scholarly journals Evaluation of death count estimates for Puerto Rico following Hurricane Maria

2018 ◽  
Author(s):  
Alexis R Santos ◽  
Jeffrey T. Howard
Keyword(s):  
Puerto Rico ◽  
Incomplete Information ◽  
Confidence Intervals ◽  
Vital Statistics ◽  
Initial Estimate ◽  
Excess Death ◽  
Estimation Process ◽  
Climate Disasters ◽  
Death Count ◽  
Excess Deaths

This descriptive finding examines estimates of death counts following Hurricane Maria in Puerto Rico for September and October 2017. We evaluate the monthly death count estimates and estimates of excess deaths in Puerto Rico based on historical patterns of variability by month for the 2010-2016 and published official death counts for 2017. Official death records from the Puerto Rico Vital Statistics Systems by month and year (2010-2016) were used to produce means and 95% confidence intervals (95% C.I.) for each month. Death count and excess death estimates for September and November 2017 are employed to: (1) illustrate the estimation process and (2) assess the accuracy of these estimates when compared to official death counts for the same period. Estimates produced with incomplete information were 2,987 (95% C.I. 2,900-3,074) and 3,043 (95% C.I. 2,995-3,091) for September and October 2017, respectively. Corresponding official death counts for the same months for 2017 were 2,928 and 3,040. Using estimated death counts, 1,085 excess deaths (95% C.I. 950-1,220) were estimated in November 2017. Using official counts yielded 1,023 excess deaths (95% C.I. 956-1,090). Despite initially overestimating the number of deaths in September and October by 1.04%, subsequent estimate of excess deaths using official death counts was within the 95% C.I. of the initial estimate. Our findings demonstrate the timely production of death count estimates following climate disasters using historical death records and a thorough study of previous experiences.

scholarly journals In Puerto Rico, excess deaths following Hurricane Georges persisted for three months

2018 ◽  
Author(s):  
Alexis R Santos
Keyword(s):  
Puerto Rico ◽  
Upper Limit ◽  
The World ◽  
Basic Services ◽  
Drinkable Water ◽  
Population Shift ◽  
Climate Disasters ◽  
Death Count ◽  
Climate Disaster ◽  
Excess Deaths

The interruption in basic services such as electricity, drinkable water, and exposure to atypical circumstances following climate disasters increases mortality risk within the settings affected by these events. Recently, some members of academia have argued that no methodology exists to study excess deaths attributable to climate disasters. This study uses death records for Puerto Rico between 1990 and 1998 to assess excess deaths following Hurricane Georges by comparing death counts for 1998 with patterns of variation from the previous eight years. Because no population shift occurred in that decade, other than expected ones based on historical information, the average number of deaths is indicative of expected deaths and the confidence intervals are the ranges of accepted variation. If a count following a climate disaster exceeds the upper limit of the confidence interval these deaths could be considered above the historical ranges of variation and this excess could be associated with the climate disaster of interest. Death counts for September-November 1998 indicate that 819 deaths were in excess of historical ranges of variation. When the year in which Hurricane Hortense is excluded from the construction of the ranges of variation, the excess is 945 deaths. A total of 811 or 937 are missing in comparison to the official death count for this Hurricane. Considering that death counts data structures are comparable across the countries of the world, this method can be used to analyze the effect of other climate disasters.

scholarly journals Estimates of excess deaths in Puerto Rico following Hurricane Maria

2017 ◽  
Author(s):  
Alexis R Santos ◽  
Jeffrey T. Howard
Keyword(s):  
Puerto Rico ◽  
Confidence Intervals ◽  
Public Safety ◽  
Vital Statistics ◽  
Aggregated Data ◽  
Estimation Techniques ◽  
Death Toll ◽  
Mortality Burden ◽  
The Difference ◽  
Excess Deaths

BACKGROUND: This descriptive finding examines excess deaths following Hurricane María, in Puerto Rico for September and October 2017. OBJECTIVE: We seek to determine the degree of excess deaths in Puerto Rico based on historical patterns of variability in deaths by month for the 2010-2016 period and using estimation techniques. METHODS: Data for this study come from death records from the Puerto Rico Vital Statistics system. We aggregated data by month and year (2010-2016) and produced means (expected deaths) and 95% confidence intervals (C.I., or patterns of variability) for each month. Using public statements from the Puerto Rico Department of Public Safety, we estimate the number of deaths for September and October 2017 and compare it to the level of expected deaths considering the pattern of variability. RESULTS: Expected deaths for September and October were 2,383 (95% C.I. 2,296-2,469) and 2,428 (95% C.I. 2,380 - 2,476), respectively. Estimates for total deaths, for September and October 2017 were 2,987 (95% CI 2,900-3,074) and 3,043 (95% C.I. 2,995-3,091), respectively. The difference between our estimates and the upper 95% CI for the average deaths is 518 deaths for September and 567 deaths for October. CONCLUSIONS: The mortality burden may higher than official counts, and may exceed the current official death toll by a factor of 10 or more.

scholarly journals Use of Death Counts From Vital Statistics to Calculate Excess Deaths in Puerto Rico Following Hurricane Maria

JAMA ◽  
2018 ◽  
Vol 320 (14) ◽  
pp. 1491 ◽  
Author(s):  
Alexis R. Santos-Lozada ◽  
Jeffrey T. Howard
Keyword(s):  
Puerto Rico ◽  
Vital Statistics ◽  
Excess Deaths

Excess mortality from COVID and non-COVID causes in minority populations

2021 ◽  
Vol 118 (39) ◽  
pp. e2101386118 ◽  
Author(s):  
Christopher J. Cronin ◽  
William N. Evans
Keyword(s):  
Excess Mortality ◽  
Time Interval ◽  
Hispanic Males ◽  
Excess Death ◽  
Life Years ◽  
Life Years Lost ◽  
Race Ethnicity ◽  
And Gender ◽  
Death Count ◽  
Excess Deaths

The 2020 US mortality totaled 2.8 million after early March, which is 17.3% higher than age-population–weighted mortality over the same time interval in 2017 to 2019, for a total excess death count of 413,592. We use data on weekly death counts by cause, as well as life tables, to quantify excess mortality and life years lost from both COVID-19 and non–COVID-19 causes by race/ethnicity, age, and gender/sex. Excess mortality from non–COVID-19 causes is substantial and much more heavily concentrated among males and minorities, especially Black, non-Hispanic males, than COVID-19 deaths. Thirty-four percent of the excess life years lost for males is from non–COVID-19 causes. While minorities represent 36% of COVID-19 deaths, they represent 70% of non–COVID-19 related excess deaths and 58% of non–COVID-19 excess life years lost. Black, non-Hispanic males represent only 6.9% of the population, but they are responsible for 8.9% of COVID-19 deaths and 28% of 2020 excess deaths from non–COVID-19 causes. For this group, nearly half of the excess life years lost in 2020 are due to non–COVID-19 causes.

scholarly journals Post-Hurricane Vital Statistics Expose Fragility of Puerto Rico’s Health System

2018 ◽  
Author(s):  
Rolando J. Acosta ◽  
Rafael A. Irizarry
Keyword(s):  
Puerto Rico ◽  
Health System ◽  
Death Rate ◽  
Hurricane Sandy ◽  
Mortality Data ◽  
Monthly Data ◽  
Daily Data ◽  
Unnecessary Death ◽  
Death Count ◽  
Excess Deaths

AbstractImportanceHurricane Maria made landfall in Puerto Rico on September 20, 2017. As recently as May of this year (2018), the official death count was 64. After a study describing a household survey reported a much higher death count estimate, as well as evidence of population displacement, extensive loss of services, and a prolonged death rate the government released death registry data. These newly released data will permit a better understanding of the effects of this hurricane.ObjectiveProvide a detailed description of the effects on mortality of Hurricane Maria and compare to other hurricanes.DesignWe fit a statistical model to mortality data that accounts for seasonal and non-hurricane related yearly effects. We then estimated the deviation from the expected death rate as a function of time.SettingWe fit this model to 1985-2018 Puerto Rico daily data, which includes the dates of hurricanes Hugo, Georges, and Maria, 2015-2018 Florida daily data, which includes the dates of Hurricane Irma, 2002-2004 Louisiana monthly data, which includes the date of Hurricane Katrina, and 2000-2016 New Jersey monthly data, which includes the date of Hurricane Sandy.ResultsWe find a prolonged increase in death rate after Maria and Katrina, lasting at least 207 and 125 days, resulting in excess deaths estimates of 3,400 (95% CI, 3,100-3,700), and 1,800 (95% CI, 1,600-2100) respectively, showing that Maria had a more long term damaging impact. Surprisingly, we also find that in 1998, Georges had a comparable impact to Katrina’s with a prolonged increase of 106 days resulting in 1,400 (95% CI, 1,200-1,700) excess deaths. For Hurricane Maria, we find sharp increases in a small number of causes of deaths, including diseases of the circulatory, endocrine and respiratory system, as well as bacterial infections and suicides.Conclusion and RelevanceOur analysis suggests that since at least 1998, Puerto Rico’s health system has been in a precarious state. Without a substantial intervention, it appears that if hit with another strong hurricane, Puerto Ricans will suffer the unnecessary death of hundreds of its citizens.Key PointsQuestion: How does the effect of Hurricane Maria on mortality in Puerto Rico compare to the effect of other hurricanes in Puerto Rico and other United States jurisdictions?Findings: We estimate about 3,000 excess deaths after Maria, a higher toll than Katrina. Only other comparable effect was after Georges, also in Puerto Rico. For Georges and Maria, we observe a prolonged death rate increase of more than 10% lasting several months. The causes of death that increased after Maria are consistent with a collapsed health systemMeaning: Puerto Rico’s health system does not appear to be ready to withstand another strong hurricane.

scholarly journals Robustness and bias of European excess death estimates in 2020 under varying model specifications

2021 ◽  
Author(s):  
Jonas Schöley
Keyword(s):  
Death Rate ◽  
Cross Validation ◽  
European Countries ◽  
Rate Model ◽  
Causal Interpretation ◽  
Excess Death ◽  
Country Level ◽  
Death Count ◽  
Excess Deaths

Various procedures are in use to calculate excess deaths during the ongoing COVID-19 pandemic. Using weekly death counts from 20 European countries, we evaluate the robustness of excess death estimates to the choice of model for expected deaths and perform a cross-validation analysis to assess the error and bias in each model's predicted death counts. We find that the different models produce very similar patterns of weekly excess deaths but disagree substantially on the level of excess. While the exact country ranking along percent excess death in 2020 is sensitive to the choice of model the top and bottom ranks are robustly identified. On the country level, the 5-year average death rate model tends to produce the lowest excess death estimates, whereas high excess deaths are produced by the popular 5-year average death count and Euromomo-style Serfling models. Cross-validation revealed these estimates to be biased under a causal interpretation of "expected deaths had COVID-19 not happened."

scholarly journals Time between death and funeral services in Puerto Rico following Hurricane María

2019 ◽  
Author(s):  
Alexis R Santos
Keyword(s):  
Puerto Rico ◽  
Forensic Science ◽  
Confidence Intervals ◽  
Descriptive Analysis ◽  
Vital Statistics ◽  
Science Institute ◽  
Funeral Services ◽  
Status Data

This descriptive finding examines patterns in time to funeral following Hurricane María, in Puerto Rico between in 2017 and 2018. I calculate average time to funeral by month, and by autopsy status. Data for this study come from death records obtained from the Puerto Rico Vital Statistics System with support from the Puerto Rico Institute of Statistics. I produce ranges of variation by month as means with corresponding 95% confidence intervals (95% CI) for each month. The average number of days after Hurricane María indicate that the number of days has reduced but was significantly higher in September 2017. The analysis by autopsy status, indicates that on average cases where an autopsy was performed had a greater number of days between death and funeral. After Hurricane Maria, the number of days was higher but patterns of reduction are observed in this descriptive analysis. Cases sent to the Forensic Science Institute for an autopsy had significantly higher number of days between death and funeral than those who were not sent.

scholarly journals Leveraging online repositories: the case of excess deaths following Hurricane Maria in Puerto Rico

2018 ◽  
Author(s):  
Alexis R Santos
Keyword(s):  
Puerto Rico ◽  
Vital Statistics ◽  
Data Repository ◽  
Working Paper ◽  
Excess Deaths

This working paper describes the process through which I created, developed and improved a data repository for data and code used to replicate our paper titled "Use of Death Counts from Vital Statistics to Calculate Excess Deaths in Puerto Rico Following Hurricane Maria". The repository can be accessed here: https://alexisrsantos.github.io/Deaths_Puerto_Rico_JAMA/. It also documents the opportunities and challenges of engaging in this endeavor.

scholarly journals Using excess deaths and testing statistics to determine COVID-19 mortalities

2021 ◽  
Author(s):  
Lucas Böttcher ◽  
Maria R. D’Orsogna ◽  
Tom Chou
Keyword(s):  
New York ◽  
New York City ◽  
Disease Prevalence ◽  
Statistical Testing ◽  
Biased Sampling ◽  
Mortality Data ◽  
Sir Epidemic Model ◽  
Excess Death ◽  
Sir Epidemic ◽  
Excess Deaths

AbstractFactors such as varied definitions of mortality, uncertainty in disease prevalence, and biased sampling complicate the quantification of fatality during an epidemic. Regardless of the employed fatality measure, the infected population and the number of infection-caused deaths need to be consistently estimated for comparing mortality across regions. We combine historical and current mortality data, a statistical testing model, and an SIR epidemic model, to improve estimation of mortality. We find that the average excess death across the entire US from January 2020 until February 2021 is 9$$\%$$ % higher than the number of reported COVID-19 deaths. In some areas, such as New York City, the number of weekly deaths is about eight times higher than in previous years. Other countries such as Peru, Ecuador, Mexico, and Spain exhibit excess deaths significantly higher than their reported COVID-19 deaths. Conversely, we find statistically insignificant or even negative excess deaths for at least most of 2020 in places such as Germany, Denmark, and Norway.

scholarly journals Forecasting Imminent Deaths

2021 ◽  
Author(s):  
Silvia Rizzi ◽  
James W Vaupel
Keyword(s):  
Short Term ◽  
Excess Death ◽  
Economic Changes ◽  
Behavioral Healthcare ◽  
Policy Interventions ◽  
Short Term Mortality ◽  
Short Term Forecasting ◽  
Mortality Forecasts ◽  
The Impact ◽  
Death Count

We introduce a new method for making short-term mortality forecasts of a few months, illustrating it by estimating how many deaths might have happened if some major shock had not occurred. We apply the method to assess excess mortality from March to June 2020 in Denmark and Sweden as a result of the first wave of the coronavirus pandemic, associated policy interventions and behavioral, healthcare, social and economic changes. We chose to compare Denmark and Sweden because reliable data were available and because the two countries are similar but chose different responses to covid-19: Denmark imposed a rather severe lockdown; Sweden did not. We make forecasts by age and sex to predict expected deaths if covid-19 had not struck. Subtracting these forecasts from observed deaths gives the excess death count. Excess deaths were lower in Denmark than Sweden during the first wave of the pandemic. The later/earlier ratio we propose for shortcasting is easy to understand, requires less data than more elaborate approaches, and may be useful in many countries in making both predictions about the future and the past to study the impact on mortality of coronavirus and other epidemics. In the application to Denmark and Sweden, prediction intervals are narrower and bias is less than when forecasts are based on averages of the last five years, as is often done. More generally, later/earlier ratios may prove useful in short-term forecasting of illnesses and births as well as economic and other activity that varies seasonally or periodically.

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