impact. However, minimum temperature, log(Rural), and log(Total population) did not demonstrate any significant effects on the incidence of dengue.

CONCLUSION

The impact of demographic-environmental factors on dengue outbreaks in 11 Asian countries is illuminated by this study. The results highlight the significance of mean temperature (Tmean), maximum temperature (Tmax), log(Urban), log(Precipitation), and population density in influencing dengue incidence rates. However, further research is needed to gain a better understanding of the role of additional variables, such as immunity levels, awareness, and vector control measures, in the spread of dengue.

Serotype-specific clinical features and spatial distribution of dengue in northern Kerala, India

Background

Collection and compilation of spatial, meteorological, entomological, and virological data are critical in mitigating climate-sensitive emerging infections like dengue. This study was a holistic attempt to understand the dengue situation in the Kasaragod district of Kerala, India.

Methods

This cross-sectional study was conducted in 13 health institutions from June to July 2021. Adult patients presenting with fever and testing positive for NS1 ELISA were subjected to Dengue RT-PCR and serotyping. The spatial and clinical features of the RT-PCR-positive patients, the district's meteorological data, and the vector indices were studied.

Results

The pre-epidemic months were marked by intermittent rainfall, peak ambient temperature and high larval indices. Among the 136 dengue RT-PCR patients studied, 41.2% had DENV2 followed by DENV1 (22.8%), DENV3 (5.9%) and DENV4 (4.4%); with 25% mixed infections. DENV1 showed a higher risk of gastrointestinal manifestations (80.6%, p=0.019) and musculoskeletal symptoms (77.4%, p=0.026) compared with other serotypes.

Conclusions

In the context of dengue hyperendemicity, the possibility of an emerging serotype's dominance coupled with the mixing up of strains should warn the health system regarding future outbreaks. Furthermore, the study emphasizes the importance of monitoring larval indices and the window of opportunity to intervene between environmental predictors and dengue outbreaks.

Exploring the urban arbovirus landscape in Rio de Janeiro, Brazil: transmission dynamics and patterns of disease spread

Background

This study focuses on urban arboviruses, specifically dengue (DENV), chikungunya (CHIKV), and Zika (ZIKV), which pose a significant public health challenge in Rio de Janeiro state, Southeast Brazil. In our research, we highlight critical findings on the transmission dynamics of these arboviruses in Rio de Janeiro, identifying distinct patterns of disease spread.

Methods

By combining genomic data with case reports from the Brazilian Ministry of Health, we have analysed the phylogenetics, prevalence and spatial distribution of these endemic viruses within the state.

Findings

Our results revealed sustained DENV transmission primarily in the northern part of the state, a significant ZIKV epidemic in 2016 affecting all mesoregions, and two major CHIKV outbreaks in 2018 and 2019, predominantly impacting the northern and southern areas. Our analysis suggests an inverse relationship between arboviral case incidence and urban density, with less populous regions experiencing higher transmission rates, potentially attributed to a complex interplay of factors such as the efficacy of vector control measures, environmental conditions, local immunity levels, and human mobility. Furthermore, our investigation unveiled distinct age and gender trends among affected individuals. Notably, dengue cases were predominantly observed in young adults aged 32, while chikungunya cases were more prevalent among individuals over 41. In contrast, cases of ZIKV were concentrated around the 33-year age group. Intriguingly, females accounted for nearly 60% of the cases, suggesting a potential gender-based difference in infection rates.

Interpretation

Our findings underscore the complexity of arbovirus transmission and the need for interventions tailored to different geographical mesoregions. Enhanced surveillance and genomic sequencing will be essential for a deeper, more nuanced understanding of regional arbovirus dynamics. Identifying potential blind spots within the state will be pivotal for developing and implementing more effective public health strategies, specifically designed to address the unique challenges posed by these viruses throughout the state.

Funding

This study was supported by the National Institutes of Health USA grant U01 AI151698 for the United World Arbovirus Research Network (UWARN) and the CRP-ICGEB RESEARCH GRANT 2020 Project CRP/BRA20-03.

The macroeconomic impact of a dengue outbreak: Case studies from Thailand and Brazil

BACKGROUND

Dengue is spreading in (sub)tropical areas, and half of the global population is at risk. The macroeconomic impact of dengue extends beyond healthcare costs. This study evaluated the impact of dengue on gross domestic product (GDP) based on approaches tailored to two dengue-endemic countries, Thailand and Brazil, from the tourism and workforce perspectives, respectively.

FINDINGS

Because the tourism industry is a critical economic sector for Thailand, lost tourism revenues were estimated to analyze the impact of a dengue outbreak. An input-output model estimated that the direct effects (on international tourism) and indirect effects (on suppliers) of dengue on tourism reduced overall GDP by 1.43 billion US dollars (USD) (0.26%) in the outbreak year 2019. The induced effect (reduced employee income/spending) reduced Thailand's GDP by 375 million USD (0.07%). Overall, lost tourism revenues reduced Thailand's GDP by an estimated 1.81 billion USD (0.33%) in 2019 (3% of annual tourism revenue). An inoperability input-output model was used to analyze the effect of workforce absenteeism on GDP due to a dengue outbreak in Brazil. This model calculates the number of lost workdays associated with ambulatory and hospitalized dengue. Input was collected from state-level epidemiological and economic data for 2019. An estimated 22.4 million workdays were lost in the employed population; 39% associated with the informal sector. Lost workdays due to dengue reduced Brazil's GDP by 876 million USD (0.05%).

CONCLUSIONS

The economic costs of dengue outbreaks far surpass the direct medical costs. Dengue reduces overall GDP and inflicts national economic losses. With a high proportion of the population lacking formal employment in both countries and low income being a barrier to seeking care, dengue also poses an equity challenge. A combination of public health measures, like vector control and vaccination, against dengue is recommended to mitigate the broader economic impact of dengue.

Human movement and environmental barriers shape the emergence of dengue

Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown. Further, no analytical framework exists to examine their roles. Here we develop a dynamic modelling approach for infectious diseases that explicitly models both connectivity via human movement and environmental suitability interactions. We apply it to better understand recently observed (1995-2019) patterns as well as predict past unobserved (1983-2000) and future (2020-2039) spread of dengue in Mexico and Brazil. We find that these models can accurately reconstruct long-term spread pathways, determine historical origins, and identify specific routes of invasion. We find early dengue invasion is more heavily influenced by environmental factors, resulting in patchy non-contiguous spread, while short and long-distance connectivity becomes more important in later stages. Our results have immediate practical applications for forecasting and containing the spread of dengue and emergence of new serotypes. Given current and future trends in human mobility, climate, and zoonotic spillover, understanding the interplay between connectivity and environmental suitability will be increasingly necessary to contain emerging and re-emerging pathogens.

The potential habitat and environmental fitness change of Aedes albopictus in Western Eurasia for 2081-2100

BACKGROUND OBJECTIVES

The range of Aedes albopictus, the most important vector mosquito in Western Eurasia is growing due to climate change. However, it is not known how it will influence the habitats occupied by the species and its environmental fitness within its future range.

METHODS

To study this question, the habitat characteristic of the mosquito was investigated for 2081-2100.

RESULTS

The models suggest a notable future spread of the mosquito in the direction of Northern Europe and the parallel northward and westward shift of the southern and eastern potential occurrences of the mosquito. The models suggest a notable increase in generation numbers in the warmest quarter, which can reach 4-5 generations in the peri-Mediterranean region. However, both the joint survival rate of larvae and pupae and the number of survival days of adults in the warmest quarter exhibit decreasing values, as does the potential disappearance of the mosquito in the southern regions of Europe and Asia Minor, along with the growing atmospheric CO2 concentration-based scenarios.

INTERPRETATION CONCLUSION

While in 1970-2000 Aedes albopictus mainly occupied the hot and warm summer temperate regions of Europe, the species will inhabit dominantly the cool summer temperate (oceanic) and the humid continental climate territories of North and North-Eastern Europe in 2081-2100.

Climate change, thermal anomalies, and the recent progression of dengue in Brazil

Dengue is rapidly expanding its transmission area across Brazil and much of South America. In this study, data-mining techniques were used to identify climatic and demographic indicators that could explain the recent (2014-2020) and simultaneous trends of expansion and exacerbation of the incidence in some regions of Brazil. The previous circulation of the virus (dengue incidence rates between 2007 and 2013), urbanization, and the occurrence of temperature anomalies for a prolonged period were the main factors that led to increased incidence of dengue in the central region of Brazil. Regions with high altitudes, which previously acted as a barrier for dengue transmission, became areas of high incidence rates. The algorithm that was developed during this study can be utilized to assess future climate scenarios and plan preventive actions.

Interactions between climate change, urban infrastructure and mobility are driving dengue emergence in Vietnam

Dengue is expanding globally, but how dengue emergence is shaped locally by interactions between climatic and socio-environmental factors is not well understood. Here, we investigate the drivers of dengue incidence and emergence in Vietnam, through analysing 23 years of district-level case data spanning a period of significant socioeconomic change (1998-2020). We show that urban infrastructure factors (sanitation, water supply, long-term urban growth) predict local spatial patterns of dengue incidence, while human mobility is a more influential driver in subtropical northern regions than the endemic south. Temperature is the dominant factor shaping dengue's distribution and dynamics, and using long-term reanalysis temperature data we show that warming since 1950 has expanded transmission risk throughout Vietnam, and most strongly in current dengue emergence hotspots (e.g., southern central regions, Ha Noi). In contrast, effects of hydrometeorology are complex, multi-scalar and dependent on local context: risk increases under either short-term precipitation excess or long-term drought, but improvements in water supply mitigate drought-associated risks except under extreme conditions. Our findings challenge the assumption that dengue is an urban disease, instead suggesting that incidence peaks in transitional landscapes with intermediate infrastructure provision, and provide evidence that interactions between recent climate change and mobility are contributing to dengue's expansion throughout Vietnam.

Prevalence and Associated Factors of Dengue Virus Circulation in the Rural Community, Handeni District in Tanga, Tanzania

Dengue virus is among the most important re-emerging arbovirus that causes global public health attention. Dengue has historically been thought of as an urban disease that frequently occurs in rapidly urbanized settings. However, dengue has become more widespread in rural regions in recent years. Understanding the changing dengue epidemiology in different geographical settings is important for targeted intervention. In Tanzania, dengue fever is not frequently reported because of the poor surveillance infrastructure, underestimation, and a lack of consideration of dengue as a priority. Therefore, the true burden as well as the risk factors for increased transmission has not been fully ascertained, particularly in rural areas. A cross-sectional community-based study was conducted in June 2021, involving a total of 362 participants of all age groups. We investigated the prevalence of acute dengue infection, seroprevalence, and associated factors among the community in three villages of the rural Handeni district. The prevalence of acute dengue infection (based on PCR) was 2.2% (8/362). Dengue-specific IgM and IgG antibodies were detected in 3.3% (12/362) and 5.2% (19/362) of the participants, respectively. Adult participants who were having vegetation around their houses were more likely to be DENV seropositive (AOR = 2.4, CI = 1.88-4.18, p value = 0.05). Children living in houses with garbage pit around their households were less likely to be DENV seropositive (AOR = 0.13, CI = 0.03-0.56, p value <0.01). DENV continues to circulate in rural Tanzania, causes an alarming situation, and necessitates prompt public health action to enhance vector surveillance and control in rural communities.

Arbovirus surveillance in mosquitoes: Historical methods, emerging technologies, and challenges ahead

Arboviruses cause millions of infections each year; however, only limited options are available for treatment and pharmacological prevention. Mosquitoes are among the most important vectors for the transmission of several pathogens to humans. Despite advances, the sampling, viral detection, and control methods for these insects remain ineffective. Challenges arise with the increase in mosquito populations due to climate change, insecticide resistance, and human interference affecting natural habitats, which contribute to the increasing difficulty in controlling the spread of arboviruses. Therefore, prioritizing arbovirus surveillance is essential for effective epidemic preparedness. In this review, we offer a concise historical account of the discovery and monitoring of arboviruses in mosquitoes, from mosquito capture to viral detection. We then analyzed the advantages and limitations of these traditional methods. Furthermore, we investigated the potential of emerging technologies to address these limitations, including the implementation of next-generation sequencing, paper-based devices, spectroscopic detectors, and synthetic biosensors. We also provide perspectives on recurring issues and areas of interest such as insect-specific viruses.

A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk

BACKGROUND

Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used.

METHODS

We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.).

RESULTS

We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures.

CONCLUSIONS

Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.

Projecting the future incidence and burden of dengue in Southeast Asia

The recent global expansion of dengue has been facilitated by changes in urbanisation, mobility, and climate. In this work, we project future changes in dengue incidence and case burden to 2099 under the latest climate change scenarios. We fit a statistical model to province-level monthly dengue case counts from eight countries across Southeast Asia, one of the worst affected regions. We project that dengue incidence will peak this century before declining to lower levels with large variations between and within countries. Our findings reveal that northern Thailand and Cambodia will show the biggest decreases and equatorial areas will show the biggest increases. The impact of climate change will be counterbalanced by income growth, with population growth having the biggest influence on increasing burden. These findings can be used for formulating mitigation and adaptation interventions to reduce the immediate growing impact of dengue virus in the region.

Spatial and temporal analyses of the influences of meteorological and environmental factors on Aedes albopictus (Diptera: Culicidae) population dynamics during the peak abundance period at a city scale

Aedes albopictus (Diptera: Culicidae) is a major vector of multiple diseases. While vaccines have been developed, preventing these Aedes-borne diseases continues to primarily depend on monitoring and controlling the vector population. Despite increasing research on the impacts of various factors on Ae. albopictus population dynamics, there is still no consensus on how meteorological or environmental factors affect vector distribution. In this study, the relationships between mosquito abundance and meteorological and environmental indicators were examined at the town level based on data collected from July to September, the peak abundance period of 2019 in Shanghai. In addition to performing Poisson regression, we employed the geographically weighted Poisson regression model to account for spatial dependency and heterogeneity. The result showed that the environmental factors (notably human population density, the Normalized Difference Vegetation Index (NDVI), socioeconomic deprivation, and road density) had more significant impacts than the meteorological variables in accounting for the spatial variation of mosquito abundance at a city scale. The dominant environmental variable differed in urban and rural places. Furthermore, our findings indicated that deprived townships are more susceptible to higher vector densities compared to non-deprived townships. Therefore, it is crucial not only to allocate more resources but also to increase attention towards controlling the vectors responsible for their transmission in these townships.

Relationship between Climate Variables and Dengue Incidence in Argentina

BACKGROUND

Climate change is an important driver of the increased spread of dengue from tropical and subtropical regions to temperate areas around the world. Climate variables such as temperature and precipitation influence the dengue vector's biology, physiology, abundance, and life cycle. Thus, an analysis is needed of changes in climate change and their possible relationships with dengue incidence and the growing occurrence of epidemics recorded in recent decades.

OBJECTIVES

This study aimed to assess the increasing incidence of dengue driven by climate change at the southern limits of dengue virus transmission in South America.

METHODS

We analyzed the evolution of climatological, epidemiological, and biological variables by comparing a period of time without the presence of dengue cases (1976-1997) to a more recent period of time in which dengue cases and important outbreaks occurred (1998-2020). In our analysis, we consider climate variables associated with temperature and precipitation, epidemiological variables such as the number of reported dengue cases and incidence of dengue, and biological variables such as the optimal temperature ranges for transmission of dengue vector.

RESULTS

The presence of dengue cases and epidemic outbreaks are observed to be consistent with positive trends in temperature and anomalies from long-term means. Dengue cases do not seem to be associated with precipitation trends and anomalies. The number of days with optimal temperatures for dengue transmission increased from the period without dengue cases to the period with occurrences of dengue cases. The number of months with optimal transmission temperatures also increased between periods but to a lesser extent.

CONCLUSIONS

The higher incidence of dengue virus and its expansion to different regions of Argentina seem to be associated with temperature increases in the country during the past two decades. The active surveillance of both the vector and associated arboviruses, together with continued meteorological data collection, will facilitate the assessment and prediction of future epidemics that use trends in the accelerated changes in climate. Such surveillance should go hand in hand with efforts to improve the understanding of the mechanisms driving the geographic expansion of dengue and other arboviruses beyond the current limits. https://doi.org/10.1289/EHP11616.

Urban vectors of Chagas disease in the American continent: A systematic review of epidemiological surveys

BACKGROUND

Chagas is a complex and multidimensional socio-environmental health phenomenon, in which different components converge and interact. Historically, this disease was associated with insect vectors found in the rural environment. However, in the Americas, we are currently facing a new paradigm, in which different scenarios allow maintaining the vectorial transmission of the parasite through triatomine populations that either occasionally enter the dwellings or colonize urban environments.

METHODOLOGY/PRINCIPAL FINDINGS

Records of scientific reports available in the PubMed and LILACS search engines were retrieved, using three criteria according to the main triatomine genera of epidemiological importance and to the general scientific production on Chagas disease in urban contexts. Results showed that records on the occurrence of vectors in urban dwellings began to increase in the last three decades. Results also showed that the main species of triatomines collected inside dwellings (18 in total) belong mainly to the genera Triatoma and Panstrongylus, with most species (16/18, 88.8%) infected with the parasite, and that infestation of triatomine species occurs in all types of cities (small, medium and large, including megalopolises), from Argentina to the USA.

CONCLUSIONS/SIGNIFICANCE

Urban Chagas represents a new challenge that adds a different dimension to the problem of Chagas disease due to the particular characteristics of the lifestyle in urban agglomerates. The new scenario will require adaptations of the programs of control of vector to this shift from rural to urban settlements.

A Bayesian modelling framework to quantify multiple sources of spatial variation for disease mapping

Spatial connectivity is an important consideration when modelling infectious disease data across a geographical region. Connectivity can arise for many reasons, including shared characteristics between regions and human or vector movement. Bayesian hierarchical models include structured random effects to account for spatial connectivity. However, conventional approaches require the spatial structure to be fully defined prior to model fitting. By applying penalized smoothing splines to coordinates, we create two-dimensional smooth surfaces describing the spatial structure of the data while making minimal assumptions about the structure. The result is a non-stationary surface which is setting specific. These surfaces can be incorporated into a hierarchical modelling framework and interpreted similarly to traditional random effects. Through simulation studies, we show that the splines can be applied to any symmetric continuous connectivity measure, including measures of human movement, and that the models can be extended to explore multiple sources of spatial structure in the data. Using Bayesian inference and simulation, the relative contribution of each spatial structure can be computed and used to generate hypotheses about the drivers of disease. These models were found to perform at least as well as existing modelling frameworks, while allowing for future extensions and multiple sources of spatial connectivity.

Optimal Validated Multi-Factorial Climate Change Risk Assessment for Adaptation Planning and Evaluation of Infectious Disease: A Case Study of Dengue Hemorrhagic Fever in Indonesia

(1) Background: This paper will present an elaboration of the risk assessment methodology by Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ), Eurac Research and United Nations University Institute for Environment and Human Security (UNU-EHS) for the assessment of dengue. (2) Methods: We validate the risk assessment model by best-fitting it with the number of dengue cases per province using the least-square fitting method. Seven out of thirty-four provinces in Indonesia were chosen (North Sumatra, Jakarta Capital, West Java, Central Java, East Java, Bali and East Kalimantan). (3) Results: A risk assessment based on the number of dengue cases showed an increased risk in 2010, 2015 and 2016 in which the effects of El Nino and La Nina extreme climates occurred. North Sumatra, Bali, and West Java were more influenced by the vulnerability component, in line with their risk analysis that tends to be lower than the other provinces in 2010, 2015 and 2016 when El Nino and La Nina occurred. (4) Conclusion: Based on data from the last ten years, in Jakarta Capital, Central Java, East Java and East Kalimantan, dengue risks were mainly influenced by the climatic hazard component while North Sumatra, Bali and West Java were more influenced by the vulnerability component.

The impact of climate suitability, urbanisation, and connectivity on the expansion of dengue in 21st century Brazil

Dengue is hyperendemic in Brazil, with outbreaks affecting all regions. Previous studies identified geographical barriers to dengue transmission in Brazil, beyond which certain areas, such as South Brazil and the Amazon rainforest, were relatively protected from outbreaks. Recent data shows these barriers are being eroded. In this study, we explore the drivers of this expansion and identify the current limits to the dengue transmission zone. We used a spatio-temporal additive model to explore the associations between dengue outbreaks and temperature suitability, urbanisation, and connectivity to the Brazilian urban network. The model was applied to a binary outbreak indicator, assuming the official threshold value of 300 cases per 100,000 residents, for Brazil’s municipalities between 2001 and 2020. We found a nonlinear relationship between higher levels of connectivity to the Brazilian urban network and the odds of an outbreak, with lower odds in metropoles compared to regional capitals. The number of months per year with suitable temperature conditions for Aedes mosquitoes was positively associated with the dengue outbreak occurrence. Temperature suitability explained most interannual and spatial variation in South Brazil, confirming this geographical barrier is influenced by lower seasonal temperatures. Municipalities that had experienced an outbreak previously had double the odds of subsequent outbreaks. We identified geographical barriers to dengue transmission in South Brazil, western Amazon, and along the northern coast of Brazil. Although a southern barrier still exists, it has shifted south, and the Amazon no longer has a clear boundary. Few areas of Brazil remain protected from dengue outbreaks. Communities living on the edge of previous barriers are particularly susceptible to future outbreaks as they lack immunity. Control strategies should target regions at risk of future outbreaks as well as those currently within the dengue transmission zone.

Dengue is a mosquito-borne disease that has expanded rapidly around the world due to increased urbanisation, global mobility and climate change. In Brazil, geographical barriers to dengue transmission exist, beyond which certain areas including South Brazil and the Amazon rainforest are relatively protected from outbreaks. However, we found that the previous barrier in South Brazil has shifted further south as a result of increased temperature suitability. The previously identified barrier protecting the western Amazon no longer exists. This is particularly concerning as we found dengue outbreaks tend to become established in areas after introduction. Highly influential cities with many transport links had increased odds of an outbreak. However, the most influential cities had lower odds of an outbreak than cities connected regionally. This study highlights the importance of monitoring the expansion of dengue outbreaks and designing disease prevention strategies for areas at risk of future outbreaks as well as areas in the established dengue transmission zone.