Paulo Sérgio Lucio

Socio-economic and Climate Factors Associated with Dengue Fever Spatial Heterogeneity: A Worked Example in New Caledonia.

Background/Objectives Understanding the factors underlying the spatio-temporal distribution of infectious diseases provides useful information regarding their prevention and control. Dengue fever spatio-temporal patterns result from complex interactions between the virus, the host, and the vector. These interactions can be influenced by environmental conditions. Our objectives were to analyse dengue fever spatial distribution over New Caledonia during epidemic years, to identify some of the main underlying factors, and to predict the spatial evolution of dengue fever under changing climatic conditions, at the 2100 horizon. Methods We used principal component analysis and support vector machines to analyse and model the influence of climate and socio-economic variables on the mean spatial distribution of 24,272 dengue cases reported from 1995 to 2012 in thirty-three communes of New Caledonia. We then modelled and estimated the future evolution of dengue incidence rates using a regional downscaling of future climate projections. Results The spatial distribution of dengue fever cases is highly heterogeneous. The variables most associated with this observed heterogeneity are the mean temperature, the mean number of people per premise, and the mean percentage of unemployed people, a variable highly correlated with peoples way of life. Rainfall does not seem to play an important role in the spatial distribution of dengue cases during epidemics. By the end of the 21st century, if temperature increases by approximately 3°C, mean incidence rates during epidemics could double. Conclusion In New Caledonia, a subtropical insular environment, both temperature and socio-economic conditions are influencing the spatial spread of dengue fever. Extension of this study to other countries worldwide should improve the knowledge about climate influence on dengue burden and about the complex interplay between different factors. This study presents a methodology that can be used as a step by step guide to model dengue spatial heterogeneity in other countries.

Modelagem hidrológica determinística e estocástica aplicada à região hidrográfica do Xingu- Pará

Hydrologic modeling is an important tool for the planning and management of water resources use in river basins. In this work, a two-parameter monthly deterministic hydrologic model and the stochastic model, ARIMA, were applied to simulate the monthly runoff of the Xingu river basin in the State of Para. The main objective of this work is to simulate the monthly runoff using the two models and to compare their results. The applied hydrological deterministic model has a simple structure and presented good results, but seems to be very sensitive to extreme precipitation events. The stochastic model ARIMA was able to capture the dynamic of the temporal series, presenting very satisfactory results for the simulation of the monthly runoff at the basin stations. Both models should be applied with caution during the rainy season, when extreme precipitation events and consequently peaks of runoff occur.

A study on the west Sahel rainfall variability: The role of the intertropical convergence zone (ITCZ)

This article provides a report of rainfall analysis results supporting the hypothesis that rainfall variability in the Western Sahel is associate with temporal variability of the incursions of ITCZ over West Africa. It is pointed out that the most significant climatic rainfall changes in Sahel most probably occurred between 1950 and 1975 with the decrease of the annual rainfall totals, a high reduction (about 70%) over the whole region. One of the most significant climatic variations has been the rainfall persistent decline in the Sahel since late 1960’s. Remarkable latitudinal shift of ITF mean position towards the South seems to generate an overall reduction of annual rainfall. In the last two decades covered in this research (1985–2004), rainfall showed some improvement, particularly in the 1990–1999 decade. However, the more humid conditions of the 1950’s and 1960’s were not reestablished yet. The trend was abruptly interrupted by a return of adequate rainfall conditions in 1994. This was considered to be the wettest of the past 30 years and was thought to indicate the end of the drought perhaps. However, the 1994 rainfall total barely exceeded the long-term mean. The 1994 rainy season was unusual in the sense that the anomalously wet conditions occurred in the end of the rainy season and the months following. The temporal characteristics of the series, such as variance, were evaluated using principal components regression.

A Case Study of the Influence of Local Weather on Aedes aegypti (L.) Aging and Mortality

ABSTRACT: The survival rate of mosquitoes is an important topic that affects many aspects of decision-making in mosquito management. This study aims to estimate the variability in the survival rate of Ae. aegypti, and climate factors that are related to such variability. It is generally assumed that the daily probability of mosquito survival is independent of natural environment conditions and age. To test this assumption, a three-year fieldwork (2005–2007) and experimental study was conducted at Fortaleza-CE in Brazil with the aim of estimating daily survival rates of the dengue vector Aedes aegypti under natural conditions in an urban city. Survival rates of mosquitoes may be age-dependent and statistical analysis is a sensitive approach for comparing patterns of mosquito survival. We studied whether weather conditions occurring on a particular day influence the mortality observed on that particular day. We therefore focused on the impact of daily meteorological fluctuations around a given climate average, rather than on the influence of climate itself. With regard to survival time, multivariate analyses using the stepwise logistic regression model, adjusted for daily temperature, relative humidity, and saturated vapor pressure deficit (SVPD), suggest that age, the seasonal factor, and the SVPD were the most dependent mortality factors. Similar results were obtained using the Cox proportional hazard model, which explores the relationships between the survival and explanatory variables.

Distribuição espacial da precipitação sobre o Rio Grande do Norte: estimativas via satélites e medidas por pluviômetros

RAINFALL SPATIAL DISTRIBUTION OVER THE RIO GRANDE DO NORTE BRAZILIAN STATE: SATELLITES ESTIMATES AND RAIN GAUGES MEASUREMENTS The aim of this study was to evaluate the monthly rainfall estimates obtained by two data sources (3B43_V6 algorithm and University of Delaware) for the State of Rio Grande do Norte, during the 1998 to 2008 period. Statistical analysis based on the linear correlation coefficient and on the performance index from a 2x2 contingency table was done. Coastland and semiarid precipitation regimes which depend on geographical location and on soil type coverage were considered. It was noted that the 3B43_V6 underestimated the coastland rainfall and overestimated the rainfall over arid zones. The Delaware mean rainfall agreed well with observed rainfall, but shows discrepancies concerning to interpolation method and grid spacing. The results suggests that both 3B43_V6 and Delaware rainfall dataset are able to capture the rainfall mean variability both in time and space; however, they show deficiency in identifing extreme precipitation events. Keywords: 3B43_V6, Delaware, contingency table, TRMM, semiarid.

The influence of local environment on the aging and mortality of Aedes aegypti (L.): case study in Fortaleza-CE, Brazil.

ABSTRACT: It is generally assumed that the daily probability of survival of mosquitoes is independent of age. To test this assumption we have conducted a three-year experimental fieldwork study (2005–2007) at Fortaleza-CE in Brazil, determining daily survival rates of the dengue vector Aedes aegypti (L.). Survival rates of adult Ae. aegypti may be age-dependent and the statistical analysis is a sensitive approach for comparing patterns of mosquito survival. The mosquito survival data were better fit by a Weibull survival function than by the more traditionally used Gompertz or logistic survival functions. Gompertz, Weibull, or logistic survival functions often fit the survival, and the tails of the survival curves usually appear to fall between the values predicted by the three functions. We corroborate that the mortality of Ae. aegypti in semi-natural conditions may no more be considered as a constant phenomenon during the life of adult mosquitoes but varies according to the age and environmental conditions under a tropical climate. This study estimates the variability in the survival rate of Ae. aegypti and environmental factors that are related to such variability. The statistical analysis shows that the fitting ability, concerning the hazard function, was in decreasing order: Seasonal Cox, the three-parameter Gompertz, and the three-parameter Weibull, that was similar to the three-parameter logistic. The advantage of using the Cox model is that it is convenient for exploring the relationship between survival and several explanatory variables. The Cox model has the advantage of preserving the variable in its original quantitative form and of using a maximum of information. The survival analyses indicate that mosquito mortality is both ageand environment-dependent.

Estimação de sub-registros de óbitos em pequenas áreas com os métodos bayesiano empírico e algoritmo EM

Un gran problema, en lo que se refiere a estimativas demograficas en Brasil, esta relacionado con el nivel y patron de la mortalidad. Los demografos que trabajan con mortalidad en el pais todavia no se sienten muy seguros sobre el comportamiento real de este componente de la dinamica poblacional. Por otro lado, es necesario que se disponga de indicadores de mortalidad para niveles geograficos mas desagregados, sobre todo municipios. El problema es que cuanto mas desagregado, mas complejo se hace el trabajo de estimar cualquier indicador social o demografico. Este trabajo tiene por objetivo estimar y proponer una correccion de subregistros de fallecimientos en el nivel municipal, segun grupos de edad, por medio de dos metodos: estimador bayesiano empirico (BE) y algoritmo EM (Expectation-Maximization). Con el objeto de que los dos metodos fueran puestos en funcionamiento entre municipios semejantes, se realizaron dos ejercicios: se agruparon los municipios segun la mesorregion; y se agruparon los municipios en grupos homogeneos, generados a partir de un analisis de cluster, utilizando las variables grado de urbanizacion, proporcion de obitos por causas externas y la poblacion de cada municipio. Se utilizaron datos del Estado de Rio Grande do Norte, referentes al ano 2000. Para el total del Estado, se estimo un subregistro de un 11% con el estimador BE y de un 12,9% con el algoritmo EM. Otro resultado importante es la posibilidad de evaluar el grado de cobertura de obitos por grupos de edad en municipios y en cualquier nivel de agregacion a partir de este nivel.

Um modelo estocástico combinado de previsão sazonal para a precipitação no Brasil

This article discusses a combined model to perform climate forecast in a seasonal scale. In it, forecasts of specific stochastic models are aggregated to obtain the best forecasts in time. Stochastic models are used in the auto regressive integrated moving average, exponential smoothing and the analysis of forecasts by canonical correlation. The quality control of the forecast is based on the residual analysis and the evaluation of the percentage of reduction of the unexplained variance of the combined model with respect to the individual ones. Examples of application of those concepts to models developed at the Brazilian National Institute of Meteorology (INMET) show good results and illustrate that the forecast of the combined model exceeds in most cases each component model, when compared to observed data.

Spatial pattern recognition of extreme temperature climatology: assessing HadCM3 simulations via NCEP reanalyses over Europe

This article attempts to quantify the spatial uncertainties associated with extreme temperature’s response, by assessing data derived from climate model. This is undertaken by a comparison of the spatial pattern of a long-term time-series aggregation (1960/61–1989/90) for extreme temperatures simulated by a particular GCM (the UK Met Offi ce - Hadley Centre climate model, HadCM3) to that of the USA NCAR NCEP Reanalyses, which are considered as ‘truth’, over the MICE (Modelling the Impacts of Climate Extremes - EU Project) spatial domain. Since evaluation of models is crucial to assessing future scenarios, the aim of this study is to investigate whether the extreme values predicted by the HadCM3 climate model can simulate those produced by NCEP Reanalyses, assuming that the extremes of both models are realizations of the same spatial stochastic process. To get more useful information about the uncertainties surrounding spatial climate projection, one also has to analyze the pattern of temperature extremes in terms of their anomalies. A common technical issue in the assessment of numerical spatial models is based on the Principal Components Analysis and Bayesian Classifi cation for spatial pattern recognition. These methodologies are very important and useful for guiding an evolutionary statistical model-building process. This study leads to the conclusion that the HadCM3 Simulations do not realistically reproduce the NCEP Reanalyses, despite the fact that the climatology of extremes has demonstrated very similar spatial patterns. It is likely therefore that such instability may persist in the future.

Characterization of risk/exposure to climate extremes for the Brazilian Northeast—case study: Rio Grande do Norte

Climate change would increase the risk of floods or droughts. So far, only a few studies have projected changes in extremes on a regional or local scale. None of these studies relied on multiple climate proxies. Only some studies have started to estimate the exposure to flooding or drought as a proxy of risk; so, here, we present an exercise in risk analysis. Studies of climate change and its impacts rarely yield consensus on the distribution of exposure, vulnerability or possible outcomes. In addition, Northeast Brazil (NEB) is known for its temporal and spatial variability of rainfall and several studies have investigated this variability in order to understand damaging episodes such as droughts and floods. In NEB, the phenomenon of drought is a complex issue because millions of people are affected, and so, it is an important object of study in various fields of knowledge. One way of trying to argue about this phenomenon is through the concept of vulnerability. In this preliminary study, one will determine the risk or exposure factor to drought, which is one component of vulnerability, mainly concerning agricultural activities. The drought risk/exposure indicator was constructed based on three indices: the standardized precipitation index (SPI), the precipitation concentration period (PCP) and the precipitation concentration degree (PCD). The exposure indices showed an increase in high values from 1979 to 2008. On the contrary, the period from 1967 to 1996 showed that the risk factor in some micro-regions had low indices in a larger number; one can note that the dynamics of the factor is in an evolution between high and extremes.