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Average Age Of Coronavirus Death

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Last Updated: 02 July 2021

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General | Latest Info

As of October 15, 216 025 Deaths from Coronavirus Disease 2019 have been reported in the United States *; however, this number might underestimate the total impact of the pandemic on mortality. Measures of excess deaths have been used to estimate the impact of public health pandemics or disasters, particularly when there are questions about underascertainment of deaths directly attributable to event or cause. Excess Deaths are defined as the number of people who have died from all causes, in excess of the expected number of deaths due to place and time. This report describes trends and demographic patterns in excess deaths during January 26 - October 3 2020. Expect numbers of deaths were estimated using overdispersed Poisson regression models with spline terms to account for seasonal patterns, using provisional mortality data from CDCs National Vital Statistics System. Weekly numbers of Deaths by age group and race / ethnicity were assessed to examine the difference between the weekly number of Deaths occurring in 2020 and the average number occurring in the same week during 2015 - 2019 and percentage change in 2020. Overall, estimated 299 028 excess Deaths have occurred in the United States from late January through October 3 2020, with two thirds of these attributed to COVID - 19. The largest percentage increases were seen among adults aged 25 - 44 years and among Hispanic or Latino people. These results provide information about the degree to which COVID - 19 deaths might be underascertained and inform efforts to prevent mortality directly or indirectly associated with COVID - 19 pandemic, such as efforts to minimize disruptions to health care. Estimates of excess deaths can provide a comprehensive account of mortality related to the COVID - 19 pandemic, including deaths that are directly or indirectly attributable to COVID - 19. Estimates of numbers of deaths directly attributable to COVID - 19 might be limited by factors such as availability and use of diagnostic testing and accurate and complete reporting of cause of Death information on death certificate. Excess Death analyses are not subject to these limitations because they examine historical trends in all - cause mortality to determine the degree to which observed numbers of deaths differ from historical norms. In April 2020, CDCs National Center for Health Statistics will begin publishing data on excess deaths associated with the COVID - 19 pandemic. This report describes trends and demographic patterns in the number of excess deaths occurring in the United States from January 26 2020, through October 3 2020, and differences by age and race / ethnicity using provisional mortality data from NVSS. Excess Deaths are typically defined as the number of people who have died from all causes, in excess of the expected number of deaths for give place and time. A detailed description of the methodology for estimating excess deaths has been described previously. Briefly, expected numbers of deaths are estimated using overdispersed Poisson regression models with spline terms to account for seasonal patterns. Average expect number, as well as upper bound of 95% prediction interval, are used as thresholds to determine the number of excess deaths and percentage excess.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Discussion

As of September 21 2020, Coronavirus Disease 2019 pandemic had resulted in more than 6 800 000 reported US cases and more than 199 000 associated deaths. * Early in the pandemic, COVID - 19 incidence was highest among older adults. Cdc examined changing age distribution of COVID - 19 pandemic in the United States during May - August by assessing three indicators: COVID - 19 - like illness - related emergency Department visits, positive reverse transcription - polymerase chain reaction test results for SARS - CoV - 2, virus that causes COVID - 19, and confirm COVID - 19 cases. Nationwide, median age of COVID - 19 cases declined from 46 years in May to 37 years in July and 38 in August. Similar patterns were seen for COVID - 19 - like illness - related ED visits and positive SARS - CoV - 2 RT - PCR test results in all US Census Regions. During June - August, COVID - 19 incidence was highest in persons aged 20 - 29 years, who account for > 20% of all confirmed cases. The Southern United States experienced regional outbreaks of COVID - 19 in June. In these regions, increases in the percentage of positive SARS - CoV - 2 test results among adults aged 20 - 39 years precede increases among adults aged 60 years by an average of 8. 7 days, suggesting that younger adults likely contributed to community transmission of COVID - 19. Give role of asymptomatic and presymptomatic transmission, strict adherence to community mitigation strategies and personal preventive behaviors by younger adults is needed to help reduce their risk for infection and subsequent transmission of SARS - CoV - 2 to persons at higher risk for severe illness. Cdc examined age trends during May - August for 50 States and the District of Columbia using three indicators: 1 COVID - 19 - like illness - related ED visits; 2 positive SARS - CoV - 2 RT - PCR test results; and 3 confirmed COVID - 19 cases. Covid - 19 - like illness - related ED visits, reported by health facilities to National Syndromic Surveillance Program NSSP, had fever with cough, shortness of breath, or difficulty breathing in chief complaint text or discharge diagnostic code for COVID - 19 and no diagnostic codes for influenza. Analyses of COVID - 19 - like illness - related ED visits were based on ED visit date. Sars - CoV - 2 RT - PCR test results were obtained from COVID - 19 electronic laboratory reporting data submitted by state Health departments in 37 States and, when age was unavailable in state - submit data, from data submitted directly by public Health, commercial, and reference laboratories in 13 States and DC. Data represents number of specimens test, not individual persons who receive testing. Analyses were based on specimen collection date or test order date. * Daily percentage of positive SARS - CoV - 2 test results percent positivity was calculated as the number of positive test results divided by the sum of positive and negative test results. Confirm COVID - 19 cases were identified from individual - level case reports submitted by state health departments; analyses were based on the date the case was reported to CDC. Confirm COVID - 19 cases had positive SARS - CoV - 2 RT - PCR test result. Case data represents individual people, some of whom might have had multiple positive test results. Monthly incidence was calculated using 2018 US Census population estimates. National case count, percentage distributions, and estimated incidence of confirmed COVID - 19 cases were calculated by 10 - year age increments and by month May - August.

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Introduction

Since its emergence, Coronavirus Disease 2019 has resulted in pandemic and has produced a huge number of cases worldwide 1. As of May 29 2020, number of confirmed cases in Italy was 382. 3, with 507. 2 in Spain, and 13. 2 in Japan 1. Of those infect, it has been reported that elderly individuals account for a large portion of fatal cases inducing large heterogeneity in age distribution of Mortality 2 3 4. The expected value of mortality is calculated as a product of the number of cases and mortality rate among cases. As background mechanism of heterogeneity of mortality by age, association of two epidemiological factors with mortality can be consider: age - dependency of susceptibility to infection, which is related to heterogeneity in number of cases, and age - dependency of severity, which is related to heterogeneity in mortality rate, eg rate of becoming symptomatic, severe, or fatal case among infected individuals. For first factor, high susceptibility to infection will generate a larger number of infections and result in an increase in fatal cases. The possibility of heterogeneity in susceptibility by age was pointed out by analysis of epidemiological data reports from Wuhan, China 4 5 6 and from Iceland 7. For second factor, increase in severity will result in a higher mortality rate and subsequently a rise in the number of fatal cases. This assumption is also reasonable because elder age as well as the existence of comorbidities, which are likely with aging, have been reported as risk factors for severe COVID - 19 infections 8 9 10 11 12 13. Although not yet shown in relation to severe acute respiratory syndrome Coronavirus 2, which is causal agent of COVID - 19, presence of age - dependent enhancement of severity has been suggested in SARS Coronavirus by analysis of innate immune responses in BALB / c mouse model 14 15 16. Additionally, it has been suggested that antibody - dependent enhancement can contribute to formation of observed age - dependency of severity, as suggested in SARS and Middle East respiratory syndrome cases 17 18 19 20 21 22. Interestingly, age distribution of mortality by COVID - 19, is similar between Italy, Japan, and Spain, even though the number of deaths is quite different between between 23 and 24 25. The The number of deaths was 3 in 0 - 9 years old, 0 in 10 - 19 yo, 11 in 20 - 29 yo, 58 in 30 - 39 yo, 257 in 40 - 49 yo, 1 051 in 50 - 59 yo, 3 107 in 60 - 69 yo, and 25 038 in 70 + yo in Italy as of May 13 2020. In Japan, that was 0 in 0 - 9 yo, 0 in 10 - 19 yo, 0 in 20 - 29 yo, 2 in 30 - 39 yo, 8 in 40 - 49 yo, 16 in 50 - 59 yo, 44 in 60 - 69 yo, and 330 in over 70 + yo as of May 7 2020.

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* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Results

During June - August, COVID - 19 pandemic in the United States affected a larger proportion of younger people than during January - May 2020. Shift toward younger ages occurred in all four US Census Regions, regardless of changes in incidence during this period, and was reflected in COVID - 19 - like illness - related ED visits, positive SARS - CoV - 2 RT - PCR test results, and confirmed COVID - 19 cases. A similar age shift occurs in Europe, where the median age of COVID - 19 cases declined from 54 years during January - May to 39 years during June - July, during which time persons aged 20 - 29 years constitute the largest proportion of cases. Case and laboratory surveillance are based on consistent availability of diagnostic testing to all segments of the population, and changes in testing across age groups could affect age distribution of positive SARS - CoV - 2 test results and confirmed cases. Although testing availability has varied by place, time, and test provider, it IS unlikely that observed age shift results solely from changes in testing availability. First, decline in median age of persons for whom all SARS - CoV - 2 tests were conducted lags behind declines in median age of persons with positive test results and confirmed cases, suggesting that infection patterns drive testing patterns. Second, age distribution of persons for whom all SARS - CoV - 2 tests were conducted shifted toward younger groups from May to June but remained relatively consistent during June - August. Third, percent positivity continued to increase in the face of increased testing volume; this was most evident in HHS Regions 4 and 6 among persons aged 20 - 39 years during early to mid - June. Fourth, median age of persons with COVID - 19 - like illness - related ED visits, which IS not dependent on testing availability, shows similar patterns to those of persons with positive test results and confirmed cases. This report provides preliminary evidence that younger adults contribute to community transmission of COVID - 19 to older adults. Across the southern United States in June 2020, increase in SARS - CoV - 2 infection among younger adults preceded an increase among older adults by 4 - 15 days. Similar observations have been reported by the World Health Organization. * Further investigation of community transmission dynamics across age groups to identify factors that might be driving infection among younger adults and subsequent transmission to older adults IS warrant. These findings have important clinical and public health implications. First, occupational and behavioral factors might put younger adults at higher risk for exposure to SARS - CoV - 2. Younger adults make up a large proportion of workers in frontline occupations and highly exposed industries, where consistent implementation of prevention strategies might be difficult or not possible. In addition, younger adults might also be less likely to follow community mitigation strategies, such as social distancing and avoiding group gatherings. Second, younger adults, WHO are more likely to have mild or no symptoms, can unknowingly contribute to presymptomatic or asymptomatic transmission to others, including to persons at higher risk for severe illness. Finally, SARS - CoV - 2 infection IS not benign in younger adults, especially among those with underlying medical conditions, WHO are at risk for hospitalization, severe illness, and death.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Materials and methods

To understand the background of robust age distribution of mortality with varied R 0, we employ a mathematical model describing transmissions of COVID - 19. Clinical observations suggest that both asymptomatic and symptomatic cases are infectious after the latent period of 48 49, We use a simple age - structured SEIRD model, which can be written as; where S n, E n, I n, R n and D n represent the proportion of susceptible, latent, infectious, recovered and dead among entire population, and subscript index n denote age group. We stratify entire population into eight groups, n = 1 2 3 4 5 6 7, and 8 for < 10 yo, 10 - 19 yo, 20 - 29 yo, 30 - 39 yo, 40 - 49 yo, 50 - 59 yo, 60 - 69 yo, and 70 + yo., K n, m, and represent transmission coefficient, element of contact matrix between age group n and m, progression rate from latent to infectious, recovery rate and mortality rate by COVID - 19 infections, respectively. N denotes susceptibility of age group n. For sake of simplicity, based on short study duration of COVID - 19 epidemics compared to length of human lifespan, births and deaths from causes other than COVID - 19 were ignore. To take into account the effect of behavioral changes outside of the household during outbreak, k n, m is decomposed by matrix for contacts within household k in, nm and that for contacts outside household k out, nm; which denotes a reduced fraction of contacts outside of household. We model age specific susceptibility as where c is susceptibility among age group 1 and constant among all age groups, denoting exponent parameter describing variation of susceptibility among age groups. Increase in means increase in variation of susceptibility among age groups, and = 0 means that susceptibility is equal among all age groups. Model 1 does not classify cases into asymptomatic and symptomatic cases explicitly. If the progression of disease is largely different between asymptomatic and symptomatic cases, estimates using model 1 can be bias. In addition, age - dependency of mortality by COVID - 19 infections is not taken into account. Model 2 takes into account both different progression of disease between asymptomatic and symptomatic cases and age - dependency of mortality by COVID - 19 infections; where I S, n and I, n represent proportion of symptomatic and asymptomatic cases among age group n. Other compartments are same as model 1. F S represents fraction of symptomatic infections among all COVID - 19 cases and n represents mortality rate by COVID - 19 infection among age group n. {matheq}{\gamma }_{s}{endmatheq} and {matheq}{\gamma }_{a}{endmatheq} denote recovery rates among symptomatic and asymptomatic cases. Other parameters are the same as model 1.

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Citation

White House coronavirus advisor Dr. Anthony Fauci debunk online theories promoted by President Donald Trump that the Centers for Disease Control and Prevention has changed its guidance for tallying coronavirus deaths, showing a fraction of total COVID - 19 fatalities. On Sunday, Twitter removed a post retweeted by Trump that claimed the CDC had quietly updated its guidance to indicate only 6% of the country's coronavirus death toll of roughly 9 000 deaths was actually caused by the virus, according to CNN Report. Tweet said the remaining 94% had other serious illnesses. Fauci told ABC Program Good Morning America on Tuesday that CDC guidance, last updated on Aug. 26, indicates that of people who have died from the virus, certain percentage of them had nothing else but just COVID. However, people with underlying illnesses also die from COVID - 19, he say. That does not mean that someone who has hypertension or diabetes who dies of COVID didn't die of COVID - 19. They do, Fauci, director of the National Institute of Allergy and Infectious Diseases, told the Program. So the numbers you 've been hearing - there are 180 000 - plus deaths - are real deaths from COVID - 19. Let not be any confusion about that. It's not 9 000 deaths from COVID - 19, it's 180 - plus - thousand deaths, Fauci say. Cdc's National Center for Health Statistics told CNBC in a statement that death certificates list all possible causes or conditions that lead to a person's death, and there may be more than one list. There were more than 161 300 death certificates that list COVID - 19 among possible causes of death as of Aug. 22, according to NCHS. About 6% of certificates that mention COVID - 19 list it as the sole cause on death certificate. The remaining 94% include other causes alongside COVID - 19. Cdc, however, considers the underlying cause of death as the condition that begins the chain of events that ultimately lead to a person's death, and in 92% of all deaths that mention COVID - 19, virus was listed as the underlying cause of death, Bob Anderson, lead Mortality statistician at NCHS, said in a statement. These data are consistent with CDC guidance that those with underlying medical conditions are at greater risk for severe illness and death from COVID - 19, Anderson say. He says the number of reported deaths, along with other underlying conditions by age group, do not represent new information as NCHS has been publishing this same information since the outset when we began posting data on COVID - 19 deaths on our web site. At least 183 600 people have died from COVID - 19 in the US as of Tuesday, accounting for just more than 21% of the world's total Report deaths, according to data compiled by Johns Hopkins University. People who are older are at greater risk for serious illness, and possibly death, from COVID - 19. Cdc reports that 8 out of 10 COVID - 19 deaths reported in the US are people over 65 years old. The risk is also higher for anyone at any age with underlying health conditions, CDC say.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Significance

T he New Coronavirus IS not an equal - opportunity killer: Being elderly and having other illnesses, for instance, greatly increase the risk of dying from the disease virus cause, COVID - 19. Its also possible being male could put you at increased risk. For both medical and public health reasons, researchers want to figure out who is most at risk of being infected and who is most at risk of developing severe or even lethal illness. With that kind of information, clinicians would know whom to treat more aggressively, government officials would have better idea of steps to take, and everyone would know whether they need to take special, additional precautions. Here is what research has shown three months into the outbreak: vast majority of cases in China 87% were in people ages 30 to 79, China Center for Disease Control report last month based on data from all 72 314 of those diagnosed with COVID - 19 as of Feb. 11. That probably reflects something about biology more than lifestyle, such as being in frequent contact with other people. Teens and people in their 20s also encounter many others, at school and work and on public transit, yet they do seem to be contracting disease at significant rates: only 8. 1% of cases were 20 - somethings 1. 2% were teens, and 0. 9% were 9 or younger. The World Health Organization Mission to China found that 78% of cases reported as of Feb. 20 were in people ages 30 to 69. The Death toll skews old even more strongly. Overall, China CDC find, 2. 3% of confirmed cases die. But the fatality rate was 14. 8% of people 80 or older, likely reflecting the presence of other diseases, weaker IMMUNE system, or simply worse overall health. By contrast, fatality rate was 1. 3% in 50 - somethings, 0. 4% in 40 - somethings, and 0. 2% in people 10 to 39. Age - related death risk probably reflects the strength, or weakness, of the respiratory system. About half of 109 COVID - 19 patients treated at Central Hospital of Wuhan, researchers there report, develop acute respiratory distress syndrome, in which fluid builds up in small air sacs of lungs. That restricts how much air lungs can take in, reducing oxygen supply to vital organs, sometimes fatally; half of ARDS patients die, compared to 9% of patients WHO do not develop syndrome. Ards patients had an average age of 61, compared to an average age of 49 for those WHO did not develop ARDS. Elderly patients were more likely to develop ARDS, researchers write, suggesting how age can make COVID - 19 more severe and even fatal: age increases the risk that the respiratory system will basically shut down under viral assault. Youth, in contrast, seem to be protective. Who Mission reports a relatively low incidence of people under 18, WHO makes up only 2. 4% of all reported cases. In fact, through mid - January, zero children in Wuhan, epicenter of the outbreak, had contracted COVID - 19. It is not clear whether that is because children do not show signs of illness even if infect.

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Period Life Expectancy

Life expectancy declines overstate impact of temporary epidemic mortality. Period life expectancy at birth is a familiar way to summarize mortality in year. In 2017the, most recent year report in detail for United Stateslife expectancy at birth was 78. 86 y, statistic which assumes people live their entire life, from birth to death, under mortality conditions of 2017. However, in the context of epidemic mortality, life expectancy at birth is a misleading indicator, because it implicitly assumes epidemic is experienced each year over and over again as people get older. When we apply the observed average age pattern of COVID - 19 mortality from Fig. 3, we found that 1 million COVID - 19 deaths would produce a life expectancy decline of 2. 94 y. Such a decline would temporarily take the US back to mortality conditions of 1995 when life expectancy was 75. 88 y, 2. 98 y less than 78. 86 in 2017. Same calculation with 250 000 COVID - 19 deaths would produce a decline of 0. 84 y in life expectancy. This decline in life expectancy is somewhat smaller than would be the case if epidemic mortality were exactly proportional to all - cause nonepidemic mortality at all agesthe slightly older ages of death of COVID - 19 deaths reduce impact on life expectancy. To estimate the effect of proportional change in mortality, we can use approximation due to Keyfitz, who show that increasing mortality at all ages causes life expectancy to drop by a factor approximately equal to H, where H is life Table entropy, typically about 0. 15 in low mortality settings. Under Keyfitzs model, 1 million epidemic deaths increasing mortality rates by about 1 / 3 at all ages would lead to a drop in period life expectancy of = 3. 94 y, about 1 y larger than our estimate based on our observed average COVID - 19 mortality schedule.


Introduction

In the past few months, numbers of deaths from novel coronavirus disease 2019 have become part of the daily news cycle world over. Impressive though these numbers are, they may not convey a clear sense of scale and pace of the pandemic. By contrast, declines in life expectancies induced by COVID - 19 mortality provide a simple and intuitive metric. Aggregate indicator of period mortality conditions over Lifespan, period life expectancy at birth is relatively insensitive to mortality changes at older ages. In high - income countries, where mortality at young ages is already low, recent changes in PLEB have been in the order of +. 2 years annually. 1 With the notable exception of periods of armed conflict, 2 declines in PLEB have become rare and similarly modest. In the US, for instance, most recent reversals in annual PLEB gains are. 3 of year decline during opioid - overdose crisis, from 78. 9 to 78. 6 years between 2014 and 2017, and earlier. 3 of year decline, from 75. 8 to 75. 5 years between 1992 and 1993, at the peak of the HIV epidemic. 3 impact of COVID - 19 mortality in 2020 - PLEB can be expected to be substantially larger than those, in the US as well as in a number of Latin American countries. 400 000 COVID - 19 deaths in US by December 31 that University of Washingtons Institute for Health Metrics and Evaluation currently projects would translate into 2020 - PLEB reduction of nearly one - and - ahalf year.S Base on this set of projections, 2020 - PLEB reductions would exceed two - and - ahalf Years in Peru and Ecuador. 4 Moreover, estimates of PLEB reductions are sensitive to the scale of the population and to the length of period they refer to. By averaging out COVID - 19 mortality conditions in least and most affected areas, national figures may conceal large within - country differences, especially in countries spread on large territories like the US, Brazil or Mexico, not to mention China or India. 2020 - PLEB similarly average mortality conditions before first COVID - 19 death and during the most severe months of the pandemic. Estimating PLEB reductions for smaller areas and during shorter periods would thus achieve double objective. First, tracking pandemics at a finer - grained geographical and temporal scale should provide better insights on pandemics than annual, national averages. Second, expected to be several times larger than these averages, estimates of PLEB reductions for most affected areas during the most intense phase of the pandemic may receive more public attention. This is important because public awareness is critical to participation on which mitigating policies depend. Indeed, some estimates of PLEB reductions have reached double - digit figures. 5 6 7 routinely acknowledge but easy to miss limitation of these estimates, however, is that intuitive interpretation of PLEB as a measure of individual Lifespan may no longer apply. Pleb estimates expect age at death of newborn experiencing mortality conditions of reference period during her entire lifetime.


Discussion

Using national case - base surveillance and supplementary data report from 16 jurisdictions, characteristics of > 10 000 decedents with laboratory - confirmed COVID - 19 were describe. More than one third of Hispanic decedents and nearly one third of nonwhite decedents were aged < 65 years, but only 13. 2% of white decedents were aged over 65 years. Consistent with reports describing characteristics of deaths in persons with COVID - 19 in the United States and China, approximately three fourths of decedents had one or more underlying medical conditions reported or were aged 65 years. Among reported underlying medical conditions, cardiovascular disease and diabetes were most common. Diabetes prevalence among decedents aged < 65 years was substantially higher than that reported in analysis of hospitalized COVID - 19 patients aged < 65 years and persons aged < 65 years in the general population. Among decedents aged over 65 years, 7. 8% die in the emergency department or at home; these out - of - hospital deaths might reflect lack of health care access, delays in seeking care, or diagnostic delays. Health communications campaigns could encourage patients, particularly those with underlying medical conditions, to seek medical care earlier in their illnesses. Additionally, health care providers should be encouraged to consider the possibility of severe disease among younger people who are Hispanic, black or have underlying medical conditions. More prompt diagnoses could facilitate earlier implementation of supportive care to minimize morbidity among individuals and earlier isolation of contagious persons to protect communities from SARS - CoV - 2 transmission. Relatively high percentages of Hispanic and nonwhite decedents aged < 65 years were notable. The median age of nonwhite persons in the United States is lower than that of white people. These differences might help explain higher proportions of Hispanic and nonwhite decedents among those aged < 65 years. Median ages among Hispanic and nonwhite decedents were 9 - 10 years lower than that of white decedents. However, percentage of Hispanic decedents aged < 65 years exceeds the percentage of Hispanic persons aged < 65 years in the US population; percentage of nonwhite COVID - 19 decedents aged < 65 years also exceeds the overall percentage of nonwhite decedents aged < 65 years in the US population. Further study is needed to understand the reasons for these differences. It is possible that rates of SARS - CoV - 2 transmission are higher among Hispanic and nonwhite persons aged < 65 years than among white persons; one potential contributing factor is higher percentages of Hispanic and nonwhite persons engage in occupations or essential activities that preclude physical distancing. It is also possible that the COVID - 19 pandemic disproportionately affected communities of younger, nonwhite people during the study period. Although these data do not permit assessment of interactions between race / ethnicity, underlying medical conditions, and nonbiologic factors, further studies to understand and address these racial / ethnic differences are needed to inform targeted efforts to prevent COVID - 19 mortality. Findings in this report are subject to at least five limitations.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

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Loss of Remaining Life

Coronavirus Disease 19, disease resulting from SARS - CoV - 2 infection, is the greatest global health crisis since the 1918 influenza pandemic and has caused significant mortality and morbidity throughout the world as well as severe economic disruption. The COVID - 19 pandemic started in Wuhan, China, with the first reported case on Dec. 8 2019, then rapidly spread throughout Europe. Since then, nearly 40 million cases have been documented world - wide with over 1 million deaths, affecting individual countries to varying degrees. For example, Italy and Spain were profoundly affected, while like South Korea experience substantially less morbidity and mortality. The United States was hit especially hard, experiencing over 20% of world infections and deaths while possessing only 4% of the world population. While differences in population structures, demographics, genetics and mitigation efforts are likely to explain distinct outcomes experience across different countries, some aspects of COVID - 19 are shared across countries. These commonalities include severity and lethality with respect to sex, age and ethnicity. Ethnicity is complicated by socioeconomic status and population density of living circumstances, which is well known to impact incidence of viral infection, for example CMV. Covid - 19 causes significant mortality and morbidity. The clinical course of COVID - 19 is notable for its extreme variability: while some individuals remain entirely asymptomatic, others experience fever, anosmia, diarrhea, severe respiratory distress, pneumonia, cardiac arrhythmia, blood clotting disorders, liver and kidney distress, enhanced cytokine release and death. Some of these infections result in long - lasting disabilities, magnitude of which will only become clear over longer time horizon. Quantifying the impact of the COVID - 19 pandemic is critical for public and policy makers to be properly informed as to the societal cost of pandemic in order to rationally determine how best to minimize social costs of disease. Significant levels of misunderstanding exist about the severity of disease and its lethality. For example, because the great majority of COVID - 19 deaths occur among elderly, false impression that the impact on society from these deaths is minimal may be conveyed since these individuals were closer to natural death. Aside from any troubling ethical implications associated with rationalization of COVID - 19 mortality along these lines, such conclusion is unwarranted for at least two reasons. First, as individuals age, their life expectancies increase too, well beyond life expectancy at birth, which is value most familiar to the general public. Second, significant number of relatively young individuals have also died from COVID - 19 and had decades of remaining life expectancy. Case fatality rates and total mortality are inadequate measures to portray the true impact of disease on the population. In order to provide a better metric for demographic impact of COVID - 19 in the United States, I calculate Potential Years of Life lose for COVID - 19 in the US using most recent death counts stratified for sex and age.

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Conclusion

Data collected in ILINet is used to produce a measure of ILI activity for all 50 States, Puerto Rico, US Virgin Islands, District of Columbia, and New York City and for each core - base statistical area where at least one provider is locate. Mean report percentage of visits due to ILI for the current week is compared with mean report during non - Influenza weeks, and activity levels correspond to the number of standard deviations below, at, or above mean. The number of jurisdictions at each activity level during Week 41 and previous Week are summarized in the table below. Additional information about medically attended Outpatient and emergency department visits For ILI and CLI: Surveillance Methods

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Sources

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

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