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Do not fill this in! == Mortality == {{Main|COVID-19 pandemic|COVID-19 pandemic death rates by country}} Several measures are commonly used to quantify mortality.<ref>{{#invoke:cite book||vauthors=((Centers for Disease Control and Prevention)) |chapter-url=https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section3.html |title=Principles of Epidemiology in Public Health Practice |edition=Third |chapter=Lesson 3: Measures of Risk Section 3: Mortality Frequency Measures |date=May 2012|publisher=U.S. [[Centers for Disease Control and Prevention]] (CDC)|access-date=28 March 2020|archive-date=28 February 2020|archive-url= https://web.archive.org/web/20200228150607/https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section3.html |url-status=live |id=No. SS1978}}</ref> These numbers vary by region and over time and are influenced by the volume of testing, healthcare system quality, treatment options, time since the initial outbreak, and population characteristics such as age, sex, and overall health.<ref>{{#invoke:cite journal ||url=https://ourworldindata.org/covid-mortality-risk |title=What do we know about the risk of dying from COVID-19? |vauthors=Ritchie H, Roser M |date=25 March 2020 |veditors=Chivers T |journal=[[Our World in Data]] |url-status=live |access-date=28 March 2020 |archive-date=28 March 2020 |archive-url=https://web.archive.org/web/20200328192730/https://ourworldindata.org/covid-mortality-risk}}</ref> The [[mortality rate]] reflects the number of deaths within a specific demographic group divided by the population of that demographic group. Consequently, the mortality rate reflects the prevalence as well as the severity of the disease within a given population. Mortality rates are highly correlated to age, with relatively low rates for young people and relatively high rates among the elderly.<ref name="JAMAPedsCOVID19">{{#invoke:cite journal || vauthors = Castagnoli R, Votto M, Licari A, Brambilla I, Bruno R, Perlini S, Rovida F, Baldanti F, Marseglia GL | title = Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in Children and Adolescents: A Systematic Review | journal = JAMA Pediatrics | volume = 174 | issue = 9 | pages = 882β889 | date = September 2020 | pmid = 32320004 | doi = 10.1001/jamapediatrics.2020.1467 | doi-access = free | title-link = doi }}</ref><ref name="Lu Zhang Du Zhang p.">{{#invoke:cite journal || vauthors = Lu X, Zhang L, Du H, Zhang J, Li YY, Qu J, Zhang W, Wang Y, Bao S, Li Y, Wu C, Liu H, Liu D, Shao J, Peng X, Yang Y, Liu Z, Xiang Y, Zhang F, Silva RM, Pinkerton KE, Shen K, Xiao H, Xu S, Wong GW | title = SARS-CoV-2 Infection in Children | journal = The New England Journal of Medicine | volume = 382 | issue = 17 | pages = 1663β1665 | date = April 2020 | pmid = 32187458 | pmc = 7121177 | doi = 10.1056/nejmc2005073 | publisher = Massachusetts Medical Society }}</ref><ref name="pediatrics_tong">{{#invoke:cite journal || vauthors = Dong Y, Mo X, Hu Y, Qi X, Jiang F, Jiang Z, Tong S | title = Epidemiology of COVID-19 Among Children in China | journal = Pediatrics | volume = 145 | issue = 6 | pages = e20200702 | date = June 2020 | pmid = 32179660 | doi = 10.1542/peds.2020-0702 | s2cid = 219118986 | doi-access = free | title-link = doi }}</ref> In fact, one relevant factor of mortality rates is the age structure of the countries' populations. For example, the case fatality rate for COVIDβ19 is lower in India than in the US since India's younger population represents a larger percentage than in the US.<ref name="Dehingia-2021">{{#invoke:cite journal||title=Sex differences in COVID-19 case fatality: do we know enough?|journal=The Lancet. Global Health|vauthors=Dehingia N|year=2021|volume=9|issue=1|pages=e14βe15|doi=10.1016/S2214-109X(20)30464-2|pmid=33160453|pmc=7834645}}</ref> === Case fatality rate === The [[case fatality rate]] (CFR) reflects the number of deaths divided by the number of diagnosed cases within a given time interval. Based on Johns Hopkins University statistics, the global death-to-case ratio is {{Cases in the COVID-19 pandemic|ratio|editlink=|ref=no}} ({{Cases in the COVID-19 pandemic|deaths|editlink=|ref=no}}/{{Cases in the COVID-19 pandemic|confirmed|editlink=|ref=no}}) as of {{Cases in the COVID-19 pandemic|date|editlink=|ref=no}}.{{Cases in the COVID-19 pandemic|ref=yes}} The number varies by region.<ref>{{#invoke:cite journal || vauthors = Lazzerini M, Putoto G | title = COVID-19 in Italy: momentous decisions and many uncertainties | journal = The Lancet. Global Health | volume = 8 | issue = 5 | pages = e641βe642 | date = May 2020 | pmid = 32199072 | pmc = 7104294 | doi = 10.1016/S2214-109X(20)30110-8 }}</ref><ref>{{#invoke:cite journal ||url=https://ourworldindata.org/covid-mortality-risk |title=What do we know about the risk of dying from COVID-19? |journal=Our World in Data |date=5 March 2020 |access-date=28 March 2020 |archive-url=https://web.archive.org/web/20200328192730/https://ourworldindata.org/covid-mortality-risk |archive-date=28 March 2020 |url-status=live| vauthors = Ritchie H, Ortiz-Ospina E, Beltekian D, Mathieu E, Hasell J, MacDonald B, Giattino C, Appel C, RodΓ©s-Guirao L, Roser M }}</ref> <gallery mode="packed" heights=140 > Cumulative confirmed COVID-19 cases.svg|Total confirmed cases over time World map of total confirmed COVID-19 cases per million people.svg|Total confirmed cases of COVIDβ19 per million people<ref>{{#invoke:Cite web||title=Total confirmed cases of COVID-19 per million people |url=https://ourworldindata.org/grapher/total-confirmed-cases-of-covid-19-per-million-people |website=Our World in Data |access-date=21 June 2022 |archive-url=https://web.archive.org/web/20200319163452/https://ourworldindata.org/grapher/total-confirmed-cases-of-covid-19-per-million-people |archive-date=19 March 2020 |url-status=live}}{{update inline|reason=referenced page and the image updated without coordination, archived version obsolete|month=August 2020|date=August 2020}}</ref> Daily and total confirmed COVID-19 deaths, World.svg|Total confirmed deaths over time World map of total confirmed COVID-19 deaths per million people by country.svg|Total confirmed deaths due to COVIDβ19 per million people<ref>{{#invoke:Cite web||title=Cumulative confirmed COVID-19 deaths per million people |url=https://ourworldindata.org/grapher/total-covid-deaths-per-million |website=[[Our World in Data]] }}</ref> </gallery> === Infection fatality rate === A key metric in gauging the severity of COVIDβ19 is the [[infection fatality rate]] (IFR), also referred to as the ''infection fatality ratio'' or ''infection fatality risk''.<ref>{{#invoke:cite journal || vauthors = Mallapaty S | title = How deadly is the coronavirus? Scientists are close to an answer | journal = Nature | volume = 582 | issue = 7813 | pages = 467β468 | date = June 2020 | pmid = 32546810 | doi = 10.1038/d41586-020-01738-2 | s2cid = 219726496 | doi-access = free | title-link = doi | bibcode = 2020Natur.582..467M }}</ref><ref>{{#invoke:cite journal || vauthors = Alwan NA, Burgess RA, Ashworth S, Beale R, Bhadelia N, Bogaert D, Dowd J, Eckerle I, Goldman LR, Greenhalgh T, Gurdasani D, Hamdy A, Hanage WP, Hodcroft EB, Hyde Z, Kellam P, Kelly-Irving M, Krammer F, Lipsitch M, McNally A, McKee M, Nouri A, Pimenta D, Priesemann V, Rutter H, Silver J, Sridhar D, Swanton C, Walensky RP, Yamey G, Ziauddeen H | title = Scientific consensus on the COVID-19 pandemic: we need to act now | journal = Lancet | volume = 396 | issue = 10260 | pages = e71βe72 | date = October 2020 | pmid = 33069277 | pmc = 7557300 | doi = 10.1016/S0140-6736(20)32153-X }}</ref><ref>{{#invoke:cite journal || vauthors = Meyerowitz-Katz G, Merone L | title = A systematic review and meta-analysis of published research data on COVID-19 infection fatality rates | journal = International Journal of Infectious Diseases | volume = 101 | pages = 138β148 | date = December 2020 | pmid = 33007452 | pmc = 7524446 | doi = 10.1016/j.ijid.2020.09.1464 }}</ref> This metric is calculated by dividing the total number of deaths from the disease by the total number of infected individuals; hence, in contrast to the [[case fatality rate|CFR]], the IFR incorporates asymptomatic and undiagnosed infections as well as reported cases.<ref name="urlGeneralized trapezoidal ogive curves for fatality rate modeling">{{#invoke:cite journal || vauthors = Zhang D, Hu M, Ji Q | title = Financial markets under the global pandemic of COVID-19 | journal = Finance Research Letters | volume = 36 | pages = 101528 | date = October 2020 | pmc = 7402242 | doi = 10.1016/j.csfx.2020.100043 | pmid = 32837360 | bibcode = 2020CSFX....500043D }}</ref> ==== Estimates ==== [[File:Graph of Covid-19 Infection Fatality Ratio by age.png|thumb|The red line shows the estimate of infection fatality rate (IFR), in percentage terms, as a function of age. The shaded region depicts the 95% confidence interval for that estimate. Markers denotes specific observations used in the meta-analysis.<ref name="EJE_levinetal" />]] [[File:Log Graph of Covid-19 Infection Fatality Ratio by age.png|thumb|The same relationship plotted on a log scale]] A December 2020 systematic review and meta-analysis estimated that population IFR during the first wave of the pandemic was about 0.5% to 1% in many locations (including France, Netherlands, New Zealand, and Portugal), 1% to 2% in other locations (Australia, England, Lithuania, and Spain), and exceeded 2% in Italy.<ref name="EJE_levinetal">{{#invoke:cite journal || vauthors = Levin AT, Hanage WP, Owusu-Boaitey N, Cochran KB, Walsh SP, Meyerowitz-Katz G | title = Assessing the age specificity of infection fatality rates for COVID-19: systematic review, meta-analysis, and public policy implications | journal = European Journal of Epidemiology | volume = 35 | issue = 12 | pages = 1123β1138 | date = December 2020 | pmid = 33289900 | pmc = 7721859 | doi = 10.1007/s10654-020-00698-1 | doi-access = free | title-link = doi }} [[File:CC BY icon.svg|50px]] Text was copied from this source, which is available under a [https://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International License] {{Webarchive|url=https://web.archive.org/web/20171016050101/https://creativecommons.org/licenses/by/4.0/ |date=16 October 2017 }}.</ref> That study also found that most of these differences in IFR reflected corresponding differences in the age composition of the population and age-specific infection rates; in particular, the metaregression estimate of IFR is very low for children and younger adults (e.g., 0.002% at age 10 and 0.01% at age 25) but increases progressively to 0.4% at age 55, 1.4% at age 65, 4.6% at age 75, and 15% at age 85.<ref name="EJE_levinetal" /> These results were also highlighted in a December 2020 report issued by the WHO.<ref>{{#invoke:cite journal||title=Background paper on Covid-19 disease and vaccines: prepared by the Strategic Advisory Group of Experts (SAGE) on immunization working group on COVID-19 vaccines|date=22 December 2020|url=https://apps.who.int/iris/handle/10665/338095|website=World Health Organization|hdl=10665/338095 | author =World Health Organization }}</ref> {| class="wikitable" |+class="nowrap"|IFR estimate per age group<br />(to December 2020)<ref name="EJE_levinetal" /> !Age group !IFR |- |0β34 |0.004% |- |35β44 |0.068% |- |45β54 |0.23% |- |55β64 |0.75% |- |65β74 |2.5% |- |75β84 |8.5% |- |85β+ |28.3% |} An analysis of those IFR rates indicates that COVID{{nbhyph}}19 is hazardous not only for the elderly but also for middle-aged adults, for whom the infection fatality rate of COVID-19 is two orders of magnitude greater than the annualised risk of a fatal automobile accident and far more dangerous than seasonal [[influenza]].<ref name="EJE_levinetal" /> ==== Earlier estimates of IFR ==== At an early stage of the pandemic, the World Health Organization reported estimates of IFR between 0.3% and 1%.<ref>{{#invoke:Cite web||title=Coronavirus disease 2019 (COVID-19) Situation Report β 30 |url=https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200219-sitrep-30-covid-19.pdf |access-date=3 June 2020 |date=19 February 2020}}</ref><ref>{{#invoke:Cite web||title=Coronavirus disease 2019 (COVID-19) Situation Report β 31 |url=https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200220-sitrep-31-covid-19.pdf |access-date=23 April 2020 |date=20 February 2020}}</ref> On 2{{spaces}}July, The WHO's chief scientist reported that the average IFR estimate presented at a two-day WHO expert forum was about 0.6%.<ref name="NYT-20200704dm">{{#invoke:cite news || vauthors = McNeil Jr DG |title=The Pandemic's Big Mystery: How Deadly Is the Coronavirus? β Even with more than 500,000 dead worldwide, scientists are struggling to learn how often the virus kills. Here's why |url=https://www.nytimes.com/2020/07/04/health/coronavirus-death-rate.html |archive-url=https://web.archive.org/web/20200704152005/https://www.nytimes.com/2020/07/04/health/coronavirus-death-rate.html |archive-date=4 July 2020 |url-access=subscription |url-status=live |date=4 July 2020 |work=The New York Times |access-date=6 July 2020}}</ref><ref>{{#invoke:cite news ||title=Global Research and Innovation Forum on COVID-19: Virtual Press Conference |url=https://www.who.int/docs/default-source/coronaviruse/virtual-press-conference---2-july---update-on-covid-19-r-d.pdf |publisher=World Health Organization |date=2 July 2020}}</ref> In August, the WHO found that studies incorporating data from broad serology testing in Europe showed IFR estimates converging at approximately 0.5β1%.<ref>{{#invoke:Cite web||title=Estimating mortality from COVID-19|url=https://www.who.int/news-room/commentaries/detail/estimating-mortality-from-covid-19|access-date=21 September 2020|website=[[World Health Organization]] (WHO)}}</ref> Firm lower limits of IFRs have been established in a number of locations such as New York City and Bergamo in Italy since the IFR cannot be less than the population fatality rate. (After sufficient time however, people can get reinfected).<ref>{{#invoke:cite journal|| vauthors = Shaffer C |date=23 October 2021|title=Covid-19 still rife in Iran |journal=New Scientist|volume=252|issue=3357|pages=10β11|doi=10.1016/S0262-4079(21)01865-0|pmid=34720322|issn=0262-4079|pmc=8536311|bibcode=2021NewSc.252...10S}}</ref> As of 10 July, in New York City, with a population of 8.4 million, 23,377 individuals (18,758 confirmed and 4,619 probable) have died with COVIDβ19 (0.3% of the population).<ref>{{#invoke:Cite web||title=COVID-19: Data |url=https://www1.nyc.gov/site/doh/covid/covid-19-data.page |publisher=City of New York}}</ref> Antibody testing in New York City suggested an IFR of β0.9%,<ref>{{#invoke:cite SSRN||title=SARS-CoV-2, COVID-19, Infection Fatality Rate (IFR) Implied by the Serology, Antibody, Testing in New York City| vauthors = Wilson L |date=May 2020|ssrn=3590771}}</ref> and β1.4%.<ref>{{#invoke:cite journal || vauthors = Yang W, Kandula S, Huynh M, Greene SK, Van Wye G, Li W, Chan HT, McGibbon E, Yeung A, Olson D, Fine A, Shaman J | title = Estimating the infection-fatality risk of SARS-CoV-2 in New York City during the spring 2020 pandemic wave: a model-based analysis | journal = The Lancet. Infectious Diseases | volume = 21 | issue = 2 | pages = 203β212 | date = February 2021 | pmid = 33091374 | pmc = 7572090 | doi = 10.1016/s1473-3099(20)30769-6 }}</ref> In [[Province of Bergamo|Bergamo province]], 0.6% of the population has died.<ref>{{#invoke:Cite web||url=https://medium.com/bccp-uc-berkeley/how-deadly-is-covid-19-data-science-offers-answers-from-italy-mortality-data-58abedf824cf|title=How deadly is COVID-19? Data Science offers answers from Italy mortality data.| vauthors = Modi C |date=21 April 2020 |website=Medium |access-date=23 April 2020}}</ref> In September 2020, the U.S. [[Centers for Disease Control and Prevention]] (CDC) reported preliminary estimates of age-specific IFRs for public health planning purposes.<ref>{{#invoke:Cite web||title=Coronavirus Disease 2019 (COVID-19) |url=https://www.cdc.gov/coronavirus/2019-ncov/hcp/planning-scenarios.html |website=U.S. [[Centers for Disease Control and Prevention]] (CDC) |access-date=9 December 2020 |date=10 September 2020}}</ref> === Sex differences === {{Main|Gendered impact of the COVID-19 pandemic}} {| class="wikitable collapsible collapsed" style="margin-left:1em; font-size: 90%; float:right; clear:right" |+ class="nowrap" | Estimated prognosis by age and sex<br />based on cases from [[COVID-19 pandemic in France|France]]<br />and [[COVID-19 pandemic on Diamond Princess|Diamond Princess ship]]<ref>{{#invoke:cite journal || vauthors = Salje H, Tran Kiem C, Lefrancq N, Courtejoie N, Bosetti P, Paireau J, Andronico A, HozΓ© N, Richet J, Dubost CL, Le Strat Y, Lessler J, Levy-Bruhl D, Fontanet A, Opatowski L, Boelle PY, Cauchemez S | title = Estimating the burden of SARS-CoV-2 in France | journal = Science | volume = 369 | issue = 6500 | pages = 208β211 | date = July 2020 | pmid = 32404476 | pmc = 7223792 | doi = 10.1126/science.abc3517 | title-link = doi | doi-access = free | bibcode = 2020Sci...369..208S }}</ref> |- !colspan="10| Percentage of infected people who are hospitalised |- ! ! 0β19 ! 20β29 ! 30β39 ! 40β49 ! 50β59 ! 60β69 ! 70β79 ! 80+ ! Total |- ! Female |{{shade|0.1}}<br /><small>(0.07β0.2)</small> |{{shade|0.5}}<br /><small>(0.3β0.8)</small> |{{shade|0.9}}<br /><small>(0.5β1.5)</small> |{{shade|1.3}}<br /><small>(0.7β2.1)</small> |{{shade|2.6}}<br /><small>(1.5β4.2)</small> |{{shade|5.1}}<br /><small>(2.9β8.3)</small> |{{shade|7.8}}<br /><small>(4.4β12.8)</small> |{{shade|19.3}}<br /><small>(10.9β31.6)</small> |{{shade|2.6}}<br /><small>(1.5β4.3)</small> |- ! Male |{{shade|0.2}}<br /><small>(0.08β0.2)</small> |{{shade|0.6}}<br /><small>(0.3β0.9)</small> |{{shade|1.2}}<br /><small>(0.7β1.9)</small> |{{shade|1.6}}<br /><small>(0.9β2.6)</small> |{{shade|3.2}}<br /><small>(1.8β5.2)</small> |{{shade|6.7}}<br /><small>(3.7β10.9)</small> |{{shade|11.0}}<br /><small>(6.2β17.9)</small> |{{shade|37.6}}<br /><small>(21.1β61.3)</small> |{{shade|3.3}}<br /><small>(1.8β5.3)</small> |- ! Total |{{shade|0.1}}<br /><small>(0.08β0.2)</small> |{{shade|0.5}}<br /><small>(0.3β0.8)</small> |{{shade|1.1}}<br /><small>(0.6β1.7)</small> |{{shade|1.4}}<br /><small>(0.8β2.3)</small> |{{shade|2.9}}<br /><small>(1.6β4.7)</small> |{{shade|5.8}}<br /><small>(3.3β9.5)</small> |{{shade|9.3}}<br /><small>(5.2β15.1)</small> |{{shade|26.2}}<br /><small>(14.8β42.7)</small> |{{shade|2.9}}<br /><small>(1.7β4.8)</small> |- !colspan="10| Percentage of hospitalised people who go to Intensive Care Unit |- ! ! 0β19 ! 20β29 ! 30β39 ! 40β49 ! 50β59 ! 60β69 ! 70β79 ! 80+ ! Total |- ! Female |{{shade|16.7}}<br /><small>(14.3β19.3)</small> |{{shade|8.7}}<br /><small>(7.5β9.9)</small> |{{shade|11.9}}<br /><small>(10.9β13.0)</small> |{{shade|16.6}}<br /><small>(15.6β17.7)</small> |{{shade|20.7}}<br /><small>(19.8β21.6)</small> |{{shade|23.1}}<br /><small>(22.2β24.0)</small> |{{shade|18.7}}<br /><small>(18.0β19.5)</small> |{{shade|4.2}}<br /><small>(4.0β4.5)</small> |{{shade|14.3}}<br /><small>(13.9β14.7)</small> |- ! Male |{{shade|26.9}}<br /><small>(23.1β31.1)</small> |{{shade|14.0}}<br /><small>(12.2β16.0)</small> |{{shade|19.2}}<br /><small>(17.6β20.9)</small> |{{shade|26.9}}<br /><small>(25.4β28.4)</small> |{{shade|33.4}}<br /><small>(32.0β34.8)</small> |{{shade|37.3}}<br /><small>(36.0β38.6)</small> |{{shade|30.2}}<br /><small>(29.1β31.3)</small> |{{shade|6.8}}<br /><small>(6.5β7.2)</small> |{{shade|23.1}}<br /><small>(22.6β23.6)</small> |- ! Total |{{shade|22.2}}<br /><small>(19.1β25.7)</small> |{{shade|11.6}}<br /><small>(10.1β13.2)</small> |{{shade|15.9}}<br /><small>(14.5β17.3)</small> |{{shade|22.2}}<br /><small>(21.0β23.5)</small> |{{shade|27.6}}<br /><small>(26.5β28.7)</small> |{{shade|30.8}}<br /><small>(29.8β31.8)</small> |{{shade|24.9}}<br /><small>(24.1β25.8)</small> |{{shade|5.6}}<br /><small>(5.3β5.9)</small> |{{shade|19.0}}<br /><small>(18.7β19.44)</small> |- !colspan="10| Percent of hospitalised people who die |- ! ! 0β19 ! 20β29 ! 30β39 ! 40β49 ! 50β59 ! 60β69 ! 70β79 ! 80+ ! Total |- ! Female |{{shade|0.5}}<br /><small>(0.2β1.0)</small> |{{shade|0.9}}<br /><small>(0.5β1.3)</small> |{{shade|1.5}}<br /><small>(1.2β1.9)</small> |{{shade|2.6}}<br /><small>(2.3β3.0)</small> |{{shade|5.2}}<br /><small>(4.8β5.6)</small> |{{shade|10.1}}<br /><small>(9.5β10.6)</small> |{{shade|16.7}}<br /><small>(16.0β17.4)</small> |{{shade|25.2}}<br /><small>(24.4β26.0)</small> |{{shade|14.4}}<br /><small>(14.0β14.8)</small> |- ! Male |{{shade|0.7}}<br /><small>(0.3β1.5)</small> |{{shade|1.3}}<br /><small>(0.8β1.9)</small> |{{shade|2.2}}<br /><small>(1.7β2.7)</small> |{{shade|3.8}}<br /><small>(3.3β4.4)</small> |{{shade|7.6}}<br /><small>(7.0β8.2)</small> |{{shade|14.8}}<br /><small>(14.1β15.6)</small> |{{shade|24.6}}<br /><small>(23.7β25.6)</small> |{{shade|37.1}}<br /><small>(36.1β38.2)</small> |{{shade|21.2}}<br /><small>(20.8β21.7)</small> |- ! Total |{{shade|0.6}}<br /><small>(0.2β1.3)</small> |{{shade|1.1}}<br /><small>(0.7β1.6)</small> |{{shade|1.9}}<br /><small>(1.5β2.3)</small> |{{shade|3.3}}<br /><small>(2.9β3.8)</small> |{{shade|6.5}}<br /><small>(6.0β7.0)</small> |{{shade|12.6}}<br /><small>(12.0β13.2)</small> |{{shade|21.0}}<br /><small>(20.3β21.7)</small> |{{shade|31.6}}<br /><small>(30.9β32.4)</small> |{{shade|18.1}}<br /><small>(17.8β18.4)</small> |- !colspan="10| Percent of infected people who die{{snd}}infection fatality rate (IFR) |- ! ! 0β19 ! 20β29 ! 30β39 ! 40β49 ! 50β59 ! 60β69 ! 70β79 ! 80+ ! Total |- ! Female |{{shade|0.001}}<br /><small>(<0.001β0.002)</small> |{{shade|0.004}}<br /><small>(0.002β0.007)</small> |{{shade|0.01}}<br /><small>(0.007β0.02)</small> |{{shade|0.03}}<br /><small>(0.02β0.06)</small> |{{shade|0.1}}<br /><small>(0.08β0.2)</small> |{{shade|0.5}}<br /><small>(0.3β0.8)</small> |{{shade|1.3}}<br /><small>(0.7β2.1)</small> |{{shade|4.9}}<br /><small>(2.7β8.0)</small> |{{shade|0.4}}<br /><small>(0.2β0.6)</small> |- ! Male |{{shade|0.001}}<br /><small>(<0.001β0.003)</small> |{{shade|0.007}}<br /><small>(0.003β0.01)</small> |{{shade|0.03}}<br /><small>(0.02β0.05)</small> |{{shade|0.06}}<br /><small>(0.03β0.1)</small> |{{shade|0.2}}<br /><small>(0.1β0.4)</small> |{{shade|1.0}}<br /><small>(0.6β1.6)</small> |{{shade|2.7}}<br /><small>(1.5β1.4)</small> |{{shade|14.0}}<br /><small>(7.9β22.7)</small> |{{shade|0.7}}<br /><small>(0.4β1.1)</small> |- ! Total |{{shade|0.001}}<br /><small>(<0.001β0.002)</small> |{{shade|0.005}}<br /><small>(0.003β0.01)</small> |{{shade|0.02}}<br /><small>(0.01β0.03)</small> |{{shade|0.05}}<br /><small>(0.03β0.08)</small> |{{shade|0.2}}<br /><small>(0.1β0.3)</small> |{{shade|0.7}}<br /><small>(0.4β1.2)</small> |{{shade|1.9}}<br /><small>(1.1β3.2)</small> |{{shade|8.3}}<br /><small>(4.7β13.5)</small> |{{shade|0.5}}<br /><small>(0.3β0.9)</small> |- |colspan=10| Numbers in parentheses are 95% [[credible interval]]s for the estimates. |} COVIDβ19 [[case fatality rate]]s are higher among men than women in most countries. However, in a few countries like India, Nepal, Vietnam, and Slovenia the fatality cases are higher in women than men.<ref name="Dehingia-2021" /> Globally, men are more likely to be admitted to the [[Intensive care unit|ICU]] and more likely to die.<ref>{{#invoke:Cite web|| vauthors = McIntosh K |title=Covid 19 Clinical Features|url=https://www.uptodate.com/contents/covid-19-clinical-features|access-date=12 May 2021|website=[[UpToDate]]|publication-date=April 2021}}</ref><ref>{{#invoke:cite journal || vauthors = Peckham H, de Gruijter NM, Raine C, Radziszewska A, Ciurtin C, Wedderburn LR, Rosser EC, Webb K, Deakin CT | title = Male sex identified by global COVID-19 meta-analysis as a risk factor for death and ITU admission | journal = Nature Communications | volume = 11 | issue = 1 | pages = 6317 | date = December 2020 | pmid = 33298944 | doi = 10.1038/s41467-020-19741-6 | pmc = 7726563 | bibcode = 2020NatCo..11.6317P }}</ref> One meta-analysis found that globally, men were more likely to get COVIDβ19 than women; there were approximately 55 men and 45 women per 100 infections ([[Confidence interval|CI]]: 51.43β56.58).<ref>{{#invoke:cite journal || vauthors = Abate BB, Kassie AM, Kassaw MW, Aragie TG, Masresha SA | title = Sex difference in coronavirus disease (COVID-19): a systematic review and meta-analysis | journal = BMJ Open | volume = 10 | issue = 10 | pages = e040129 | date = October 2020 | pmid = 33028563 | doi = 10.1136/bmjopen-2020-040129 | pmc = 7539579 }}</ref> The [[Chinese Center for Disease Control and Prevention]] reported the death rate was 2.8% for men and 1.7% for women.<ref name="Epidemiology17Feb2020"/> Later reviews in June 2020 indicated that there is no significant difference in susceptibility or in CFR between genders.<ref>{{#invoke:cite journal || vauthors = Hu Y, Sun J, Dai Z, Deng H, Li X, Huang Q, Wu Y, Sun L, Xu Y | title = Prevalence and severity of corona virus disease 2019 (COVID-19): A systematic review and meta-analysis | journal = Journal of Clinical Virology | volume = 127 | pages = 104371 | date = June 2020 | pmid = 32315817 | pmc = 7195434 | doi = 10.1016/j.jcv.2020.104371 }}</ref><ref>{{#invoke:cite journal || vauthors = Fu L, Wang B, Yuan T, Chen X, Ao Y, Fitzpatrick T, Li P, Zhou Y, Lin YF, Duan Q, Luo G, Fan S, Lu Y, Feng A, Zhan Y, Liang B, Cai W, Zhang L, Du X, Li L, Shu Y, Zou H | title = Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: A systematic review and meta-analysis | journal = The Journal of Infection | volume = 80 | issue = 6 | pages = 656β665 | date = June 2020 | pmid = 32283155 | pmc = 7151416 | doi = 10.1016/j.jinf.2020.03.041 }}</ref> One review acknowledges the different mortality rates in Chinese men, suggesting that it may be attributable to lifestyle choices such as smoking and drinking alcohol rather than genetic factors.<ref>{{#invoke:cite journal || vauthors = Yuki K, Fujiogi M, Koutsogiannaki S | title = COVID-19 pathophysiology: A review | journal = Clinical Immunology | volume = 215 | pages = 108427 | date = June 2020 | pmid = 32325252 | pmc = 7169933 | doi = 10.1016/j.clim.2020.108427 | s2cid = 216028003 }}</ref> Smoking, which in some countries like China is mainly a male activity, is a habit that contributes to increasing significantly the case fatality rates among men.<ref name="Dehingia-2021" /> Sex-based immunological differences, lesser prevalence of smoking in women and men developing co-morbid conditions such as hypertension at a younger age than women could have contributed to the higher mortality in men.<ref name="nyt-italy">{{#invoke:cite news || vauthors = Rabin RC | title = In Italy, Coronavirus Takes a Higher Toll on Men |url=https://www.nytimes.com/2020/03/20/health/coronavirus-italy-men-risk.html |archive-url=https://web.archive.org/web/20200320214013/https://www.nytimes.com/2020/03/20/health/coronavirus-italy-men-risk.html |archive-date=20 March 2020 |url-access=subscription |url-status=live |access-date=7 April 2020 |work=The New York Times |date=20 March 2020}}</ref> In Europe as of February 2020, 57% of the infected people were men and 72% of those died with COVIDβ19 were men.<ref>{{#invoke:Cite web||title=COVID-19 weekly surveillance report |url=https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/weekly-surveillance-report |archive-url=https://web.archive.org/web/20200315074508/https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/weekly-surveillance-report |url-status=dead |archive-date=15 March 2020 |website=[[World Health Organization]] (WHO) |access-date=7 April 2020}}</ref> As of April 2020, the US government is not tracking sex-related data of COVIDβ19 infections.<ref name="nytimesus">{{#invoke:cite news || vauthors = Gupta AH | title = Does Covid-19 Hit Women and Men Differently? U.S. Isn't Keeping Track |url=https://www.nytimes.com/2020/04/03/us/coronavirus-male-female-data-bias.html |archive-url=https://web.archive.org/web/20200403135013/https://www.nytimes.com/2020/04/03/us/coronavirus-male-female-data-bias.html |archive-date=3 April 2020 |url-access=subscription |url-status=live |access-date=7 April 2020 |work=The New York Times |date=3 April 2020}}</ref> Research has shown that viral illnesses like Ebola, HIV, influenza and SARS affect men and women differently.<ref name="nytimesus" /> === Ethnic differences === In the US, a greater proportion of deaths due to COVIDβ19 have occurred among African Americans and other minority groups.<ref name="AVD">{{#invoke:cite journal || vauthors = Dorn AV, Cooney RE, Sabin ML | title = COVID-19 exacerbating inequalities in the US | journal = Lancet | volume = 395 | issue = 10232 | pages = 1243β1244 | date = April 2020 | pmid = 32305087 | pmc = 7162639 | doi = 10.1016/S0140-6736(20)30893-X }}</ref> Structural factors that prevent them from practising social distancing include their concentration in crowded substandard housing and in "essential" occupations such as retail grocery workers, public transit employees, health-care workers and custodial staff. Greater prevalence of lacking [[health insurance]] and care of underlying conditions such as [[diabetes]],<ref name="Shauly-Aharonov-2021">{{#invoke:cite journal ||last1=Shauly-Aharonov |first1=Michal |last2=Shafrir |first2=Asher |last3=Paltiel |first3=Ora |last4=Calderon-Margalit |first4=Ronit |last5=Safadi |first5=Rifaat |last6=Bicher |first6=Roee |last7=Barenholz-Goultschin |first7=Orit |last8=Stokar |first8=Joshua |date=22 July 2021 |title=Both high and low pre-infection glucose levels associated with increased risk for severe COVID-19: New insights from a population-based study |journal=PLOS ONE |volume=16 |issue=7 |pages=e0254847 |doi=10.1371/journal.pone.0254847 |issn=1932-6203 |pmc=8297851 |pmid=34293038|bibcode=2021PLoSO..1654847S |doi-access=free }}</ref> hypertension, and [[heart disease]] also increase their risk of death.<ref>{{#invoke:cite journal || vauthors = Adams ML, Katz DL, Grandpre J | title = Population-Based Estimates of Chronic Conditions Affecting Risk for Complications from Coronavirus Disease, United States | journal = Emerging Infectious Diseases | volume = 26 | issue = 8 | pages = 1831β1833 | date = August 2020 | pmid = 32324118 | pmc = 7392427 | doi = 10.3201/eid2608.200679 | title-link = doi | doi-access = free }}</ref> Similar issues affect [[Indigenous peoples of the Americas|Native American]] and [[Latino (demonym)|Latino]] communities.<ref name="AVD" /> On the one hand, in the Dominican Republic there is a clear example of both gender and ethnic inequality. In this Latin American territory, there is great inequality and precariousness that especially affects Dominican women, with greater emphasis on those of Haitian descent.<ref name="Batthyany-2020">{{#invoke:Cite web|| vauthors = BatthyΓ‘ny K |title=Coronavirus y Desigualdades preexistentes: GΓ©nero y Cuidados|url=https://www.clacso.org/coronavirus-y-desigualdades-preexistentes-genero-y-cuidados/|access-date=22 April 2021|website=CLACSO (Consejo Latinoamericano de Ciencias Sociales)|date=13 October 2020}}</ref> According to a US health policy non-profit, 34% of American Indian and Alaska Native People (AIAN) non-elderly adults are at risk of serious illness compared to 21% of white non-elderly adults.<ref>{{#invoke:Cite web||url=https://www.kff.org/coronavirus-covid-19/issue-brief/covid-19-presents-significant-risks-for-american-indian-and-alaska-native-people/|title=COVID-19 Presents Significant Risks for American Indian and Alaska Native People|date=14 May 2020}}</ref> The source attributes it to disproportionately high rates of many health conditions that may put them at higher risk as well as living conditions like lack of access to clean water.<ref>{{#invoke:Cite web||title=COVID-19 Presents Significant Risks for American Indian and Alaska Native People|url=https://www.kff.org/coronavirus-covid-19/issue-brief/covid-19-presents-significant-risks-for-american-indian-and-alaska-native-people/|date=14 May 2020}}</ref> Leaders have called for efforts to research and address the disparities.<ref>{{#invoke:cite journal || vauthors = Laurencin CT, McClinton A | title = The COVID-19 Pandemic: a Call to Action to Identify and Address Racial and Ethnic Disparities | journal = Journal of Racial and Ethnic Health Disparities | volume = 7 | issue = 3 | pages = 398β402 | date = June 2020 | pmid = 32306369 | pmc = 7166096 | doi = 10.1007/s40615-020-00756-0 }}</ref> In the UK, a greater proportion of deaths due to COVIDβ19 have occurred in those of a [[Black British people|Black]], [[British Asian|Asian]], and other ethnic minority background.<ref>{{#invoke:Cite web||date=9 June 2020|title=How coronavirus deaths in the UK compare by race and ethnicity|url=https://www.independent.co.uk/news/uk/home-news/coronavirus-death-toll-uk-race-white-black-asian-bame-ethnicity-cases-a9557076.html|access-date=10 June 2020|website=The Independent}}</ref><ref>{{#invoke:Cite web||title=Emerging findings on the impact of COVID-19 on black and minority ethnic people|url=https://www.health.org.uk/news-and-comment/charts-and-infographics/emerging-findings-on-the-impact-of-covid-19-on-black-and-min|access-date=10 June 2020|publisher=The Health Foundation}}</ref><ref>{{#invoke:cite news || vauthors = Butcher B, Massey J |date=9 June 2020|title=Why are more BAME people dying from coronavirus?|work=BBC News |url=https://www.bbc.com/news/uk-52219070 |access-date=10 June 2020}}</ref> More severe impacts upon patients including the relative incidence of the necessity of hospitalisation requirements, and vulnerability to the disease has been associated via DNA analysis to be expressed in genetic variants at chromosomal region 3, features that are associated with European [[Neanderthal]] heritage. That structure imposes greater risks that those affected will develop a more severe form of the disease.<ref name=Neanderthal>{{#invoke:Cite web|| title=The ancient Neanderthal hand in severe COVID-19 | website=ScienceDaily | date=30 September 2020 | url=https://www.sciencedaily.com/releases/2020/09/200930094758.htm | access-date=13 December 2020}}</ref> The findings are from Professor Svante PÀÀbo and researchers he leads at the [[Max Planck Institute for Evolutionary Anthropology]] and the [[Karolinska Institutet]].<ref name=Neanderthal /> This admixture of modern human and Neanderthal genes is estimated to have occurred roughly between 50,000 and 60,000 years ago in Southern Europe.<ref name=Neanderthal /> === Comorbidities === [[biology|Biological]] factors (immune response) and the general behaviour (habits) can strongly determine the consequences of COVIDβ19.<ref name="Dehingia-2021" /> Most of those who die of COVIDβ19 have [[pre-existing condition|pre-existing (underlying) conditions]], including hypertension, [[diabetes mellitus]],<ref name="Shauly-Aharonov-2021" /> and [[cardiovascular disease]].<ref name="WHO-2020a">{{#invoke:Cite web||url=https://www.who.int/dg/speeches/detail/who-director-general-s-statement-on-the-advice-of-the-ihr-emergency-committee-on-novel-coronavirus |title=WHO Director-General's statement on the advice of the IHR Emergency Committee on Novel Coronavirus |website=[[World Health Organization]] (WHO)}}</ref> According to March data from the United States, 89% of those hospitalised had preexisting conditions.<ref>{{#invoke:cite journal || vauthors = Garg S, Kim L, Whitaker M, O'Halloran A, Cummings C, Holstein R, Prill M, Chai SJ, Kirley PD, Alden NB, Kawasaki B, Yousey-Hindes K, Niccolai L, Anderson EJ, Openo KP, Weigel A, Monroe ML, Ryan P, Henderson J, Kim S, Como-Sabetti K, Lynfield R, Sosin D, Torres S, Muse A, Bennett NM, Billing L, Sutton M, West N, Schaffner W, Talbot HK, Aquino C, George A, Budd A, Brammer L, Langley G, Hall AJ, Fry A | title = Hospitalization Rates and Characteristics of Patients Hospitalized with Laboratory-Confirmed Coronavirus Disease 2019 β COVID-NET, 14 States, March 1β30, 2020 | journal = MMWR. Morbidity and Mortality Weekly Report | volume = 69 | issue = 15 | pages = 458β464 | date = April 2020 | pmid = 32298251 | pmc = 7755063 | doi = 10.15585/mmwr.mm6915e3 | title-link = doi | doi-access = free }}</ref> The Italian Istituto Superiore di SanitΓ reported that out of 8.8% of deaths where [[medical record|medical charts]] were available, 96.1% of people had at least one [[comorbidity]] with the average person having 3.4 diseases.<ref name="ISSCharacteristics">{{#invoke:cite report||url=https://www.epicentro.iss.it/en/coronavirus/bollettino/Report-COVID-2019_22_July_2020.pdf|title=Characteristics of SARS-CoV-2 patients dying in Italy Report based on available data on July 22nd, 2020|date=22 July 2020|publisher=[[Istituto Superiore di SanitΓ ]]|access-date=4 October 2020|vauthors=Palmieri L, Andrianou X, Barbariol P, Bella A, Bellino S, Benelli E, Bertinato L, Boros S, Brambilla G, Calcagnini G, Canevelli M, Castrucci MR, Censi F, Ciervo A, Colaizzo E, D'Ancona F, Del Manso M, Donfrancesco C, Fabiani M, Filia A, Floridia M, Giuliano M, Grisetti T, Langer M, Lega I, Lo Noce C, Maiozzi P, Malchiodi Albedi F, Manno V, Martini M, Mateo Urdiales A, Mattei E, Meduri C, Meli P, Minelli G, Nebuloni M, NisticΓ² L, Nonis M, Onder G, Palmisano L, Petrosillo N, Pezzotti P, Pricci F, Punzo O, Puro V, Raparelli V, Rezza G, Riccardo F, Rota MC, Salerno P, Serra D, Siddu A, Stefanelli P, Tamburo De Bella M, Tiple D, Unim B, Vaianella L, Vanacore N, Vichi M, Villani ER, Brusaferro S}}</ref> According to this report the most common comorbidities are hypertension (66% of deaths), [[type 2 diabetes]] (29.8% of deaths), [[ischemic heart disease|ischaemic heart disease]] (27.6% of deaths), [[atrial fibrillation]] (23.1% of deaths) and [[chronic renal failure]] (20.2% of deaths). Most critical respiratory comorbidities according to the US [[Centers for Disease Control and Prevention]] (CDC), are: moderate or severe [[asthma]], pre-existing [[Chronic obstructive pulmonary disease|COPD]], [[pulmonary fibrosis]], [[cystic fibrosis]].<ref>{{#invoke:Cite web||date=11 February 2020|title=Coronavirus Disease 2019 (COVID-19)|url=https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/groups-at-higher-risk.html|access-date=19 June 2020|website=U.S. [[Centers for Disease Control and Prevention]] (CDC) }}</ref> Evidence stemming from [[meta-analysis]] of several smaller research papers also suggests that smoking can be associated with worse outcomes.<ref>{{#invoke:cite journal || vauthors = Zhao Q, Meng M, Kumar R, Wu Y, Huang J, Lian N, Deng Y, Lin S | title = The impact of COPD and smoking history on the severity of COVID-19: A systemic review and meta-analysis | journal = Journal of Medical Virology | volume = 92 | issue = 10 | pages = 1915β1921 | date = October 2020 | pmid = 32293753 | pmc = 7262275 | doi = 10.1002/jmv.25889 }}</ref><ref>{{#invoke:Cite web||title=Smoking and COVID-19|url=https://www.who.int/news-room/commentaries/detail/smoking-and-covid-19|access-date=19 June 2020|website=[[World Health Organization]] (WHO)}}</ref> When someone with existing respiratory problems is infected with COVIDβ19, they might be at greater risk for severe symptoms.<ref>{{#invoke:Cite web||title=Coronavirus Disease 2019 (COVID-19)|url=https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/groups-at-higher-risk.html|date=11 February 2020|website=U.S. [[Centers for Disease Control and Prevention]] (CDC) |access-date=4 May 2020}}</ref> COVIDβ19 also poses a greater risk to people who [[Opioid use disorder|misuse opioids]] and [[Stimulant use disorder|amphetamines]], insofar as their drug use may have caused lung damage.<ref>{{#invoke:Cite web||title=People who use drugs are more vulnerable to coronavirus. Here's what clinics are doing to help.|url=https://www.theadvocate.com/baton_rouge/news/coronavirus/article_f80cf77e-84fa-11ea-88d5-2b37dc9dd966.html| vauthors = DeRobertis J |date=3 May 2020|website=The Advocate (Louisiana)|access-date=4 May 2020}}</ref> In August 2020, the CDC issued a caution that [[tuberculosis]] (TB) infections could increase the risk of severe illness or death. The WHO recommended that people with respiratory symptoms be screened for both diseases, as testing positive for COVIDβ19 could not rule out co-infections. Some projections have estimated that reduced TB detection due to the pandemic could result in 6.3 million additional TB cases and 1.4 million TB-related deaths by 2025.<ref>{{#invoke:Cite web||url=https://www.cdc.gov/coronavirus/2019-ncov/global-covid-19/TB-non-us-settings.html|title=Coronavirus Disease 2019 (COVID-19)|date=11 February 2020|website=U.S. [[Centers for Disease Control and Prevention]] (CDC) }}</ref> Summary: Please note that all contributions to Christianpedia may be edited, altered, or removed by other contributors. If you do not want your writing to be edited mercilessly, then do not submit it here. You are also promising us that you wrote this yourself, or copied it from a public domain or similar free resource (see Christianpedia:Copyrights for details). Do not submit copyrighted work without permission! Cancel Editing help (opens in new window) Discuss this page