Increasing Role of Roof Gutters as Aedes aegypti (Diptera: Culicidae) Breeding Sites in Guadeloupe (French West Indies) and Consequences on Dengue Transmission and Vector Control

During the past ten years, the islands of Guadeloupe (French West Indies) are facing dengue epidemics with increasing numbers of cases and fatal occurrences. The vector Aedes aegypti is submitted to intensive control, with little effect on mosquito populations. The hypothesis that important Ae. aegypti breeding sites are not controlled is investigated herein. For that purpose, the roof gutters of 123 houses were systematically investigated, and the percentage of gutters positive for Ae. aegypti varied from 17.2% to 37.5%, from humid to dry locations. In the dryer location, most of houses had no other breeding sites. The results show that roof gutters are becoming the most important Ae. aegypti breeding sites in some locations in Guadeloupe, with consequences on dengue transmission and vector control

The Relation Between Temperature, Ozone, and Mortality in Nine French Cities During the Heat Wave of 2003

BACKGROUND: During August 2003, record high temperatures were observed across Europe, and France was the country most affected. During this period, elevated ozone concentrations were measured all over the country. Questions were raised concerning the contribution of O(3) to the health impact of the summer 2003 heat wave. METHODS: We used a time-series design to analyze short-term effects of temperature and O(3) pollution on mortality. Counts of deaths were regressed on temperatures and O(3) levels, controlling for possible confounders: long-term trends, season, influenza outbreaks, day of the week, and bank holiday effects. For comparison with previous results of the nine cities, we calculated pooled excess risk using a random effect approach and an empirical Bayes approach. FINDINGS: For the nine cities, the excess risk of death is significant (1.01%; 95% confidence interval, 0.58–1.44) for an increase of 10 μg/m(3) in O(3) level. For the 3–17 August 2003 period, the excess risk of deaths linked to O(3) and temperatures together ranged from 10.6% in Le Havre to 174.7% in Paris. When we compared the relative contributions of O(3) and temperature to this joint excess risk, the contribution of O(3) varied according to the city, ranging from 2.5% in Bordeaux to 85.3% in Toulouse. INTERPRETATION: We observed heterogeneity among the nine cities not only for the joint effect of O(3) and temperatures, but also for the relative contribution of each factor. These results confirmed that in urban areas O(3) levels have a non-negligible impact in terms of public health

Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors

BACKGROUND: During the last decades, dengue viruses have spread throughout the Americas region, with an increase in the number of severe forms of dengue. The surveillance system in Guadeloupe (French West Indies) is currently operational for the detection of early outbreaks of dengue. The goal of the study was to improve this surveillance system by assessing a modelling tool to predict the occurrence of dengue epidemics few months ahead and thus to help an efficient dengue control. METHODS: The Box-Jenkins approach allowed us to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA) model of dengue incidence from 2000 to 2006 using clinical suspected cases. Then, this model was used for calculating dengue incidence for the year 2007 compared with observed data, using three different approaches: 1 year-ahead, 3 months-ahead and 1 month-ahead. Finally, we assessed the impact of meteorological variables (rainfall, temperature and relative humidity) on the prediction of dengue incidence and outbreaks, incorporating them in the model fitting the best. RESULTS: The 3 months-ahead approach was the most appropriate for an effective and operational public health response, and the most accurate (Root Mean Square Error, RMSE = 0.85). Relative humidity at lag-7 weeks, minimum temperature at lag-5 weeks and average temperature at lag-11 weeks were variables the most positively correlated to dengue incidence in Guadeloupe, meanwhile rainfall was not. The predictive power of SARIMA models was enhanced by the inclusion of climatic variables as external regressors to forecast the year 2007. Temperature significantly affected the model for better dengue incidence forecasting (p-value = 0.03 for minimum temperature lag-5, p-value = 0.02 for average temperature lag-11) but not humidity. Minimum temperature at lag-5 weeks was the best climatic variable for predicting dengue outbreaks (RMSE = 0.72). CONCLUSION: Temperature improves dengue outbreaks forecasts better than humidity and rainfall. SARIMA models using climatic data as independent variables could be easily incorporated into an early (3 months-ahead) and reliably monitoring system of dengue outbreaks. This approach which is practicable for a surveillance system has public health implications in helping the prediction of dengue epidemic and therefore the timely appropriate and efficient implementation of prevention activities

Émergence du chikungunya dans les Départements Français d’Amérique : résultats de la surveillance épidémiologique mise en œuvre en avril 2014

National audienc

Airborne exposure to pesticides: a decision-making tool to identify priority areas

National audienceAs part of the Ecophyto2 plan, the Regional Administration of Food, Agriculture and Forestry (Draaf) of Occitania has developed the "EXPO'PHYTO" project. Its aim is to lead a collective and concerted approach in small communities to reduce airborne exposure to plant protection products (PPPs). To test the relevance and feasibility of this approach, Draaf wanted to be able to identify some areas where exposure reduction was a priority over others, by ranking the cantons of the Occitania region in order of their potential exposure burden. Two quantitative indicators, for agricultural professionals and the general population respectively, were constructed at cantonal scale level by combining the use of crop-exposure matrices with population data and urbanization level. The cantons could thus be classified by decreasing value of the indicators. A sensitivity analysis was conducted to verify the robustness of the results. This showed, for each of the two populations, that some predominantly wine-growing cantons remain in the top ten of the 269 listed in Occitania: five cantons for the occupationally exposed population and three cantons for the general population. These three also ranked among the top ten for the occupationally exposed population, regardless of the calculation parameters used. Practices in the use of PPPs are not specific to these cantons, but they have demographic and land-use characteristics that make them more vulnerable in terms of potential exposure. In addition, the presence of vineyards is consistent with recent scientific knowledge. The approach implemented is a decision-making tool to identify priority areas where is needed to reduce the population's airborne PPP exposure and its potential impacts

Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors

Abstract Background During the last decades, dengue viruses have spread throughout the Americas region, with an increase in the number of severe forms of dengue. The surveillance system in Guadeloupe (French West Indies) is currently operational for the detection of early outbreaks of dengue. The goal of the study was to improve this surveillance system by assessing a modelling tool to predict the occurrence of dengue epidemics few months ahead and thus to help an efficient dengue control. Methods The Box-Jenkins approach allowed us to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA) model of dengue incidence from 2000 to 2006 using clinical suspected cases. Then, this model was used for calculating dengue incidence for the year 2007 compared with observed data, using three different approaches: 1 year-ahead, 3 months-ahead and 1 month-ahead. Finally, we assessed the impact of meteorological variables (rainfall, temperature and relative humidity) on the prediction of dengue incidence and outbreaks, incorporating them in the model fitting the best. Results The 3 months-ahead approach was the most appropriate for an effective and operational public health response, and the most accurate (Root Mean Square Error, RMSE = 0.85). Relative humidity at lag-7 weeks, minimum temperature at lag-5 weeks and average temperature at lag-11 weeks were variables the most positively correlated to dengue incidence in Guadeloupe, meanwhile rainfall was not. The predictive power of SARIMA models was enhanced by the inclusion of climatic variables as external regressors to forecast the year 2007. Temperature significantly affected the model for better dengue incidence forecasting (p-value = 0.03 for minimum temperature lag-5, p-value = 0.02 for average temperature lag-11) but not humidity. Minimum temperature at lag-5 weeks was the best climatic variable for predicting dengue outbreaks (RMSE = 0.72). Conclusion Temperature improves dengue outbreaks forecasts better than humidity and rainfall. SARIMA models using climatic data as independent variables could be easily incorporated into an early (3 months-ahead) and reliably monitoring system of dengue outbreaks. This approach which is practicable for a surveillance system has public health implications in helping the prediction of dengue epidemic and therefore the timely appropriate and efficient implementation of prevention activities.</p

Correction: Underestimation of Leptospirosis Incidence in the French West Indies.

[This corrects the article DOI: 10.1371/journal.pntd.0004668.]

Comités d'Experts des Maladies Infectieuses & Émergentes aux Antilles françaises

National audienc