A digitized catalog of COVID-19 epidemiology data

Wanyu Tao, Zhengqing Yu, Jing-Dong J. Han

PDF(439 KB)
PDF(439 KB)
Quant. Biol. ›› 2021, Vol. 9 ›› Issue (1) : 23-46. DOI: 10.15302/J-QB-020-0230
MINI REVIEW
MINI REVIEW

A digitized catalog of COVID-19 epidemiology data

Author information +
History +

Abstract

COVID-19 is now rapidly spreading worldwide. While the majority of COVID-19 patients show only mild or moderate symptoms, some could deteriorate quickly and may succumb to a sudden death. It is therefore important to identify who will be more likely to develop severe outcomes and be treated with particular or preventive care. Here in this literature survey, we collected epidemiologic and clinical data from 36 articles on 51,270 patients with different severity of COVID-19, aiming to characterize the population that are prone to severe condition and bad outcomes. These data reveal that old males and those with high BMI or underlying diseases, especially cardiovascular disease, hypertension and diabetes, are overrepresented among severe cases. High leukocyte and lymphopenia are common features in severe and critical patients. Upon deterioration of the disease, both CD4+ and CD8+ T cells are decreased, while almost all serum cytokines, especially pro-inflammatory cytokines, increased.

Graphical abstract

Keywords

COVID-19 / severity / epidemiology / immune cells / cytokine

Cite this article

Download citation ▾
Wanyu Tao, Zhengqing Yu, Jing-Dong J. Han. A digitized catalog of COVID-19 epidemiology data. Quant. Biol., 2021, 9(1): 23‒46 https://doi.org/10.15302/J-QB-020-0230

References

[1]
WHO. (2020) Coronavirus disease (COVID-2019) situation reports. Available from the website of World Health Organization.
[2]
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., (2020) Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet, 395, 497–506
CrossRef Pubmed Google scholar
[3]
Wang, T., Du, Z., Zhu, F., Cao, Z., An, Y., Gao, Y. and Jiang, B. (2020) Comorbidities and multi-organ injuries in the treatment of COVID-19. Lancet, 395, e52
CrossRef Pubmed Google scholar
[4]
Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P. and Stewart, L. A., and the PRISMA-P Group. (2015) Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev., 4, 1
CrossRef Pubmed Google scholar
[5]
Chen, L., Liu, H. G., Liu, W., Liu, J., Liu, K., Shang, J., Deng, Y. and Wei, S. (2020) Analysis of clinical features of 29 patients with 2019 novel coronavirus pneumonia. Zhonghua Jie He He Hu Xi Za Zhi, 43, E005, in Chinese
CrossRef Pubmed Google scholar
[6]
Wang, D., Hu, B., Hu, C., Zhu, F., Liu, X., Zhang, J., Wang, B., Xiang, H., Cheng, Z., Xiong, Y., (2020) Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA, 323, 1061–1069
CrossRef Pubmed Google scholar
[7]
Liu, Y., Yang, Y., Zhang, C., Huang, F., Wang, F., Yuan, J., Wang, Z., Li, J., Li, J., Feng, C., (2020) Clinical and biochemical indexes from 2019-nCoV infected patients linked to viral loads and lung injury. Sci. China Life Sci., 63, 364–374
CrossRef Pubmed Google scholar
[8]
The Epidemiology Working Group for NCIP Epidemic Response, Chinese Center for Disease Control and Prevention. (2020) The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. Zhonghua Liu Xing Bing Xue Za Zhi, 41, 145–151, in Chinese
Pubmed
[9]
Zhang, J. J., Dong, X., Cao, Y. Y., Yuan, Y. D., Yang, Y. B., Yan, Y. Q., Akdis, C. A. and Gao, Y. D. (2020) Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China. Allergy, 75, 1730–1741
CrossRef Pubmed Google scholar
[10]
Yang, X., Yu, Y., Xu, J., Shu, H., Xia, J., Liu, H., Wu, Y., Zhang, L., Yu, Z., Fang, M., (2020) Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir. Med., 8, 475–481
CrossRef Pubmed Google scholar
[11]
Tian, S., Hu, N., Lou, J., Chen, K., Kang, X., Xiang, Z., Chen, H., Wang, D., Liu, N., Liu, D., (2020) Characteristics of COVID-19 infection in Beijing. J. Infect., 80, 401–406
CrossRef Pubmed Google scholar
[12]
Guan, W. J., Ni, Z. Y., Hu, Y., Liang, W. H., Ou, C. Q., He, J. X., Liu, L., Shan, H., Lei, C. L., Hui, D. S. C., (2020) Clinical characteristics of coronavirus disease 2019 in China. N. Engl. J. Med., 382, 1708–1720
CrossRef Pubmed Google scholar
[13]
Young, B. E., Ong, S. W. X., Kalimuddin, S., Low, J. G., Tan, S. Y., Loh, J., Ng, O.-T., Marimuthu, K., Ang, L. W., Mak, T. M., (2020) Epidemiologic features and clinical course of patients infected with SARS-CoV-2 in Singapore. JAMA, 323, 1488–1494
CrossRef Pubmed Google scholar
[14]
Ruan, Q., Yang, K., Wang, W., Jiang, L. and Song, J. (2020) Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med., 46, 846–848
CrossRef Pubmed Google scholar
[15]
Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., Xiang, J., Wang, Y., Song, B., Gu, X., (2020) Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet, 395, 1054–1062
CrossRef Pubmed Google scholar
[16]
Deng, Y., Liu, W., Liu, K., Fang, Y.-Y., Shang, J., zhou, L., Wang, K., Leng, F., Wei, S., Chen, L., (2020) Clinical characteristics of fatal and recovered cases of coronavirus disease 2019 (COVID-19) in Wuhan, China: a retrospective study. Chin. Med. J., 133, 1261–1267
CrossRef Google scholar
[17]
CDC. U. S. (2020) Severe Outcomes Among Patients with Coronavirus Disease 2019 (COVID-19) — United States, February 12–March 16, 2020. MMWR Morb. Mortal Wkly Rep., 343–346
[18]
Chen, T., Wu, D., Chen, H., Yan, W., Yang, D., Chen, G., Ma, K., Xu, D., Yu, H., Wang, H., (2020) Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ, 368, m1091
CrossRef Pubmed Google scholar
[19]
Cao, W. (2020) Clinical features and laboratory inspection of novel coronavirus pneumonia (COVID-19) in Xiangyang, Hubei. medRxiv, 20026963
CrossRef Google scholar
[20]
Chen, G., Wu, D., Guo, W., Cao, Y., Huang, D., Wang, H., Wang, T., Zhang, X., Chen, H., Yu, H., (2020) Clinical and immunological features of severe and moderate coronavirus disease 2019. J. Clin. Invest., 130, 2620–2629
CrossRef Pubmed Google scholar
[21]
Deng, C. Yang, Y., Chen, H., Chen, W., Chen, Z., Ma, K. and Wang, J. (2020) Ocular dectection of SARS-CoV-2 in 114 cases of COVID-19 pneumonia in Wuhan, China: An observational study. SSRN Electronic Journal, 10.2139/ssrn.3543587
[22]
Diao, B., Wang, C., Tan, Y., Chen, X., Liu, Y., Ning, L., Chen, L., Li, M., Liu, Y., Wang, G., (2020) Reduction and functional exhaustion of T cells in patients with coronavirus disease 2019 (COVID-19). Front. Immunol., 11, 827
CrossRef Pubmed Google scholar
[23]
Liu, T., Zhang, J., Yang, Y., Ma, H., Li, Z., Zhang, J., Cheng, J., Zhang, X., Zhao, Y., Xia, Z. (2020) The potential role of IL-6 in monitoring severe case of coronavirus disease 2019. medRxiv, 20029769
CrossRef Google scholar
[24]
Liu, J., Li, S., Liu, J., Liang, B., Wang, X., Wang, H., Li, W., Tong, Q., Yi, J., Zhao, L., (2020) Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients. EBioMedicine, 55, 102763
CrossRef Pubmed Google scholar
[25]
Mao, L., Jin, H., Wang, M., Hu, Y., Chen, S., He, Q., Chang, J., Hong, C., Zhou, Y., Wang, D., (2020) Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan, China. JAMA Neurol., 77, 683–690
CrossRef Pubmed Google scholar
[26]
Qian, G. Q., Yang, N. B., Ding, F., Ma, A. H. Y., Wang, Z. Y., Shen, Y. F., Shi, C. W., Lian, X., Chu, J. G., Chen, L., (2020) Epidemiologic and clinical characteristics of 91 hospitalized patients with COVID-19 in Zhejiang, China: a retrospective, multi-centre case series. QJM, 113, 474–481
CrossRef Pubmed Google scholar
[27]
Qin, C., Zhou, L., Hu, Z., Zhang, S., Yang, S., Tao, Y., Xie, C., Ma, K., Shang, K., Wang, W., (2020) Dysregulation of immune response in patients with COVID-19 in Wuhan, China. Clin. Infect. Dis., 71, 762–768
CrossRef Pubmed Google scholar
[28]
Liu, S., Luo, H., Wang, Y., Wang, D., Ju, S. and Yang, Y. (2020) Characteristics and associations with severity in COVID-19 Patients: A multicentre cohort study from Jiangsu province, China. SSRN Electronic Journal, 10.2139/ssrn.3548753
[29]
Wan, S., Yi, Q., Fan, S., Lv, J., Zhang, X., Guo, L., Lang, C., Xiao, Q., Xiao, K., Yi, Z., (2020) Relationships among lymphocyte subsets, cytokines, and the pulmonary inflammation index in coronavirus (COVID-19) infected patients. Br. J. Haematol., 189, 428–437
CrossRef Pubmed Google scholar
[30]
Wang, L., Li, X., Chen, H., Yan, S., Li, Y., Li, D. and Gong, Z. (2020) SARS-CoV-2 infection does not significantly cause acute renal injury: an analysis of 116 hospitalized patients with COVID-19 in a single hospital, Wuhan, China. medRxiv, 20025288
CrossRef Google scholar
[31]
Wang, F., Nie, J., Wang, H., Xiao, Y., Wang, H., Liu, X., Deng, L., Xing, Y., Chen, T., Chen, X., (2020) Characteristics of peripheral lymphocyte subset alteration in 2019-nCoV pneumonia. SSRN Electronic Journal, 10.2139/ssrn.3539681
[32]
Zheng, Y., Huang, Z., Ying, G., Zhang, X., Ye, W., Hu, Z., Hu, C., Wei, H., Zeng, Y., Chi, Y., (2020) Comparative study of the lymphocyte change between COVID-19 and non-COVID-19 pneumonia cases suggesting uncontrolled inflammation might not be the main reason of tissue injury. medRxiv, 20024885
CrossRef Google scholar
[33]
Zhou, Y., Fu, B., Zheng, X., Wang, D. and Zhao, C.qi, Y., Sun, R., Tian, Z., Xu, X. and Wei, H. (2020) Pathogenic T cells and inflammatory monocytes incite inflammatory storm in severe COVID-19 patients. Natl. Sci. Rev., doi:10.1093/nsr/nwaa041
[34]
Zeng, Q., Li, Y.-Z., Huang, G., Wu, W., Dong, S.-Y. and Xu, Y. (2020) Mortality of COVID-19 is associated with cellular immune function compared to immune function in Chinese Han population. medRxiv, 20031229
CrossRef Google scholar
[35]
Liu, Y., Zhang, C., Huang, F., Yang, Y., Wang, F., Yuan, J., Zhang, Z., Qin, Y., Li, X., Zhao, D., (2020) 2019-novel coronavirus (2019-nCoV) infections trigger an exaggerated cytokine response aggravating lung injury. ChinaXiv, 202002.00018v1
[36]
Cai, Q., Huang, D., Ou, P., Yu, H., Zhu, Z., Xia, Z., Su, Y., Ma, Z., Zhang, Y., Li, Z., (2020) COVID-19 in a designated infectious diseases hospital outside Hubei Province, China. Allergy, 75, 1742–1752
CrossRef Pubmed Google scholar
[37]
Huang, R., Zhu, L., Xue, L., Liu, L., Yan, X., Wang, J., Zhang, B., Xu, T., Ji, F., Zhao, Y., (2020) Clinical findings of patients with coronavirus disease 2019 in Jiangsu province, China: A retrospective, multi-center study. PLoS Negl. Trop. Dis., 14, e0008280
CrossRef Pubmed Google scholar
[38]
Xu, Y., Xu, Z., Liu, X., Cai, L., Zheng, H., Huang, Y., Zhou, L., Huang, L., Lin, Y., Deng, L., (2020) Clinical findings in critical ill patients infected with SARS-Cov-2 in Guangdong Province, China: a multi-center, retrospective, observational study. medRxiv, 20030668,
CrossRef Google scholar
[39]
He, W., Li, Q., Yang, M., Jiao, J., Ma, X., Zhou, Y., Song, A., Heymsfield, S. B., Zhang, S. and Zhu, S. (2015) Lower BMI cutoffs to define overweight and obesity in China. Obesity (Silver Spring), 23, 684–691
CrossRef Pubmed Google scholar
[40]
Kupferschmidt, K. and Cohen, J. (2020) WHO launches global megatrial of the four most promising coronavirus treatments.
[41]
Lu, X., Zhang, L., Du, H., Zhang, J., Li, Y. Y., Qu, J., Zhang, W., Wang, Y., Bao, S., Li, Y., (2020) SARS-CoV-2 Infection in Children. N. Engl. J. Med., 382, 1663–1665
CrossRef Pubmed Google scholar
[42]
Wei, M., Yuan, J., Liu, Y., Fu, T., Yu, X. and Zhang, Z.-J. (2020) Novel Coronavirus Infection in Hospitalized Infants Under 1 Year of Age in China. JAMA, 323, 1313–1314
CrossRef Pubmed Google scholar
[43]
Liu, W., Zhang, Q., Chen, J., Xiang, R., Song, H., Shu, S., Chen, L., Liang, L., Zhou, J., You, L., (2020) Detection of covid-19 in children in early January 2020 in Wuhan, China. N. Engl. J. Med., 382, 1370–1371
CrossRef Pubmed Google scholar
[44]
Karlberg, J., Chong, D. S. Y. and Lai, W. Y. Y. (2004) Do men have a higher case fatality rate of severe acute respiratory syndrome than women do? Am. J. Epidemiol., 159, 229–231
CrossRef Pubmed Google scholar
[45]
Hong, K.-H., Choi, J.-P., Hong, S.-H., Lee, J., Kwon, J.-S., Kim, S.-M., Park, S. Y., Rhee, J.-Y., Kim, B.-N., Choi, H. J., (2018) Predictors of mortality in Middle East respiratory syndrome (MERS). Thorax, 73, 286–289
CrossRef Pubmed Google scholar
[46]
Channappanavar, R., Fett, C., Mack, M., Ten Eyck, P. P., Meyerholz, D. K. and Perlman, S. (2017) Sex-based differences in susceptibility to severe acute respiratory syndrome coronavirus infection. J. Immunol., 198, 4046–4053
CrossRef Pubmed Google scholar
[47]
Chen, J., Jiang, Q., Xia, X., Liu, K., Yu, Z., Tao, W., Gong, W. and Han, J.D. (2020) Individual Variation of the SARS-CoV2 Receptor ACE2 Gene Expression and Regulation. Aging Cell, https://doi.org/10.1111/acel.13168
CrossRef Google scholar
[48]
Horstman, A. M., Dillon, E. L., Urban, R. J. and Sheffield-Moore, M. (2012) The role of androgens and estrogens on healthy aging and longevity. J. Gerontol. A Biol. Sci. Med. Sci., 67, 1140–1152
CrossRef Pubmed Google scholar
[49]
Klein, S. L. and Flanagan, K. L. (2016) Sex differences in immune responses. Nat. Rev. Immunol., 16, 626–638
CrossRef Pubmed Google scholar
[50]
Peng, Y. D., Meng, K., Guan, H. Q., Leng, L., Zhu, R. R., Wang, B. Y., He, M. A., Cheng, L. X., Huang, K. and Zeng, Q. T. (2020) Clinical characteristics and outcomes of 112 cardiovascular disease patients infected by 2019-nCoV. Zhonghua Xin Xue Guan Bing Za Zhi, 48, 450–455, in Chinese
CrossRef Pubmed Google scholar
[51]
Liu, J., Ouyang, L., Guo, P., Wu, H. S., Fu, P., Chen, Y. l., Yang, D., Han, X. Y., Cao, Y. K., Alwalid, O., (2020) Epidemiological, clinical characteristics and outcome of medical staff infected with COVID-19 in Wuhan, China: A retrospective case series analysis. medRxiv, 20033118,
CrossRef Google scholar
[52]
Bhupathiraju, S. N. and Hu, F. B. (2016) Epidemiology of obesity and diabetes and their cardiovascular complications. Circ. Res., 118, 1723–1735
CrossRef Pubmed Google scholar
[53]
Tchkonia, T., Morbeck, D. E., Von Zglinicki, T., Van Deursen, J., Lustgarten, J., Scrable, H., Khosla, S., Jensen, M. D. and Kirkland, J. L. (2010) Fat tissue, aging, and cellular senescence. Aging Cell, 9, 667–684
CrossRef Pubmed Google scholar
[54]
Morin, C. L., Pagliassotti, M. J., Windmiller, D. and Eckel, R. H. (1997) Adipose tissue-derived tumor necrosis factor-α activity is elevated in older rats. J. Gerontol. A Biol. Sci. Med. Sci., 52A, B190–B195
CrossRef Pubmed Google scholar
[55]
Starr, M. E., Evers, B. M. and Saito, H. (2009) Age-associated increase in cytokine production during systemic inflammation: adipose tissue as a major source of IL-6. J. Gerontol. A Biol. Sci. Med. Sci., 64A, 723–730
CrossRef Pubmed Google scholar
[56]
Korppi, M., Kröger, L. and Laitinen, M. (1993) White blood cell and differential counts in acute respiratory viral and bacterial infections in children. Scand. J. Infect. Dis., 25, 435–440
CrossRef Pubmed Google scholar
[57]
Thevarajan, I., Nguyen, T. H. O., Koutsakos, M., Druce, J., Caly, L., van de Sandt, C. E., Jia, X., Nicholson, S., Catton, M., Cowie, B., (2020) Breadth of concomitant immune responses prior to patient recovery: a case report of non-severe COVID-19. Nat. Med., 26, 453–455
CrossRef Pubmed Google scholar
[58]
Chen, J., Qi, T., Liu, L., Ling, Y., Qian, Z., Li, T., Li, F., Xu, Q., Zhang, Y., Xu, S., (2020) Clinical progression of patients with COVID-19 in Shanghai, China. J. Infect., 80, e1–e6
CrossRef Pubmed Google scholar
[59]
Xu, Z., Shi, L., Wang, Y., Zhang, J., Huang, L., Zhang, C., Liu, S., Zhao, P., Liu, H., Zhu, L., (2020) Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir. Med., 8, 420–422
CrossRef Pubmed Google scholar
[60]
Zheng, H.-Y., Zhang, M., Yang, C.-X., Zhang, N., Wang, X.-C., Yang, X.-P., Dong, X.-Q. and Zheng, Y.-T. (2020) Elevated exhaustion levels and reduced functional diversity of T cells in peripheral blood may predict severe progression in COVID-19 patients. Cell. Mol. Immunol., 17, 541–543
CrossRef Pubmed Google scholar
[61]
Gu, J., Gong, E., Zhang, B., Zheng, J., Gao, Z., Zhong, Y., Zou, W., Zhan, J., Wang, S., Xie, Z., (2005) Multiple organ infection and the pathogenesis of SARS. J. Exp. Med., 202, 415–424
CrossRef Pubmed Google scholar
[62]
Shi, Y., Wang, Y., Shao, C., Huang, J., Gan, J., Huang, X., Bucci, E., Piacentini, M., Ippolito, G. and Melino, G. (2020) COVID-19 infection: the perspectives on immune responses. Cell Death Differ., 27, 1451–1454
CrossRef Pubmed Google scholar
[63]
Turner, M. D., Nedjai, B., Hurst, T. and Pennington, D. J. (2014) Cytokines and chemokines: at the crossroads of cell signalling and inflammatory disease. Biochim. Biophys. Acta, 1843, 2563– 2582
CrossRef Pubmed Google scholar
[64]
Maraskovsky, E., Chen, W. F. and Shortman, K. (1989) IL-2 and IFN-gamma are two necessary lymphokines in the development of cytolytic T cells. J. Immunol., 143, 1210–1214
Pubmed
[65]
Wong, C. K., Lam, C. W. K., Wu, A. K. L., Ip, W. K., Lee, N. L. S., Chan, I. H. S., Lit, L. C. W., Hui, D. S. C., Chan, M. H. M., Chung, S. S. C., (2004) Plasma inflammatory cytokines and chemokines in severe acute respiratory syndrome. Clin. Exp. Immunol., 136, 95–103
CrossRef Pubmed Google scholar
[66]
Mahallawi, W. H., Khabour, O. F., Zhang, Q., Makhdoum, H. M. and Suliman, B. A. (2018) MERS-CoV infection in humans is associated with a pro-inflammatory Th1 and Th17 cytokine profile. Cytokine, 104, 8–13
CrossRef Pubmed Google scholar
[67]
de Jong, M. D., Simmons, C. P., Thanh, T. T., Hien, V. M., Smith, G. J. D., Chau, T. N. B., Hoang, D. M., Van Vinh Chau, N., Khanh, T. H., Dong, V. C., (2006) Fatal outcome of human influenza A (H5N1) is associated with high viral load and hypercytokinemia. Nat. Med., 12, 1203–1207
CrossRef Pubmed Google scholar
[68]
Guo, J., Huang, F., Liu, J., Chen, Y., Wang, W., Cao, B., Zou, Z., Liu, S., Pan, J., Bao, C., (2015) The serum profile of hypercytokinemia factors identified in H7N9-infected patients can predict fatal outcomes. Sci. Rep., 5, 10942
CrossRef Pubmed Google scholar
[69]
Guideline for the Diagnosis and Treatment of COVID-19 (7th version).
[70]
Leng, Z., Zhu, R., Hou, W., Feng, Y., Yang, Y., Han, Q., Shan, G., Meng, F., Du, D., Wang, S., (2020) Transplantation of ACE2- mesenchymal stem cells improves the outcome of patients with COVID-19 pneumonia. Aging Dis., 11, 216–228
CrossRef Pubmed Google scholar
[71]
Zhang, Y., Yu, L., Tang, L., Zhu, M., Jin, Y., Wang, Z. and Li, L. (2020) A promising anti-cytokine-storm targeted therapy for COVID-19: the artificial-liver blood-purification system. Engineering (Beijing), doi:10.1016/j.eng.2020.03.006
Pubmed

ACKNOWLEDGEMENTS

This work was supported by grants from the National Natural Science Foundation of China (No. 91749205) and China Ministry of Science and Technology (No. 2016YFE0108700) to J.D.J.H.

COMPLIANCE WITH ETHICS GUIDELINES

The authors Wanyu Tao, Zhengqing Yu and Jing-Dong J. Han declare that they have no conflict of interests.
All procedures performed in studies were in accordance with the ethical standards of the institution or practice at which the studies were conducted, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

RIGHTS & PERMISSIONS

2020 Higher Education Press
AI Summary AI Mindmap
PDF(439 KB)

Accesses

Citations

Detail

Sections
Recommended

/