scholarly journals The impact of the 2003 heat wave on daily mortality in England and Wales and the use of rapid weekly mortality estimates

2005 ◽  
Vol 10 (7) ◽  
pp. 15-16 ◽  
Author(s):  
H Johnson ◽  
S Kovats ◽  
G McGregor ◽  
J Stedman ◽  
M Gibbs ◽  
...  
Keyword(s):  
Heat Wave ◽  
Excess Mortality ◽  
Heat Waves ◽  
Mortality Data ◽  
Daily Mortality ◽  
England And Wales ◽  
National Statistics ◽  
The United Kingdom ◽  
The Impact ◽  
Mortality Estimates

This paper describes a retrospective analysis of the impact of the 2003 heat wave on mortality in England and Wales, and compares this with rapid estimates based on the Office for National Statistics routine weekly deaths reporting system. Daily mortality data for 4 to 13 August 2003, when temperatures were much hotter than normally seen in England, were compared with averages for the same period in years 1998 to 2002. The August 2003 heat wave was associated with a large short-term increase in mortality, particularly in London. Ozone and particulate matter concentrations were also elevated during the heat wave. Overall, there were 2139 (16%) excess deaths in England and Wales. Worst affected were people over the age of 75 years. The impact was greatest in the London region where deaths in those over the age of 75 increased by 59%. Estimated excess mortality was greater than for other recent heat waves in the United Kingdom. The estimated number of deaths registered each week is reported by the Office for National Statistics. The first clear indication of a substantial increase in deaths was published on 21 August 2003. This provided a quick first estimate of the number of deaths attributable to the heat wave and reflected the pattern of daily deaths in relation to the hottest days, but underestimated the excess when compared with the later analysis.

The Impact of Heat Waves on Mortality in Nanjing Area from 2004 to 2010

2013 ◽  
Vol 726-731 ◽  
pp. 931-935
Author(s):  
Yuan Shu Jing ◽  
Di Zhang ◽  
Min Fei Yan ◽  
Jian Guo Tan
Keyword(s):  
Heat Wave ◽  
Excess Mortality ◽  
Heat Waves ◽  
Residual Disease ◽  
Meteorological Data ◽  
Age Groups ◽  
Maximum Temperature ◽  
Mortality Data ◽  
Average Maximum ◽  
The Impact

This paper analyzed the excess mortality change in nine districts of Nanjing city, based on mortality data and meteorological data from 2004 to 2010. Taken a typical heat waves process in summer of 2006 as an example, it was discussed of the effect of the heat process on different gender, different age groups , and various disease death toll and excess mortality changes. The excess mortality was associated with the average maximum temperature and average minimum temperature during the heat waves. Excess mortality occurred in the middle of June heat wave when excess mortality was much higher than in other time periods. In late June, early July to early August, the excess mortality is relatively small. The average daily deaths are increasing with increasing age for male and female, and every age death numbers is higher than that with no heat waves during the heat wave period. In addition to the respiratory system diseases, diseases of the genitourinary system, other diseases, residual disease in the heat waves has increased, and diseases of the nervous system and the endocrine system diseases of excess mortality rate reached a staggering 342.93% and 119.63%, accounting for almost half of the total heat excess mortality. The heat waves effect is very obvious. The conclusion is of great significance for prevention of high temperature heat harm.

scholarly journals Excess Mortality in England during the 2019 Summer Heatwaves

Climate ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 14
Author(s):  
Natasha Rustemeyer ◽  
Mark Howells
Keyword(s):  
Public Health ◽  
United Kingdom ◽  
Excess Mortality ◽  
Summer Period ◽  
The Public ◽  
National Statistics ◽  
The United Kingdom ◽  
The Impact ◽  
Excess Deaths ◽  
Related Mortality

There is increasing evidence that rising temperatures and heatwaves in the United Kingdom are associated with an increase in heat-related mortality. However, the Public Health England (PHE) Heatwave mortality monitoring reports, which use provisional death registrations to estimate heat-related mortality in England during heatwaves, have not yet been evaluated. This study aims to retrospectively quantify the impact of heatwaves on mortality during the 2019 summer period using daily death occurrences. Second, using the same method, it quantifies the heat-related mortality for the 2018 and 2017 heatwave periods. Last, it compares the results to the estimated excess deaths for the same period in the PHE Heatwave mortality monitoring reports. The number of cumulative excess deaths during the summer 2019 heatwaves were minimal (161) and were substantially lower than during the summer 2018 heatwaves (1700 deaths) and summer 2017 heatwaves (1489 deaths). All findings were at variance with the PHE Heatwave mortality monitoring reports which estimated cumulative excess deaths to be 892, 863 and 778 during the heatwave periods of 2019, 2018 and 2017, respectively. Issues are identified in the use of provisional death registrations for mortality monitoring and the reduced reliability of the Office for National Statistics (ONS) daily death occurrences database before 2019. These findings may identify more reliable ways to monitor heat mortality during heatwaves in the future.

scholarly journals Estimating the burden of COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: A population-level analysis

2020 ◽  
Author(s):  
José Manuel Aburto ◽  
Ridhi Kashyap ◽  
Jonas Schöley ◽  
Colin Angus ◽  
John Ermisch ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Population Health ◽  
Mortality Risk ◽  
Excess Mortality ◽  
England And Wales ◽  
National Statistics ◽  
Life Expectancy At Birth ◽  
The Impact ◽  
Age And Sex ◽  
Excess Deaths

AbstractBackgroundDeaths directly linked to COVID-19 infection may be misclassified, and the pandemic may have indirectly affected other causes of death. To overcome these measurement challenges, we estimate the impact of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality from week 10, when the first COVID-19 death was registered, to week 47 ending November 20, 2020 in England and Wales through an analysis of excess mortality.MethodsWe estimated age and sex-specific excess mortality risk and deaths above a baseline adjusted for seasonality with a systematic comparison of four different models using data from the Office for National Statistics. We additionally provide estimates of life expectancy at birth and lifespan inequality defined as the standard deviation in age at death.ResultsThere have been 57,419 (95% Prediction Interval: 54,197, 60,752) excess deaths in the first 47 weeks of 2020, 55% of which occurred in men. Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups. Life expectancy at birth dropped 0.9 and 1.2 years for females and males relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period by five months for both sexes.ConclusionQuantifying excess deaths and their impact on life expectancy at birth provides a more comprehensive picture of the burden of COVID-19 on mortality. Whether mortality will return to -or even fall below-the baseline level remains to be seen as the pandemic continues to unfold and diverse interventions are put in place.Summary boxesWhat is already known on this topicCOVID-19 related deaths may be misclassified thereby inaccurately estimating the full impact of the pandemic on mortality. The pandemic may also have indirect effects on other causes due to changed behaviours, as well as the social and economic consequences resulting from its management. Excess mortality, the difference between observed deaths and what would have been expected in the absence of the pandemic, is a useful metric to quantify the overall impact of the pandemic on mortality and population health. Life expectancy at birth and lifespan inequality assess the cumulative impact of the pandemic on population health.What this study addsWe examine death registration data from the Office for National Statistics from 2010 to week 47 (ending on November 20) in 2020 to quantify the impact of the COVID-19 pandemic on mortality in England and Wales thus far. We estimate excess mortality risk by age and sex, and quantify the impact of excess mortality risk on excess deaths, life expectancy and lifespan inequality. During weeks 10 through 47 of 2020, elevated mortality rates resulted in 57,419 additional deaths compared with baseline mortality. Life expectancy at birth for females and males over the 47 weeks of 2020 was 82.6 and 78.7 years, with 0.9 and 1.2 years of life lost relative to the year 2019. Lifespan inequality, a measure of the spread or variation in ages at death, declined due to the increase of mortality at older ages.

scholarly journals Mining Social Media to Identify Heat Waves

2019 ◽  
Vol 16 (5) ◽  
pp. 762 ◽  
Author(s):  
Francesca Cecinati ◽  
Tom Matthews ◽  
Sukumar Natarajan ◽  
Nick McCullen ◽  
David Coley
Keyword(s):  
Social Media ◽  
Heat Wave ◽  
Excess Mortality ◽  
Heat Waves ◽  
Mortality Data ◽  
Climatic Data ◽  
Quantitative Definition ◽  
Related Mortality ◽  
Or In Developing Countries ◽  
Better Than

Heat waves are one of the deadliest of natural hazards and their frequency and intensity will likely increase as the climate continues to warm. A challenge in studying these phenomena is the lack of a universally accepted quantitative definition that captures both temperature anomalies and associated mortality. We test the hypothesis that social media mining can be used to identify heat wave mortality. Applying the approach to India, we find that the number of heat-related tweets correlates with heat-related mortality much better than traditional climate-based indicators, especially at larger scales, which identify many heat wave days that do not lead to excess mortality. We conclude that social media based heat wave identification can complement climatic data and can be used to: (1) study heat wave impacts at large scales or in developing countries, where mortality data are difficult to obtain and uncertain, and (2) to track dangerous heat wave events in real time.

scholarly journals Local mortality estimates during the COVID-19 pandemic in Italy

2021 ◽  
Author(s):  
Augusto Cerqua ◽  
Roberta Di Stefano ◽  
Marco Letta ◽  
Sara Miccoli
Keyword(s):  
Machine Learning ◽  
Excess Mortality ◽  
Control Method ◽  
Local Level ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Mortality Data ◽  
Official Method ◽  
Learning Techniques ◽  
Mortality Estimates

AbstractEstimates of the real death toll of the COVID-19 pandemic have proven to be problematic in many countries, Italy being no exception. Mortality estimates at the local level are even more uncertain as they require stringent conditions, such as granularity and accuracy of the data at hand, which are rarely met. The “official” approach adopted by public institutions to estimate the “excess mortality” during the pandemic draws on a comparison between observed all-cause mortality data for 2020 and averages of mortality figures in the past years for the same period. In this paper, we apply the recently developed machine learning control method to build a more realistic counterfactual scenario of mortality in the absence of COVID-19. We demonstrate that supervised machine learning techniques outperform the official method by substantially improving the prediction accuracy of the local mortality in “ordinary” years, especially in small- and medium-sized municipalities. We then apply the best-performing algorithms to derive estimates of local excess mortality for the period between February and September 2020. Such estimates allow us to provide insights about the demographic evolution of the first wave of the pandemic throughout the country. To help improve diagnostic and monitoring efforts, our dataset is freely available to the research community.

Analysis of the impact of heat waves on daily mortality in urban and rural areas in Madrid

2021 ◽  
Vol 195 ◽  
pp. 110892
Author(s):  
J.A. López-Bueno ◽  
M.A. Navas-Martín ◽  
C. Linares ◽  
I.J. Mirón ◽  
M.Y. Luna ◽  
...  
Keyword(s):  
Rural Areas ◽  
Heat Waves ◽  
Daily Mortality ◽  
Urban And Rural Areas ◽  
The Impact

Abstract P069: Heat, Heat Waves and Hospital Admissions in Indianapolis, Indiana

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Yi Wang
Keyword(s):  
Myocardial Infarction ◽  
Heart Failure ◽  
Relative Risk ◽  
Heat Wave ◽  
Hospital Admissions ◽  
Heat Waves ◽  
Global Climate ◽  
Extreme Heat ◽  
Apparent Temperature ◽  
The Impact

Background: The association between heat and hospital admissions is well studied, but in Indiana where the regulatory agencies cites lack of evidence for global climate change, local evidence of such an association is critical for Indiana to mitigate the impact of increasing heat. Methods: Using a distributed-lag non-linear model, we studied the effects of moderate (31.7 °C or 90 th percentile of daily mean apparent temperature (AT)), severe (33.5 °C or 95 th percentile of daily mean apparent temperature (AT)) and extreme (36.4 °C or 99 th percentile of AT) heat on hospital admissions (June-August 2007-2012) for cardiovascular (myocardial infarction, myocardial infarction, heart failure) and heat-related diseases in Indianapolis, Indiana located in Marion County. We also examined the added effects of moderate heat waves (AT above the 90 th percentile lasting 2-6 days), severe heat waves (AT above the 95 th percentile lasting 2-6 days) and extreme heat waves (AT above the 99 th percentile lasting 2-6 days). In sensitivity analysis, we tested robustness of our results to 1) different temperature and lag structures and 2) temperature metrics (daily min, max and diurnal temperature range). Results: The relative risks of moderate heat, relative to 29.2°C (75 th percentile of AT), on admissions for cardiovascular disease (CVD), myocardial infarction (MI), heart failure (HF), and heat-related diseases (HD) were 0.98 (0.67, 1.44), 6.28 (1.48, 26.6), 1.38 (0.81, 2.36) and 1.73 (0.58, 5.11). The relative risk of severe heat on admissions for CVD, MI, HF, and HD were 0.93 (0.60, 1.43), 4.46 (0.85, 23.4), 1.30 (0.72, 2.34) and 2.14 (0.43, 10.7). The relative risk of extreme heat were 0.79 (0.26, 2.39), 0.11 (0.087, 1.32), 0.68 (0.18, 2.61), and 0.32 (0.005, 19.5). We also observed statistically significant added effects of moderate heat waves lasting 4 or 6 days on hospital admission for MI and HD and extreme heat waves lasting 4 days on hospital admissions for HD. Results were strengthened for people older than 65. Conclusions: Moderate heat wave lasting 4-6 days were associated with increased hospital admissions for MI and HD diseases and extreme heat wave lasting 4 days were associated with increased admissions for HD.

scholarly journals The new automated daily mortality surveillance system in Portugal

2010 ◽  
Vol 15 (13) ◽  
Author(s):  
P J Nogueira ◽  
A Machado ◽  
E Rodrigues ◽  
B Nunes ◽  
L Sousa ◽  
...  
Keyword(s):  
Information Acquisition ◽  
Surveillance System ◽  
Warning System ◽  
Automated System ◽  
Mortality Data ◽  
Fast Method ◽  
Daily Mortality ◽  
Public Health Action ◽  
The Impact ◽  
Mortality Surveillance

The experience reported in an earlier Eurosurveillance issue on a fast method to evaluate the impact of the 2003 heatwave on mortality in Portugal, generated a daily mortality surveillance system (VDM) that has been operating ever since jointly with the Portuguese Heat Health Watch Warning System. This work describes the VDM system and how it evolved to become an automated system operating year-round, and shows briefly its potential using mortality data from January 2006 to June 2009 collected by the system itself. The new system has important advantages such as: rapid information acquisition, completeness (the entire population is included), lightness (very little information is exchanged, date of death, age, sex, place of death registration). It allows rapid detection of impacts (within five days) and allows a quick preliminary quantification of impacts that usually took several years to be done. These characteristics make this system a powerful tool for public health action. The VDM system also represents an example of inter-institutional cooperation, bringing together organisations from two different ministries, Health and Justice, aiming at improving knowledge about the mortality in the population.

scholarly journals The Impact of the July 2007 Heat Wave on Daily Mortality in Belgrade, Serbia

2013 ◽  
Vol 21 (3) ◽  
pp. 140-145 ◽  
Author(s):  
Dragan C. Bogdanović ◽  
Zoran G. Milošević ◽  
Konstansa K. Lazarević ◽  
Zana Ć. Dolićanin ◽  
Dragan M. Ranđelović ◽  
...  
Keyword(s):  
Heat Wave ◽  
Daily Mortality ◽  
The Impact

scholarly journals Excess mortality in Guadeloupe and Martinique, islands of the French West Indies, during the chikungunya epidemic of 2014

2018 ◽  
Vol 146 (16) ◽  
pp. 2059-2065 ◽  
Author(s):  
A. R. R. Freitas ◽  
P. M. Alarcón-Elbal ◽  
M. R. Donalisio
Keyword(s):  
Strong Correlation ◽  
Excess Mortality ◽  
Pearson Correlation ◽  
Age Groups ◽  
Epidemiological Data ◽  
Mortality Data ◽  
Surveillance Systems ◽  
Mortality And Morbidity ◽  
The Impact ◽  
Excess Deaths

AbstractIn some chikungunya epidemics, deaths are not completely captured by traditional surveillance systems, which record case and death reports. We evaluated excess deaths associated with the 2014 chikungunya virus (CHIKV) epidemic in Guadeloupe and Martinique, Antilles. Population (784 097 inhabitants) and mortality data, estimated by sex and age, were accessed from the Institut National de la Statistique et des Études Économiques in France. Epidemiological data, cases, hospitalisations and deaths on CHIKV were obtained from the official epidemiological reports of the Cellule de Institut de Veille Sanitaire in France. Excess deaths were calculated as the difference between the expected and observed deaths for all age groups for each month in 2014 and 2015, considering the upper limit of 99% confidence interval. The Pearson correlation coefficient showed a strong correlation between monthly excess deaths and reported cases of chikungunya (R= 0.81,p< 0.005) and with a 1-month lag (R= 0.87,p< 0.001); and a strong correlation was also observed between monthly rates of hospitalisation for CHIKV and excess deaths with a delay of 1 month (R= 0.87,p< 0.0005). The peak of the epidemic occurred in the month with the highest mortality, returning to normal soon after the end of the CHIKV epidemic. There were excess deaths in almost all age groups, and excess mortality rate was higher among the elderly but was similar between male and female individuals. The overall mortality estimated in the current study (639 deaths) was about four times greater than that obtained through death declarations (160 deaths). Although the aetiological diagnosis of all deaths associated with CHIKV infection is not always possible, already well-known statistical tools can contribute to the evaluation of the impact of CHIKV on mortality and morbidity in the different age groups.

Sign in / Sign up

Export Citation Format

Share Document