Estimating air temperature using MODIS surface temperature images for assessing Aedes aegypti thermal niche in Bangkok, Thailand.

Dengue, the most widespread urban vector-borne disease, is transmitted to human by the mosquito Aedes aegypti. Its distribution in urban areas is heterogeneous over time and space. In time, it is linked to seasonal variations such as warm and cold seasons, as well as rainy and dry seasons. In space, it is linked to social and environmental conditions, which alternate between rich and deprived neighborhoods, vegetated and densely built areas. These variations in terms of land cover can affect surface and air temperature. As a result of its influence on the mosquito's life cycle, temperature plays a crucial part in dengue epidemics potential. Thus, deciphering the thermal variations effects within cities could lead to the identification of precise thermal comfort zones, favorable to the survival of mosquito populations during inter-epidemic periods. The maps that could be produced as a result would enable health authorities to target specific areas. Most cities are equipped with meteorological stations. However, the network is generally not dense enough to precisely identify thermal comfort zones. Remote sensing can be used as a tool to solve this issue. The methodological objective of this paper is to assess the potential of the TVX (Temperature-Vegetation indeX) approach applied to MODIS thermal images for the purpose of estimating daily minimum and maximum air temperatures in the city of Bangkok, Thailand. The TVX approach has been seldom used over urban areas due to the heterogeneous nature of cities in terms of land cover. However, our study shows that in vegetated cities such as Bangkok, the TVX method provides valuable results which can be used to assess thermal niche of A. aegypti.

Importance of Public Transport Networks for Reconciling the Spatial Distribution of Dengue and the Association of Socio-Economic Factors with Dengue Risk in Bangkok, Thailand.

Dengue is the most widespread mosquito-borne viral disease of man and spreading at an alarming rate. Socio-economic inequality has long been thought to contribute to providing an environment for viral propagation. However, identifying socio-economic (SE) risk factors is confounded by intra-urban daily human mobility, with virus being ferried across cities. This study aimed to identify SE variables associated with dengue at a subdistrict level in Bangkok, analyse how they explain observed dengue hotspots and assess the impact of mobility networks on such associations. Using meteorological, dengue case, national statistics, and transport databases from the Bangkok authorities, we applied statistical association and spatial analyses to identify SE variables associated with dengue and spatial hotspots and the extent to which incorporating transport data impacts the observed associations. We identified three SE risk factors at the subdistrict level: lack of education, % of houses being cement/brick, and number of houses as being associated with increased risk of dengue. Spatial hotspots of dengue were found to occur consistently in the centre of the city, but which did not entirely have the socio-economic risk factor characteristics. Incorporation of the intra-urban transport network, however, much improved the overall statistical association of the socio-economic variables with dengue incidence and reconciled the incongruous difference between the spatial hotspots and the SE risk factors. Our study suggests that incorporating transport networks enables a more real-world analysis within urban areas and should enable improvements in the identification of risk factors.

A spatiotemporal dataset for integrated assessment and modelling of crop-livestock integration with the MAELIA simulation platform.

The general purpose of the primary and secondary data available in this article is to support an integrated assessment of scenarios of crop-livestock integration at the territorial level i.e. of exchanges between arable and livestock farms. The data is a result of a research collaboration between the scientist from INRAE, agricultural advisers from Chamber of Agriculture of Pays de la Loire (CRAPL) and a collective of five arable and two livestock farmers located in the district of Pays de Pouzauges (Vendée department, western France). All participants formed part of the DiverIMPACTS project (https://www.diverimpacts.net/) that aims to achieve the full potential of diversification of cropping systems for improved productivity, delivery of ecosystem services and resource-efficient and sustainable value chains in Europe. The first dataset corresponds to the inputs of MAELIA (http://maelia-platform.inra.fr/), a spatial agent-based simulation platform that was used to support an iterative design and assessment of scenarios to redesign cropping systems. The second dataset corresponds to the outputs of MAELIA simulations and the associated indicators at the farm, group and territory level. The data comprise multiple shape and csv files characterizing the edaphic-climatic heterogeneity of the territory and cropping systems, farmers' crop management rules (IF-THEN rules) and general information about the farms (e.g. crops, agricultural equipment, average crop yields). Data is reported for the baseline situation and three exchange scenarios containing different innovative cropping systems co-designed by scientists, agricultural advisers and the farmers. The data presented here can be found in the Portail Data INRA repository (https://doi.org/10.15454/3ZTCF5) and were used in the research article "Fostering local crop-livestock integration via legume exchanges using an innovative integrated assessment and modelling approach: MAELIA" [1].

Impact of neighbourhood socio-economic status on bystander cardiopulmonary resuscitation in Paris.

BACKGROUND: No European data currently describe the relation between neighbourhood socio-economic status (SES) and rates of out-of-hospital cardiac arrest (OHCA) bystander cardiopulmonary resuscitation (CPR). This study aims to analyse this effect with a robust deprivation index. METHODS: Data about all OHCA in Paris were collected prospectively between 2000 and 2010. A geographical neighbourhood unit was assigned to each case. Median household income, and rates of blue-collar workers, unemployment, and adults without high school diplomas were selected as SES characteristics and used to classify neighbourhoods as low SES or higher SES. We analysed the relationship between neighbourhood SES characteristics and the probability of receiving bystander CPR. RESULTS: Of the 4009 OHCA with mappable addresses recorded, 777 (19.4%) received bystander CPR. Compared to OHCA who did not receive bystander CPR, those receiving CPR were significantly more likely to have occurred in public locations, have had a witness to their OHCA, and not to have collapsed in a low SES neighbourhood, or in a neighbourhood with a median household income in the lowest quartile and with rates of no high school diplomas and blue-collar workers in the highest quartile. In the multilevel analyses, bystander CPR provision was significantly less frequent in low than in higher SES neighbourhoods (OR 0.85; 95% confidence interval [CI] 0.72-0.99). CONCLUSION: In the city of Paris, OHCA victims were less likely to receive bystander CPR in low SES neighbourhoods. These first European data are consistent with observations in North America and Asia.

Urban climate versus global climate change-what makes the difference for dengue?

The expansion in the geographical distribution of vector-borne diseases is a much emphasized consequence of climate change, as are the consequences of urbanization for diseases that are already endemic, which may be even more important for public health. In this paper, we focus on dengue, the most widespread urban vector-borne disease. Largely urban with a tropical/subtropical distribution and vectored by a domesticated mosquito, Aedes aegypti, dengue poses a serious public health threat. Temperature plays a determinant role in dengue epidemic potential, affecting crucial parts of the mosquito and viral life cycles. The urban predilection of the mosquito species will further exacerbate the impact of global temperature change because of the urban heat island effect. Even within a city, temperatures can vary by 10 °C according to urban land use, and diurnal temperature range (DTR) can be even greater. DTR has been shown to contribute significantly to dengue epidemic potential. Unraveling the importance of within-city temperature is as important for dengue as for the negative health consequences of high temperatures that have thus far been emphasized, for example, pollution and heat stroke. Urban and landscape planning designed to mitigate the non-infectious negative effects of temperature should additionally focus on dengue, which is currently spreading worldwide with no signs of respite.

Optimization of automated external defibrillator deployment outdoors: An evidence-based approach.

BACKGROUND: The benefits of available automatic external defibrillators (AEDs) for out-of-hospital cardiac arrests (OHCAs) are well known, but strategies for their deployment outdoors remain somewhat arbitrary. Our study sought to assess different strategies for AED deployment. METHODS: All OHCAs in Paris between 2000 and 2010 were prospectively recorded and geocoded. A guidelines-based strategy of placing an AED in locations where more than one OHCA had occurred within the past five years was compared to two novel strategies: a grid-based strategy with a regular distance between AEDs and a landmark-based strategy. The expected number of AEDs necessary and their median (IQR) distance to the nearest OHCA were assessed for each strategy. RESULTS: Of 4176 OHCAs, 1372 (33%) occurred in public settings. The first strategy would result in the placement of 170 AEDs, with a distance to OHCA of 416 (180-614) m and a continuous increase in the number of AEDS. In the second strategy, the number of AEDs and their distance to the closest OHCA would change with the grid size, with a number of AEDs between 200 and 400 seeming optimal. In the third strategy, median distances between OHCAs and AEDs would be 324m if placed at post offices (n=195), 239 at subway stations (n=302), 137 at bike-sharing stations (n=957), and 142 at pharmacies (n=1466). CONCLUSION: This study presents an original evidence-based approach to strategies of AED deployment to optimize their number and location. This rational approach can estimate the optimal number of AEDs for any city.