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      The Impact of the February 2012 Cold Spell on Health in Italy Using Surveillance Data

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          Abstract

          In February 2012 Italy was hit by an exceptional cold spell with extremely low temperatures and heavy snowfall. The aim of this work is to estimate the impact of the cold spell on health in the Italian cities using data from the rapid surveillance systems. In Italy, a national mortality surveillance system has been operational since 2004 in 34 cities for the rapid monitoring of daily mortality. Data from this system were used to evaluate the impact of the February 2012 cold spell on mortality shortly after the occurrence of the event. Furthermore, a cause-specific analysis was conducted in Roma using the Regional Mortality Registry and the emergency visits (ER) surveillance system. Cold spell episodes were defined as days when mean temperatures were below the 10 th percentile of February distribution for more than three days. To estimate the impact of the cold spell, excess mortality was calculated as the difference between observed and daily expected values. An overall 1578 (+25%) excess deaths among the 75+ age group was recorded in the 14 cities that registered a cold spell in February 2012. A statistically significant excess in mortality was observed in several cities ranging from +22% in Bologna to +58% in Torino. Cause-specific analysis conducted in Roma showed a statistically significant excess in mortality among the 75+ age group for respiratory disease (+64%), COPD (+57%), cardiovascular disease +20% ischemic heart disease (14%) and other heart disease (+33%). Similar results were observed for ER visits. Surveillance systems need to become are a key component of prevention plans as they can help improve public health response and are a valid data source to rapidly quantify the impact on health. Cold-related mortality is still an important issue and should not be underestimated by public health Authorities.

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          Most cited references23

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          Heat-related and cold-related deaths in England and Wales: who is at risk?

          Despite the high burden from exposure to both hot and cold weather each year in England and Wales, there has been relatively little investigation on who is most at risk, resulting in uncertainties in informing government interventions. To determine the subgroups of the population that are most vulnerable to heat-related and cold-related mortality. Ecological time-series study of daily mortality in all regions of England and Wales between 1993 and 2003, with postcode linkage of individual deaths to a UK database of all care and nursing homes, and 2001 UK census small-area indicators. A risk of mortality was observed for both heat and cold exposure in all regions, with the strongest heat effects in London and strongest cold effects in the Eastern region. For all regions, a mean relative risk of 1.03 (95% confidence interval (CI) 1.02 to 1.03) was estimated per degree increase above the heat threshold, defined as the 95th centile of the temperature distribution in each region, and 1.06 (95% CI 1.05 to 1.06) per degree decrease below the cold threshold (set at the 5th centile). Elderly people, particularly those in nursing and care homes, were most vulnerable. The greatest risk of heat mortality was observed for respiratory and external causes, and in women, which remained after control for age. Vulnerability to either heat or cold was not modified by deprivation, except in rural populations where cold effects were slightly stronger in more deprived areas. Interventions to reduce vulnerability to both hot and cold weather should target all elderly people. Specific interventions should also be developed for people in nursing and care homes as heat illness is easily preventable.
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            The impact of influenza epidemics on mortality: introducing a severity index.

            The purpose of this study was to assess the impact of recent influenza epidemics on mortality in the United States and to develop an index for comparing the severity of individual epidemics. A cyclical regression model was applied to weekly national vital statistics from 1972 through 1992 to estimate excesses in pneumonia and influenza mortality and all-cause mortality for each influenza season. Each season was categorized on the basis of increments of 2000 pneumonia and influenza excess deaths, and each of these severity categories was correlated with a range of all-cause excess mortality. Each of the 20 influenza seasons studied was associated with an average of 5600 pneumonia and influenza excess deaths (range, 0-11,800) and 21,300 all-cause excess deaths (range, 0-47,200). Most influenza A(H3N2) seasons fell into severity categories 4 to 6 (23,000-45,000 all-cause excess deaths), whereas most A(H1N1) and B seasons were ranked in categories 1 to 3 (0-23,000 such deaths). From 1972 through 1992, influenza epidemics accounted for a total of 426,000 deaths in the United States, many times more than those associated with recent pandemics. The influenza epidemic severity index was useful for categorizing severity and provided improved seasonal estimates of the total number of influenza-related deaths.
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              Cold exposure and winter mortality from ischaemic heart disease, cerebrovascular disease, respiratory disease, and all causes in warm and cold regions of Europe. The Eurowinter Group.

              (1997)
              Differences in baseline mortality, age structure, and influenza epidemics confound comparisons of cold-related increases in mortality between regions with different climates. The Eurowinter study aimed to assess whether increases in mortality per 1 degree C fall in temperature differ in various European regions and to relate any differences to usual winter climate and measures to protect against cold. Percentage increases in deaths per day per 1 degree C fall in temperature below 18 degrees C (indices of cold-related mortality) were estimated by generalised linear modelling. We assessed protective factors by surveys and adjusted by regression to 7 degrees C outdoor temperature. Cause-specific data gathered from 1988 to 1992 were analysed by multiple regression for men and women aged 50-59 and 65-74 in north Finland, south Finland, Baden-Württemburg, the Netherlands, London, and north Italy (24 groups). We used a similar method to analyse 1992 data in Athens and Palermo. The percentage increases in all-cause mortality per 1 degree C fall in temperature below 18 degrees C were greater in warmer regions than in colder regions (eg, Athens 2.15% [95% CI 1.20-3.10] vs south Finland 0.27% [0.15-0.40]). At an outdoor temperature of 7 degrees C, the mean living-room temperature was 19.2 degrees C in Athens and 21.7 degrees C in south Finland; 13% and 72% of people in these regions, respectively, wore hats when outdoors at 7 degrees C. Multiple regression analyses (with allowance for sex and age, in the six regions with full data) showed that high indices of cold-related mortality were associated with high mean winter temperatures, low living-room temperatures, limited bedroom heating, low proportions of people wearing hats, gloves, and anoraks, and inactivity and shivering when outdoors at 7 degrees C (p 0.05 for mortality from ischaemic heart disease and cerebrovascular disease). Mortality increased to a greater extent with given fall of temperature in regions with warm winters, in populations with cooler homes, and among people who wore fewer clothes and were less active outdoors.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                18 April 2013
                : 8
                : 4
                : e61720
                Affiliations
                [1 ]Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
                [2 ]National Centre for the Prevention of Heat Health Effects, Department of Civil Protection, Rome, Italy
                Public Health Agency of Barcelona, Spain
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: FKD PM ML MD. Analyzed the data: ML FKD DN. Contributed reagents/materials/analysis tools: ML FKD DN. Wrote the paper: FKD ML PM MD.

                Article
                PONE-D-12-25152
                10.1371/journal.pone.0061720
                3630119
                23637892
                7f23b7e2-c968-40f6-86c0-d23a08f4867e
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 20 August 2012
                : 13 March 2013
                Page count
                Pages: 9
                Funding
                This work was carried out within the National Program for the Prevention of Heat Health Effects funded by the Italian Ministry of Health and the EU project “Public Health Adaptation Strategies to Extreme weather events – PHASE” (contract number EAHC 20101103). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Population Biology
                Epidemiology
                Environmental Epidemiology
                Epidemiology of Aging
                Medicine
                Cardiovascular
                Clinical Research Design
                Survey Research
                Epidemiology
                Environmental Epidemiology
                Non-Clinical Medicine
                Environmental Health
                Public Health
                Environmental Health
                Social and Behavioral Sciences
                Sociology
                Demography
                Death Rate

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                Uncategorized

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