Dengue Risk Research Articles

Methodological framework for early detection of dengue outbreaks in Tanzania

Abstract Background Dengue fever is a major public health problem because it is a widespread and rapidly transmitted mosquito-borne viral disease. We developed a framework for early detection of dengue outbreaks in Tanzania, starting with detection of suspected and/or confirmed cases, followed by site-specific risk characterization, both useful for planning and prioritizing outbreak interventions or epidemic preparedness. Methods Our initial focus was on the identification and categorization of indicators that are specifically tailored to the early detection and classification of outbreak events. The framework was then evaluated using (i) available cases with syndromic and laboratory-confirmed disease information from ProMED emails using decision tree analysis, and (ii) available historical dengue epidemic data at the local level from 2019 with 6,795 confirmed cases using negative binomial regression analysis adjusted for month and area. Results The laboratory-confirmed diagnosis (dengue yes or no) was consistent with the results of the suspected case classification algorithm for clinically defined syndromic cases. There was strong evidence of an increase in dengue cases with higher site-specific risk (rate ratio = 2.51 (95% CI = [1.76, 3.58])) when regressing confirmed dengue cases in 2019 as the dependent variable and site-specific risk as the independent variable. Conclusions The rapid dengue outbreak risk assessment developed may be useful in controlling the epidemic in Tanzania. The suspected case classification algorithm can be a very useful tool to better assess whether a potential dengue case is present and thus requires laboratory confirmation. The framework can be used to rapidly predict the risk of dengue outbreaks, which is useful for planning and prioritizing interventions or for epidemic preparedness. Key messages • Framework for a novel rapid risk assessment for early detection of dengue outbreaks in Tanzania. • Framework relevant to epidemic preparedness.

Effects of climate variability on the spatio-temporal distribution of Dengue in Valle del Cauca, Colombia, from 2001 to 2019.

Dengue is a vector-borne disease that has increased over the past two decades, becoming a global public health emergency. The transmission of dengue is contingent upon various factors, among which climate variability plays a significant role. However, there remains substantial uncertainty regarding the underlying mechanisms. This study aims to investigate the spatial and temporal patterns of dengue risk and to quantify the associated risk factors in Valle del Cauca, Colombia, from 2001 to 2019. To achieve this, a spatio-temporal Bayesian hierarchical model was developed, integrating delayed and non-linear effects of climate variables, socio-economic factors, along with spatio-temporal random effects to account for unexplained variability. The results indicate that average temperature is positively associated with dengue risk 0-2 months later, showing a 35% increase in the risk. Similarly, high precipitation levels lead to increased risk approximately 2-3 months later, while relative humidity showed a constant risk within a 6 months-lag. These findings could be valuable for local health authorities interested in developing early warning systems to predict future risks in advance.

“Dengue fever is not just urban or rural: Reframing its spatial categorization.”

Infectious diseases exploit niches that are often spatially defined as urban and/or rural. Yet spatial research on infectious diseases often fails to define “urban” and “rural” and how these contexts might influence their epidemiology. We use dengue fever, thought to be mostly an urban disease with rural foci, as a device to explore local definitions of urban and rural spaces and the impact of these spaces on dengue risk in the provinfine urban and rural locales. Interviews conducted from 2019 to 2021 with 71 residents and 23 health personce of Esmeraldas, Ecuador. Ecuador, like many countries, only uses population size and administrative function to denel found that they identified the availability of basic services, extent of their control over their environment, and presence of underbrush and weeds (known in Ecuador as monte and maleza and conceptualized in this paper as natural disorder) as important links to their conceptions of space and dengue risk. This broader conceptualization of space articulated by local residents and professionals reflects a more sophisticated approach to characterizing dengue risk than using categories of urban and rural employed by the national census and government. Rather than this dichotomous category of space, dengue fever can be better framed for health interventions in terms of specific environmental features and assemblages of high-risk spaces. An understanding of how community members perceive risk enhances our ability to collaborate with them to develop optimal mitigation strategies.

Impact of compound warm and wet events on dengue fever infection in South and Southeast Asian countries

BackgroundMultiple studies have reported the profound influence of various climate factors on dengue fever infection, while the effects of joint exposure to warm and wet environment, a condition favouring dengue vectors, on disease transmission were less evaluated. This study aims to investigate the impact of various compound temperature, rainfall, and relative humidity exposures on dengue fever infection in the South and Southeast Asia regions. MethodsWeekly dengue fever surveillance data from 2012 to 2020 were collected from 48 locations in four countries named Singapore (1 location), Sri Lanka (15 locations), Malaysia (9 locations), and Thailand (23 locations, with 11 locations having different study periods). The distributed lag non-linear models were built to assess the impacts of compound temperature, rainfall, and relative humidity exposures on dengue fever infection risks. ResultsA total of 1,359,993 dengue fever cases were reported with 9.33%, 24.02%, 48.73%, and 17.91% cases contributed by Singapore, Sri Lanka, Malaysia, and Thailand, respectively. Compared to non-warm-non-wet, compound warm-wet was associated with an increased dengue risk (RR:1.32, 95% CI:1.21–1.44). Compared to moderate temperature-humidity, warm-wet environment was also associated with an increase in dengue risk (RR:1.37, 95% CI:1.22–1.55). In comparison to weeks with moderate temperature-rainfall, warm-wet weeks was linked to an elevated dengue risk (RR:1.39, 95% CI:1.27–1.52), whereas cold-dry weather would significantly reduce the infection risk (RR:0.70, 95% CI:0.62–0.80). Modification effects showed that the hot effect on dengue infection was more pronounced under higher humidity, while the impact of rainfall increased with warmer temperature. ConclusionWarm-wet events were associated with an increased dengue fever risk, while the infection risk would decline in cold-dry environment, and modification effects exist among exposures. Findings from this study highlight the importance of considering joint temperature, humidity, and rainfall dependency of dengue fever infection in disease prevention and control.

The fuzzy system ensembles entomological, epidemiological, demographic and environmental data to unravel the dengue transmission risk in an endemic city

BackgroundThe effectiveness of dengue control interventions depends on an effective integrated surveillance system that involves analysis of multiple variables associated with the natural history and transmission dynamics of this arbovirus. Entomological indicators associated with other biotic and abiotic parameters can assertively characterize the spatiotemporal trends related to dengue transmission risk. However, the unpredictability of the non-linear nature of the data, as well as the uncertainty and subjectivity inherent in biological data are often neglected in conventional models.MethodsAs an alternative for analyzing dengue-related data, we devised a fuzzy-logic approach to test ensembles of these indicators across categories, which align with the concept of degrees of truth to characterize the success of dengue transmission by Aedes aegypti mosquitoes in an endemic city in Brazil. We used locally gathered entomological, demographic, environmental and epidemiological data as input sources using freely available data on digital platforms. The outcome variable, risk of transmission, was aggregated into three categories: low, medium, and high. Spatial data was georeferenced and the defuzzified values were interpolated to create a map, translating our findings to local public health managers and decision-makers to direct further vector control interventions.ResultsThe classification of low, medium, and high transmission risk areas followed a seasonal trend expected for dengue occurrence in the region. The fuzzy approach captured the 2020 outbreak, when only 14.06% of the areas were classified as low risk. The classification of transmission risk based on the fuzzy system revealed effective in predicting an increase in dengue transmission, since more than 75% of high-risk areas had an increase in dengue incidence within the following 15 days.ConclusionsOur study demonstrated the ability of fuzzy logic to characterize the city’s spatiotemporal heterogeneity in relation to areas at high risk of dengue transmission, suggesting it can be considered as part of an integrated surveillance system to support timely decision-making.

Reconciling heterogeneous dengue virus infection risk estimates from different study designs.

Uncovering rates at which susceptible individuals become infected with a pathogen, i.e. the force of infection (FOI), is essential for assessing transmission risk and reconstructing distribution of immunity in a population. For dengue, reconstructing exposure and susceptibility statuses from the measured FOI is of particular significance as prior exposure is a strong risk factor for severe disease. FOI can be measured via many study designs. Longitudinal serology are considered gold standard measurements, as they directly track the transition of seronegative individuals to seropositive due to incident infections (seroincidence). Cross-sectional serology can provide estimates of FOI by contrasting seroprevalence across ages. Age of reported cases can also be used to infer FOI. Agreement of these measurements, however, have not been assessed. Using 26 years of data from cohort studies and hospital-attended cases from Kamphaeng Phet province, Thailand, we found FOI estimates from the three sources to be highly inconsistent. Annual FOI estimates from seroincidence was 2.46 to 4.33-times higher than case-derived FOI. Correlation between seroprevalence-derived and case-derived FOI was moderate (correlation coefficient=0.46) and no systematic bias. Through extensive simulations and theoretical analysis, we show that incongruences between methods can result from failing to account for dengue antibody kinetics, assay noise, and heterogeneity in FOI across ages. Extending standard inference models to include these processes reconciled the FOI and susceptibility estimates. Our results highlight the importance of comparing inferences across multiple data types to uncover additional insights not attainable through a single data type/analysis.

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

BackgroundFor 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.MethodsIn 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.ResultsOur 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.ConclusionOur 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.

An effective pan-serotype dengue vaccine and enhanced control strategies could help in reducing the severe dengue burden in Bangladesh-A perspective.

Dengue is an important vector-borne disease occurring globally. Dengue virus (DENV) infection can result in a potentially life-threatening disease. To date, no DENV-specific antiviral treatment is available. Moreover, an equally effective pan-serotype dengue virus vaccine is not available. Recently, two DENV vaccines, Dengvaxia and Qdenga, were licensed for limited use. However, none of them have been approved in Bangladesh. DENV is transmitted by Aedes mosquitoes, and global warming caused by climate change favoring Aedes breeding plays an important role in increasing DENV infections in Bangladesh. Dengue is a serious public health concern in Bangladesh. In the year 2023, Bangladesh witnessed its largest dengue outbreak, with the highest number of dengue cases (n = 321,179) and dengue-related deaths (n = 1,705) in a single epidemic year. There is an increased risk of severe dengue in individuals with preexisting DENV-specific immunoglobulin G if the individuals become infected with different DENV serotypes. To date, vector control has remained the mainstay for controlling dengue; therefore, an immediate, strengthened, and effective vector control program is critical and should be regularly performed for controlling dengue outbreaks in Bangladesh. In addition, the use of DENV vaccine in curbing dengue epidemics in Bangladesh requires more consideration and judgment by the respective authority of Bangladesh. This review provides perspectives on the control and prevention of dengue outbreaks. We also discuss the challenges of DENV vaccine use to reduce dengue epidemics infection in Bangladesh.

Assessing Wolbachia-mediated sterility for dengue control: emulation of a cluster-randomized target trial in Singapore.

Matings between male Aedes aegypti mosquitoes infected with wAlbB strain of Wolbachia and wildtype females yield non-viable eggs. We evaluated the efficacy of releasing wAlbB-infected Ae. aegypti male mosquitoes to suppress dengue. We specified the protocol of a two-arm cluster-randomized test-negative controlled trial (cRCT) and emulated it using a nationally representative test-negative/positive database of individuals reporting for febrile illness to any public hospital, general practitioner or polyclinic. We retrospectively built a cohort of individuals who reside in Wolbachia locations vs a comparator control group who do not reside in Wolbachia locations, using a nationally representative database of all individuals whom report for febrile illness and were tested for dengue at the Environmental Health Institute/hospital laboratories/commercial diagnostic laboratories, through general practitioner clinic, polyclinic or public/private hospital from epidemiological week (EW) 1 2019 to EW26 2022. We emulated a constrained randomization protocol used in cRCTs to balance dengue risk between intervention and control arms in the pre-intervention period. We used the inverse probability weighting approach to further balance the intervention and control groups using a battery of algorithmically selected sociodemographic, environmental and anthropogenic variables. Intention-to-treat analyses were conducted to estimate the risk reduction of dengue given Wolbachia exposure. Intention-to-treat analyses revealed that, compared with controls, Wolbachia releases for 3, 6 and ≥12 months was associated to 47% (95% confidence interval: 25-69%), 44% (33-77%) and 61% (38-78%) protective efficacy against dengue, respectively. When exposed to ≥12 months of Wolbachia releases, protective efficacies ranged from 49% (13-72%) to 77% (60-94%) across years. The proportion of virologically confirmed dengue cases was lower overall in the intervention arm. Protective efficacies were found across all years, age and sex subgroups, with higher durations of Wolbachia exposure associated to greater risk reductions of dengue. Results demonstrated that Wolbachia-mediated sterility can strengthen dengue control in tropical cities, where dengue burden is the greatest.

Impact of deforestation and climate on spatio-temporal spread of dengue fever in Mexico

Dengue prevalence results from the interaction of multiple socio-environmental variables which influence its spread. This study investigates the impact of forest loss, precipitation, and temperature on dengue incidence in Mexico from 2010 to 2020 using a Bayesian hierarchical spatial model. Three temporal structures—AR1, RW1, and RW2—were compared, with RW2 showing superior performance. Findings indicate that a 1 % loss of municipal forest cover correlates with a 16.9 % increase in dengue risk. Temperature also significantly affects the vectors' ability to initiate and maintain outbreaks, highlighting the significant role of environmental factors. The research emphasizes the importance of multilevel modeling, finer temporal data resolution, and understanding deforestation causes to enhance the predictability and effectiveness of public health interventions. As dengue continues affecting global populations, particularly in tropical and subtropical regions, this study contributes insights, advocating for an integrated approach to health and environmental policy to mitigate the impact of vector-borne diseases.

Mucocutaneous Manifestations in Patients with Dengue Fever: From the EPIDENGUE Cohort on Reunion Island.

Nearly 4 billion people live in a dengue risk area worldwide. The prevalence of dengue-related mucocutaneous manifestations and their association with severe dengue differ across studies. The aim of the study was to describe the characteristics of patients with dengue-related mucocutaneous manifestations and to investigate those were associated with severe dengue. A retrospective study was conducted in 2019 among patients with a positive RT-PCR for dengue at the University Hospital of Reunion, which has been experiencing a re-emergence of dengue since 2018. Of 847 patients with confirmed dengue, 283 (33.4%) developed mucocutaneous manifestations. Only manifestations of dehydration such as glossitis, dysgeusia, or conjunctivitis were associated with severe dengue, unlike pruritus and rash, in bivariate analysis but not in multivariate analysis. The rash and pruritus of dengue appear to be accompanied by a pronounced flu-like syndrome in younger people without comorbidity or severity, although careful examination of mucous membranes would better identify signs of dehydration and thus cases likely to worsen.

Risk of severe dengue during secondary infection: A population-based cohort study in Taiwan

BackgroundDengue poses a significant public health concern. Secondary dengue infections with different dengue virus (DENV) serotypes have been linked to an increased risk of severe dengue. This study aimed to assess the risk of severe dengue during secondary infection in Taiwan. MethodsA retrospective cohort study was conducted using Taiwan's National Health Insurance Research Database to identify dengue cases with secondary dengue infection born after 1944 from 2014 to 2015. Ten matched patients with primary infection were selected as controls using propensity score matching for each secondary dengue infection case. The odds ratio (OR) for severe dengue in secondary versus primary infections was calculated using conditional logistic regression. ResultsThis study included 357 cases with secondary dengue infection and 3570 matched controls. The risk of severe dengue was found to be 7.8% in individuals with secondary infection, compared to 3.8% in those with primary dengue infection. Secondary infection significantly increased the risk of severe dengue (OR 2.13, 95% CI: 1.40–3.25, P = 0.0004). Notably, a significant association between secondary infection and severe dengue was observed only when the interval between the first and secondary infection was greater than two years (OR 3.19, 95% CI 2.04–5.00, P < 0.0001). ConclusionSecondary dengue infection significantly increases the risk of severe disease in Taiwan, particularly when the interval between infections is over two years.Healthcare professionals should maintain heightened vigilance for individuals with a history of previous dengue infection, particularly if their initial diagnosis was more than two years prior.

Delineating dengue risk zones in Jaipur: An interdisciplinary approach to inform public health strategies.

Dengue fever (DF) is a pervasive public health concern in tropical climates, with densely populated regions, such as India, disproportionately affected. Addressing this issue requires a multifaceted understanding of the environmental and sociocultural factors that contribute to the risk of dengue infection. This study aimed to identify high-risk zones for DF in Jaipur, Rajasthan, India, by integrating physical, demographic, and epidemiological data in a comprehensive risk analysis framework. We investigated environmental variables, such as soil type and plant cover, to characterize the potential habitats of Aedes aegypti, the primary dengue vector. Concurrently, demographic metrics were evaluated to assess the population's susceptibility to dengue outbreaks. High-risk areas were systematically identified through a comparative analysis that integrated population density and incidence rates per ward. The results revealed a significant correlation between high population density and an increased risk of dengue, predominantly facilitated by vertical transmission. Spatially, these high-risk zones are concentrated in the northern and southern sectors of Jaipur, with the northern and southwestern wards exhibiting the most acute risk profiles. This study underscores the importance of targeted public health interventions and vaccination campaigns in vulnerable areas. It further lays the groundwork for future research to evaluate the effectiveness of such interventions, thereby contributing to the development of robust evidence-based strategies for dengue risk mitigation.

Potential climate change effects on the distribution of urban and sylvatic dengue and yellow fever vectors

ABSTRACT Climate change may increase the risk of dengue and yellow fever transmission by urban and sylvatic mosquito vectors. Previous research primarily focused on Aedes aegypti and Aedes albopictus. However, dengue and yellow fever have a complex transmission cycle involving sylvatic vectors. Our aim was to analyze how the distribution of areas favorable to both urban and sylvatic vectors could be modified as a consequence of climate change. We projected, to future scenarios, baseline distribution models already published for these vectors based on the favorability function, and mapped the areas where mosquitoes’ favorability could increase, decrease or remain stable in the near (2041–2060) and distant (2061–2080) future. Favorable areas for the presence of dengue and yellow fever vectors show little differences in the future compared to the baseline models, with changes being perceptible only at regional scales. The model projections predict dengue vectors expanding in West and Central Africa and in South-East Asia, reaching Borneo. Yellow fever vectors could spread in West and Central Africa and in the Amazon. In some locations of Europe, the models suggest a reestablishment of Ae. aegypti, while Ae. albopictus will continue to find new favorable areas. The results underline the need to focus more on vectors Ae. vittatus, Ae. luteocephalus and Ae. africanus in West and Central sub-Saharan Africa, especially Cameroon, Central Africa Republic, and northern Democratic Republic of Congo; and underscore the importance of enhancing entomological monitoring in areas where populations of often overlooked vectors may thrive as a result of climate changes.

Epidemiology of travel-associated dengue from 2007 to 2022: A GeoSentinel analysis.

Dengue is a leading cause of febrile illness among international travellers. We aimed to describe the epidemiology and clinical characteristics of imported dengue in returning travellers evaluated at GeoSentinel sites from 2007 to 2022. We retrieved GeoSentinel records of dengue among travellers residing in non-endemic countries. We considered dengue confirmed when diagnosed by a positive dengue virus (DENV)-specific reverse-transcriptase polymerase chain reaction, positive NS-1 antigen and/or anti-DENV IgG seroconversion, and probable when diagnosed by single anti-DENV IgM or high-titre anti-DENV IgG detection. Severe dengue was defined as evidence of clinically significant plasma leakage or bleeding, organ failure, or shock, according to the 2009 World Health Organization guidance. Complicated dengue was defined as either severe dengue or dengue with presence of any warning sign. Analyses were descriptive. This analysis included 5958 travellers with confirmed (n = 4859; 81.6%) or probable (n = 1099; 18.4%) dengue. The median age was 33 years (range: <1-91); 3007 (50.5%) travellers were female. The median travel duration was 21 days (interquartile range [IQR]: 15-32). The median time between illness onset and GeoSentinel site visit was 7 days (IQR: 4-15). The most frequent reasons for travel were tourism (67.3%), visiting friends or relatives (12.2%) and business (11.0%). The most frequent regions of acquisition were South East Asia (50.4%), South Central Asia (14.9%), the Caribbean (10.9%) and South America (9.2%). Ninety-five (1.6%) travellers had complicated dengue, of whom 27 (0.5%) had severe dengue and one died. Of 2710 travellers with data available, 724 (26.7%) were hospitalized. The largest number of cases (n = 835) was reported in 2019. A broad range of international travellers should be aware of the risk of acquiring dengue and receive appropriate pre-travel counselling regarding preventive measures. Prospective cohort studies are needed to further elucidate dengue risk by destination and over time, as well as severe outcomes and prolonged morbidity (long dengue) due to travel-related dengue.

Current and lagged associations of meteorological variables and Aedes mosquito indices with dengue incidence in the Philippines.

Dengue is an increasing health burden that has spread throughout the tropics and sub-tropics. There is currently no effective vaccine and control is only possible through integrated vector management. Early warning systems (EWS) to alert potential dengue outbreaks are currently being explored but despite showing promise are yet to come to fruition. This study addresses the association of meteorological variables with both mosquito indices and dengue incidences and assesses the added value of additionally using mosquito indices for predicting dengue incidences. Entomological surveys were carried out monthly for 14 months in six sites spread across three environmentally different cities of the Philippines. Meteorological and dengue data were acquired. Non-linear generalized additive models were fitted to test associations of the meteorological variables with both mosquito indices and dengue cases. Rain and the diurnal temperature range (DTR) contributed most to explaining the variation in both mosquito indices and number of dengue cases. DTR and minimum temperature also explained variation in dengue cases occurring one and two months later and may offer potentially useful variables for an EWS. The number of adult mosquitoes did associate with the number of dengue cases, but contributed no additional value to meteorological variables for explaining variation in dengue cases. The use of meteorological variables to predict future risk of dengue holds promise. The lack of added value of using mosquito indices confirms several previous studies and given the onerous nature of obtaining such information, more effort should be placed on improving meteorological information at a finer scale to evaluate efficacy in early warning of dengue outbreaks.

A CONCEPTUAL FRAMEWORK FOR ASSESSING THE FIELD EFFICIENCY OF DRONES IN IDENTIFYING POTENTIAL BREEDING SITES OF THE Aedes MOSQUITO

The identification of breeding sites is key to dengue prevention strategies. Community involvement and breeding site surveillance play a vital role in controlling the Aedes population. Drones have emerged as a promising tool to be used in surveillance activities. Therefore, the aim of this paper is to develop a conceptual framework and present comprehensive intervention methods to control dengue cases. This study explores the concepts of community engagement, habitat profiling and mapping, and technology integration that will be implemented in the three main phases. Phase I: Community engagement, in which to understand the implementation characteristics of the proposed system using the Consolidated Framework for Implementation Research (CFIR) and Human-Centred Design (HCD); Phase II: Profiling and mapping potential breeding sites, in order to compare and characterise vector breeding sites of the Aedes mosquito in selected urban and rural areas using innovative drone technologies; Phase III: Technology integration by developing automated linkage of information on the mapping of mosquito breeding sites for dengue risk to an application platform. This conceptual framework can assess the efficiency of drones as an alternative tool for dengue surveillance and the use of technology to locate breeding sites effortlessly, which can later be applied in dengue-endemic regions.

A system dynamics modelling and analytical framework for imported dengue outbreak surveillance and risk mapping

System Dynamics (SD) models have been used to understand complex, multi-faceted dengue transmission dynamics, but a gap persists between research and actionable public health tools for decision-making. Spain is an at-risk country of imported dengue outbreaks, but only qualitative assessments are available to guide public health action and control. We propose a modular SD model combining temperature-dependent vector population, transmission parameters, and epidemiological interactions to simulate outbreaks from imported cases accounting for heterogeneous local climate-related transmission patterns. Under our assumptions, 15 provinces sustain vector populations capable of generating outbreaks from imported cases, with heterogeneous risk profiles regarding seasonality, magnitude and risk window shifting from late Spring to early Autum. Results being relative to given vector-to-human populations allow flexibility when translating outcomes between geographic scales. The model and the framework are meant to serve public health by incorporating transmission dynamics and quantitative-qualitative input to the evidence-based decision-making chain. It is a flexible tool that can easily adapt to changing contexts, parametrizations and epidemiological settings thanks to the modular approach.

Climate change is aggravating dengue and yellow fever transmission risk

Dengue and yellow fever have complex cycles, involving urban and sylvatic mosquitoes, and non‐human primate hosts. To date, efforts to assess the effect of climate change on these diseases have neglected the combination of such crucial factors. Recent studies only considered urban vectors. This is the first study to include them together with sylvatic vectors and the distribution of primates to analyse the effect of climate change on these diseases. We used previously published models, based on machine learning algorithms and fuzzy logic, to identify areas where climatic favourability for the relevant transmission agents could change: 1) favourable areas for the circulation of the viruses due to the environment and to non‐human primate distributions; 2) the favourability for urban and sylvatic vectors. We obtained projections of future transmission risk for two future periods and for each disease, and implemented uncertainty analyses to test for predictions reliability. Areas currently favourable for both diseases could keep being climatically favourable, while global favourability could increase a 7% for yellow fever and a 10% increase for dengue. Areas likely to be more affected in the future for dengue include West Africa, South Asia, the Gulf of Mexico, Central America and the Amazon basin. A possible spread of dengue could take place into Europe, the Mediterranean basin, the UK and Portugal; and, in Asia, into northern China. For yellow fever, climate could become more favourable in Central and Southeast Africa; India; and in north and southeast South America, including Brazil, Paraguay, Bolivia, Peru, Colombia and Venezuela. In Brazil, favourability for yellow fever will probably increase in the south, the west and the east. Areas where the transmission risk spread is consistent to the dispersal of vectors are highlighted in respect of areas where the expected spread is directly attributable to environmental changes. Both scenarios could involve different prevention strategies.

The empowered family: New narratives to rethink dengue prevention and control in Córdoba, Colombia.

Dengue is a disease that constitutes a public health problem difficult to control due to the multidimensionality of associated factors and the particularities of the territories. This article analyzes the notion of family empowerment related to the prevention and control of dengue in Córdoba, Colombia. From July to October 2023, using a qualitative approach, semi-structured interviews were conducted with 30 family groups located in the municipalities of San Andrés de Sotavento, San Bernardo del Viento, Pueblo Nuevo, and Montería, selected for being indigenous, Afro-descendant, or rural and urban populations in vulnerable conditions. The results show that families, beyond their particular arrangements in terms of structure and dynamics, are aware of their role in the prevention and control of diseases, identifying the capacities required to face dengue. However, they reproduce narratives of conceptual and power dominance that assign a greater commitment on the part of educational and health agents to promote alternatives that contribute to reducing the risks of dengue. The challenges that must be faced for effective family empowerment are discussed, so that prevention practices gain greater strength.