Excess deaths reveal unequal impact of COVID-19 in Ecuador

Latin America has struggled to control the transmission of COVID-19. Comparison of excess death (ED) rates during the pandemic reveals that Ecuador is among the highest impacted countries. In this analysis, we update our previous findings with the most complete all-cause mortality records available for 2020, disaggregated by sex, age, ethnicity and geography. Our study shows that in 2020, Ecuador had a 64% ED rate (95% CI 63% to 65%) or 64% more deaths than expected. Men had a higher ED rate, 75% (95% CI 73% to 76%), than women’s 51% (95% CI 49% to 52%), and this pattern of higher EDs for men than women held for most age groups. The only exception was the 20–29 age group, where women had 19% more deaths, compared to 10% more deaths for men, but that difference is not statistically significant. The analysis provides striking evidence of the lack of COVID-19 diagnostic testing in Ecuador: the confirmed COVID-19 deaths in 2020 accounted for only 21% of total EDs. Our significant finding is that indigenous populations, who typically account for about 5% of the deaths, show almost four times the ED rate of the majority mestizo group. Indigenous women in each age group have higher ED rates than the general population and, in ages between 20 and 49 years, they have higher ED rates than indigenous men. Indigenous women in the age group 20–29 years had an ED rate of 141%, which is commensurate to the ED rate of indigenous women older than 40 years.

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Estimation of excess all-cause mortality due to COVID-19 in Thailand

10.1101/2022.01.07.22268886 ◽

2022 ◽

Author(s):

Chaiwat Wilasang ◽

Thanchanok Lincharoen ◽

Charin Modchang ◽

Sudarat Chadsuthi

Keyword(s):

Correlation Coefficient ◽

Mixed Models ◽

New Record ◽

Excess Mortality ◽

Generalized Linear Mixed Models ◽

Age Groups ◽

Significant Rise ◽

Excess Death ◽

All Cause Mortality ◽

Excess Deaths

Background: Thailand has recently experienced the most prominent COVID-19 outbreak, resulting in a new record for COVID-19 cases and deaths. To assess the influence of the COVID-19 outbreak on mortality, we aimed to estimate excess mortality in Thailand. Methods: We estimated the baseline number of deaths in the absence of COVID-19 using generalized linear mixed models (GLMMs). The models were adjusted for seasonality and demographics. We evaluated the excess mortality from April to October 2021 in Thailand. Results: We found that the estimated cumulative excess death from April to October 2021 was 14.3% (95% CI: 8.6%-18.8%) higher than the baseline. The results also showed that the excess deaths in males were higher than in females by approximately 26.3%. The excess deaths directly caused by the COVID-19 infections accounted for approximately 75.0% of the all-cause excess deaths. Furthermore, the cumulative COVID-19 cases were found to be correlated with the cumulative excess deaths with a correlation coefficient of 0.9912 (95% CI, 0.9392-0.9987). Conclusions: The recent COVID-19 outbreak in Thailand significantly impacts mortality and affects people for specific ages and sex. During the outbreak in 2021, there was a significant rise in excess fatalities, especially in the older age groups. The increase in mortality was higher in men than in women.

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Estimation of Excess Mortality and Years of Life Lost to COVID-19 in Norway and Sweden between March and November 2020

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18083913 ◽

2021 ◽

Vol 18 (8) ◽

pp. 3913

Author(s):

Martin Rypdal ◽

Kristoffer Rypdal ◽

Ola Løvsletten ◽

Sigrunn Holbek Sørbye ◽

Elinor Ytterstad ◽

...

Keyword(s):

Excess Mortality ◽

Age Groups ◽

Years Of Life Lost ◽

Regressive Model ◽

Epidemic Period ◽

All Cause Mortality ◽

Auto Regressive ◽

Expected Mortality ◽

Auto Regressive Model ◽

Excess Deaths

We estimate the weekly excess all-cause mortality in Norway and Sweden, the years of life lost (YLL) attributed to COVID-19 in Sweden, and the significance of mortality displacement. We computed the expected mortality by taking into account the declining trend and the seasonality in mortality in the two countries over the past 20 years. From the excess mortality in Sweden in 2019/20, we estimated the YLL attributed to COVID-19 using the life expectancy in different age groups. We adjusted this estimate for possible displacement using an auto-regressive model for the year-to-year variations in excess mortality. We found that excess all-cause mortality over the epidemic year, July 2019 to July 2020, was 517 (95%CI = (12, 1074)) in Norway and 4329 [3331, 5325] in Sweden. There were 255 COVID-19 related deaths reported in Norway, and 5741 in Sweden, that year. During the epidemic period of 11 March–11 November, there were 6247 reported COVID-19 deaths and 5517 (4701, 6330) excess deaths in Sweden. We estimated that the number of YLL attributed to COVID-19 in Sweden was 45,850 [13,915, 80,276] without adjusting for mortality displacement and 43,073 (12,160, 85,451) after adjusting for the displacement accounted for by the auto-regressive model. In conclusion, we find good agreement between officially recorded COVID-19 related deaths and all-cause excess deaths in both countries during the first epidemic wave and no significant mortality displacement that can explain those deaths.

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Trends in winter excess mortality in Mexico 1991 - 2008

10.7287/peerj.preprints.1273v1 ◽

2015 ◽

Author(s):

Omar González-Santiago ◽

Evangelina Ramirez-Lara ◽

Sandra L. Gracia-Vásquez ◽

Isaias Balderas-Rentería

Keyword(s):

General Population ◽

Excess Mortality ◽

Age Groups ◽

Winter Season ◽

Age Group ◽

Old People ◽

Mediterranean Countries ◽

All Cause Mortality ◽

Main Factors ◽

Low Levels

Objective: Analyze the mortality by all causes in México during the Winter season. Methods: We extracted and tabulated data on monthly all-cause mortality in the general population from 1991 to 2008 from database INEGI. Coefficients of seasonal variation in mortality were calculated. Results: An increase of 15 % in mortality for general population during Winter was observed during the studied period. The more susceptible age groups were old people and children with an increase of winter deaths of 19 % and 11 % respectively. Months with low levels of mortality were April, October and September for children, adolescents and old people respectively. Conclusions: In Mexico winter months shown the highest levels of mortality. The increase in mortality is similar to some Mediterranean countries. More susceptible age groups correspond to child and old people. Months with low levels of mortality are different for each age group. In México it is necessary identify the main factors that contribute to low mortality among different months according age groups.

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Trends in winter excess mortality in Mexico 1991 - 2008

10.7287/peerj.preprints.1273 ◽

2015 ◽

Author(s):

Omar González-Santiago ◽

Evangelina Ramirez-Lara ◽

Sandra L. Gracia-Vásquez ◽

Isaias Balderas-Rentería

Keyword(s):

General Population ◽

Excess Mortality ◽

Age Groups ◽

Winter Season ◽

Age Group ◽

Old People ◽

Mediterranean Countries ◽

All Cause Mortality ◽

Main Factors ◽

Low Levels

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Abstract 16309: Age Specific Baseline Predictors of All-cause Mortality in Systolic Blood Pressure Intervention Trial (SPRINT) Identified by Machine Learning

Circulation ◽

10.1161/circ.142.suppl_3.16309 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Nuha Gani ◽

Anwar Husain ◽

Gauri Dandi ◽

Ian Atkinson ◽

Zyannah Mallick ◽

...

Keyword(s):

Machine Learning ◽

Blood Pressure ◽

Systolic Blood Pressure ◽

Age Groups ◽

Cox Proportional Hazards Model ◽

Data Repository ◽

Diabetic Patients ◽

Age Group ◽

Intervention Trial ◽

All Cause Mortality

Introduction: The NHLBI supported Systolic Blood Pressure (SBP) Intervention Trial (SPRINT) (NCT01206062) aimed to identify an SBP target to reduce incidence of cardiovascular (CV) morbidity and mortality in hypertensive, non-diabetic patients of age ≥ 50 at increased CV risk. It found that intensive treatment (SBP target <120 mmHg) led to fewer major CV events and death but higher rates of adverse events. We reused publicly available patient-level SPRINT data from NHLBI Data Repository (BioLINCC) to perform hypothesis-generating secondary analyses by machine learning (ML) using random survival forest (RSF), to identify age specific baseline (bl) predictors for all-cause mortality (ACM). Methods: RSF was performed on 30 bl variables from 9361 patients in age group specific cohorts (50-59, 60-69, 70-79, 80-90). The identified top 10 predictors from each cohort were included in a multivariate analysis using a Cox proportional hazards model. Results: The top 10 predictors of ACM for age specific subgroups are shown in Figure 1. As expected, cardiovascular disease (CVD) predictors were selected, yet RSF distinctively identified renal biomarkers as important predictors, consistent with our previous analyses. Smoking status and history of CVD ranked as top predictors among age groups 50-59, 60-69, and 70-79. RSF also identified social factors, including race among age groups 60-69 and 80-90 and female gender among age groups 50-59 and 80-90 as important predictors for ACM. Lipid markers and medications used also showed up as top predictors. Specifically, polypharmacy emerged as a top predictor in age groups 60-69, 70-79, and 80-90, notably ranking higher in the 80-90 age group. Conclusions: Using ML, we uncovered in an unbiased fashion, unanticipated age specific top predictors for ACM in SPRINT trial. This highlights the value of ML for analyzing disease and therapeutic intervention outcomes and age specific prognostic factors to advance precision medicine.

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PM2.5 exposure on daily cardio-respiratory mortality in Lima, Peru, from 2010 to 2016.

10.21203/rs.2.23559/v1 ◽

2020 ◽

Author(s):

Vilma Tapia ◽

Kyle Steenland ◽

Bryan Vu ◽

Yang Liu ◽

Vanessa Vasquez ◽

...

Keyword(s):

Air Pollution ◽

Cardiovascular Diseases ◽

Poisson Regression ◽

Age Groups ◽

Age Group ◽

Respiratory Mortality ◽

Air Pollution Exposure ◽

All Cause Mortality ◽

Pm2.5 Exposure ◽

Pollution Exposure

Abstract Background: There have been no studies of air pollution and mortality in Lima, Peru. We evaluate whether daily environmental PM2.5 exposure is associated to respiratory and cardiovascular mortality in Lima during 2010 to 2016.Methods: We analyzed 86,970 deaths from respiratory and cardiovascular diseases in Lima from 2010-2016. Estimated daily PM2.5 was assigned based on district of residence. Poisson regression was used to estimate associations between daily district-level PM2.5 exposures and daily counts of deaths. Results: An increase in one interquartile range in PM2.5 (6.2 ug/m3) on the day before was significantly associated with daily all-cause mortality (RR 1.018; CI 95%: 1.005 – 1.032) across all ages and in the age group over 65 (RR 1.034; CI 95%: 1.003 – 1.057) which included 74% of all deaths. We also observed associations with circulatory deaths for all age groups (RR 1.037; CI 95%: 1.005 – 1.069), and those over 65 (RR 1.038; IC 95% 1.001 - 1.077). A borderline significant trend was seen (RR 1.029; IC 95% 0.99 – 1.06; p= 0.06) for respiratory deaths in persons aged over 65. Trends were driven by the highest quintile of exposure.Conclusions: PM2.5 exposure is associated with daily all-cause, cardiovascular and respiratory mortality in Lima, especially for older people. Our data suggest that the existing limits on air pollution exposure are too high.

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Spatial determinants of excess all-cause mortality during the first wave of the COVID-19 epidemic in France

BMC Public Health ◽

10.1186/s12889-021-12203-8 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Hugo Pilkington ◽

Thierry Feuillet ◽

Stéphane Rican ◽

Jeanne Goupil de Bouillé ◽

Olivier Bouchaud ◽

...

Keyword(s):

Primary Healthcare ◽

Excess Mortality ◽

Social Deprivation ◽

National Level ◽

Age Groups ◽

Geographical Location ◽

Age Group ◽

Contextual Variables ◽

Complex Situation ◽

All Cause Mortality

Abstract Background The first wave of the COVID-19 pandemic in France was associated with high excess mortality, and anecdotal evidence pointed to differing excess mortality patterns depending on social and environmental determinants. In this study we aimed to investigate the spatial distribution of excess mortality during the first wave of the COVID-19 pandemic in France and relate it at the subnational level to contextual determinants from various dimensions (socioeconomic, population density, overall health status, healthcare access etc.). We also explored whether the determinants identified at the national level varied depending on geographical location. Methods We used available national data on deaths in France to calculate excess mortality by department for three age groups: 0–49, 50–74 and > 74 yrs. between March 1st and April 27th, 2020. We selected 15 variables at the department level that represent four dimensions that may be related to overall mortality at the ecological level, two representing population-level vulnerabilities (morbidity, social deprivation) and two representing environmental-level vulnerabilities (primary healthcare supply, urbanization). We modelled excess mortality by age group for our contextual variables at the department level. We conducted both a global (i.e., country-wide) analysis and a multiscale geographically weighted regression (MGWR) model to account for the spatial variations in excess mortality. Results In both age groups, excess all-cause mortality was significantly higher in departments where urbanization was higher (50–74 yrs.: β = 15.33, p < 0.001; > 74 yrs.: β = 18.24, p < 0.001) and the supply of primary healthcare providers lower (50–74 yrs.: β = − 8.10, p < 0.001; > 74 yrs.: β = − 8.27, p < 0.001). In the 50–74 yrs. age group, excess mortality was negatively associated with the supply of pharmacists (β = − 3.70, p < 0.02) and positively associated with work-related mobility (β = 4.62, p < 0.003); in the > 74 yrs. age group our measures of deprivation (β = 15.46, p < 0.05) and morbidity (β = 0.79, p < 0.008) were associated with excess mortality. Associations between excess mortality and contextual variables varied significantly across departments for both age groups. Conclusions Public health strategies aiming at mitigating the effects of future epidemics should consider all dimensions involved to develop efficient and locally tailored policies within the context of an evolving, socially and spatially complex situation.

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All-cause excess mortality observed by age group and regions in the first wave of the COVID-19 pandemic in England

Eurosurveillance ◽

10.2807/1560-7917.es.2020.25.28.2001239 ◽

2020 ◽

Vol 25 (28) ◽

Cited By ~ 5

Author(s):

Mary A Sinnathamby ◽

Heather Whitaker ◽

Laura Coughlan ◽

Jamie Lopez Bernal ◽

Mary Ramsay ◽

...

Keyword(s):

Excess Mortality ◽

Age Groups ◽

Age Group ◽

The Past ◽

All Cause Mortality

England has experienced one of the highest excess in all-cause mortality in Europe during the current COVID-19 pandemic. As COVID-19 emerged, the excess in all-cause mortality rapidly increased, starting in March 2020. The excess observed during the pandemic was higher than excesses noted in the past 5 years. It concerned all regions and all age groups, except the 0–14 year olds, but was more pronounced in the London region and in those aged ≥ 85 years.

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Assessing the Impact of Human Mobility to Predict Regional Excess Death in Ecuador

10.1101/2021.05.19.21257056 ◽

2021 ◽

Author(s):

Leticia Cuellar ◽

Irene Torres ◽

Ethan Obie Romero-Severson ◽

Riya Mahesh ◽

Nathaniel Ortega ◽

...

Keyword(s):

Human Mobility ◽

Age Groups ◽

Sharp Decrease ◽

Progressive Increase ◽

Control Measures ◽

Excess Death ◽

Country Level ◽

Global Trend ◽

The Impact ◽

Excess Deaths

COVID-19 outbreaks have had high mortality in low- and medium-income countries such as Ecuador. Human mobility is an important factor influencing the spread of diseases possibly leading to a high burden of disease at the country level. Drastic control measures, such as complete lockdown are effective epidemic controls, yet in practice, one hopes that a partial shutdown would suffice. It is an open problem to determine how much mobility can be allowed while controlling an outbreak. In this paper, we use statistical models to relate human mobility to the excess death in Ecuador while controlling for demographic factors. The mobility index provided by GRANDATA, based on mobile phone users, represents the change of number of out-of-home events with respect to a benchmark date (March 2nd, the first date the data is available). The study confirms the global trend that more men are dying than expected compared to women, and that people under 30 show less deaths than expected. Specifically, individuals in the age groups younger than 20, we found have their death rate reduced during the pandemic between 22% and 27% of the expected deaths in the absence of COVID-19. The weekly median mobility time series shows a sharp decrease in human mobility immediately after a national lockdown was declared on March 17, 2020 and a progressive increase towards the pre-lockdown level within two months. Relating median mobility to excess death shows a lag in its effect: first, a decrease in mobility in the previous two to three weeks decreases the excess death and more novel, we found that an increase of mobility variability four weeks prior, increases the number of excess deaths.

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Abstract 13267: Age-Related Long-Term Benefit of Cardiac Resynchronization Therapy in LBBB Patients - a MADIT-CRT Long-Term Follow-Up Substudy

Circulation ◽

10.1161/circ.130.suppl_2.13267 ◽

2014 ◽

Vol 130 (suppl_2) ◽

Author(s):

Sabu Thomas ◽

Arthur J Moss ◽

Wojciech Zareba ◽

Scott McNitt ◽

Alon Barsheshet ◽

...

Keyword(s):

Heart Failure ◽

Cardiac Resynchronization Therapy ◽

Age Groups ◽

Cardiac Resynchronization ◽

Age Group ◽

Resynchronization Therapy ◽

All Cause Mortality ◽

Long Term Follow Up

Background: Among patients with heart failure (HF), cardiac resynchronization therapy (CRT) combined with a defibrillator (CRT-D) reduces HF events and mortality compared with a defibrillator (ICD) alone. Whether these benefits extend to all age-groups during long-term follow-up is unclear. Hypothesis: We hypothesized that CRT-D would benefit all age groups with respect to reductions in HF events and all-cause mortality. Methods: We assessed the effect of age on HF events and death among patients in the MADIT-CRT long-term follow up study. 1281 patients with class I or II heart failure and left-bundle branch block (LBBB) were randomized to CRT-D or ICD alone. Patients were divided into 3 age groups: <60, 60-74 or ≥75 years and evaluated over 7 years for mortality and HF events. We compared cumulative events using the log-rank test and adjustments were made using a multivariate logistic regression model with various pre-specified covariates. Results: Overall 761 patients received CRT-D and 520 received ICD alone. The median age was 65 years. Among the three age groups, <60, 60-74 and ≥75 there were 399, 651 and 231 patients respectively. Multivariate analysis (Table) revealed that CRT-D compared to ICD alone significantly reduced the composite outcome of HF or death across all age groups: <60 years relative risk reduction (RRR)=39%, p=0.0236; 60-74 years RRR=59%, p<0.001; ≥75 years RRR=55%, p<0.001. CRT-D also significantly reduced HF events in all age groups <60 years RRR=52%, p=0.003; 60-74 years RRR=61%, p<0.001; ≥75 years RRR=73%, p<0.001. CRT-D was associated with significant mortality reduction only in the 60-74 year age group RRR 58%, p<0.001. Conclusion: Among patients with asymptomatic or mild heart failure, reduced LVEF and LBBB, CRT-D results in significant reduction of HF events and in the composite of all-cause mortality and HF events during long-term follow-up. All-cause mortality was significantly reduced with CRT-D only in the 60-74 year age group.

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