I don't have the time at the moment to attempt to validate these sources. I will later.Yes, this peer review has sources that are used within the peer review. I'm suspicious of that... So what I'm saying, respectively, is your sources are second hand ( as well as the peer review.) It's not the original information. Also, when you actually look up where this peer review has sourced it's information from... it just raises more questions. Most of these sources are not "science" just political sources. The information from the sources themselves have sources they have received their information from. For example... The world Health Organization is a used source. They are under the scope of being challenged for falsifying misinformation and doing business with foreign politics to fulfill their own agenda. But, the point I am trying to convey is... a lot of this "Science" is simply politics and not science. The new yourk times source is not science. The are a leftist group that basically talks crap. The sources are an endless rabit hole that eventually gets lost.
Here are the sources from your peer review. As follows:
Data availability All study code and data are fully replicable and available in the following Open Science Framework (OSF) reposi-tory: https:// osf. io/ 5j9nc/? view_ only= 48f0f 69952 814e3 a8e96 7370e 7b509 54.Received: 10 September 2020; Accepted: 27 January 2021References
1. Salje, H. et al. Estimating the burden of SARS-CoV-2 in France. Science369, 208–211. https:// doi. org/ 10. 1126/ science. abc35 17(2020).
2. Wu, J., McCann, A., Katz, J. & Peltier, E. 107,000 Missing Deaths: Tracking the True Toll of the Coronavirus Outbreak. The New York Times. ---------------------------------------The new york times has repeatidly lied and exaggerated info/statistics to fullfill political agendas.
3. Leon, D. A. et al. COVID-19: a need for real-time monitoring of weekly excess deaths. Lancet395, e81. https:// doi. org/ 10. 1016/S0140- 6736(20) 30933-8 (2020).
4. Riffe, T. & Acosta, E. Coverage-db: Covid-19 cases and deaths by age database. https:// doi. org/ 10. 17605/ OSF. IO/ MPWJQ (2020).
5. Human Mortality Database (2020) www. morta lity. org or www. human morta lity. de. University of California, Berkeley (USA), and Max Planck Institute for Demographic Research (Germany).
6. Dicker, D. et al. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet392, 1684–1735. https:// doi. org/ 10. 1016/ S0140- 6736(18) 31891-9 (2018).
7. United Nations, Department of Economic and Social Affairs & Population Division. World Population Prospects Highlights, 2019 Revision Highlights, 2019 Revision (2019). OCLC: 1142478963.
8. Walker, P. G. T. et al. The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries. Science369, 413–422. https:// doi. org/ 10. 1126/ scien ce. abc00 35 (2020).
9. Global Health Data Exchange | GHDx (2020).
10. 1126/ scien ce. abc00 35 (2020). 9. Global Health Data Exchange | GHDx (2020). 10. Varga, Z. et al. Endothelial cell infection and endotheliitis in COVID-19. Lancet395, 1417–1418. https:// doi. org/ 10. 1016/ S0140-6736(20) 30937-5 (2020).
11. Sun, H. et al. Risk factors for mortality in 244 older adults with COVID-19 in Wuhan, China: a retrospective study. J. Am. Geriatr. Soc.https:// doi. org/ 10. 1111/ jgs. 16533 (2020).
12. Banerjee, A. et al. Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study. Lancet395, 1715–1725. https:// doi. org/ 10. 1016/ S0140- 6736(20) 30854-0 (2020).
13. Gémes, K. et al. Burden and prevalence of prognostic factors for severe Covid-19 in Sweden. Eur. J. Epidemiol.https:// doi. org/ 10.1007/ s10654- 020- 00646-z (2020).
14. Jin, J.-M. et al. Gender differences in patients with COVID-19: focus on severity and mortality. Front. Public Health8, 152.
https://doi./ org/ 10. 3389/ fpubh. 2020. 00152 (2020).
15. Flaxman, S. et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe. Naturehttps:// doi. org/ 10.1038/ s41586- 020- 2405-7 (2020).
16. Onder, G., Rezza, G. & Brusaferro, S. Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy. JAMA323, 1775–1776. https:// doi. org/ 10. 1001/ jama. 2020. 4683 (2020).
17. Chen, N. et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet395, 507–513. https:// doi. org/ 10. 1016/ S0140- 6736(20) 30211-7 (2020).
18. Robilotti, E. V. et al. Determinants of COVID-19 disease severity in patients with cancer. Nat. Med.https:// doi. org/ 10. 1038/ s41591-020- 0979-0 (2020).
19. World Health Organization. Who Methods and Data Sources for Global Burden of Disease Estimates 2000–2011. Technical report WHO/HIS/HSI/GHE/2013.4 (2013).
20. Xiong, Q. et al. Clinical sequelae of Covid-19 survivors in Wuhan, China: a single-centre longitudinal study. Clin. Microbiol. Infect.27, 89–95 (2020).
21. Huang, C. et al. 6-month consequences of COVID-19 in patients discharged from hospital: a cohort study. Lancethttps:// doi. org/10. 1016/ S0140- 6736(20) 32656-8 (2021).
Those are journal articles, not political sources in the slightest. Those are all peer reviewed journals like Science, The Lancet, and Nature, i.e. some of the most sought after journals to publish your papers in.
If you don't even recognize those it's pretty obvious you don't know the first thing about science.