Raquel Martins Lana

Seasonal and nonseasonal dynamics of Aedes aegypti in Rio de Janeiro, Brazil: Fitting mathematical models to trap data

Mathematical models suggest that seasonal transmission and temporary cross-immunity between serotypes can determine the characteristic multi-year dynamics of dengue fever. Seasonal transmission is attributed to the effect of climate on mosquito abundance and within host virus dynamics. In this study, we validate a set of temperature and density dependent entomological models that are built-in components of most dengue models by fitting them to time series of ovitrap data from three distinct neighborhoods in Rio de Janeiro, Brazil. The results indicate that neighborhoods differ in the strength of the seasonal component and that commonly used models tend to assume more seasonal structure than found in data. Future dengue models should investigate the impact of heterogeneous levels of seasonality on dengue dynamics as it may affect virus maintenance from year to year, as well as the risk of disease outbreaks.

Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis

BackgroundIn the process of geographical retraction of malaria, some important endemicity pockets remain. Here, we report results from a study developed to obtain detailed community data from an important malaria hotspot in Latin America (Alto Juruá, Acre, Brazil), to investigate the association of malaria with socioeconomic, demographic and living conditions.MethodsA household survey was conducted in 40 localities (nxa0=xa0520) of Mâncio Lima and Rodrigues Alves municipalities, Acre state. Information on previous malaria, schooling, age, gender, income, occupation, household structure, habits and behaviors related to malaria exposure was collected. Multiple correspondence analysis (MCA) was applied to characterize similarities between households and identify gradients. The association of these gradients with malaria was assessed using regression.ResultsThe first three dimensions of MCA accounted for almost 50% of the variability between households. The first dimension defined an urban/rurality gradient, where urbanization was associated with the presence of roads, basic services as garbage collection, water treatment, power grid energy, and less contact with the forest. There is a significant association between this axis and the probability of malaria atxa0the household level, OR = 1.92 (1.23–3.02). The second dimension described a gradient from rural settlements in agricultural areas to those in forested areas. Access via dirt road or river, access to electricity power-grid services and aquaculture were important variables. Malaria was at lower risk at the forested area, OR = 0.55 (1.23–1.12). The third axis detected intraurban differences and did not correlate with malaria.ConclusionsLiving conditions in the study area are strongly geographically structured. Although malaria is found throughout all the landscapes, household traits can explain part of the variation found in the odds of having malaria. It is expected these results stimulate further discussions on modelling approaches targeting a more systemic and multi-level view of malaria dynamics.

Playing against dengue design and development of a serious game to help tackling dengue

Dengue is a global public health challenge. The dengue virus is transmitted mainly by the Aedes aegypti mosquito, which is also a vector of other diseases such as zika, chikungunya and urban yellow fever. Its transmission dynamics is complex, involving several actors, factors and processes. Acting against vectors is still an important strategy, mainly due to limitations in efficacy and accessibility of vaccines. We believe that including and awareness of population is an important factor to address the problem. This project aims to design and develop a serious game to support actions and strategies based on prevention and epidemiological surveillance. In order to raise awareness about vector ecology and disease transmission dynamics, the game design presents information and seeks to encourage behavior changes in a playful environment. Moreover, gamification strategies are being used to stimulate concrete actions in real world. A mix of 2D-based game, augmented reality, virtual reality and the real world itself, will provide the proper environment to offer fun with the purpose of helping to deal with this complex problem. This paper presents the game design and current development stage. The artifacts are being developed in an iterative and incremental way, involving activities of conception, design, construction/prototyping and evaluation. Results include the game design, prototypes and the release of a demo version.

DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics

The prevention and control of dengue are great public health challenges for many countries, particularly since 2015, as other arboviruses have been observed to interact significantly with dengue virus. Different approaches and methodologies have been proposed and discussed by the research community. An important tool widely used is modeling and simulation, which help us to understand epidemic dynamics and create scenarios to support planning and decision making processes. With this aim, we proposed and developed DengueME, a collaborative open source platform to simulate dengue disease and its vector’s dynamics. It supports compartmental and individual-based models, implemented over a GIS database, that represent Aedes aegypti population dynamics, human demography, human mobility, urban landscape and dengue transmission mediated by human and mosquito encounters. A user-friendly graphical interface was developed to facilitate model configuration and data input, and a library of models was developed to support teaching-learning activities. DengueME was applied in study cases and evaluated by specialists. Other improvements will be made in future work, to enhance its extensibility and usability.

Factors associated with overweight: are the conclusions influenced by choice of the regression method?

BackgroundDifferent analytical techniques have been used to study the determinants of overweight. However, certain commonly used techniques may be limited by the continuous nature and skewed distribution of body mass index (BMI) data. In this article, different regression models are compared to identify the best approach for analysing predictors of BMI.MethodsData collected on 2270 nurses at 18 public hospitals in Rio de Janeiro, RJ (2010–2011) were analysed (80.6xa0% of the respondents). The explanatory variables considered were age, marital status, race/colour, mother’s schooling, domestic overload, years worked at night, consumption of fried food, physical inactivity, self-rated health and BMI at age 20xa0years. In addition to gamma regression, regarded as the reference method for selecting the set of explanatory variables described here, other modelling strategies – including linear, quantile (for the 0.25, 0.50 and 0.75 quantiles), binary and multinomial logistic regression – were compared in terms of final results and measures of fit.ResultsThe variables age, marital status, race/colour, domestic overload, self-rated health, physical inactivity and BMI at age 20xa0years were significantly associated with BMI, independently of the method used. In the same way, consumption of fried food was significant in all the models, but a dose–response pattern was identified only in the gamma and normal models and the quantile model for the 0.75 quantile. Years worked at night was also associated with BMI in these three models only. The variable mother’s schooling returned significant results only for the category 12 or more years of schooling, except for overweight in the multinomial model and for the 0.50 quantile in the quantile model, in which the two categories were not significant. The results of the quantile regression showed that, generally, the effects of the variables investigated were greater in the upper quantiles of the BMI distribution. Of the models using BMI in its continuous form, the gamma model showed best fit, followed by the quantile models (0.25 and 0.5 quantiles).ConclusionsThe different strategies used produced similar results for the factors associated with BMI, but differed in the magnitude of the associations and goodness of fit. We recommend using the different approaches in combination, because they furnish complementary information on the problem studied.

A framework for modeling and simulating aedes aegypti and dengue fever dynamics

Dengue fever represents a great challenge for many countries, and methodologies to prevent and/or control its transmission have been largely discussed by the research community. Modeling is a powerful tool to understand epidemic dynamics and to evaluate costs, benefits and effectiveness of control strategies. In order to assist decision-makers and researchers in the evaluation of different methodologies, we developed DengueME, a collaborative open source platform to simulate dengue disease and its vectors dynamics. DengueME provides a series of compartmental and individual-based models, implemented over a GIS database, that represents the Aedes aegyptis life cycle, human demography, human mobility, urban landscape and dengue transmission. The platform is designed to allow easy simulation of intervention scenarios. A GUI was developed to facilitate model configuration and data input.

Assessment of a trap based Aedes aegypti surveillance program using mathematical modeling

The goal of this study was to assess the goodness-of-fit of theoretical models of population dynamics of Aedes aegypti to trap data collected by a long term entomological surveillance program. The carrying capacity K of this vector was estimated at city and neighborhood level. Adult mosquito abundance was measured via adults collected weekly by a network of sticky traps (Mosquitraps) from January 2008 to December 2011 in Vitória, Espírito Santo, Brazil. K was the only free parameter estimated by the model. At the city level, the model with temperature as a driver captured the seasonal pattern of mosquito abundance. At the local level, we observed a spatial heterogeneity in the estimated carrying capacity between neighborhoods, weakly associated with environmental variables related to poor infrastructure. Model goodness-of-fit was influenced by the number of sticky traps, and suggests a minimum of 16 traps at the neighborhood level for surveillance.

The Urban Gradient in Malaria-Endemic Municipalities in Acre: Revisiting the Role of Locality

Urbanization has altered the distribution of diseases of public health importance along gradients of human occupation. Adopting dichotomous urban/rural categories to explain differences in the risk of exposure, as well as the prevention of diseases is insufficient. In this paper, we present the potential of representations based on the gradient perspective to characterize the living spaces of municipalities where malaria is endemic in northwest Acre. Inventoried data in 40 localities in the Mâncio Lima and Rodrigues Alves municipalities and information on land use and land cover obtained from the TerraClass Database were used to characterize the urban spatial forms and their social content. Results showed a gradient of intensities: from municipal seats to the most connected localities through the road network to riverine communities. Based on the results, we hope to advance the discussion about the use of normative definitions of “urban” and “rural” for public policies and actions to control and eliminate malaria, considering the position of each locality in its own locally referenced urban gradient.

The introduction of dengue follows transportation infrastructure changes in the state of Acre, Brazil: A network-based analysis

Human mobility, presence and passive transportation of Aedes aegypti mosquito, and environmental characteristics are a group of factors which contribute to the success of dengue spread and establishment. To understand this process, we assess data from dengue national and municipal basins regarding population and demographics, transportation network, human mobility, and Ae. aegypti monitoring for the Brazilian state of Acre since the first recorded dengue case in the year 2000 to the year 2015. During this period, several changes in Acre’s transport infrastructure and urbanization have been started. To reconstruct the process of dengue introduction in Acre, we propose an analytic framework based on concepts used in malaria literature, namely vulnerability and receptivity, to inform risk assessments in dengue-free regions as well as network theory concepts for disease invasion and propagation. We calculate the probability of dengue importation to Acre from other Brazilian states, the evolution of dengue spread between Acrean municipalities and dengue establishment in the state. Our findings suggest that the landscape changes associated with human mobility have created favorable conditions for the establishment of dengue virus transmission in Acre. The revitalization of its major roads, as well as the increased accessibility by air to and within the state, have increased dengue vulnerability. Unplanned urbanization and population growth, as observed in Acre during the period of study, contribute to ideal conditions for Ae. aegypti mosquito establishment, increase the difficulty in mosquito control and consequently its local receptivity.

Correction to: Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis

After publication of the article [1], it has been brought to our attention that the y-axis of Fig.xa06 has been labeled incorrectly. It should read “linear predictor”. This has now been corrected in the original article.