scholarly journals Bayesian Updating of Earthquake Vulnerability Functions with Application to Mortality Rates

2017 ◽  
Vol 33 (3) ◽  
pp. 1173-1189 ◽  
Author(s):  
Hae-Young Noh ◽  
Anne Kiremidjian ◽  
Luis Ceferino ◽  
Emily So
Keyword(s):  
Exponential Distribution ◽  
Expert Opinion ◽  
Bayesian Model ◽  
Mortality Rates ◽  
Mortality Data ◽  
Gamma Model ◽  
Statistical Framework ◽  
Earthquake Vulnerability ◽  
Probability Densities ◽  
Vulnerability Functions

Vulnerability functions often rely on data from expert opinion, post-earthquake investigations, or analytical simulations. Combining the information can be particularly challenging. In this paper, a Bayesian statistical framework is presented to combining disparate information. The framework is illustrated through application to earthquake mortality data obtained from the 2005 Pakistan earthquake and from PAGER. Three different models are tested including an exponential, a combination of Bernoulli and exponential and Bernoulli and gamma fit to model respectively zero and non-zero mortality rates. A novel Bayesian model for the Bernoulli-exponential and Bernoulli-gamma probability densities is introduced. It is found that the exponential distribution represents the zero casualties very poorly. The Bernoulli-exponential and Bernoulli-gamma models capture the data for both the zero and non-zero mortality rates. It is also shown that the Bernoulli-gamma model fits the 2005 Pakistan data the best and has uncertainties that are smaller than either the ones from the 2005 Pakistan data or the PAGER data.

Inequalities and Impact of Socioeconomic-Cultural Factors in Suicide Rates Across Italy

Crisis ◽  
2011 ◽  
Vol 32 (4) ◽  
pp. 178-185 ◽  
Author(s):  
Maurizio Pompili ◽  
Marco Innamorati ◽  
Monica Vichi ◽  
Maria Masocco ◽  
Nicola Vanacore ◽  
...  
Keyword(s):  
Suicide Rate ◽  
Age Groups ◽  
Premature Death ◽  
Mortality Rates ◽  
Mortality Data ◽  
Italian Population ◽  
Comprehensive Overview ◽  
Suicide Rates ◽  
Younger Age ◽  
Age And Sex

Background: Suicide is a major cause of premature death in Italy and occurs at different rates in the various regions. Aims: The aim of the present study was to provide a comprehensive overview of suicide in the Italian population aged 15 years and older for the years 1980–2006. Methods: Mortality data were extracted from the Italian Mortality Database. Results: Mortality rates for suicide in Italy reached a peak in 1985 and declined thereafter. The different patterns observed by age and sex indicated that the decrease in the suicide rate in Italy was initially the result of declining rates in those aged 45+ while, from 1997 on, the decrease was attributable principally to a reduction in suicide rates among the younger age groups. It was found that socioeconomic factors underlined major differences in the suicide rate across regions. Conclusions: The present study confirmed that suicide is a multifaceted phenomenon that may be determined by an array of factors. Suicide prevention should, therefore, be targeted to identifiable high-risk sociocultural groups in each country.

scholarly journals Mortality beyond emergency threshold in a silent crisis– results from a population-based mortality survey in Ouaka prefecture, Central African Republic, 2020

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Eve Robinson ◽  
Lawrence Lee ◽  
Leslie F. Roberts ◽  
Aurelie Poelhekke ◽  
Xavier Charles ◽  
...  
Keyword(s):  
Central African Republic ◽  
Causes Of Death ◽  
Maternal Mortality Ratio ◽  
Mortality Rates ◽  
Population Based ◽  
Access To Healthcare ◽  
Mortality Data ◽  
Humanitarian Emergency ◽  
The World ◽  
Mortality Survey

Abstract Background The Central African Republic (CAR) suffers a protracted conflict and has the second lowest human development index in the world. Available mortality estimates vary and differ in methodology. We undertook a retrospective mortality study in the Ouaka prefecture to obtain reliable mortality data. Methods We conducted a population-based two-stage cluster survey from 9 March to 9 April, 2020 in Ouaka prefecture. We aimed to include 64 clusters of 12 households for a required sample size of 3636 persons. We assigned clusters to communes proportional to population size and then used systematic random sampling to identify cluster starting points from a dataset of buildings in each commune. In addition to the mortality survey questions, we included an open question on challenges faced by the household. Results We completed 50 clusters with 591 participating households including 4000 household members on the interview day. The median household size was 7 (interquartile range (IQR): 4—9). The median age was 12 (IQR: 5—27). The birth rate was 59.0/1000 population (95% confidence interval (95%-CI): 51.7—67.4). The crude and under-five mortality rates (CMR & U5MR) were 1.33 (95%-CI: 1.09—1.61) and 1.87 (95%-CI: 1.37–2.54) deaths/10,000 persons/day, respectively. The most common specified causes of death were malaria/fever (16.0%; 95%-CI: 11.0–22.7), violence (13.2%; 95%-CI: 6.3–25.5), diarrhoea/vomiting (10.6%; 95%-CI: 6.2–17.5), and respiratory infections (8.4%; 95%-CI: 4.6–14.8). The maternal mortality ratio (MMR) was 2525/100,000 live births (95%-CI: 825—5794). Challenges reported by households included health problems and access to healthcare, high number of deaths, lack of potable water, insufficient means of subsistence, food insecurity and violence. Conclusions The CMR, U5MR and MMR exceed previous estimates, and the CMR exceeds the humanitarian emergency threshold. Violence is a major threat to life, and to physical and mental wellbeing. Other causes of death speak to poor living conditions and poor access to healthcare and preventive measures, corroborated by the challenges reported by households. Many areas of CAR face similar challenges to Ouaka. If these results were generalisable across CAR, the country would suffer one of the highest mortality rates in the world, a reminder that the longstanding “silent crisis” continues.

scholarly journals Outcomes for Children and Adolescents With Cancer: Challenges for the Twenty-First Century

2010 ◽  
Vol 28 (15) ◽  
pp. 2625-2634 ◽  
Author(s):  
Malcolm A. Smith ◽  
Nita L. Seibel ◽  
Sean F. Altekruse ◽  
Lynn A.G. Ries ◽  
Danielle L. Melbert ◽  
...  
Keyword(s):  
United States ◽  
Childhood Cancer ◽  
Cancer Mortality ◽  
Lymphoblastic Leukemia ◽  
The United States ◽  
Mortality Rates ◽  
Mortality Data ◽  
Childhood Cancers ◽  
Essential Information ◽  
The Impact

Purpose This report provides an overview of current childhood cancer statistics to facilitate analysis of the impact of past research discoveries on outcome and provide essential information for prioritizing future research directions. Methods Incidence and survival data for childhood cancers came from the Surveillance, Epidemiology, and End Results 9 (SEER 9) registries, and mortality data were based on deaths in the United States that were reported by states to the Centers for Disease Control and Prevention by underlying cause. Results Childhood cancer incidence rates increased significantly from 1975 through 2006, with increasing rates for acute lymphoblastic leukemia being most notable. Childhood cancer mortality rates declined by more than 50% between 1975 and 2006. For leukemias and lymphomas, significantly decreasing mortality rates were observed throughout the 32-year period, though the rate of decline slowed somewhat after 1998. For remaining childhood cancers, significantly decreasing mortality rates were observed from 1975 to 1996, with stable rates from 1996 through 2006. Increased survival rates were observed for all categories of childhood cancers studied, with the extent and temporal pace of the increases varying by diagnosis. Conclusion When 1975 age-specific death rates for children are used as a baseline, approximately 38,000 childhood malignant cancer deaths were averted in the United States from 1975 through 2006 as a result of more effective treatments identified and applied during this period. Continued success in reducing childhood cancer mortality will require new treatment paradigms building on an increased understanding of the molecular processes that promote growth and survival of specific childhood cancers.

scholarly journals Do Different Models Induce Changes in Mortality Indicators? That Is a Key Question for Extending the Lee-Carter Model

2021 ◽  
Vol 18 (4) ◽  
pp. 2204
Author(s):  
Ana Debón ◽  
Steven Haberman ◽  
Francisco Montes ◽  
Edoardo Otranto
Keyword(s):  
Historical Data ◽  
Mortality Rates ◽  
Parametric Model ◽  
Mortality Data ◽  
Block Bootstrap ◽  
Functional Anova ◽  
Model Block ◽  
The Usa ◽  
Data Constraints ◽  
Carter Model

The parametric model introduced by Lee and Carter in 1992 for modeling mortality rates in the USA was a seminal development in forecasting life expectancies and has been widely used since then. Different extensions of this model, using different hypotheses about the data, constraints on the parameters, and appropriate methods have led to improvements in the model’s fit to historical data and the model’s forecasting of the future. This paper’s main objective is to evaluate if differences between models are reflected in different mortality indicators’ forecasts. To this end, nine sets of indicator predictions were generated by crossing three models and three block-bootstrap samples with each of size fifty. Later the predicted mortality indicators were compared using functional ANOVA. Models and block bootstrap procedures are applied to Spanish mortality data. Results show model, block-bootstrap, and interaction effects for all mortality indicators. Although it was not our main objective, it is essential to point out that the sample effect should not be present since they must be realizations of the same population, and therefore the procedure should lead to samples that do not influence the results. Regarding significant model effect, it follows that, although the addition of terms improves the adjustment of probabilities and translates into an effect on mortality indicators, the model’s predictions must be checked in terms of their probabilities and the mortality indicators of interest.

Abstract P261: Intensive Systolic Blood Pressure Lowering Will Prevent Over 100,000 Deaths Annually

Hypertension ◽  
2016 ◽  
Vol 68 (suppl_1) ◽  
Author(s):  
Holly Kramer ◽  
Adam Bress ◽  
Srinivasan Beddhu ◽  
Paul Muntner ◽  
Richard S Cooper
Keyword(s):  
Blood Pressure ◽  
Mortality Rate ◽  
Systolic Blood Pressure ◽  
Mortality Rates ◽  
Mortality Data ◽  
Blood Pressure Lowering ◽  
Cvd Risk ◽  
Pressure Lowering ◽  
Annual Mortality ◽  
The U.S

Background: The Systolic Blood Pressure Intervention Trial (SPRINT) trial randomized 9,361 adults aged ≥50 years at high cardiovascular disease (CVD) risk without diabetes or stroke to intensive systolic blood pressure (SBP) lowering (≤120 mmHg) or standard SBP lowering (≤140 mmHg). After a median follow up of 3.26 years, all-cause mortality was 27% (95% CI 40%, 10%) lower with intensive SBP lowering. We estimated the potential number of prevented deaths with intensive SBP lowering in the U.S. population meeting SPRINT criteria. Methods: SPRINT eligibility criteria were applied to the National Health and Nutrition Examination Survey 1999-2006, a representative survey of the U.S. population, linked with the mortality data through December 2011. Eligibility included (1) age ≥50 years with (2) SBP 130-180 mmHg depending on number of antihypertensive classes being taken, and (3) presence of ≥1 CVD risk conditions (history of coronary heart disease, estimated glomerular filtration rate (eGFR) 20 to 59 ml/min/1.73 m 2 , 10-year Framingham risk score ≥15%, or age ≥75 years). Adults with diabetes, stroke history, >1 g/day proteinuria, heart failure, on dialysis, or eGFR<20 ml/min/1.73m 2 were excluded. Annual mortality rates for adults meeting SPRINT criteria were calculated using Kaplan-Meier methods and the expected reduction in mortality rates with intensive SBP lowering in SPRINT was used to determine the number of potential deaths prevented. Analyses accounted for the complex survey design. Results: An estimated 18.1 million U.S. adults met SPRINT criteria with 7.4 million taking blood pressure lowering medications. The mean age was 68.6 years and 83.2% and 7.4% were non-Hispanic white and non-Hispanic black, respectively. The annual mortality rate was 2.2% (95% CI 1.9%, 2.5%) and intensive SBP lowering was projected to prevent 107,453 deaths per year (95% CI 45,374 to 139,490). Among adults with SBP ≥145 mmHg, the annual mortality rate was 2.5% (95% CI 2.1%, 3.0%) and intensive SBP lowering was projected to prevent 60,908 deaths per year (95% CI 26, 455 to 76, 792). Conclusions: We project intensive SBP lowering could prevent over 100,000 deaths per year of intensive treatment.

scholarly journals Births to Teens Older and Younger Than 17 Years in San Bernardino County and California

2004 ◽  
Vol 2 (2) ◽  
pp. 20-27
Author(s):  
Kofi Adade Boafo ◽  
Bruce Smith ◽  
Naomi N Modeste ◽  
Thomas J Prendergast, Jr
Keyword(s):  
Infant Mortality ◽  
Very Low Birth Weight ◽  
Age Groups ◽  
Mortality Rates ◽  
Teen Mothers ◽  
Mortality Data ◽  
San Bernardino County ◽  
Low Birth Weight Infants ◽  
Data Set ◽  
San Bernardino

Objective: The purpose of this cohort, descriptive study was to attempt to understand the variables associated with discordant infant mortality among teenagers 17-19 years old whose infants demonstrated higher mortality than infants of teenagers who were younger than 17 years old in San Bernardino County, California. The intent was to elicit further research and/or define appropriate interventions for teen mothers within the age range 17-19 years. Methods: Data was abstracted from an electronic infant mortality data set, the State of California Birth Cohort File in which birth records from San Bernardino County for the period 1989 through 1993 were matched with mortality records. Results: The data showed that infants of white teens within the 17-19 age groups were more likely to have higher infant mortality rates when compared to their younger peers. Infant mortality rates among offspring of Hispanic and black teenage mothers showed no discrepancy between the two groups nor between county and state rates. Conclusions: Further study is needed to answer why infants of white teen mothers in the 17-19 age groups have higher mortality rates. There is also a need to review the services rendered to pregnant and parenting adolescents in San Bernardino County. In addition, very low birth weight infants were much more likely to die when born to older teens than when born to younger teens.

scholarly journals STOCHASTIC DIFFERENTIAL EQUATION: AN APPLICATION TO MORTALITY DATA

2020 ◽  
Vol 8 (6) ◽  
Author(s):  
Rajani P. Agadi ◽  
A. S. Talawar
Keyword(s):  
Differential Equation ◽  
New Zealand ◽  
Stochastic Differential Equation ◽  
Mortality Rates ◽  
Mortality Data

In the present paper we consider an application of stochastic differential equation to model age-specific mortalities. We use New Zealand mortality data for the period 1948–2015 to fit the model. The point predictions of mortality rates at ages 40, 60 and 80 are quite good, almost undistinguishable from the true mortality rates observed.  

NEONATAL MORTALITY IN THE EMPOWERED ACTION GROUP STATES OF INDIA: TRENDS AND DETERMINANTS

2008 ◽  
Vol 40 (2) ◽  
pp. 183-201 ◽  
Author(s):  
PERIANAYAGAM AROKIASAMY ◽  
ABHISHEK GAUTAM
Keyword(s):  
Health Care ◽  
Infant Mortality ◽  
Neonatal Mortality ◽  
Universal Coverage ◽  
Mortality Rates ◽  
Mortality Data ◽  
Registration System ◽  
Action Group ◽  
Eag States ◽  
The Impact

SummaryIn India, the eight socioeconomically backward states of Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttaranchal and Uttar Pradesh, referred to as the Empowered Action Group (EAG) states, lag behind in the demographic transition and have the highest infant mortality rates in the country. Neonatal mortality constitutes about 60% of the total infant mortality in India and is highest in the EAG states. This study assesses the levels and trends in neonatal mortality in the EAG states and examines the impact of bio-demographic compared with health care determinants on neonatal mortality. Data from India’s Sample Registration System (SRS) and National Family and Health Survey (NFHS-2, 1998–99) are used. Cox proportional hazard models are applied to estimate adjusted neonatal mortality rates by health care, bio-demographic and socioeconomic determinants. Variations in neonatal mortality by these determinants suggest that universal coverage of all pregnant women with full antenatal care, providing assistance at delivery and postnatal care including emergency care are critical inputs for achieving a reduction in neonatal mortality. Health interventions are also required that focus on curtailing the high risk of neonatal deaths arising from the mothers’ younger age at childbirth, low birth weight of children and higher order births with short birth intervals.

Impacts of recolonizing gray wolves (Canis lupus) on survival and mortality in two sympatric ungulates

2018 ◽  
Vol 96 (7) ◽  
pp. 760-768 ◽  
Author(s):  
J.A. Dellinger ◽  
C.R. Shores ◽  
M. Marsh ◽  
M.R. Heithaus ◽  
W.J. Ripple ◽  
...  
Keyword(s):  
Canis Lupus ◽  
Mule Deer ◽  
Survival Rates ◽  
Odocoileus Hemionus ◽  
Mortality Rates ◽  
Adult Survival ◽  
Mortality Data ◽  
Gray Wolf ◽  
Gray Wolves ◽  
Large Predators

There is growing recognition that humans may mediate the strength and nature of the ecological effects of large predators. We took advantage of ongoing gray wolf (Canis lupus Linnaeus, 1758) recolonization in Washington, USA, to contrast adult survival rates and sources of mortality for mule deer (Odocoileus hemionus (Rafinesque, 1817)) and white-tailed deer (Odocoileus virginianus (Zimmermann, 1780)) in areas with and without wolf packs in a managed landscape dominated by multiple human uses. We tested the hypothesis that the addition of wolves to the existing predator guild would augment predator-induced mortality rates for both ungulates. Source of mortality data from adult mule deer and white-tailed deer, respectively, revealed that wolf-related mortality was low compared with that inflicted by other predators or humans. Predator-caused mortality was largely confined to winter. There was little effect of wolf presence on adult deer mortality rates, and there was no difference in mortality between the two deer species relative to wolf-free or wolf-occupied sites. Although this study occurred early in wolf recovery in Washington, our results differ from those demonstrated for gray wolves in protected areas. Thus, we encourage further investigation of effects of direct predation by recolonizing large carnivores on prey in human-dominated landscapes.

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