Dengue In Mexico Research Articles

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.

Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data.

In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other hand, the amount of precipitation reported annually was slightly less than the previous year. Similarly, the minimum-mean-maximum temperatures recorded annually were below the previous year. In the literature, it is possible to find studies focused on the spread of dengue only for some specific regions of Mexico. However, given the increase in the number of cases during 2022 in regions not considered by previously published works, this study covers cases reported in all states of the country. On the other hand, determining a relationship between the dynamics of dengue cases and climatic factors through a computational model can provide relevant information on the transmission of the virus. A multiple-learning computational approach was developed to simulate the number of the different risks of dengue cases according to the classification reported per epidemiological week by considering climatic factors in Mexico. For the development of the model, the data were obtained from the reports published in the Epidemiological Panorama of Dengue in Mexico and in the National Meteorological Service. The classification of non-severe dengue, dengue with warning signs, and severe dengue were modeled in parallel through an artificial neural network model. Five variables were considered to train the model: the monthly average of the minimum, mean, and maximum temperatures, the precipitation, and the number of the epidemiological week. The selection of variables in this work is focused on the spread of the different risks of dengue once the mosquito begins transmitting the virus. Therefore, temperature and precipitation were chosen as climatic factors due to the close relationship between the density of adult mosquitoes and the incidence of the disease. The Levenberg-Marquardt algorithm was applied to fit the coefficients during the learning process. In the results, the ANN model simulated the classification of the different risks of dengue with the following precisions (R2): 0.9684, 0.9721, and 0.8001 for non-severe dengue, with alarm signs and severe, respectively. Applying a correlation matrix and a sensitivity analysis of the ANN model coefficients, both the average minimum temperature and precipitation were relevant to predict the number of dengue cases. Finally, the information discovered in this work can support the decision-making of the Ministry of Health to avoid a syndemic between the increase in dengue cases and other seasonal diseases.

The ecological determinants of severe dengue: A Bayesian inferential model

Low socioeconomic status (SES), high temperature, and increasing rainfall patterns are associated with increased dengue case counts. However, the effect of climatic variables on individual dengue virus (DENV) serotypes and the extent to which serotype count affects the rate of severe dengue in Mexico have not been studied before. A principal components analysis was used to determine the poverty indices across Mexico. Conditional autoregressive Bayesian models were used to determine the effect of poverty and climatic variables on the rate of serotype distribution and severe dengue in Mexico. A unit increase in poverty increased the rate of DENV-1, DENV-2, DENV-3, and DENV-4 by 8.4%, 5%, 16%, and 13.8% respectively. An increase in one case attributable to DENV-1, DENV-2, DENV-3, and DENV-4 was independently associated with an increase in the rate of severe dengue by 0.02%, 0.1%, 0.03%, and 5.8% respectively. Hotspots of all DENV serotypes and severe dengue are found mostly in parts of the Northeastern, Center west, and Southeastern regions of Mexico. The association between climatic parameters predominant in the Southeast region and severe dengue leaves several states in this region at an increased risk of a higher number of severe dengue cases. Our study's results may guide policies that help allocate public health resources to the most vulnerable municipalities in Mexico.

Climate-driven mosquito-borne viral suitability index: measuring risk transmission of dengue, chikungunya and Zika in Mexico

BackgroundClimate variability influences the population dynamics of the Aedes aegypti mosquito that transmits the viruses that cause dengue, chikungunya and Zika. In recent years these diseases have grown considerably. Dengue is now the fastest-growing mosquito-transmitted disease worldwide, putting 40 per cent of the global population at risk. With no effective antiviral treatments or vaccines widely available, controlling mosquito population remains one of the most effective ways to prevent epidemics. This paper analyses the temporal and spatial dynamics of dengue in Mexico during 2000–2020 and that of chikungunya and Zika since they first appeared in the country in 2014 and 2015, respectively. This study aims to evaluate how seasonal climatological variability affects the potential risk of transmission of these mosquito-borne diseases. Mexico is among the world’s most endemic countries in terms of dengue. Given its high incidence of other mosquito-borne diseases and its size and wide range of climates, it is a good case study.MethodsWe estimate the recently proposed mosquito-borne viral suitability index P, which measures the transmission potential of mosquito-borne pathogens. This index mathematically models how humidity, temperature and precipitation affect the number of new infections generated by a single infected adult female mosquito in a host population. We estimate this suitability index across all Mexico, at small-area level, on a daily basis during 2000–2020.ResultsWe find that the index P predicted risk transmission is strongly correlated with the areas and seasons with a high incidence of dengue within the country. This correlation is also high enough for chikungunya and Zika in Mexico. We also show the index P is sensitive to seasonal climatological variability, including extreme weather shocks.ConclusionsThe paper shows the dynamics of dengue, chikungunya and Zika in Mexico are strongly associated with seasonal climatological variability and the index P. This potential risk of transmission index, therefore, is a valuable tool for surveillance for mosquito-borne diseases, particularly in settings with varied climates and limited entomological capacity.

Cluster Analysis of Dengue Morbidity and Mortality in Mexico from 2007 to 2020: Implications for the Probable Case Definition.

Dengue cases and deaths occur frequently in Mexico, although the trend is not uniform across the country. We performed a Spatio-temporal analysis of dengue cases and deaths in Mexico from 2007 to 2020, and clustered states according to whether there was a low, moderate, or high risk of dengue. A total of 501,600 confirmed dengue cases were registered from 2007 to 2020, with 378,122 cases classified as dengue fever (DF) and 123,478 cases classified as dengue hemorrhagic fever (DHF). For each confirmed case, there were 4.68 probable cases. There were 1,230 dengue deaths, with highest numbers reported in 2009, 2012, 2013, and 2019. The number of deaths had a significant correlation (P ≤ 0.01) with DF (r = 0.82), DHF (r = 0.94), and probable dengue cases (r = 0.84). States were clustered using Machine Learning technique according to select indices associated with dengue. Cluster 1 (low risk) primarily contained states in the northwest, northcentral, and east. Cluster 2 (moderate risk) includes states in the northeast. Cluster 3 (high risk) mostly contained coastal states in the southeast, southwest, and west. The generation of the clusters was supported by the Kruskal-Wallis test. A significant difference was found in the incidence, mortality rates, and case-fatality rates of dengue among the clusters (P ≤ 0.01). Notably, cluster 3 contributed 71.4% of the confirmed cases and 89.2% of the deaths. Public health and vector control strategies designed to mitigate the burden of dengue in Mexico should consider the states in cluster 3 as high priority areas.

A Bayesian Functional Methodology for Dengue Risk Mapping in Latin America and the Caribbean

Dengue fever has become one of the most outstanding infectious diseases in the world. Besides, the incidence and prevalence of dengue are increasing in the endemic areas of the tropical and subtropical regions. Space and time disease mapping models are common instruments to explain the patterns of disease counts, where hierarchical Bayesian models constitute a suitable framework for their formulation. These random events reflect interactions between nearby geographic locations, as well as correlations between close temporary instants. Functional data analysis techniques can better describe the evolution of disease mapping.In this paper, the risk of dengue in Mexico, Central and South America is studied from a Functional approach through a Bayesian estimation model focused on Hilbert-valued autoregressive processes combined with the Kalman filtering algorithm. Thus, the temporal functional evolution of spatial geographic patterns of incidence risk in disease mapping during 1998-2018 is approximated. Applying this methodology, the excess of smoothing that occurs with traditional models is avoided and the heterogeneity is conserved across the years. It improves the number of false positives created by noise and the number of false negatives as well. The results obtained with the application of this model are compared with those of previous models, corroborating the preceding statements and obtaining better results in the relative risk estimates, providing greater robustness and stability of disease risk estimates.

Demographic and climatic factors associated with dengue prevalence in a hyperendemic zone in Mexico: an empirical approach.

Many models for predicting dengue epidemics use incidence and short-term changes in climate variables, however, studies in real-life scenarios for correlations of seroprevalence (SP) with long-term climate variables and with integration of socio-economic factors are scarce. Our objective was to analyse the combined correlation between socio-economic and climate variables with the SP of dengue in Mexico. We performed a seroepidemiological ecological study on the Mexican Pacific coast. Dengue SP was estimated by the presence of immunoglobulin G antibodies in 1278 inhabitants. We implemented multiple correlations with socio-economic, climatic and topographic characteristics using logistic regression, generalized linear models and non-linear regressions. Dengue SP was 58%. The age-adjusted correlation was positive with the male sex, while a negative correlation was seen with socio-economic status (SES) and scholl level (SL). The annual temperature showed a positive correlation, while the altitude was negative. It should be noted that these correlations showed a marked 'S' shape in the non-linear model, suggesting three clearly defined scenarios for dengue risk. Low SES and SL showed an unexpected paradoxical protective effect. Altitude above sea level and annual temperature are the main determinants for dengue in the long term. The identification of three clearly delineated scenarios for transmission could improve the accuracy of predictive models.

REAL-WORLD EVIDENCE OF DENGUE BURDEN ON HOSPITALS IN MEXICO: INSIGHTS FROM THE AUTOMATED SUBSYSTEM OF HOSPITAL DISCHARGES (SAEH) DATABASE.

The incidence of dengue in Mexico has increased in recent decades. It has been suggested that dengue outbreaks may compromise treatment quality in hospitals. The objective of the study was to quantify the burden imposed by dengue on hospital services in Mexico. We analyzed 19.2 million records contained in the database of hospital services of the Mexican Ministry of Health between 2008 and 2014. The number of admissions due to dengue was compared to other potentially preventable hospitalizations. Hospital departments were categorized to reflect dengue-related activity as high dengue activity (HDA), low dengue activity (LDA), or zero dengue activity departments, and the impact of dengue activity on general in-hospital mortality in HDA departments was assessed. Dengue was the cause of more hospital admissions than most of the potentially preventable prevalent acute and chronic conditions and other infectious diseases. In HDA departments, dengue patient load was found to be a significant risk factor for overall in-hospital mortality. There was an approximately two-fold higher dengue case-fatality rate in LDA versus HDA departments, irrespective of dengue severity. This study confirms that dengue is an important cause of hospitalization in Mexico and highlights the impact of dengue activity not only on dengue case-fatality rate but also on the overall in-hospital mortality.

Economic impact of dengue in Mexico considering reported cases for 2012 to 2016.

BackgroundGiven that dengue disease is growing and may progress to dengue hemorrhagic fever (DHF), data on economic cost and disease burden are important. However, data for Mexico are limited.Methodology/Principal findingsBurden of dengue fever (DF) and DHF in Mexico was assessed using official databases for epidemiological information, disabilities weights from Shepard et al, the reported number of cases and deaths, and costs. Overall costs of dengue were summed from direct medical costs to the health system, cost of dengue to the patient (out-of-pocket expenses [medical and non-medical], indirect costs [loss of earnings, patient and/or caregiver]), and other government expenditures on prevention/surveillance. The first three components, calculated as costs per case by a micro-costing approach (PAATI; program, actions, activities, tasks, inputs), were scaled up to overall cost using epidemiology data from official databases. PAATI was used to calculate cost of vector control and prevention, education, and epidemiological surveillance, based on an expert consensus and normative construction of an ideal scenario.Disability-adjusted life years (DALYs) for Mexico in 2016 were calculated to be 2283.46 (1.87 per 100,000 inhabitants). Overall economic impact of dengue in Mexico for 2012 was US$144 million, of which US$44 million corresponded to direct medical costs and US$5 million to the costs from the patient’s perspective. The estimated cost of prevention/surveillance was calculated with information provided by federal government to be US$95 million. The overall economic impact of DF and DHF showed an increase in 2013 to US$161 million and a decrease to US$133, US$131 and US$130 million in 2014, 2015 and 2016, respectively.Conclusions/SignificanceThe medical and economic impact of dengue were in agreement with other international studies, and highlight the need to include governmental expenditure for prevention/surveillance in overall cost analyses given the high economic impact of these, increasing the necessity to evaluate its effectiveness.

Asymptotic analysis of non-periodical cointegration with high seasonals

Cointegration tests are studied for seasonal time series with large periods. The study is performed asymptotically as the period tends to infinity, which is shown to allow a simple limit distribution to be established. These results offer a simple diagnostic tool for cointegration when the seasonal period is expected to be large, and its critical values do not depend on the form of the deterministic components present in the model. An application to climatic factors and outbreaks of dengue in Mexico illustrates the methods.

Seroprevalence of Dengue Antibodies in Three Urban Settings in Yucatan, Mexico.

.Dengue transmission in Mexico has become a major public health problem. Few epidemiological studies have examined the seroprevalence of dengue in Mexico, and recent estimates are needed to better understand dengue transmission dynamics. We conducted a dengue seroprevalence survey among 1,668 individuals including all age groups in three urban settings in Yucatan, Mexico. Children (< 19 years old) were selected randomly from schools. The adults (≥ 19 years old) were selected from healthcare facilities. Participants were asked to provide a venous blood sample and to answer a brief questionnaire with demographic information. Previous exposure to dengue was determined using indirect immunoglobulin G enzyme-linked immunosorbent assay. The overall seroprevalence was 73.6%. The age-specific seroprevalence increased with age, going from 51.4% (95% confidence interval [CI] = 45.0–57.9%) in children ≤ 8 years to 72% (95% CI = 66.3–77.2%) in the 9- to 14-years old. The highest seroprevalence was 83.4% (95% CI = 77–82.2%) in adults greater than 50 years. The seroprevalence in Merida was 68.6% (95% CI = 65–72%), in Progreso 68.7% (95% CI = 64.2–72.8%), and in Ticul 85.3% (95% CI = 81.9–88.3%). Ticul had the highest seroprevalence in all age groups. Logistic regression analysis showed that age and city of residence were associated with greater risk of prior dengue exposure. The results highlight the level of past exposure to dengue virus including young children. Similar studies should be conducted elsewhere in Mexico and other endemic countries to better understand the transmission dynamics of dengue.

Predicting the Potential Role of Non-human Hosts in Zika Virus Maintenance.

Arboviruses are often maintained in complex cycles involving vertebrates such as mammals or birds and blood-feeding mosquitoes. However, the role of wildlife hosts in their emergence or re-emergence in human populations has received little attention. The recent emergence of Zika virus in America, and previous occurrences of chikungunya and dengue, forces us to confront a potential new disease-emergence phenomenon. Using a spatial data mining framework to identify potential biotic interactions, based on the degree of co-occurrence between different species, we identified those mammal species with the highest potential for establishing mammal–vector interactions, considering as principal vector Aedes aegypti. Seven of the top ten identified mammal species with highest potential were bats, with two of them having previously been confirmed as positive hosts for dengue in Mexico. We hope that this will raise interest of Mexican public health authorities and academic institutions to assess the role of wild hosts in the maintenance and spread of arboviruses.

Persistent Symptoms of Dengue: Estimates of the Incremental Disease and Economic Burden in Mexico.

Dengue is mostly considered an acute illness with three phases: febrile, critical with possible hemorrhagic manifestations, and recovery. But some patients present persistent symptoms, including fatigue and depression, as acknowledged by the World Health Organization. If persistent symptoms affect a non-negligible share of patients, the burden of dengue will be underestimated. On the basis of a systematic literature review and econometric modeling, we found a significant relationship between the share of patients reporting persisting symptoms and time. We updated estimates of the economic burden of dengue in Mexico, addressing uncertainty in productivity loss and incremental expenses using Monte Carlo simulations. Persistent symptoms represent annually about US$22.6 (95% certainty level [CL]: US$13–US$29) million in incremental costs and 28.2 (95% CL: 21.6–36.2) additional disability-adjusted life years per million population, or 13% and 43% increases over previous estimates, respectively. Although our estimates have uncertainty from limited data, they show a substantial, unmeasured burden. Similar patterns likely extend to other dengue-endemic countries.

Dengue Awareness in Latin American Populations: A Questionnaire Study.

IntroductionDengue is an escalating public health concern in Latin American Countries with a dramatic increase of cases reported during the past decade. The objectives of this study were to identify and provide insights into current management and attitudes toward dengue and to understand attitudes to vaccination and current behaviors to prevent dengue in Mexico and Colombia.MethodsThis was a community-based, cross-sectional, descriptive study conducted in urban and rural areas in endemic and non-endemic regions. The interviews were conducted face-to-face using a structured questionnaire containing 58 questions. A quota sampling approach was used to obtain a nationally representative sample of the adult population. All data were weighted to correct for differences between the samples surveyed in each country relative to their general population.ResultsA total of 1978 participants completed the survey. Two percent and 10% of participants in Mexico and Colombia, respectively, had experienced dengue fever, with just under one-third of adults and almost two-thirds of their children hospitalized as a result of the illness. Awareness of dengue was similar in Colombia (76%) and Mexico (68%), with awareness higher in endemic regions than in non-endemic regions. Colombia had a higher proportion of participants (84%) who considered dengue to be a common disease in their country, compared with Mexico (56%). In Mexico and Colombia, 55% and 54% in endemic areas, and 28% and 46% in non-endemic areas believed that everyone was at risk of contracting dengue. In both countries, the most common action undertaken by participants to prevent dengue infection was removal of standing water. At least 70% of participants believe their government could do more to prevent dengue in their country.ConclusionsDengue was identified as a severe and common disease in Mexico and Colombia. Most participants recognized the need to reduce the risk of dengue infection by removal of standing water. Awareness was similar in Colombia and Mexico.Electronic supplementary materialThe online version of this article (doi:10.1007/s40121-015-0068-8) contains supplementary material, which is available to authorized users.

Economic and disease burden of dengue in Mexico.

BackgroundDengue imposes a substantial economic and disease burden in most tropical and subtropical countries. Dengue incidence and severity have dramatically increased in Mexico during the past decades. Having objective and comparable estimates of the economic burden of dengue is essential to inform health policy, increase disease awareness, and assess the impact of dengue prevention and control technologies.Methods and FindingsWe estimated the annual economic and disease burden of dengue in Mexico for the years 2010–2011. We merged multiple data sources, including a prospective cohort study; patient interviews and macro-costing from major hospitals; surveillance, budget, and health data from the Ministry of Health; WHO cost estimates; and available literature. We conducted a probabilistic sensitivity analysis using Monte Carlo simulations to derive 95% certainty levels (CL) for our estimates. Results suggest that Mexico had about 139,000 (95%CL: 128,000–253,000) symptomatic and 119 (95%CL: 75–171) fatal dengue episodes annually on average (2010–2011), compared to an average of 30,941 symptomatic and 59 fatal dengue episodes reported. The annual cost, including surveillance and vector control, was US$170 (95%CL: 151–292) million, or $1.56 (95%CL: 1.38–2.68) per capita, comparable to other countries in the region. Of this, $87 (95%CL: 87–209) million or $0.80 per capita (95%CL: 0.62–1.12) corresponds to illness. Annual disease burden averaged 65 (95%CL: 36–99) disability-adjusted life years (DALYs) per million population. Inclusion of long-term sequelae, co-morbidities, impact on tourism, and health system disruption during outbreaks would further increase estimated economic and disease burden.ConclusionWith this study, Mexico joins Panama, Puerto Rico, Nicaragua, and Thailand as the only countries or areas worldwide with comprehensive (illness and preventive) empirical estimates of dengue burden. Burden varies annually; during an outbreak, dengue burden may be significantly higher than that of the pre-vaccine level of rotavirus diarrhea. In sum, Mexico’s potential economic benefits from dengue control would be substantial.

Instruments for Health Adaptation in Latin America: a Tale of Two Methods

Introduction: The high vulnerability to climate change impacts in health in Latin America calls for the development of tools for health adaptation. In this context, a multi-country project to develop and implement methods to measure vulnerability and for monitoring adaptation intervention was designed in five countries (Bolivia, Brazil, Colombia, Mexico and Paraguay). Methods: Scientific teams from each of the countries met initially to agree on the general objectives, possible approaches, concepts and definitions, and a time frame of the project. It was agreed that each team would work independently from one another in order to respond to countries needs and specificities. Requirements included the need to be based on quantitative methods and based on existing information and data sources. Periodical meetings were held with countries´ decision makers in order to ensure political agreement, commitment and application of results. Each time defined the different models of vulnerability with the aim to develop indicators or an overall vulnerability index. Climate change scenarios were applied for the indicators and indexes. Results: At the end of the three year study two main approaches emerged: one general index spatially based by municipality or equivalent levels of aggregation where developed in Brazil and Paraguay. The other three countries developed a similar spatially based approach but specific for climate sensitive diseases (dengue in Mexico, dengue, malaria and Chagas in Bolivia and dengue and malaria in Colombia). Vulnerability maps were constructed at different levels of aggregation and for different climate change scenarios. Conclusions and Recommendations: Policy makers can use these tools in order to better understand health vulnerabilities and therefore better implement and monitor adaptation interventions. Both methods have their merits and can be applied in different situations as needed.

Dengue en México: incremento en la población juvenil durante la última década

Dengue is one of the principal vector-transmitted diseases leading to important public health problems in Mexico and Latin America. On the American continent this disease has been reported mostly in adults, which contrasts with Asian countries where pediatric dengue is more prominent. During the last decade a shift towards pediatric dengue has been reported in various countries of the American continent. This review, elaborated from data published by the Mexican Ministry of Health, focuses on dengue in Mexico during the last three decades, showing that during the last decade dengue fever and dengue hemorrhagic fever has begun to shift towards a juvenile and pediatric population.

Dimensiones culturales sobre el Dengue en profesionales de la salud de México y Colombia

Understanding cultural dimensions concerning Mexican and Colombian healthcare workers suffering from dengue to produce information and elements for healthcare and prevention.This was a cognitive anthropological study. Purposive sampling was used to select 197 healthcare workers in Morelia, Mexico, and Santiago de Cali, Colombia; free associations lists and pile sorting were used. Terms associated with the concept of dengue and conceptual dimension groups were investigated.Participants cultural conceptions regarding dengue in Mexico emphasised prevention, whilst those in Colombia concentrated on biomedical language and symptoms. Overall, a holistic vision was shown which included a medical vision and related social aspects.Health professionals require more information about dengue and its prevention.

Short communication: Impact of climate variability on the incidence of dengue in Mexico

We evaluated the impact of weather variables and climatic indicators associated with the incidence of dengue in two municipalities of the state of Veracruz, Mexico, from 1995 to 2003. A retrospective ecological study was conducted, using time-series analysis in which we compiled the weekly reported cases of dengue and the weather and climatic parameters: temperature, rainfall and sea-surface temperature (SST), the latter as an El Niño Southern Oscillation indicator. We statistically evaluated the data with autogressive models. The models' predictive abilities were evaluated using data collected from 1995 to 2002 and were validated with those observed for 2003. Each degree Centigrade increase in SST was followed by an increase in the number of dengue cases: 46% in San Andrés Tuxtla (P = 0.001) 16 weeks later and 42% in Veracruz 20 weeks later (P = 0.002). Increases in weekly minimum temperature and rainfall were also significant factors in the increase in the reported cases of dengue. We recommend future studies using the same method, involving larger populations with different geographic location, climate and weather. We also recommend strengthening environmental, health and entomological surveillance systems to improve preparedness and emergency responses.

Impact of Climate Variability on the Incidence of Dengue in Mexico

TM4-O-09 Introduction: Recent scientific evidence suggests that the climatic event known as El Niño/Southern Oscillation (ENSO) intensifies vector-borne disease. ENSO effects on dengue have not been elucidated; therefore, we evaluated the impact of climatic variations associated with this phenomenon on the incidence of dengue in 2 municipalities of the state of Veracruz, San Andrés Tuxtla, and Veracruz, Mexico during the period 1995 to 2003. Methods: We carried out a retrospective ecologic study with time-series analysis in which we compiled the cases of dengue reported weekly and the climatic parameters: temperature, rainfall, and surface sea temperature (SST), the latter as an ENOS indicator. Statistical models were developed using autoregressive integrated moving average models (ARIMA). The model's predictive ability was evaluated using data collected from 1995 to 2002, and it was validated with those observed for 2003. Results: Results showed that each degree Centigrade increase in sea surface temperature was associated with increased number of weekly cases of dengue by 46% (P = 0.001) and 42% (P = 0.002) with 16 weeks and 20 weeks delay in the municipalities of San Andrés Tuxtla and Veracruz, respectively. Increases in weekly minimum temperature and rainfall were also significant factors in the increase in reported cases of dengue. Comparing climate variables coefficients of each municipality, we found no significant differences. Discussion and Conclusions: This study demonstrates, with a series of weekly data, which include 2 ENSO events, that an increase in SST, minimum temperature, and precipitation is associated with an increase of dengue transmission cycles in costal municipalities of the Gulf of Mexico. The results and methods of this study may serve to develop an Early Warning System (EWS), which should be complemented with other variables that influence the transmission of the disease.