Weather conditions and visits to the medical wing of emergency rooms in a metropolitan area during the warm season in Israel: a predictive model

Implications of climate and outdoor thermal comfort on tourism: the case of Italy

Whether a journey is pleasant or not usually depends on the climatic conditions which permit to perform outdoor activities. The perception of climatic conditions, determined by physiological and psychological factors, can vary according to different adaptation phenomena related to the person involved and the weather conditions of the place where they live. Studying the bioclimatology of a country characterized by a high flux of tourism, as e.g. Italy, can provide some important information about where and when is it better to visit a place. Some differences have to be specified though, like the local tourism, which is used to that type of climate, and international tourism, which is formed by people coming from countries with different types of climates. Therefore this paper examined the climatic conditions and outdoor thermal comfort through the Mediterranean Outdoor Comfort Index (MOCI) for local tourism and through the predicted mean vote (PMV) for international tourism. The cities examined were three (Venice, Rome and Palermo located in the North, Centre and South of Italy, respectively), where average information were collected every week for an entire year. Finally, a map of the entire Italian territory reporting the seasonal average values of these indexes was also reported.

Forecasting asthma-related hospital admissions in London using negative binomial models

Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.

A comparative climate analysis of heat-related emergency 911 dispatches: Chicago, Illinois and Phoenix, Arizona USA 2003 to 2006

Research into the health impacts of heat has proliferated since 2000. Temperature increases could exacerbate the increased heat already experienced by urban populations due to urbanization. Heat-related mortality studies have found that hot southern cities in North America have not experienced the summer increases in mortality found in their more northern counterparts. Heat-related morbidity studies have not assessed this possible regional difference. This comparison study uses data from emergency 911 dispatches [referred to as heat-related dispatches (HRD)] identified by responders as heat-related for two United States cities located in different regions with very different climates: Chicago, Illinois in the upper midwest and Phoenix, Arizona in the southwest. Phoenix's climate is hot and arid. Chicago's climate is more temperate, but can also experience days with unusually high temperatures combined with high humidity. This study examines the relationships between rising HRD and daily temperatures: maximum (Tmax); apparent (ATmax): minimum (Tmin) and two energy balance indices (PET and UTCI). Phoenix had more HRD cumulatively, over a longer warm weather season, but did not experience the large spikes in HRD that occurred in Chicago, even though it was routinely subjected to much hotter weather conditions. Statistical analyses showed the strongest relationships to daily ATmax for both cities. Phoenix's lack of HRD spikes, similar to the summer mortality patterns for southern cities, suggests an avenue for future research to better understand the dynamics of possible physiological or behavioral adaption that seems to reduce residents' vulnerability to heat.

Climate change and health in Israel: adaptation policies for extreme weather events

Climatic changes have increased the world-wide frequency of extreme weather events such as heat waves, cold spells, floods, storms and droughts. These extreme events potentially affect the health status of millions of people, increasing disease and death. Since mitigation of climate change is a long and complex process, emphasis has recently been placed on the measures required for adaptation. Although the principles underlying these measures are universal, preparedness plans and policies need to be tailored to local conditions. In this paper, we conducted a review of the literature on the possible health consequences of extreme weather events in Israel, where the conditions are characteristic of the Mediterranean region. Strong evidence indicates that the frequency and duration of several types of extreme weather events are increasing in the Mediterranean Basin, including Israel. We examined the public health policy implications for adaptation to climate change in the region, and proposed public health adaptation policy options. Preparedness for the public health impact of increased extreme weather events is still relatively limited and clear public health policies are urgently needed. These include improved early warning and monitoring systems, preparedness of the health system, educational programs and the living environment. Regional collaboration should be a priority.

Semistructured black-box prediction: proposed approach for asthma admissions in London

Asthma is a global public health problem and the most common chronic disease among children. The factors associated with the condition are diverse, and environmental factors appear to be the leading cause of asthma exacerbation and its worsening disease burden. However, it remains unknown how changes in the environment affect asthma over time, and how temporal or environmental factors predict asthma events. The methodologies for forecasting asthma and other similar chronic conditions are not comprehensively documented anywhere to account for semistructured noncausal forecasting approaches. This paper highlights and discusses practical issues associated with asthma and the environment, and suggests possible approaches for developing decision-making tools in the form of semistructured black-box models, which is relatively new for asthma. Two statistical methods which can potentially be used in predictive modeling and health forecasting for both anticipated and peak events are suggested. Importantly, this paper attempts to bridge the areas of epidemiology, environmental medicine and exposure risks, and health services provision. The ideas discussed herein will support the development and implementation of early warning systems for chronic respiratory conditions in large populations, and ultimately lead to better decision-making tools for improving health service delivery.