1. Hu, Ben and Guo, Hua and Zhou, Peng and Shi, Zheng-Li Characteristics of {SARS}-{CoV}-2 and {COVID}-19. 19(3): 141--154 https://doi.org/10.1038/s41579-020-00459-7, Texto completo:C\:\\Users\\alex-\\Zotero\\storage\\KS2MKS65\\Hu et al. - 2021 - Characteristics of SARS-CoV-2 and COVID-19.pdf:application/pdf, english, 2021-03, 2024-02-02, Nat Rev Microbiol, Nature Reviews Microbiology, https://www.nature.com/articles/s41579-020-00459-7, 1740-1526, 1740-1534
2. {WHO} Coronavirus ({COVID}-19) Dashboard.. https://covid19.who.int.
3. Nasserie, Tahmina and Hittle, Michael and Goodman, Steven N. Assessment of the Frequency and Variety of Persistent Symptoms Among Patients With {COVID}-19: A Systematic Review. 4(5): e2111417 https://doi.org/10.1001/jamanetworkopen.2021.11417, Texto completo:C\:\\Users\\alex-\\Zotero\\storage\\MRTARACL\\Nasserie et al. - 2021 - Assessment of the Frequency and Variety of Persist.pdf:application/pdf, english, 2021-05-26, 2024-02-02, {JAMA} Netw Open, {JAMA} Network Open, Assessment of the Frequency and Variety of Persistent Symptoms Among Patients With {COVID}-19, https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2780376, 2574-3805
4. Bergman, Jonathan and Ballin, Marcel and Nordstr öm, Anna and Nordstr öm, Peter Risk factors for {COVID}-19 diagnosis, hospitalization, and subsequent all-cause mortality in Sweden: a nationwide study. 36(3): 287--298 https://doi.org/10.1007/s10654-021-00732-w, Texto completo:C\:\\Users\\alex-\\Zotero\\storage\\74UJEPMQ\\Bergman et al. - 2021 - Risk factors for COVID-19 diagnosis, hospitalizati.pdf:application/pdf, english, 2021-03, 2024-02-02, Eur J Epidemiol, European Journal of Epidemiology, Abstract We conducted a nationwide, registry-based study to investigate the importance of 34 potential risk factors for coronavirus disease 2019 ({COVID}-19) diagnosis, hospitalization (with or without intensive care unit [{ICU}] admission), and subsequent all-cause mortality. The study population comprised all {COVID}-19 cases confirmed in Sweden by mid-September 2020 (68,575 non-hospitalized, 2494 {ICU} hospitalized, and 13,589 non-{ICU} hospitalized) and 434,081 randomly sampled general-population controls. Older age was the strongest risk factor for hospitalization, although the odds of {ICU} hospitalization decreased after 60 –69 years and, after controlling for other risk factors, the odds of non-{ICU} hospitalization showed no trend after 40 –49 years. Residence in a long-term care facility was associated with non-{ICU} hospitalization. Male sex and the presence of at least one investigated comorbidity or prescription medication were associated with both {ICU} and non-{ICU} hospitalization. Three comorbidities associated with both {ICU} and non-{ICU} hospitalization were asthma, hypertension, and Down syndrome. History of cancer was not associated with {COVID}-19 hospitalization, but cancer in the past year was associated with non-{ICU} hospitalization, after controlling for other risk factors. Cardiovascular disease was weakly associated with non-{ICU} hospitalization for {COVID}-19, but not with {ICU} hospitalization, after adjustment for other risk factors. Excess mortality was observed in both hospitalized and non-hospitalized {COVID}-19 cases. These results confirm that severe {COVID}-19 is related to age, sex, and comorbidity in general. The study provides new evidence that hypertension, asthma, Down syndrome, and residence in a long-term care facility are associated with severe {COVID}-19., Risk factors for {COVID}-19 diagnosis, hospitalization, and subsequent all-cause mortality in Sweden, http://link.springer.com/10.1007/s10654-021-00732-w, 0393-2990, 1573-7284
5. Bowyer, Ruth C. E. and Huggins, Charlotte and Toms, Renin and Shaw, Richard J. and Hou, Bo and Thompson, Ellen J. and Kwong, Alex S. F. and Williams, Dylan M. and Kibble, Milla and Ploubidis, George B. and Timpson, Nicholas J. and Sterne, Jonathan A. C. and Chaturvedi, Nishi and Steves, Claire J. and Tilling, Kate and Silverwood, Richard J. and {the CONVALESCENCE Study} Characterising patterns of {COVID}-19 and long {COVID} symptoms: evidence from nine {UK} longitudinal studies. 38(2): 199--210 https://doi.org/10.1007/s10654-022-00962-6, Texto completo:C\:\\Users\\alex-\\Zotero\\storage\\3UAMJN6D\\Bowyer et al. - 2023 - Characterising patterns of COVID-19 and long COVID.pdf:application/pdf, english, 2023-02, 2024-02-02, Eur J Epidemiol, European Journal of Epidemiology, Abstract Multiple studies across global populations have established the primary symptoms characterising Coronavirus Disease 2019 ({COVID}-19) and long {COVID}. However, as symptoms may also occur in the absence of {COVID}-19, a lack of appropriate controls has often meant that specificity of symptoms to acute {COVID}-19 or long {COVID}, and the extent and length of time for which they are elevated after {COVID}-19, could not be examined. We analysed individual symptom prevalences and characterised patterns of {COVID}-19 and long {COVID} symptoms across nine {UK} longitudinal studies, totalling over 42,000 participants. Conducting latent class analyses separately in three groups ( ‘no {COVID}-19 ’, ‘{COVID}-19 in last 12 weeks ’, ‘{COVID}-19 {\textgreater} 12 weeks ago ’), the data did not support the presence of more than two distinct symptom patterns, representing high and low symptom burden, in each group. Comparing the high symptom burden classes between the ‘{COVID}-19 in last 12 weeks ’ and ‘no {COVID}-19 ’ groups we identified symptoms characteristic of acute {COVID}-19, including loss of taste and smell, fatigue, cough, shortness of breath and muscle pains or aches. Comparing the high symptom burden classes between the ‘{COVID}-19 {\textgreater} 12 weeks ago ’ and ‘no {COVID}-19 ’ groups we identified symptoms characteristic of long {COVID}, including fatigue, shortness of breath, muscle pain or aches, difficulty concentrating and chest tightness. The identified symptom patterns among individuals with {COVID}-19 {\textgreater} 12 weeks ago were strongly associated with self-reported length of time unable to function as normal due to {COVID}-19 symptoms, suggesting that the symptom pattern identified corresponds to long {COVID}. Building the evidence base regarding typical long {COVID} symptoms will improve diagnosis of this condition and the ability to elicit underlying biological mechanisms, leading to better patient access to treatment and services., Characterising patterns of {COVID}-19 and long {COVID} symptoms, https://link.springer.com/10.1007/s10654-022-00962-6, 0393-2990, 1573-7284