❗Muy arriesgada la afirmación de Christian Drosten: "En mi opinión, la pandemia ha terminado."🤔
Y más viendo cómo China sufre la mayor ola de desde el inicio de la pandemia.
Ojalá acierte 🙏

My spreadsheet of #COVID19 studies showing longer-term damage to the body has grown to 100 studies. Here's a link and a thread of some of the most interesting. The conclusion is that COVID can attack many parts of the body, remain present in the body, increase risks of serious cardiovascular, brain, lung and immune system disorders, and increase risk of death and disability. Stop taking it so lightly!

docs.google.com/spreadsheets/d

@mcvmaaay97@mastodon.social Con juventud no se debe decaer. Nunca🤗

Children aged 10 to 19y played the greatest relative role in propagating Omicron epidemics, particularly when schools were open, followed by children aged 0 to 9y and adults aged 20 to 29y, as well as adults aged 30 to 49y. Persons aged over 50y played a more limited role in propagating Omicron infection in the community.
medrxiv.org/content/10.1101/20

On the role of different age groups in propagating Omicron epidemics in France

Background There is limited information on the role of different age groups in propagating SARS-CoV-2 epidemics driven by the Omicron variants. Methods We examined the role of individuals in different age groups in propagating the Spring, Summer, and Autumn waves of the Omicron epidemics in France using the previously developed methodology based on the relative risk (RR) statistic that measures the change in the group’s proportion among all cases admitted to ICU for COVID-19 before vs. after the peak of an epidemic wave. Higher value of the RR statistic for a given age group suggests a disproportionate depletion of susceptible individuals in that age group during the epidemic’s ascent (due to increased contact rates and/or susceptibility to infection). Results For the Spring wave (March 14 - May 15), the highest RR estimate belonged to children aged 10-19y (RR=1.92 (95% CI (1.18,3.12)), followed by adults aged 40-49y (RR=1.45 (1.09,1.93)) and children aged 0-9y (RR=1.31 (0.98,1.74)). For the Summer wave (June 27 – Aug. 21), the highest RR estimate belonged to children aged 0-9y (RR=1.61 (1.12,2.3)) followed by children aged 10-19y (RR=1.46 (0.72,2.93)) and adults aged 20-29y (RR=1.42 (0.91,2.23)). For the Autumn wave (Sep. 18 – Nov. 12), the highest RR estimate belonged to children aged 10-19y (RR=1.63 (0.72,3.71)), followed by adults aged 30-34y (RR=1.34 (0.8,2.25)) and 20-24y (RR=1.20 (0.65,2.21)). Conclusions Children aged 10-19y played the greatest relative role in propagating Omicron epidemics, particularly when schools were open, followed by children aged 0-9y and adults aged 20-29y, as well as adults aged 30-49y. Persons aged over 50y played a more limited role in propagating Omicron infection in the community. Additional efforts are needed to increase vaccination coverage in children aged 10-19y, as well as younger children and young adults to mitigate Omicron epidemics in the community. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes This study is based on aggregate, de-identified, publicly available data that can be accessed through refs. 11-13 <https://www.santepubliquefrance.fr/dossiers/coronavirus-covid-19/coronavirus-chiffres-cles-et-evolution-de-la-covid-19-en-france-et-dans-le-monde> <https://www.data.gouv.fr/fr/datasets/donnees-hospitalieres-relatives-a-lepidemie-de-covid-19/> <https://www.insee.fr/fr/statistiques/2381472#graphique-Donnes>

www.medrxiv.org

RT @TRyanGregory@twitter.com

Huh. So kids do transmit COVID, just like every other respiratory virus. 🤷‍♂️

medrxiv.org/content/10.1101/20

🐦🔗: twitter.com/TRyanGregory/statu

On the role of different age groups in propagating Omicron epidemics in France

Background There is limited information on the role of different age groups in propagating SARS-CoV-2 epidemics driven by the Omicron variants. Methods We examined the role of individuals in different age groups in propagating the Spring, Summer, and Autumn waves of the Omicron epidemics in France using the previously developed methodology based on the relative risk (RR) statistic that measures the change in the group’s proportion among all cases admitted to ICU for COVID-19 before vs. after the peak of an epidemic wave. Higher value of the RR statistic for a given age group suggests a disproportionate depletion of susceptible individuals in that age group during the epidemic’s ascent (due to increased contact rates and/or susceptibility to infection). Results For the Spring wave (March 14 - May 15), the highest RR estimate belonged to children aged 10-19y (RR=1.92 (95% CI (1.18,3.12)), followed by adults aged 40-49y (RR=1.45 (1.09,1.93)) and children aged 0-9y (RR=1.31 (0.98,1.74)). For the Summer wave (June 27 – Aug. 21), the highest RR estimate belonged to children aged 0-9y (RR=1.61 (1.12,2.3)) followed by children aged 10-19y (RR=1.46 (0.72,2.93)) and adults aged 20-29y (RR=1.42 (0.91,2.23)). For the Autumn wave (Sep. 18 – Nov. 12), the highest RR estimate belonged to children aged 10-19y (RR=1.63 (0.72,3.71)), followed by adults aged 30-34y (RR=1.34 (0.8,2.25)) and 20-24y (RR=1.20 (0.65,2.21)). Conclusions Children aged 10-19y played the greatest relative role in propagating Omicron epidemics, particularly when schools were open, followed by children aged 0-9y and adults aged 20-29y, as well as adults aged 30-49y. Persons aged over 50y played a more limited role in propagating Omicron infection in the community. Additional efforts are needed to increase vaccination coverage in children aged 10-19y, as well as younger children and young adults to mitigate Omicron epidemics in the community. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes This study is based on aggregate, de-identified, publicly available data that can be accessed through refs. 11-13 <https://www.santepubliquefrance.fr/dossiers/coronavirus-covid-19/coronavirus-chiffres-cles-et-evolution-de-la-covid-19-en-france-et-dans-le-monde> <https://www.data.gouv.fr/fr/datasets/donnees-hospitalieres-relatives-a-lepidemie-de-covid-19/> <https://www.insee.fr/fr/statistiques/2381472#graphique-Donnes>

www.medrxiv.org

@mcvmaaay97@mastodon.social Sin datos parece que no hay pandemia, pero nada cambia y el virus sigue a lo suyo.

COVID minimizers and deniers have been wrong every step of the way:

- Mass infection didn't give us herd immunity, it left millions dead/disabled globally

- Masks and stay-at-home orders reduced spread

- Schools were transmission hubs

- Kids have died/gotten long COVID

- Vaccines have saved millions

But being wrong hasn't stopped them from publicly fantasizing about holding public trials/executions of public health officials.

Feliz Navidad🎄y venturoso año nuevo 2023.☃️

Merry Christmas🎄 and happy new year 2023.☃️

RT @LiangRhea
It's awful seeing China become a natural experiment for what happens when a country with a well developed health system and a highly masked popn lifts #COVID19 controls without sufficient vaccination. It's Swiss cheese- we should learn. ALL mitigations are required.
HT @MackayIM

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