scholarly journals Novel COVID-19 Mortality Rate Prediction (MRP) Model for India Using Regression Model With Optimized Hyperparameter

2021 ◽  
Vol 23 (4) ◽  
pp. 1-12
Author(s):  
Dhamodharavadhani S. ◽  
R. Rathipriya
Keyword(s):  
Mortality Rate ◽  
Regression Model ◽  
Death Rate ◽  
Historical Data ◽  
Gaussian Process Regression ◽  
Mortality Rates ◽  
Regression Method ◽  
Rate Prediction ◽  
Mortality Models ◽  
The U.S

The main objective of this study is to estimate the future COVID-19 mortality rate for India using COVID-19 mortality rate models from different countries. Here, the regression method with the optimal hyperparameter is used to build these models. In the literature, numerous mortality models for infectious diseases have been proposed, most of which predict future mortality by extending one or more disease-related attributes or parameters. But most of these models predict mortality rates from historical data. In this paper, the Gaussian process regression model with the optimal hyperparameter is used to develop the COVID-19 mortality rate prediction (MRP) model. Five different MRP models have been built for the U.S., Italy, Germany, Japan, and India. The results show that Germany has the lowest death rate in 2000 plus COVID-19 confirmed cases. Therefore, if India follows the strategy pursued by Germany, India will control the COVID-19 mortality rate even in the increase of confirmed cases.

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 Mortality Forecasting: How Far Back Should We Look in Time?

Risks ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 22 ◽  
Author(s):  
Han Li ◽  
Colin O’Hare
Keyword(s):  
Predictive Power ◽  
Historical Data ◽  
Mortality Rates ◽  
Point Of View ◽  
Mortality Data ◽  
Male Mortality ◽  
Historical Information ◽  
Mortality Forecasting ◽  
Mortality Models ◽  
Forecasting Performance

Extrapolative methods are one of the most commonly-adopted forecasting approaches in the literature on projecting future mortality rates. It can be argued that there are two types of mortality models using this approach. The first extracts patterns in age, time and cohort dimensions either in a deterministic fashion or a stochastic fashion. The second uses non-parametric smoothing techniques to model mortality and thus has no explicit constraints placed on the model. We argue that from a forecasting point of view, the main difference between the two types of models is whether they treat recent and historical information equally in the projection process. In this paper, we compare the forecasting performance of the two types of models using Great Britain male mortality data from 1950–2016. We also conduct a robustness test to see how sensitive the forecasts are to the changes in the length of historical data used to calibrate the models. The main conclusion from the study is that more recent information should be given more weight in the forecasting process as it has greater predictive power over historical information.

scholarly journals Increased Fall-Related Mortality Rates in New Mexico, 1999–2005

2011 ◽  
Vol 126 (6) ◽  
pp. 861-867 ◽  
Author(s):  
Aaron M. Wendelboe ◽  
Michael G. Landen
Keyword(s):  
New Mexico ◽  
Mortality Rate ◽  
Asian American ◽  
The United States ◽  
Mortality Rates ◽  
Prevention Measures ◽  
Effective Prevention ◽  
Hispanic People ◽  
The U.S ◽  
Related Mortality

Objective. In 2000, fall injuries affected 30% of U.S. residents aged ≥65 years and cost $19 billion. In 2005, New Mexico (NM) had the highest fall-related mortality rate in the United States. We described factors associated with these elevated fall-related mortality rates. Methods. To better understand the epidemiology of fatal falls in NM, we used state and national (Web-based Injury Statistics Query and Reporting System) vital records data for 1999–2005 to identify unintentional falls that were the underlying cause of death. We calculated age-adjusted mortality rates, rate ratios (RRs), and 95% confidence intervals (CIs) by sex, ethnicity, race, and year. Results. For 1999–2005 combined, NM's fall-related mortality rate (11.7 per 100,000 population) was 2.1 times higher than the U.S. rate (5.6 per 100,000 population). Elevated RRs persisted when stratified by sex (male RR=2.0, female RR=2.2), ethnicity (Hispanic RR=2.5, non-Hispanic RR=2.1), race (white RR=2.0, black RR=1.7, American Indian RR=2.3, and Asian American/Pacific Islander RR=3.1), and age (≥50 years RR=2.0, <50 years RR=1.2). Fall-related mortality rates began to increase exponentially at age 50 years, which was 15 years younger than the national trend. NM non-Hispanic individuals had the highest demographic-specific fall-related mortality rate (11.8 per 100,000 population, 95% CI 11.0, 12.5). NM's 69.5% increase in fall-related mortality rate was approximately twice the U.S. increase (31.9%); the increase among non-Hispanic people (86.2%) was twice that among Hispanic people (43.5%). Conclusions. NM's fall-related mortality rate was twice the U.S. rate; exhibited a greater increase than the U.S. rate; and persisted across sex, ethnicity, and race. Fall-related mortality disproportionately affects a relatively younger population in NM. Characterizing fall etiology will assist in the development of effective prevention measures.

scholarly journals Excess Mortality in a Nephrology Clinic during First Months of Coronavirus Disease-19 Pandemic: A Pragmatic Approach

2020 ◽  
Vol 8 (T1) ◽  
pp. 598-604
Author(s):  
Lada Trajceska ◽  
Aleksandra Canevska ◽  
Nikola Gjorgjievski ◽  
Mimoza Milenkova ◽  
Adrijana Spasovska-Vasilevska ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Hospital Mortality ◽  
Death Rate ◽  
Excess Mortality ◽  
Mortality Rates ◽  
Pragmatic Approach ◽  
Related Factors ◽  
Republic Of Macedonia ◽  
Delayed Referral ◽  
The University

BACKGROUND: Excess mortality is defined as mortality above what would be expected based on the non-crisis mortality rate in the population of interest. AIM: In this study, we aimed to access weather the coronavirus disease (COVID)-19 pandemic had impact on the in-hospital mortality during the first 6 months of the year and compare it with the data from the previous years. METHODS: A retroprospective study was conducted at the University Clinic of Nephrology Skopje, Republic of Macedonia. In-hospital mortality rates were calculated for the first half of the year (01.01–30.06) from 2015 until 2020, as monthly number of dead patients divided by the number of non-elective hospitalized patents in the same period. The excess mortality rate (p-score) was calculated as ratio or percentage of excess deaths relative to expected average deaths: (Observed mortality rate–expected average death rate)/expected average death rate *100%. RESULTS: The expected (average) overall death mortality rate for the period 2015–2019 was 8.9% and for 2020 was 15.3%. The calculated overall excess mortality in 2020 was 72% (pscore 0.72). CONCLUSION: In this pragmatic study, we have provided clear evidence of high excess mortality at our nephrology clinic during the 1st months of the COVID-19 pandemic. The delayed referral of patients due to the patient and health care system-related factors might partially explain the excess mortality during pandemic crises. Further analysis is needed to estimate unrecognized probable COVID-19 deaths.

scholarly journals INOVASI PELAYANAN KESEHATAN ‘BUMIL RISTI’ SEBAGAI UPAYA MENURUNKAN ANGKA KEMATIAN IBU DAN BAYI DI PUSKESMAS SEMPU KECAMATAN SEMPU KABUPATEN BANYUWANGI

2021 ◽  
Vol 6 (1) ◽  
pp. 1-13
Author(s):  
Yusticia Tria Parwita
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Health Center ◽  
Public Service ◽  
Death Rate ◽  
Health Sector ◽  
Service Innovation ◽  
Mortality Rates ◽  
High Rate ◽  
Research Findings

Abstract This paper aims to describe the innovation of public services in the health sector through the Bumil Risti program at the Sempu Health Center, Sempu District, Banyuwangi Regency. Puskesmas Sempu face a problem, namely the high rate of maternal and infant mortality in Banyuwangi. The high mortality rate in this region occurs due to the slow service of pregnant women. Puskesmas Sempu create innovations in their services to be able to overcome the problems that are in the spotlight. The research findings show that the Bumil Risti service innovation carried out by Puskesmas Sempu is effective and efficient in reducing maternal and infant mortality rates in its operational areas. Innovations are made by providing services that end access, which can be obtained inside and outside the health center. By implementing this innovation, Puskesmas Sempu succeeded in eliminating the death rate in 2014 and 2015.Keywords: Innovation, Public Service, Bumil RistiAbstrak Tulisan ini bertujuan untuk mendeskripsikan inovasi pelayanan publik dibidang kesehatan melalui program Bumil Risti di Puskesmas Sempu, Kecamatan Sempu, Kabupaten Banyuwangi. Puskesmas Sempu menghadapi masalah yaitu tingginya jumlah angka kematian ibu dan bayi tertinggi di Banyuwangi. Tingginya angka kematian di wilayah ini terjadi karena lambatnya pelayanan ibu hamil. Puskesmas Sempu menciptakan inovasi dalam layanan mereka untuk dapat mengatasi masalah yang menjadi sorotan. Temuan penelitian menunjukkan bahwa inovasi layanan Bumil Risti yang dilakukan oleh Puskesmas Sempu efektif dan efisien dalam menurunkan angka kematian ibu dan bayi di wilayah operasinya. Inovasi yang dilakukan dengan memberikan pelayanan yang menekankan kemudahan akses, yang dapat diperoleh di dalam dan di luar pusat kesehatan. Dengan menerapkan inovasi ini, Puskesmas Sempu berhasil meniadakan tingkat kematian pada tahun 2014 dan 2015.Kata Kunci : Inovasi, Pelayanan Publik, Bumil Risti

DIFFERENCES IN EUROPEAN MORTALITY RATES: A GEOMETRIC APPROACH ON THE AGE–PERIOD PLANE

2015 ◽  
Vol 45 (3) ◽  
pp. 477-502 ◽  
Author(s):  
Marcus C. Christiansen ◽  
Evgeny Spodarev ◽  
Verena Unseld
Keyword(s):  
Mortality Rate ◽  
Historical Data ◽  
Geometric Approach ◽  
Mortality Rates ◽  
Two Dimensional ◽  
Parametric Approach ◽  
Multiple Populations ◽  
Geometric Patterns ◽  
Proposed Model ◽  
Starting Point

AbstractAge and period are the most widely used parameters for forecasting mortality rates. Empirical mortality rate differences in multiple populations often show strong geometric patterns on the two-dimensional age–period plane. The idea of this paper is to take these geometric patterns as the starting point for the development of forecasts. A parametric approach is presented and discussed which uses simple techniques from spatial statistics. The proposed model is statistically parsimonious and yields forecasts that are consistent with the historical data and coherent for multiple populations.

scholarly journals The Challenge of Infant Mortality: Have We Reached a Plateau?

2009 ◽  
Vol 124 (5) ◽  
pp. 670-681 ◽  
Author(s):  
Marian F. MacDorman ◽  
T.J. Mathews
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Infant Death ◽  
Low Birthweight ◽  
Ethnic Disparities ◽  
Mortality Rates ◽  
Infant Mortality Rate ◽  
Racial And Ethnic Disparities ◽  
Live Births ◽  
The U.S

Objectives. Infant mortality is a major indicator of the health of a nation. We analyzed recent patterns and trends in U.S. infant mortality, with an emphasis on two of the greatest challenges: ( 1) persistent racial and ethnic disparities and ( 2) the impact of preterm and low birthweight delivery. Methods. Data from the national linked birth/infant death datasets were used to compute infant mortality rates per 100,000 live births by cause of death (COD), and per 1,000 live births for all other variables. Infant mortality rates and other measures of infant health were analyzed and compared. Leading and preterm-related CODs, and international comparisons of infant mortality rates were also examined. Results. Despite the rapid decline in infant mortality during the 20th century, the U.S. infant mortality rate did not decline from 2000 to 2005, and declined only marginally in 2006. Racial and ethnic disparities in infant mortality have persisted and increased, as have the percentages of preterm and low birthweight deliveries. After decades of improvement, the infant mortality rate for very low birthweight infants remained unchanged from 2000 to 2005. Infant mortality rates from congenital malformations and sudden infant death syndrome declined; however, rates for preterm-related CODs increased. The U.S. international ranking in infant mortality fell from 12th place in 1960 to 30th place in 2005. Conclusions. Infant mortality is a complex and multifactorial problem that has proved resistant to intervention efforts. Continued increases in preterm and low birthweight delivery present major challenges to further improvement in the infant mortality rate.

scholarly journals Learning Interpretable Mixture of Weibull Distributions—Exploratory Analysis of How Economic Development Influences the Incidence of COVID-19 Deaths

Data ◽  
2021 ◽  
Vol 6 (12) ◽  
pp. 125
Author(s):  
Róbert Csalódi ◽  
Zoltán Birkner ◽  
János Abonyi
Keyword(s):  
Mortality Rate ◽  
Health Sector ◽  
Mortality Rates ◽  
Regression Method ◽  
Distribution Functions ◽  
Proportional Hazard ◽  
Cox Proportional Hazard ◽  
Significant Difference ◽  
Weibull Models ◽  
Cox Proportional Hazard Regression

This paper presents an algorithm for learning local Weibull models, whose operating regions are represented by fuzzy rules. The applicability of the proposed method is demonstrated in estimating the mortality rate of the COVID-19 pandemic. The reproducible results show that there is a significant difference between mortality rates of countries due to their economic situation, urbanization, and the state of the health sector. The proposed method is compared with the semi-parametric Cox proportional hazard regression method. The distribution functions of these two methods are close to each other, so the proposed method can estimate efficiently.

scholarly journals Covid-19 Pandemic: ARIMA and Regression Model based Worldwide Death Cases Predictions

2020 ◽  
Author(s):  
Vikas Chaurasia ◽  
Saurabh Pal
Keyword(s):  
Mortality Rate ◽  
Regression Model ◽  
Death Rate ◽  
Arima Model ◽  
Training Data ◽  
Percentage Error ◽  
Data Set ◽  
Short Period ◽  
The Government ◽  
Death Cases

Abstract Covid-19 has now taken a frightening form. As the day passes, it is becoming more and more widespread and now it has become an epidemic. The death rate, which was earlier in the hundreds, changed to thousands and then progressed to millions respectively. If the same situation persists over time, the day is not far when the humanity of all the countries on the globe will be endangered and we yearn for breath. From January 2020 till now, many scientists, researchers and doctors are also trying to solve this complex problem so that proper arrangements can be made by the governments in the hospitals and the death rate can be reduced. The presented research article shows the estimated mortality rate by the ARIMA model and the Regression model. This dataset has been collected precisely from DataHub-Novel Coronavirus 2019 - Dataset from 22nd January to 29th June 2020. In order to show the current mortality rate of the entire subject, the correlation coefficients of attributes (MAE, MSE, RMSE and MAPE) were used, where the average absolute percentage error validated the model by 99.09%. The ARIMA model is used to generate auto_arima SARIMAX results, auto_arima residual plots, ARIMA model results, and corresponding prediction plots on the training data set. These data indicate a continuous decline in death cases. By applying a regression model, the coefficients generated by the regression model are estimated, and the actual death cases and expected death cases are compared and analyzed. It is found that the predicted mortality rate has decreased after May 2, 2020. It will learn help the government and doctors prepare for the next plans. Based on short- period predictions these methods can use forecast for long- period.

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