| Literature DB >> 32574293 |
Ali Ahmed1, Areeba Ali2, Sana Hasan3.
Abstract
The objective of this study is to compare the epidemiological variations in COVID-19 patients reported in studies from inside and outside of China. We selected COVID-19 observational studies from eight countries, including, China, Italy, Australia, Canada, Korea, Taiwan, Singapore, and the USA, comprising a total of 13 studies and performed a meta-analysis for age, gender, fatality rate, and clinical symptoms of fever, cough, shortness of breath, and diarrhea. The meta-analysis shows that there are differences in symptoms and other characteristics reported by the patients of COVID-19 inside and outside China. Patients in China have a higher proportion of fever, cough, and shortness of breath as compared to patients outside of China. However, we found the opposite results for the gastrointestinal symptoms such as Diarrhea. Patients outside of China have a significantly higher proportion of Diarrhea as compared to patients within China. We also observed gender disparity among our studies, with the male population being more susceptible than the female population. Moreover, the analysis suggests that the fatality rate in China is relatively lower as compared to the fatality rate in other countries. These findings also suggest that the clinical symptoms of COVID-19 should not be generalized to fever, shortness of breath, and cough only but other symptoms such as diarrhea are also prevalent in patients with COVID-19.Entities:
Keywords: 2019-nCoV; COVID-19; epidemiological characteristics; meta-analysis; symptoms
Mesh:
Year: 2020 PMID: 32574293 PMCID: PMC7226658 DOI: 10.3389/fpubh.2020.00193
Source DB: PubMed Journal: Front Public Health ISSN: 2296-2565
Figure 1Systematic literature review process the flow sheet diagram represents the systematic review of literature for the characteristics of clinical symptoms (16).
Studies Included in the meta-analysis.
| Study 1 | Huang et al. ( | 1/24/2020 | Wuhan, China | 41 |
| Study 2 | Li et al. ( | 1/29/2020 | Wuhan China | 425 |
| Study 3 | Wang et al. ( | 2/7/2020 | Wuhan, China | 138 |
| Study 4 | Chen et al. ( | 2/15/2020 | Wuhan, China | 99 |
| Study 5 | Guan et al. ( | 2/20/2020 | Mainland China | 1,099 |
| Study 6 | Wu et al. ( | 2/29/2020 | Jiangsu, China | 80 |
| Study 1 | Kong et al. ( | 2/21/2020 | South Korea | 28 |
| Study 2 | Young et al. ( | 3/3/2020 | Singapore | 18 |
| Study 3 | COVID-19 National Incident Room Surveillance ( | 3/5/2020 | Australia | 71 |
| Study 4 | Lin et al. ( | 3/6/2020 | Toronto, Canada | 135 |
| Study 5 | Su and Lai ( | 3/14/2020 | Taiwan | 10 |
| Study 6 | Livingston and Bucher ( | 3/17/2020 | Lombardy, Italy | 22,512 |
| Study 7 | Arentz et al. ( | 3/19/2020 | Washington, USA | 21 |
Age, gender and fatality rate.
| Huang et al. ( | 41–58 | 49 | 30 (73%) | 6 (15%) |
| Li et al. ( | 26–82 | 56 | 281 (66%) | – |
| Wang et al. ( | 42–68 | 56 | 75 (54%) | 6 (4%) |
| Chen et al. ( | 21–82 | 56 | 67 (68%) | 11 (11%) |
| Guan et al. ( | 35–58 | 47 | 637 (58%) | 15 (1%) |
| Kong et al. ( | 20–73 | 42.6 | 15 (54%) | 0 (0%) |
| Wu et al. ( | 30–62 | 46.1 | 38 (48%) | 0 (0%) |
| Young et al. ( | 31–73 | 47 | 9 (50%) | 0 (0%) |
| COVID-19 National Incident Room Surveillance ( | 0–94 | 45 | – | 2 (3%) |
| Lin et al. ( | 23–49 | 28 | 59 (44%) | 0 (0%) |
| Su and Lai ( | – | 49 | 3 (30%) | 0 (0%) |
| Livingston and Bucher ( | 0–90 | 50 | 13,282 (59%) | 1,625(7.2%) |
| Arentz et al. ( | 43–92 | 70 | 11 (52%) | 11 (52%) |
| – | 47 ± 7 | – | 0.07 ± 0.14 |
Clinical symptoms.
| Huang et al. ( | 40 (98%) | 31 (76%) | 23 (55%) | – | 1 (3%) | – | 3 (8%) | 11 (28%) | 18 (44%) | 2 (5%) | |
| Li et al. ( | 281 (66%) | – | – | – | – | – | – | – | – | – | 238 (56%) |
| Wang et al. ( | 136 (98%) | 82 (82%) | 43 (31%) | – | 14 (10%) | 0(0%) | 9 (7%) | 37 (27%) | 96 (70%) | 10 (10%) | 53 (39%) |
| Chen et al. ( | 82 (83%) | 81 (82%) | 31 (31%) | 5 (5%) | 2 (2%) | 5 (5%) | 8 (8%) | – | 11 (11%) | 11 (1%) | |
| Guan et al. ( | 975 (88%) | 745 (68%) | 206 (19%) | 153 (14%) | 43 (4%) | – | 149 (14%) | 363 (34%) | 418 (38%) | 1 (5%) | 299 (27%) |
| Kong et al. ( | 9 (32%) | 5 (18%) | – | 9 (32%) | – | – | 3 (11%) | 5 (18%) | 4 (14%) | – | 5 (18%) |
| Wu et al. ( | 63 (78 %) | 51 (64%) | 30 (38%) | – | 0 (0%) | 5 (6%) | 13 (16%) | – | 18 (23%) | – | – |
| Young et al. ( | 13 (72%) | 15 (83%) | 2 (11%) | 11 (61%) | 3(17%) | 5 (29%) | – | – | – | – | – |
| COVID-19 National Incident Room Surveillance ( | 46 (65%) | 50 (71%) | – | 36 (50%) | 18 (26%) | – | 25 (35%) | – | 13 (18%) | 4 (6%) | – |
| Lin et al. ( | 65 (48%) | 111 (82%) | 111 (82%) | 41 (30%) | 14 (10%) | 41 (30%) | – | – | 23 (17%) | – | |
| Su and Lai ( | 5 (50%) | 6 (60%) | – | – | – | – | – | 4 (40%) | 1 (10%) | – | – |
| Livingston and Bucher ( | – | – | – | – | – | – | – | – | – | – | – |
| Arentz et al. ( | 11 (52%) | 10 (48%) | 16 (76%) | – | – | – | – | – | – | – | – |
Figure 2Meta-analysis forest plot overall and comparison of inside and outside of China. (A) Forest Plot by using a random-effects model for Gender (Male). (B) Comparison of Gender (Male) inside and outside of China. (C) Forest Plot by using a random-effects model for fever symptoms. (D) Comparison of Fever inside and outside of China. (E) Forest Plot by using a random-effect model for cough symptoms. (F) Comparison of cough inside and outside of China. (G) Forest Plot using Random effect model shown for Diarrhea of 8 studies. (H) Comparison of inside and outside of China for Diarrhea. (I) Forest Plot using Random effect model shown for 8 studies for Shortness of breath. (J) Comparison of inside and outside of China for Shortness of breath. (K) Forest Plot using Random Effect model for Fatality rate in 7 studies. (L) Comparison of inside and outside of China for a fatality rate.