scholarly journals Estimating Lower Bounds for COVID-19 Mortality from Northern Italian Towns

2020 ◽  
Author(s):  
Thomas S. Coleman
Keyword(s):  
Infection Rate ◽  
Lower Bounds ◽  
Excess Mortality ◽  
Fatality Rate ◽  
Epidemiological Modeling ◽  
Specific Mortality ◽  
Italian Provinces ◽  
Using Data ◽  
The Town ◽  
Age And Sex

AbstractFor COVID-19 the Infection Fatality Rate or IFR – a crucial variable in epidemiological modeling – is difficult to estimate because many cases are asymptomatic and the overall infection rate is generally not known. Circumstances in the Italian provinces of Milano, Bergamo, Brescia, and Lodi allow estimation of lower bounds for age- and sex-specific all-cause excess mortality (a proxy for IFR) since anecdotal reports indicate some towns were close to fully infected. Using data from ISTAT on mortality from January 1 through April 15 for 2020 and the three preceding years, I estimate excess mortality by sex and age categories (0-14, 15-54, 55-64, 65-74, and 75+ years) while controlling for town-specific mortality that proxies for town-specific infection rate. The 99th percentile from the tail of the town distribution gives a lower-bound estimate for COVID-19 mortality. The overall population-weighted mortality at the 99th percentile is 1.09 percent (95% CI 1.06-1.14). The age- and sex-specific rates vary considerably: for men age 65-74 the estimate is 2.10 percent (95% CI 1.94-2.28) which is 3.5-times higher than men 55-64 and 2.7-times higher than women 65-74.

scholarly journals EXCESS MORTALITY FROM COVID-19. WEEKLY EXCESS DEATH RATES BY AGE AND SEX FOR SWEDEN AND ITS MOST AFFECTED REGION

2020 ◽  
Author(s):  
Karin Modig ◽  
Anders Ahlbom ◽  
Marcus Ebeling
Keyword(s):  
Causes Of Death ◽  
Excess Mortality ◽  
National Level ◽  
Mortality Rates ◽  
Regional Level ◽  
Death Rates ◽  
Excess Death ◽  
All Cause Mortality ◽  
Specific Mortality ◽  
Age And Sex

Abstract Background Sweden has one of the highest numbers of COVID-19 deaths per inhabitant globally. However, absolute death counts can be misleading. Estimating age- and sex-specific mortality rates is necessary in order to account for the underlying population structure. Furthermore, given the difficulty of assigning causes of death, excess all-cause mortality should be estimated to assess the overall burden of the pandemic. Methods By estimating weekly age- and sex-specific death rates during 2020 and during the preceding five years, our aim is to get more accurate estimates of the excess mortality attributed to COVID-19 in Sweden, and in the most affected region Stockholm. Results Eight weeks after Sweden’s first confirmed case, the death rates at all ages above 60 were higher than for previous years. Persons above age 80 were disproportionally more affected, and men suffered greater excess mortality than women in ages up to 75 years. At older ages, the excess mortality was similar for men and women, with up to 1.5 times higher death rates for Sweden and up to 3 times higher for Stockholm. Life expectancy at age 50 declined by less than 1 year for Sweden and 1.5 years for Stockholm compared to 2019. Conclusions The excess mortality has been high in older ages during the pandemic, but it remains to be answered if this is because of age itself being a prognostic factor or a proxy for comorbidity. Only monitoring deaths at a national level may hide the effect of the pandemic on the regional level.

scholarly journals Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem

2020 ◽  
Author(s):  
Charles F. Manski ◽  
Francesca Molinari
Keyword(s):  
New York ◽  
Missing Data ◽  
Infection Rate ◽  
Severe Illness ◽  
Fatality Rate ◽  
Infection Rates ◽  
Inference Problem ◽  
Logical Problem ◽  
Current Context ◽  
Using Data

AbstractAs a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Italy is substantially lower than reported.

scholarly journals Analysis of Austrian COVID-19 deaths by age and sex

2020 ◽  
Vol 132 (21-22) ◽  
pp. 685-689 ◽  
Author(s):  
Martin Posch ◽  
Peter Bauer ◽  
Alexander Posch ◽  
Franz König
Keyword(s):  
Mortality Rate ◽  
Age Groups ◽  
International Studies ◽  
Fatality Rate ◽  
Age Dependency ◽  
Additional Risk ◽  
Risk Of Death ◽  
Specific Mortality ◽  
Population Sizes ◽  
Age And Sex

SummaryWe analyze the age and sex distribution of the reported COVID-19 deaths in Austria. In accordance with international studies, the Austrian data also suggests that the risk of death increases substantially with age. The observed age dependency of the proportions of registered COVID-19 deaths in relation to the population sizes in the age groups is approximately exponential, similar to the age dependency of the general age specific mortality rate. Furthermore, we compare the general age specific mortality rate in Austria with the estimates of the SARS-CoV‑2 infection fatality rate by Ferguson et al. (2020). The parallels to the general age specific mortality rates do not imply that COVID-19 does not pose an additional risk. On the contrary, it follows from the structure and magnitude of the infection fatality rate that it is substantial, especially for higher age groups. However, since in many cases persons with severe pre-existing conditions are affected, it is not yet possible to estimate what effects COVID-19 will have on life expectancy.

scholarly journals Estimating SARS-CoV-2 infection fatality rate using data from one of the most affected areas worldwide

2021 ◽  
Keyword(s):  
Excess Mortality ◽  
Seroconversion Rate ◽  
Uncertain Data ◽  
Mortality Data ◽  
Fatality Rate ◽  
Worst Case ◽  
The World ◽  
Unique Approach ◽  
Computational Errors ◽  
Using Data

The real estimate of the infection fatality rate of SARS-CoV-2 is a pivotal aspect of the COVID-19 pandemic. However, this number is still debated, since both the numerator and the denominator are uncertain. Data analysis from the most affected areas in the world minimizes computational errors and represents a unique approach for estimating infection fatality rate. We first extracted data from PubMed/Medline, Google, traditional media and social media to obtain the rate of SARS-CoV-2 antibodies seroprevalence in the most affected and best-studied areas in the world: Val Seriana (Italy), Ischgl (Austria) and Manaus (Brasil). We then searched mortality data from national institutes of statistics and calculated excess mortality. We estimated the infection fatality rate considering several scenarios according to the mortality attributable to COVID-19 and the proportion of the population infected with the virus. We found that the seropositivity was surprisingly close to 40% in all the considered areas. We calculated the SARS-CoV-2 infection fatality rate for Val Seriana, using from half to the entire excess mortality (1208 deaths) and considering from 40% to 80% of the population as being infected with SARS-CoV-2. In the most conservative scenario, infection fatality rate was as low as 0.55%, while in the worst-case one it was 2.2%. We found that the seroconversion rate in the most affected areas worldwide is about 40%. We consequently estimated the infection fatality rate to be between 0.55% and 2.2% in an area with a relatively elderly population.

'A town built on migration?' Calculating the human capital value of migration to Reading, 1851-1871

2019 ◽  
pp. 26-54
Author(s):  
Daniel James Gooch
Keyword(s):  
Human Capital ◽  
Economic Value ◽  
Infrastructure Projects ◽  
Economic Output ◽  
Net Migration ◽  
A Value ◽  
Time Period ◽  
The Town ◽  
Age And Sex ◽  
Capital Value

This article provides an estimate of the human capital value of migration to Reading in the period 1851-1871 to the town's economy. This is determined by estimating total net migration to the town across this period by age and sex and assigning all migrants a value for expected lifetime economic output less expected lifetime consumption costs. The final figures are contextualised by comparison with the value of social overhead capital used to fund significant local infrastructure projects in the same time period and show that, from a human capital perspective, the value of migration to Reading was very significant. This article thus addresses significant historiographical gaps in the study of Victorian labour migration to southern provincial towns and provides an original perspective to studies of the economic value of migration and its role in the growth of such communities.

Prevalence of Linguatula sp., a food-borne zoonotic aberrant arthropod, in river buffaloes slaughtered at Tabriz slaughterhouse, Iran

2020 ◽  
Author(s):  
Nasser Hajipour ◽  
Jennifer Ketzis ◽  
Parviz Hassanzadeh
Keyword(s):  
Infection Rate ◽  
Statistical Association ◽  
Intermediate Hosts ◽  
Mesenteric Lymph Nodes ◽  
Intensity Of Infection ◽  
Mesenteric Lymph ◽  
Food Borne ◽  
Different Seasons ◽  
Significant Statistical Association ◽  
Age And Sex

Abstract Background Canids and herbivores are the definitive and intermediate hosts of Linguatula sp., respectively. Methods Mesenteric lymph nodes (n=32 525) were randomly collected from 7585 buffaloes from July 2016 to July 2019 and examined macroscopically. Results Results showed that 388 (5.11%) buffaloes were infected. The intensity of infection was determined to be 3.07±0.07. Significant statistical association was identified between infection rate and age and sex. Although there were no significant differences in the infection rate over different seasons, the highest infection rate was observed in autumn. Conclusions These data highlight the importance of inspection at slaughter.

scholarly journals Meta-analysis and metaregression of risk factors associated with mortality in hip fracture patients during the COVID-19 pandemic

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Firas J. Raheman ◽  
Djamila M. Rojoa ◽  
Jvalant Nayan Parekh ◽  
Reshid Berber ◽  
Robert Ashford
Keyword(s):  
Hip Fracture ◽  
Hip Fractures ◽  
Case Fatality Rate ◽  
Excess Mortality ◽  
Meta Analysis ◽  
Case Fatality ◽  
Pooled Analysis ◽  
Fatality Rate ◽  
Increased Risk ◽  
The Impact

AbstractIncidence of hip fractures has remained unchanged during the pandemic with overlapping vulnerabilities observed in patients with hip fractures and those infected with COVID-19. We aimed to investigate the independent impact of COVID-19 infection on the mortality of these patients. Healthcare databases were systematically searched over 2-weeks from 1st–14th November 2020 to identify eligible studies assessing the impact of COVID-19 on hip fracture patients. Meta-analysis of proportion was performed to obtain pooled values of prevalence, incidence and case fatality rate of hip fracture patients with COVID-19 infection. 30-day mortality, excess mortality and all-cause mortality were analysed using a mixed-effects model. 22 studies reporting 4015 patients were identified out of which 2651 (66%) were assessed during the pandemic. An excess mortality of 10% was seen for hip fractures treated during the pandemic (OR 2.00, p = 0.007), in comparison to the pre-pandemic controls (5%). Estimated mortality of COVID-19 positive hip fracture patients was four-fold (RR 4.59, p < 0.0001) and 30-day mortality was 38.0% (HR 4.73, p < 0.0001). The case fatality rate for COVID-19 positive patients was 34.74%. Between-study heterogeneity for the pooled analysis was minimal (I2 = 0.00) whereas, random effects metaregression identified subgroup heterogeneity for male gender (p < 0.001), diabetes (p = 0.002), dementia (p = 0.001) and extracapsular fractures (p = 0.01) increased risk of mortality in COVID-19 positive patients.

scholarly journals Estimation of the true infection rate and infection fatality rate of coronavirus disease 2019 in each country

2021 ◽  
Author(s):  
Masahiro Sonoo ◽  
Takamichi Kanbayashi ◽  
Takayoshi Shimohata ◽  
Masahito Kobayashi ◽  
Masashi Idogawa ◽  
...  
Keyword(s):  
Infection Rate ◽  
Fatality Rate ◽  
True Infection

scholarly journals Magnitude, change over time, demographic characteristics and geographic distribution of excess deaths among nursing home residents during the first wave of COVID-19 in France: a nationwide cohort study

2021 ◽  
Author(s):  
Florence Canouï-Poitrine ◽  
Antoine Rachas ◽  
Martine Thomas ◽  
Laure Carcaillon-Bentata ◽  
Roméo Fontaine ◽  
...  
Keyword(s):  
Nursing Home ◽  
General Population ◽  
Excess Mortality ◽  
Nursing Home Residents ◽  
Primary Objective ◽  
List Type ◽  
Key Points ◽  
Standardized Mortality Ratios ◽  
Using Data ◽  
Excess Deaths

AbstractImportanceNursing home (NH) residents are particularly vulnerable to SARS-CoV-2 infections and coronavirus disease 2019 (COVID-19) lethality. However, excess deaths in this population have rarely been documented.ObjectivesThe primary objective was to assess the number of excess deaths among NH residents during the first wave of the COVID-19 pandemic in France. The secondary objectives were to determine the number of excess deaths as a proportion of the total excess deaths in the general population and determine whether a harvesting effect was present.DesignWe studied a cohort of 494,753 adults (as of March 1st, 2020) aged 60 and over in 6,515 NHs in mainland France. This cohort was exposed to the first wave of the COVID-19 pandemic (from March 1st to May 31st, 2020) and was compared with the corresponding, reference cohorts from 2014 to 2019 (using data from the French National Health Data System).Main outcome and measuresThe main outcome was all-cause death. Weekly excess deaths and standardized mortality ratios (SMRs) were estimated.ResultThere were 13,505 excess deaths among NH residents. Mortality increased by 43% (SMR: 1.43). The mortality excess was higher among males than among females (SMR: 1.51 and 1.38, respectively) and decreased with age (SMRs in females: 1.61 in the 60-74 age group, 1.58 for 75-84, 1.41 for 85-94, and 1.31 for 95 or over; Males: SMRs: 1.59 for 60-74, 1.69 for 75-84, 1.47 for 85-94, and 1.41 for 95 or over). We did not observe a harvesting effect (up until August 30th, 2020). By extrapolating to all NH residents nationally (N=570,003), the latter accounted for 51% of the total excess deaths in the general population (N=15,114 out of 29,563).ConclusionNH residents accounted for about half of the total excess deaths in France during the first wave of the COVID-19 pandemic. The excess death rate was higher among males than females and among younger residents than among older residents. We did not observe a harvesting effect. A real-time mortality surveillance system and the identification of individual and environmental risk factors might help to design the future model of care for older dependent adults.Key pointsDuring the first wave of the COVID-19 pandemic in France, the mortality among nursing home residents increased by 43%.Nursing home residents accounted for 51% of the total excess deaths in France.The excess mortality was higher among younger residents than among older residents.The excess mortality was higher among males than among females.We did not observe a harvesting effect during the study period (ending on August 30th, 2020, i.e., three months after the end of the first wave).

Estimation of All-Cause Excess Mortality by Age-Specific Mortality Patterns of COVID-19 Pandemic in Peru in 2020

2021 ◽  
Author(s):  
Peter Lloyd-Sherlock ◽  
Shah Ebrahim ◽  
Ramón Martínez ◽  
Martin McKee ◽  
Enrique Acosta ◽  
...  
Keyword(s):  
Excess Mortality ◽  
Specific Mortality
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