Dengue is a product of the environment: an approach to the impacts of the environment on the Aedes aegypti mosquito and disease cases.

Dengue is an arbovirus infection whose etiologic agent is transmitted by the Aedes aegypti mosquito. Since the early 1980s, when the circulation of the dengue virus (DENV) was confirmed in Brazil, the disease has become a growing multifactorial public health problem. This article presented the main factors that have contributed to the frequent dengue epidemics in recent years, such as the behavior of the vector, climate change, and social, political, and economic aspects. The intersection between these different factors in the dynamics of the disease is highlighted, including the increase in the mosquito population due to higher temperatures and rainy periods, as well as the influence of socioeconomic conditions on the incidence of dengue. Some mosquito control strategies are also addressed, including the use of innovative technologies such as drones and the Wolbachia bacterium, as well as the hope represented by the dengue vaccine. Nevertheless, the need for integrated and effective public policies to reduce social inequalities and the impacts of climate change on the spread of dengue is emphasized.

Beyond the biting - limited impact of explicit mosquito dynamics in dengue models.

Mathematical models play a crucial role in assisting public health authorities in timely disease control decision-making. For vector-borne diseases, integrating host and vector dynamics into models can be highly complex, particularly due to limited data availability, making system validation challenging. In this study, two compartmental models akin to the SIR type were developed to characterize vector-borne infectious disease dynamics. Motivated by dengue fever epidemiology, the models varied in their treatment of vector dynamics, one with implicit vector dynamics and the other explicitly modeling mosquito-host contact. Both considered temporary immunity after primary infection and disease enhancement in secondary infection, analogous to the temporary cross-immunity and the Antibody-dependent enhancement biological processes observed in dengue epidemiology. Qualitative analysis using bifurcation theory and numerical experiments revealed that the immunity period and disease enhancement outweighed the impact of explicit vector dynamics. Both models demonstrated similar bifurcation structures, indicating that explicit vector dynamics are only justified when assessing the effects of vector control methods. Otherwise, the extra equations are irrelevant, as both systems display similar dynamics scenarios. The study underscores the importance of using simple models for mathematical analysis, initiating crucial discussions among the modeling community in vector-borne diseases.

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.

Determining dengue infection risk in the Colombo district of Sri Lanka by inferencing the genetic parameters of Aedes mosquitoes.

BACKGROUND: For decades, dengue has posed a significant threat as a viral infectious disease, affecting numerous human lives globally, particularly in tropical regions, yet no cure has been discovered. The genetic trait of vector competence in Aedes mosquitoes, which facilitates dengue transmission, is difficult to measure and highly sensitive to environmental changes. METHODS: In this study we attempt, for the first time in a non-laboratory setting, to quantify the vector competence of Aedes mosquitoes assuming its homogeneity across both species; aegypti and albopictus and across the four Dengue serotypes. Estimating vector competence in relation to varying rainfall patterns was focused in this study to showcase the changes in this vector trait with respect to environmental variables. We quantify it using an existing mathematical model originally developed for malaria in a Bayesian inferencing setup. We conducted this study in the Colombo district of Sri Lanka where the highest number of human populations are threatened with dengue. Colombo district experiences continuous favorable temperature and humidity levels throughout the year creating ideal conditions for Aedes mosquitoes to thrive and transmit the Dengue disease. Therefore we only used the highly variable and seasonal rainfall as the primary environmental variable as it significantly influences the number of breeding sites and thereby impacting the population dynamics of Aedes. RESULTS: Our research successfully deduced vector competence values for the four identified seasons based on Monsoon rainfalls experienced in Colombo within a year. We used dengue data from 2009 - 2022 to infer the estimates. These estimated values have been corroborated through experimental studies documented in the literature, thereby validating the malaria model to estimate vector competence for dengue disease. CONCLUSION: Our research findings conclude that environmental conditions can amplify vector competence within specific seasons, categorized by their environmental attributes. Additionally, the deduced vector competence offers compelling evidence that it impacts disease transmission, irrespective of geographical location, climate, or environmental factors.

Peri-domestic entomological surveillance using private traps allows detection of dengue virus in Aedes albopictus during an autochthonous transmission event in mainland France, late summer 2023.

While locally-acquired dengue virus (DENV) human infections occur in mainland France since 2010, data to identify the mosquito species involved and to trace the virus are frequently lacking. Supported by a local network gathering public health agencies and research laboratories, we analysed, in late summer 2023, mosquitoes from privately-owned traps within a French urban neighbourhood affected by a dengue cluster. The cluster, in Auvergne-Rhône-Alpes, comprised three cases, including two autochthonous ones. Upon return from a recent visit to the French Caribbean Islands, the third case had consulted healthcare because of dengue-compatible symptoms, but dengue had not been recognised. For the two autochthonous cases, DENV-specific antibodies in serum or a positive quantitative PCR for DENV confirmed DENV infection. The third case had anti-flavivirus IgMs. No DENV genetic sequences were obtained from affected individuals but Aedes albopictus mosquitoes trapped less than 200 m from the autochthonous cases' residence contained DENV. Genetic data from the mosquito-derived DENV linked the cluster to the 2023-2024 dengue outbreak in the French Caribbean Islands. This study highlights the importance of raising mosquito-borne disease awareness among healthcare professionals. It demonstrates Ae. albopictus as a DENV vector in mainland France and the value of private mosquito traps for entomo-virological surveillance.

Effects of the El Niño-Southern Oscillation and seasonal weather conditions on Aedes aegypti infestation in the State of São Paulo (Brazil): A Bayesian spatio-temporal study.

BACKGROUND: Seasonal fluctuations in weather are recognized as factors that affect both Aedes (Ae.) aegypti mosquitoes and the diseases they carry, such as dengue fever. The El Niño-Southern Oscillation (ENSO) is widely regarded as one of the most impactful atmospheric phenomena on Earth, characterized by the interplay of shifting ocean temperatures, trade wind intensity, and atmospheric pressure, resulting in extensive alterations in climate conditions. In this study, we investigate the influence of ENSO and local weather conditions on the spatio-temporal variability of Ae. aegypti infestation index. METHODS: We collected seasonal entomological survey data of immature forms of Ae. aegypti mosquitoes (Breteau index), as well as data on temperature, rainfall and the Oceanic Niño Index (ONI) for the period 2008-2018 over the 645 municipalities of the subtropical State of São Paulo (Brazil). We grounded our analytical approach on a Bayesian framework and we used a hierarchical spatio-temporal model to study the relationship between ENSO tracked by ONI, seasonal weather fluctuations and the larval index, while adjusting for population density and wealth inequalities. RESULTS: Our results showed a relevant positive effect for El Niño on the Ae. aegypti larval index. In particular, we found that the number of positive containers would be expected to increase by 1.30-unit (95% Credible Intervals (CI): 1.23 to 1.37) with El Niño events (i.e., ≥ 1°C, moderate to strong) respect to neutral (and weak) events. We also found that seasonal rainfall exceeding 153.12 mm appears to have a notable impact on vector index, leading potentially to the accumulation of ample water in outdoor discarded receptacles, supporting the aquatic phase of mosquito development. Additionally, seasonal temperature above 23.30°C was found positively associated to the larval index. Although the State of São Paulo as a whole has characteristics favourable to proliferation of the vector, there were specific areas with a greater tendency for mosquito infestation, since the most vulnerable areas are predominantly situated in the central and northern regions of the state, with hot spots of abundance in the south, especially during El Niño events. Our findings also indicate that social disparities present in the municipalities contributes to Ae. aegypti proliferation. CONCLUSIONS: Considering the anticipated rise in both the frequency and intensity of El Niño events in the forthcoming decades as a consequence of climate change, the urgency to enhance our ability to track and diminish arbovirus outbreaks is crucial.

Vector competence of Aedes albopictus field populations from Reunion Island exposed to local epidemic dengue viruses.

Dengue virus (DENV) is the most prevalent mosquito-borne Flavivirus that affects humans worldwide. Aedes albopictus, which is naturally infected with the bacteria Wolbachia, is considered to be a secondary vector of DENV. However, it was responsible for a recent DENV outbreak of unprecedented magnitude in Reunion Island, a French island in the South West Indian Ocean. Moreover, the distribution of the cases during this epidemic showed a spatially heterogeneous pattern across the island, leading to questions about the differential vector competence of mosquito populations from different geographic areas. The aim of this study was to gain a better understanding of the vector competence of the Ae. albopictus populations from Reunion Island for local DENV epidemic strains, while considering their infection by Wolbachia. Experimental infections were conducted using ten populations of Ae. albopictus sampled across Reunion Island and exposed to three DENV strains: one strain of DENV serotype 1 (DENV-1) and two strains of DENV serotype 2 (DENV-2). We analyzed three vector competence parameters including infection rate, dissemination efficiency and transmission efficiency, at different days post-exposition (dpe). We also assessed whether there was a correlation between the density of Wolbachia and viral load/vector competence parameters. Our results show that the Ae. albopictus populations tested were not able to transmit the two DENV-2 strains, while transmission efficiencies up to 40.79% were observed for the DENV-1 strain, probably due to difference in viral titres. Statistical analyses showed that the parameters mosquito population, generation, dpe and area of sampling significantly affect the transmission efficiencies of DENV-1. Although the density of Wolbachia varied according to mosquito population, no significant correlation was found between Wolbachia density and either viral load or vector competence parameters for DENV-1. Our results highlight the importance of using natural mosquito populations for a better understanding of transmission patterns of dengue.

Circulating serotypes and genotypes of dengue virus during the 2023 outbreak in Eastern Nepal.

Dengue virus (DENV) is one of the most significant mosquito-borne diseases in Nepal. In 2023, DENV outbreaks began in Eastern Nepal, near the border with India, and rapidly spread nationwide. The study aims to describe the outbreak's epidemiological pattern, laboratory characteristics, DENV serotypes, and genotypes. A hospital-based cross-sectional study was conducted in four hospitals in Jhapa, Eastern Nepal, in 2023. Acute serum samples were obtained from dengue suspected patients within 7 days of illness and subjected to virus isolation, conventional and real-time polymerase chain reaction (RT-PCR), and phylogenetic analysis. Out of 60 samples, 42 (70 %), 11 (18.3 %) and 7 (11.7 %) were primary, secondary and non-dengue infection, respectively. Among 53 dengue confirmed patients, 46 (86.7 %) were positive for NS1 and 12 (22.6 %) were positive for both NS1 and IgM. Out of 42 dengue isolates, a new clade of the cosmopolitan genotype of DENV-2 was the most prevalent (28, 66.7 %), followed by genotype III of DENV-3 (11, 26.2 %) and genotype V of DENV-1 (3, 7.1 %). Genotype III of DENV-3 was first introduced in 2022-2023 in Nepal. Phylogenetic analysis of the E gene revealed the DENV-2 isolates from Nepal had 98 % homologous nucleotide similarity with the strains from India and Bangladesh. To our knowledge, this is the first report of circulating serotypes and genotypes of DENV in Jhapa. Integrating molecular findings into the dengue control plan can enhance surveillance efforts, monitor disease trends, and implement proactive measures to reduce the burden of dengue and prevent fatalities in future outbreaks.

[The epidemiological characteristics of the outbreak of Dengue fever in Fuzhou City from 2016 to 2023].

To analyze the epidemiological characteristics of dengue fever in Fuzhou City from 2016 to 2023, it was found that a total of 1 697 cases of Dengue fever (1 512 local cases and 185 imported cases) were reported in Fuzhou City from 2016 to 2023, and a total of 15 dengue-related public health emergencies were reported, with an average duration of the epidemic. The average duration of the epidemic was 71.6 days. Local dengue fever cases: the peak incidence period was concentrated in August-October, accounting for 96.69% (1 462/1 512); distributed in 10 counties and districts, the three counties with the highest annual average incidence rate were Minhou County (9.95/100 000), Cangshan District (6.03/100 000), and Taijiang District (5.58/100 000); in 2019 (Moran's I=0.18, P<0.05) and 2023 (Moran's I=0.5, P<0.05) the spatial distribution of local dengue fever cases in Fuzhou City showed a clustering pattern, with Gulou, Taijiang, Cangshan, and Jin'an districts as high-high clustering areas, and the outbreaks basically clustered in the urban areas; the median age was 47 years old, and the proportion of 40-70 years old was 50.93% (770/1 512). Among the local cases of Dengue fever, 81.15% (1 227/1 512) were unemployed, and 6.81% (103/1 512) were students with the highest proportion.The median time between onset diagnosis was 3.38 d, 6.67 d, 3.50 d, 3.75 d in 2016-2019, and 3.46 d in 2023, respectively, and the years of onset. The difference in the median time between onset and diagnosis was not statistically significant (χ²=8.556 4, P>0.05). Imported cases: mainly from Southeast Asian countries, Cambodia, Papua New Guinea, Indonesia accounted for the highest proportion of 62.70% (116/185); May to September is the active period of Aedes albopictus, and the results of Aedes albopictus resistance test showed that the mosquito larvae were sensitive to residual chlorpyrifos, and the Aedes albopictus adult mosquitoes showed sensitivity to two organophosphorus insecticides (chlorpyrifos, malathion), and to one type of Aedes albopictus adults were sensitive to two kinds of organophosphorus insecticides (chlorpyrifos, malathion) and a kind of pyrethroid carbamate insecticide (carbofuran).

Bayesian spatio-temporal analysis of dengue transmission in Lao PDR.

Dengue, a zoonotic viral disease transmitted by Aedes mosquitoes, poses a significant public health concern throughout the Lao People's Democratic Republic (Lao PDR). This study aimed to describe spatial-temporal patterns and quantify the effects of environmental and climate variables on dengue transmission at the district level. The dengue data from 2015 to 2020 across 148 districts of Lao PDR were obtained from the Lao PDR National Center for Laboratory and Epidemiology (NCLE). The association between monthly dengue occurrences and environmental and climate variations was investigated using a multivariable Zero-inflated Poisson regression model developed in a Bayesian framework. The study analyzed a total of 72,471 dengue cases with an incidence rate of 174 per 100,000 population. Each year, incidence peaked from June to September and a large spike was observed in 2019. The Bayesian spatio-temporal model revealed a 9.1% decrease (95% credible interval [CrI] 8.9%, 9.2%) in dengue incidence for a 0.1 unit increase in monthly normalized difference vegetation index at a 1-month lag and a 5.7% decrease (95% CrI 5.3%, 6.2%) for a 1 cm increase in monthly precipitation at a 6-month lag. Conversely, dengue incidence increased by 43% (95% CrI 41%, 45%) for a 1 °C increase in monthly mean temperature at a 3-month lag. After accounting for covariates, the most significant high-risk spatial clusters were detected in the southern regions of Lao PDR. Probability analysis highlighted elevated trends in 45 districts, emphasizing the importance of targeted control strategies in high-risk areas. This research underscores the impact of climate and environmental factors on dengue transmission, emphasizing the need for proactive public health interventions tailored to specific contexts in Lao PDR.

The greatest Dengue epidemic in Brazil: Surveillance, Prevention, and Control.

In this review, we discuss dengue surveillance, prevention, and control measures in Brazil. Data on dengue epidemics between 2000 and 2024 indicates an increase in the number of dengue cases and deaths. Global climate change is a key driver of this growth. Over the past 25 years, nearly 18 million Brazilians have been infected with the dengue virus, and the highest number of dengue cases in Brazil's history is projected to reach 2024. Dengue mortality in Brazil increased geographically over time. As of June, there were approximately 6 million probable cases and 4,000 confirmed deaths in Brazil, which represents the greatest dengue epidemic to date. Several technologies have been developed to control Aedes aegypti, including the deployment of Wolbachia-infected mosquitoes, indoor residual spraying, sterile insect techniques, and mosquito-disseminated insecticides. The Ministry of Health recommends integrating these technologies into health services. Brazil is the first country to incorporate the Takeda vaccine into its public health system, and the Butantan vaccine is currently undergoing Phase 3 clinical trials. Increasing the vaccination coverage and implementing novel Ae. aegypti control technologies could reduce the number of dengue cases in Brazil in the coming years. Community activities such as home cleaning and elimination of potential mosquito breeding sites, facilitated by social media and health education initiatives, must continue to achieve this reduction. Ultimately, a multisectoral approach encompassing sanitary improvements, mosquito control, vaccination, and community mobilization is crucial in the fight against dengue epidemics.

Impact of storm drains on the maintenance of dengue endemicity in Presidente Prudente, São Paulo, Brazil: a geospatial and epidemiologic approach.

Introduction: Dengue is a public health challenge worldwide. Brazil registered about 70% of cases in Latin America in 2023; in 2024, the country is experiencing an unprecedented increase in the number of infected individuals. By May 2024, more than 4 million people were infected. Our goal was to: (1) determine the epidemiology of dengue cases and their spatiotemporal distribution and (2) carry out a survey of the storm drains and through a geospatial analysis to determine their possible correlation with cases of dengue in Presidente Prudente, São Paulo, Brazil. Methods: Cases and information on the habitat of mosquito in the storm drain underground drainage system from 2020 to 2021 were obtained from public agencies. Larvae, pupae, and Ae. aegypti were identified according to species and described in taxonomic keys. Kernel density maps were constructed. Results: From 1996 to 2023, the prevalence of cases peaked in 2016 and 2019, and in 2023 reached alarming levels, and the city was considered hyperendemic. In 2021, 2,609 cases were registered with 2 clusters of high density. Of 5,492 storm drains analyzed, 18.0% were found to have water, 9.0% had larvae or pupae of Aedes aegypti and 91.0% were classified as dirty or damaged. A direct correlation between the kernel layer of cases in 2021 with the kernel layer of storm drains containing water (r = 0.651) and larvae and pupae (r = 0.576) was found, suggesting that storm drains are risk factors and have an impact on the maintenance of dengue endemicity. The high number of damaged units found demonstrated the lack of storm drain management, compromising the urban drainage system and possibly contributing to dengue outbreaks. Conclusion: Policymakers may use these findings to improve existing dengue control strategies focusing on the control of storm drains and increase local and global perspectives on reducing dengue outbreaks.

Dengue epidemic in China before 1978.

Dengue, an acute febrile disease transmitted by Aedes mosquitoes, is caused by the dengue virus (DENV), presenting a formidable challenge to global public health. By examining clues from ancient Chinese books and conducting a comprehensive review, this study elucidates the characteristics of potential dengue epidemics in China prior to 1978. This evidence indicates that China may not have experience dengue epidemics before 1840. During 1840-1949, however, it experienced a noticeable dengue occurrence and prevalence in the 1870s, 1920s, and 1940s. Then from 1949 to 1978, only sporadic reports were accounted. The disparity in the frequency of dengue occurrences across three time periods suggests that the persistent characteristic of dengue epidemics in China primarily arises from imported cases resulting from international exchanges, subsequently leading to local outbreaks influenced by global epidemic trend. This research offers a novel perspective on retrospectively examining the historical trajectory of dengue epidemics and provides valuable insights into exploration of DENV epidemic patterns.

Vector-Borne Diseases Potpourri.

The Intergovernmental Panel on Climate Change has reported that the prevalence of vector-borne diseases has increased in recent decades and that the prevalence of malaria, Lyme disease, dengue, and, in particular, West Nile virus infection are expected to increase further if control measures are not strengthened. (1)(2) This review article summarizes the epidemiology, various clinical manifestations, and management strategies of these vector-borne diseases with increasing prevalence both in the United States and worldwide.

Spatio-temporal patterns of dengue in Bangladesh during 2019 to 2023: Implications for targeted control strategies.

BACKGROUND: Dengue, a viral infection transmitted by Aedes species mosquitoes, presents a substantial global public health concern, particularly in tropical regions. In Bangladesh, where dengue prevalence is noteworthy, accurately mapping the distribution of high-risk and low-risk areas and comprehending the clustering of dengue cases throughout the year is essential for the development of effective risk-based prevention and control strategies. Our objective was to identify dengue hotspots and temporal patterns over the years across Bangladesh in the years 2019-2023 excluding year 2020. METHODS: A sequential spatial analysis was employed for each year to identify high-risk areas for dengue cases. Choropleth graphs were used to visualize the geographic distribution of dengue incidence rates per million population across the areas. Monthly distribution analysis was performed to identify temporal trends over the year 2022 and 2023. Additionally, the global Moran's I test was used to assess the overall geographical pattern. Subsequently, Anselin local Moran's I test was employed to identified clustering and hotspots of dengue incidences. RESULTS: Dengue cases in Bangladesh exhibited a significant increase from 2019 to 2023 (excluding 2020 data), with a cumulative total of 513,344 reported cases. Dhaka city initially bore substantial burden, accounting for over half (51%) of the 101,354 cases in 2019. The case fatality rate also demonstrated a steadily rise, reaching 0.5% in 2023 with 321,179 cases (a five-fold increase compare to 2022). Interestingly, the proportion of cases in Dhaka city decreased from 51% in 2019 to 34% in 2023. Notably, the southeast and central regions of Bangladesh showed the highest dengue rates, persisting throughout the study period. Cases were concentrated in urban regions, with Dhaka exhibiting the highest caseload in most years, followed by Manikganj in 2023. A distinct temporal shift in dengue transmission was observed in 2023, when the peak incidence occurred three months earlier in July with complete geographic coverage (all the 64 districts) compared to the peak in October 2022 (covering 95%, 61 districts). Positive global autocorrelation analysis revealed spatial dependence, with more stable trends in 2023 compared to previous years. Several districts like, Bagerhat, Barisal, and Faridpur remained persistent hotspots or emerged as new hotspots in 2023. Conversely, districts like Dinajpur, Gaibandha, Nilphamari, Rangpur and Sylhet consistently exhibited low caseloads, categorized as dengue coldspots throughout most of the years. Jhalokati in 2019 and Gopalganj in 2022, both initially classified as low-incidence district surrounded by high-incidence districts, emerged as hotspots in 2023. CONCLUSION: This study sheds light on the spatiotemporal dynamics of dengue transmission in Bangladesh, particularly by identifying hotspots and clustering patterns. These insights offer valuable information for designing and implementing targeted public health interventions and control strategies. Furthermore, the observed trends highlight the need for adaptable strategies to address the region's evolving nature of dengue transmission effectively.

Central and Peripheral Nervous System Manifestations Associated with Dengue Illness.

Dengue illness, caused by the dengue viruses, continues to be a major global health concern, with increasing incidence and the emergence of severe manifestations such as neurological complications. An overview of the current understanding of dengue epidemiology, clinical manifestations, and research priorities is presented here. Dengue transmission has escalated in recent years, exacerbated by factors such as vector expansion, climate change, and socioeconomic challenges. The clinical spectrum of dengue ranges from mild febrile illness to severe manifestations, including hemorrhagic fever and neurological complications. Neurological manifestations of dengue, once considered rare, are now increasingly reported, encompassing encephalitis, myelitis, and Guillain-Barré Syndrome, among others. Diagnosis primarily relies on laboratory methods such as RT/PCR, NS1 antigen detection, and serological assays. Despite advancements in understanding the dengue pathogenesis, there remains a critical need for effective vaccines, antiviral drugs, improved surveillance methods, predictive models for disease severity, and long-term studies on post-Dengue sequelae. Integrated programs and holistic approaches to dengue control are essential for mitigating its impact. Addressing these research priorities will be pivotal in combating dengue and reducing its global burden.

A new lineage nomenclature to aid genomic surveillance of dengue virus.

Dengue virus (DENV) is currently causing epidemics of unprecedented scope in endemic settings and expanding to new geographical areas. It is therefore critical to track this virus using genomic surveillance. However, the complex patterns of viral genomic diversity make it challenging to use the existing genotype classification system. Here, we propose adding 2 sub-genotypic levels of virus classification, named major and minor lineages. These lineages have high thresholds for phylogenetic distance and clade size, rendering them stable between phylogenetic studies. We present assignment tools to show that the proposed lineages are useful for regional, national, and subnational discussions of relevant DENV diversity. Moreover, the proposed lineages are robust to classification using partial genome sequences. We provide a standardized neutral descriptor of DENV diversity with which we can identify and track lineages of potential epidemiological and/or clinical importance. Information about our lineage system, including methods to assign lineages to sequence data and propose new lineages, can be found at: dengue-lineages.org.

Global Warming and Rising Threat of Dengue Fever: Expectations in Disease Management.

SUMMARY: Arbovirus-borne dengue fever remains a global public health threat. The actual burden of dengue infection may be underestimated due to undiagnosed or misdiagnosed fever cases. The distribution of dengue is influenced by both climatic and nonclimatic factors, including global warming, which affects the vector population and transmission period. Other factors, such as serotype evolution and host immunity, also contribute to the spread of the virus. Different serotypes of the dengue virus show different clinical manifestations. The prevalence of serotypes varies geographically and over time. Early diagnosis and characterization of circulating viruses at the genomic level are important for disease prevention and control.

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.