QUANTIFICATION DE L'EFFICACITE DES PRATIQUES DE CONTROLE DES MALADIES DES GRANDES CULTURES EN FRANCE

A l'heure où l'opinion publique pousse à une réduction de l'utilisation des pesticides, l'efficacité et la nécessité des pratiques agricoles actuelles sur la protection des cultures est sur la sellette (Delbos et al., 2014; Duru et al., 2014; Bonaudo et al. 2014). Les pertes de rendement moyennes induites par les bioagresseurs sont mal connues du fait de la grande variabilité de présence des bioagresseurs et de l'apparition régulière de résistances qui dégradent l'efficacité des traitements (Comins, 1977; Jutsum et al., 1998). De plus les estimations disponibles sont généralement des pertes maximales et non moyennes, estimées en comparant des bandes traitées et non - traitées. Cela ne permet pas l'estimation de l'impact des bioagresseurs non évitée par le traitement. Ici, nous analysons des données de suivis d'épidémiosurveillance de 13 maladies et de 12 insectes dans toute la France sur une période de 9 ans. La pression de chaque bio- agresseur est calculée à l'échelle du département à partir des observations faites sur l'année. Plusieurs modèles sont ensuite testés afin de prédire l'impact d'un groupe de bio-agresseurs sur le rendement départemental de leur culture cible. Nous montrons que la majorité des bio-agresseurs étudiés n'a globalement pas d'impact significatif sur le rendement, ce qui suggère qu'ils sont bien contenus à l'échelle nationale par les différents traitements appliqués sur blé, orge et colza. La septoriose (Septoria tritici) et le puceron des épis (Sitobion avenae) sur blé, ainsi que les charançons du bourgeon et des siliques sur colza apparaissent comme les plus problématiques car ayant un impact négatif significatif dans la plupart des modèles testés

Mapping the Spatial Distribution of a Disease-Transmitting Insect in the Presence of Surveillance Error and Missing Data

Maps of the distribution of epidemiological data often ignore surveillance error or possible correlations between missing information and outcomes. We analyse presence–absence data at the household level (12050 points) of a disease‐carrying insect in Mariano Melgar, Peru, collected as part of the Arequipan Ministry of Health\u27s efforts to control Chagas disease. We construct a Bayesian hierarchical model to locate regions that are vulnerable to under‐reporting due to surveillance error, accounting for variability in participation due to infestation status. The spatial correlation in the data allows us to identify relative inspector sensitivity and to elucidate the relationship between participation and infestation. We show that naive estimates of prevalence would be biased by surveillance error and missingness at random assumptions. We validate our results through simulations and observe how randomized inspector assignments may improve prevalence estimates. Our results suggests that bias due to imperfect observations and missingness at random can be assessed and corrected in prevalence estimates of spatially auto-correlated binary variables

Racial Disparities in Geographic Access to Primary Care in Philadelphia

Although Philadelphia has an adequate supply of primary care providers overall, spatial analysis shows wide variation across neighborhoods, with stark racial disparities. This study identifies six low-access areas within the city that warrant attention

Multi-scale studies of the relationships between cropping structure and pest and disease regulation services

International audienceThe early detection of DNA mutations such as DNA mismatches is of major interest. Indeed, the accumulation of mismatches into the genome arises from deficiencies of the cellular mismatch repair machinery that is often associated with several types of cancers being resistant to classic chemotherapeutics. In this context, ruthenium(II) compounds bearing a planar extended ligand appear to be excellent candidates as DNA photoprobes since they exhibit high affinity for DNA as well as tuneable luminescence properties. Herein, we report on the synthesis of a novel dissymmetric acridine based Ru(II) complex, [Ru (bpy) 2 napp] 2+ , along with the study of its ability to photodetect DNA mismatches. We also investigated the origin of the ability of the complex to photodetect mismatches via CD-melting assays and bio-layer interferometry. Interestingly, this behaviour may be attributed to a better protection of the excited state of the complex from non-radiative deexcitation sources (e.g., collisions with the solvent, oxygen photosensi-tization, etc.) when intercalated into well-matched compared to mismatched DNA

Is Participation Contagious? Evidence From a Household Vector Control Campaign in Urban Peru

Objective: High rates of household participation are critical to the success of door-to-door vector control campaigns. We used the Health Belief Model to assess determinants of participation, including neighbour participation as a cue to action, in a Chagas disease vector control campaign in Peru. Methods: We evaluated clustering of participation among neighbours; estimated participation as a function of household infestation status, neighbourhood type and number of participating neighbours; and described the reported reasons for refusal to participate in a district of 2911 households. Results: We observed significant clustering of participation along city blocks (p\u3c0.0001). Participation was significantly higher for households in new versus established neighbourhoods, for infested households, and for households with more participating neighbours. The effect of neighbour participation was greater in new neighbourhoods. Conclusions: Results support a ‘contagion’ model of participation, highlighting the possibility that one or two participating households can tip a block towards full participation. Future campaigns can leverage these findings by making participation more visible, by addressing stigma associated with spraying, and by employing group incentives to spray

The Effects of City Streets on an Urban Disease Vector.

With increasing urbanization vector-borne diseases are quickly developing in cities, and urban control strategies are needed. If streets are shown to be barriers to disease vectors, city blocks could be used as a convenient and relevant spatial unit of study and control. Unfortunately, existing spatial analysis tools do not allow for assessment of the impact of an urban grid on the presence of disease agents. Here, we first propose a method to test for the significance of the impact of streets on vector infestation based on a decomposition of Moran’s spatial autocorrelation index; and second, develop a Gaussian Field Latent Class model to finely describe the effect of streets while controlling for cofactors and imperfect detection of vectors. We apply these methods to cross-sectional data of infestation by the Chagas disease vector Triatoma infestans in the city of Arequipa, Peru. Our Moran’s decomposition test reveals that the distribution of T. infestans in this urban environment is significantly constrained by streets (p,0.05). With the Gaussian Field Latent Class model we confirm that streets provide a barrier against infestation and further show that greater than 90% of the spatial component of the probability of vector presence is explained by the correlation among houses within city blocks. The city block is thus likely to be an appropriate spatial unit to describe and control T. infestans in an urban context. Characteristics of the urban grid can influence the spatial dynamics of vector borne disease and should be considered when designing public health policies

Lokalmeteorologiska förhållanden i Västra Ängby, Knivsta : förstudie /

<p>Variation of pollen beetle abundance along within-field (A) and between-field (B) transects as a function of distance (km) to woodland edges. (A) Number of pollen beetles per sampling point within two different OSR fields (fields in complex site, C). (B) Mean number of pollen beetles per field in three transects (in zones S, for simple landscape, and HC, for highly complex landscape). Abundance were measured on 10 OSR plants at each sampling point during three (A) or four (B) consecutive weeks (dates 1 to 4). Trans: Transect.</p

Evaluation of Spatially Targeted Strategies to Control Non-Domiciliated Triatoma dimidiata Vector of Chagas Disease

Chagas disease is one of the most important parasitic diseases in Latin America. Since the 1980's, many national and international initiatives have contributed to eliminate vectors developing inside human domiciles. Today's challenge is to control vectors that are non-adapted to the human domicile, but still able to transmit the parasite through regular short stay in the houses. Here, we assess the potential of different control strategies applied in specific spatial patterns using a mathematical model that reproduces the dynamic of dispersion of such ‘non-domiciliated’ vectors within a village of the Yucatan Peninsula, Mexico. We show that no single strategy applied in the periphery of the village, where the insects are more abundant, provides satisfying protection to the whole village. However, combining the use of insect screens in houses at the periphery of the village (to simultaneously fight insects dispersing from the garden and the forest), and the cleaning of the peri-domicile areas of the centre of the village (where sylvatic insects are absent), would provide a cost-effective control. This type of spatially mixed strategy offers a promising way to reduce the cost associated with the repeated interventions required to control non-domiciliated vectors that permanently attempt to infest houses

Characterization of the Dispersal of Non-Domiciliated Triatoma dimidiata through the Selection of Spatially Explicit Models

Chagas disease is one of the most important neglected diseases in Latin America. Although insecticides have been successfully sprayed to control domiciliated vector populations, this strategy has proven to be ineffective in areas where non-domiciliated vectors immigrating from peridomestic or sylvatic ecotopes can (re-)infest houses. The development of strategies for the control of non-domiciliated vectors has thus been identified by the World Health Organization as a major challenge. Such development primarily requires a description of the spatio-temporal dynamics of infestation by these vectors, and a good understanding of their dispersal. We combined for the first time extensive spatio-temporal data sets describing house infestation dynamics by Triatoma dimidiata inside one village, and spatially explicit population dynamics models. The models fitted and predicted remarkably the observed infestation dynamics. They thus provided both key insights into the dispersal of T. dimidiata in this area, and a suitable mathematical background to evaluate the efficacy of various control strategies. Interestingly, the observed and modelled patterns of infestation suggest that interventions could focus on the periphery of the village, where there is the highest risk of transmission. Such spatial optimization may allow for reducing the cost of control, compensating for repeated interventions necessary for non-domiciliated vectors