Prevalence of Coronavirus Disease 2019 (COVID-19) in Different Clinical Stages before the National COVID-19 Vaccination Programme in Malaysia: A Systematic Review and Meta-Analysis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Subjects and Ethics
2.2. Literature Search for Meta-Analysis
2.3. Study Eligibility
2.4. Data Extraction
2.5. Quality Assessment and Risk of Bias
2.6. Statistical Analyses
3. Results
3.1. Characteristics of the Subjects in the Early Phase of the Study
3.2. Study Characteristics of Meta-Analysis
3.3. Meta-Analyses Outcomes
3.4. Publication Bias and Sensitivity Analysis
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- World Health Organization. Available online: https://covid19.who.int/ (accessed on 2 September 2021).
- Oran, D.P.; Topol, E.J. The proportion of SARS-CoV-2 infections that are asymptomatic. Ann. Intern. Med. 2021, 174, 655–662. [Google Scholar] [CrossRef]
- Sah, P.; Fitzpatrick, M.C.; Zimmer, C.F.; Abdollahi, E.; Juden-Kelly, L.; Moghadas, S.M.; Singer, B.H.; Galvani, A.P. Asymptomatic SARS-CoV-2 infection: A systematic review and meta-analysis. Proc. Natl. Acad. Sci. USA 2021, 118, e2109229118. [Google Scholar] [CrossRef]
- Alene, M.; Yismaw, L.; Assemie, M.A.; Ketema, D.B.; Mengist, B.; Kassie, B.; Birhan, T.Y. Magnitude of asymptomatic COVID-19 cases throughout the course of infection: A systematic review and meta-analysis. PLoS ONE 2021, 16, e0249090. [Google Scholar] [CrossRef]
- The Centre for Evidence-Based Medicine. Available online: https://www.cebm.net/covid-19/covid-19-what-proportion-are-asymptomatic/ (accessed on 6 September 2021).
- Buitrago-Garcia, D.; Egli-Gany, D.; Counotte, M.J.; Hossmann, S.; Imeri, H.; Ipekci, A.M.; Salanti, G.; Low, N. Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis. PLoS Med. 2020, 17, e1003346. [Google Scholar] [CrossRef]
- Huang, C.; Wang, Y.; Li, X.; Ren, L.; Zhao, J.; Hu, Y.; Zhang, L.; Fan, G.; Xu, J.; Gu, X.; et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020, 395, 497–506. [Google Scholar] [CrossRef] [Green Version]
- Qin, C.; Zhou, L.; Hu, Z.; Zhang, S.; Yang, S.; Tao, Y.; Xie, C.; Ma, K.; Shang, K.; Wang, W.; et al. Dysregulation of immune response in patients with coronavirus 2019 (COVID-19) in Wuhan, China. Clin. Infect. Dis. 2020, 71, 762–768. [Google Scholar] [CrossRef]
- Wu, Z.; McGoogan, J.M. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: Summary of a report of 72,314 cases from the Chinese Center for Disease Control and Prevention. JAMA 2020, 323, 239–1242. [Google Scholar] [CrossRef]
- World Health Organization. Available online: https://www.who.int/news-room/commentaries/detail/transmission-of-sars-cov-2-implications-for-infection-prevention-precautions (accessed on 2 September 2021).
- World Health Organization. Available online: https://www.who.int/publications/i/item/who-convened-global-study-of-origins-of-sars-cov-2-china-part (accessed on 2 September 2021).
- Richardson, S.; Hirsch, J.S.; Narasimhan, M.; Crawford, J.M.; McGinn, T.; Davidson, K.W.; the Northwell COVID-19 Research Consortium; Barnaby, D.P.; Becker, L.B.; Chelico, J.D.; et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalised with COVID-19 in the New York City area. JAMA 2020, 323, 2052–2059. [Google Scholar] [CrossRef]
- Grasselli, G.; Zangrillo, A.; Zanella, A.; Antonelli, M.; Cabrini, L.; Castelli, A.; Cereda, D.; Coluccello, A.; Foti, G.; Fumagalli, R.; et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA 2020, 323, 1574–1581. [Google Scholar] [CrossRef] [Green Version]
- van der Made, C.I.; Simons, A.; Schuurs-Hoeijmakers, J.; van den Heuvel, G.; Mantere, T.; Kersten, S.; van Deuren, R.C.; Steehouwer, M.; van Reijmersdal, S.V.; Jaeger, M.; et al. Presence of genetic variants among young men with severe COVID-19. JAMA 2020, 324, 663–673. [Google Scholar] [CrossRef]
- Zhou, F.; Yu, T.; Du, R.; Fan, G.; Liu, Y.; Liu, Z.; Xiang, J.; Wang, Y.; Song, B.; Gu, X.; et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020, 395, 1054–1062. [Google Scholar] [CrossRef]
- Pouwels, K.B.; Pritchard, E.; Matthews, P.C.; Stoesser, N.; Eyre, D.W.; Vihta, K.-D.; House, T.; Hay, J.; Bell, J.I.; Newton, J.N.; et al. Effect of Delta variant on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UK. Nat. Med. 2021, 27, 2127–2135. [Google Scholar] [CrossRef] [PubMed]
- Ministry of Health Malaysia. Available online: https://covid-19.moh.gov.my/ (accessed on 2 September 2021).
- Hu, Y.; Sun, J.; Dai, Z.; Deng, H.; Li, X.; Huang, Q.; Wu, Y.; Sun, L.; Xu, Y. Prevalence and severity of corona virus disease 2019 (COVID-19): A systematic review and meta-analysis. J. Clin. Virol. 2020, 127, 104371. [Google Scholar] [CrossRef] [PubMed]
- Badal, S.; Thapa Bajgain, K.; Badal, S.; Thapa, R.; Bajgain, B.B.; Santana, M.J. Prevalence, clinical characteristics, and outcomes of pediatric COVID-19: A systematic review and meta-analysis. J. Clin. Virol. 2021, 135, 104715. [Google Scholar] [CrossRef] [PubMed]
- The Ottawa Hospital Research Institute. The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-Analyses. Available online: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp (accessed on 3 September 2021).
- Egger, M.; Smith, G.D.; Schneider, M.; Minder, C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997, 315, 629. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Higgins, J.P.T.; Thompson, S.G.; Deeks, J.J.; Altman, D.G. Measuring inconsistency in meta-analyses. BMJ 2003, 327, 557. [Google Scholar] [CrossRef] [Green Version]
- Tan, J.K.; Leong, D.; Munusamy, H.; Zenol Ariffin, N.H.; Kori, N.; Hod, R.; Periyasamy, P. The prevalence and clinical significance of presymptomatic COVID-19 patients: How we can be one step ahead in mitigating a deadly pandemic. BMC Infect. Dis. 2021, 21, 249. [Google Scholar] [CrossRef]
- Thiam, C.N.; Hasmukharay, K.; Lim, W.C.; Ng, C.C.; Pang, G.H.M.; Abdullah, A.; Saedon, N.I.; Khor, H.M.; Ong, T. COVID-19 infection among older people admitted to hospital: A cross-sectional analysis. Geriatrics 2021, 6, 25. [Google Scholar] [CrossRef]
- Sim, B.L.H.; Chidambaram, S.K.; Wong, X.C.; Pathmanathan, M.D.; Peariasamy, K.M.; Hor, C.P.; Chua, H.J.; Goh, P.P. Clinical characteristics and risk factors for severe COVID-19 infections in Malaysia: A nationwide observational study. Lancet Reg. Health West. Pac. 2020, 4, 100055. [Google Scholar] [CrossRef] [PubMed]
- Tan-Loh, J.; Cheong, B.M.K. A descriptive analysis of clinical characteristics of COVID-19 among healthcare workers in a district specialist hospital. Med. J. Malays. 2021, 76, 24–28. [Google Scholar]
- Chong, E.T.J.; Lee, P.C. Prevalence of overweight and obesity in Malaysia, 2010–2016: A comprehensive meta-analysis. Southeast Asian J. Trop. Med. Publ. Health 2018, 49, 859–869. [Google Scholar]
- Institute for Public Health. National Health and Morbidity Survey (NHMS) 2019: Vol. I: NCDs—Non-Communicable Diseases: Risk Factors and Other Health Problems; NMRR-18-3085-44207; Ministry of Health Malaysia: Putrajaya, Malaysia, 2020. [Google Scholar]
- World Health Organization. Available online: https://www.who.int/health-topics/obesity (accessed on 5 September 2021).
- Pi-Sunyer, X. The medical risks of obesity. Postgrad. Med. 2009, 121, 21–33. [Google Scholar] [CrossRef]
- Centres for Disease Control and Prevention. Available online: https://www.cdc.gov/obesity/adult/causes.html (accessed on 5 September 2021).
- Simonnet, A.; Chetboun, M.; Poissy, J.; Raverdy, V.; Noulette, J.; Duhamel, A.; Labreuche, J.; Mathieu, D.; Pattou, F.; Jourdain, M. High prevalence of obesity in Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation. Obesity 2020, 28, 1195–1199. [Google Scholar] [CrossRef] [PubMed]
- Sattar, N.; Valabhji, J. Obesity as a risk factor for severe COVID-19: Summary of the best evidence and implications for health care. Curr. Obes. Rep. 2021, 10, 282–289. [Google Scholar] [CrossRef]
- Mubarik, S.; Liu, X.; Eshak, E.S.; Liu, K.; Liu, Q.; Wang, F.; Shi, F.; Wen, H.; Bai, J.; Yu, C.; et al. The association of hypertension with the severity of and mortality from the COVID-19 in the early stage of the epidemic in Wuhan, China: A multicenter retrospective cohort study. Front. Med. 2021, 8, 631. [Google Scholar] [CrossRef]
- Zhang, Q.; Wei, Y.; Chen, M.; Wan, Q.; Chen, X. Clinical analysis of risk factors for severe COVID-19 patients with type 2 diabetes. J. Diabetes. Complicat. 2020, 34, 107666. [Google Scholar] [CrossRef]
- Liguoro, I.; Pilotto, C.; Bonanni, M.; Ferrari, M.E.; Pusiol, A.; Nocerino, A.; Vidal, E.; Cogo, P. SARS-COV-2 infection in children and newborns: A systematic review. Eur. J. Pediatr. 2020, 179, 1029–1046. [Google Scholar] [CrossRef]
- Ludvigsson, J.F. Systematic review of COVID-19 in children shows milder cases and a better prognosis than adults. Acta Paediatr. 2020, 109, 1088–1095. [Google Scholar] [CrossRef]
- Castagnoli, R.; Votto, M.; Licari, A.; Brambilla, I.; Bruno, R.; Perlini, S.; Rovida, F.; Baldanti, F.; Marseglia, G.L. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in children and adolescents: A systematic review. JAMA Pediatr. 2020, 174, 882–889. [Google Scholar] [CrossRef] [Green Version]
- World Health Organization. COVID-19 Clinical Management: Living Guidance, 25 January 2021; WHO/2019-nCoV/clinical/2021.1; World Health Organization: Geneva, Switzerland, 2021. [Google Scholar]
- Chu, L.; Huang, F.; Zhang, M.; Huang, B.; Wang, Y. Current status of traditional Chinese medicine for the treatment of COVID-19 in China. Chin. Med. 2021, 16, 63. [Google Scholar] [CrossRef]
- Hu, K.; Guan, W.-J.; Bi, Y.; Zhang, W.; Li, L.; Zhang, B.; Liu, Q.; Song, Y.; Li, X.; Duan, Z.; et al. Efficacy and safety of Lianhuaqingwen capsules, a repurposed Chinese herb, in patients with coronavirus disease 2019: A multicenter, prospective, randomised controlled trial. Phytomedicine 2021, 85, 153242. [Google Scholar] [CrossRef] [PubMed]
- Blasiak, A.; Truong, A.T.L.; Remus, A.; Hooi, L.; Seah, S.G.K.; Wang, P.; Chye, D.H.; Lim, A.P.C.; Ng, K.T.; Teo, S.T.; et al. The IDentif.AI 2.0 pandemic readiness platform: Rapid prioritisation of optimised COVID-19 combination therapy regimens. medRxiv 2021. [Google Scholar] [CrossRef]
- Blasiak, A.; Lim, J.J.; Seah, S.G.K.; Kee, T.; Remus, A.; Chye, D.H.; Wong, P.S.; Hooi, L.; Truong, A.T.L.; Le, N.; et al. IDentif.AI: Rapidly optimising combination therapy design against severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) with digital drug development. Bioeng. Transl. Med. 2020, 6, e10196. [Google Scholar] [PubMed]
- Weinreich, D.M.; Sivapalasingam, S.; Norton, T.; Ali, S.; Gao, H.; Bhore, R.; Xiao, J.; Hooper, A.T.; Hamilton, J.D.; Musser, B.J.; et al. REGEN-COV antibody cocktail clinical outcomes study in Covid-19 outpatients. medRxiv 2021. [Google Scholar] [CrossRef]
- Kronbichler, A.; Kresse, D.; Yoon, S.; Lee, K.H.; Effenberger, M.; Shin, J.I. Asymptomatic patients as a source of COVID-19 infections: A systematic review and meta-analysis. Int. J. Infect. Dis. 2020, 98, 180–186. [Google Scholar] [CrossRef]
- Johansson, M.A.; Quandelacy, T.M.; Kada, S.; Prasad, P.V.; Steele, M.; Brooks, J.T.; Slayton, R.B.; Biggerstaff, M.; Butler, J.C. SARS-CoV-2 transmission from people without COVID-19 symptoms. JAMA Netw. Open 2021, 4, e2035057. [Google Scholar] [CrossRef]
- Wu, S.L.; Mertens, A.N.; Crider, Y.S.; Nguyen, A.; Pokpongkiat, N.N.; Djajadi, S.; Seth, A.; Hsiang, M.S.; Colford, J.M.; Reingold, A.; et al. Substantial underestimation of SARS-CoV-2 infection in the United States. Nat. Commun. 2020, 11, 4507. [Google Scholar] [CrossRef] [PubMed]
- Moustapha, D.; Papa Samba, B.; Moustapha, L.; Ndong, E.; Betty, F.; Mathilde Ndèye, S.; Mouhamadou, N.; Bruce, W.; Fatou Kiné Mbaye, S.; Ndèye Aissatou, L.; et al. Factors associated with severe COVID-19 in an epidemic treatment center at Dakar. J. Infect. Dis. Epidemiol. 2021, 7, 203. [Google Scholar] [CrossRef]
- Park, H.-Y.; Lee, J.H.; Lim, N.-K.; Lim, D.S.; Hong, S.O.; Park, M.-J.; Lee, S.Y.; Kim, G.; Park, J.K.; Song, D.S.; et al. Presenting characteristics and clinical outcome of patients with COVID-19 in South Korea: A nationwide retrospective observational study. Lancet Reg. Health West. Pac. 2020, 5, 100061. [Google Scholar] [CrossRef]
- Bruminhent, J.; Ruangsubvilai, N.; Nabhindhakara, J.; Ingsathit, A.; Kiertiburanakul, S. Clinical characteristics and risk factors for coronavirus disease 2019 (COVID-19) among patients under investigation in Thailand. PLoS ONE 2020, 15, e0239250. [Google Scholar] [CrossRef]
- Ishii, M.; Terai, H.; Kabata, H.; Masaki, K.; Chubachi, S.; Tateno, H.; Nakamura, M.; Nishio, K.; Koh, H.; Watanabe, R.; et al. Clinical characteristics of 345 patients with coronavirus disease 2019 in Japan: A multicenter retrospective study. J. Infect. 2020, 81, e3–e5. [Google Scholar] [CrossRef] [PubMed]
- Kee, B.P.; Lian, L.H.; Lee, P.C.; Lai, T.X.; Chua, K.H. Genetic data for 15 STR loci in a Kadazan-Dusun population from East Malaysia. Genet. Mol. Res. 2011, 10, 739–743. [Google Scholar] [CrossRef] [PubMed]
- Goh, L.P.W.; Chong, E.T.J.; Chua, K.H.; Chuah, J.A.; Lee, P.-C. Significant genotype difference in the CYP2E1 PstI polymorphism of indigenous groups in Sabah, Malaysia with Asian and Non-Asian populations. Asian Pac. J. Cancer Prev. 2014, 15, 7377–7381. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- National Institutes of Health. Available online: https://www.covid19treatmentguidelines.nih.gov/management/critical-care/general-considerations/ (accessed on 8 September 2021).
Characteristics | Stage 1 (N = 25) | Stage 2 (N = 39) | Stage 3 (N = 74) | Stage 4 (N = 68) | Stage 5 (N = 9) |
---|---|---|---|---|---|
Asymptomatic | Mild | Moderate | Severe | Critical | |
Gender | |||||
Male | 14 | 19 | 35 | 46 | 6 |
Female | 11 | 20 | 39 | 22 | 3 |
Age | 55.32 ± 14.92 | 49.36 ± 15.50 | 49.22 ± 13.64 | 51.06 ± 13.15 | 51.89 ± 9.52 |
Height (cm) | 157.54 ± 9.02 | 161.88 ± 8.69 | 161.18 ± 9.78 | 161.59 ± 6.97 | 162.00 ± 8.06 |
Weight (kg) | 68.54 ± 12.97 | 65.18 ± 16.44 | 71.79 ± 15.60 | 73.93 ± 16.04 | 77.00 ± 11.84 |
BMI (kg/m2) | 27.46 ± 3.75 | 24.84 ± 5.76 | 27.48 ± 4.75 | 28.23 ± 5.53 | 29.53 ± 5.46 |
Morbidities *, N (%) | |||||
Hypertension | 11 (44.0%) | 14 (35%) | 38 (51.4%) | 34 (50.0%) | 6 (66.7%) |
Diabetes mellitus | 4 (16.0%) | 7 (17.9%) | 19 (25.7%) | 10 (14.7%) | 3 (33.3%) |
Dyslipidaemia | 4 (16.0%) | 5 (12.8%) | 15 (20.3%) | 10 (14.7) | 1 (11.1%) |
Obesity (BMI ≥ 30.0) | 4 (16.0%) | 7 (17.9%) | 21 (28.4%) | 22 (32.4%) | 5 (55.5%) |
Study (N = 5) | Study Design | NOS Score | Number of Cases, N (%) | |||||
---|---|---|---|---|---|---|---|---|
Overall | Stage 1 | Stage 2 | Stage 3 | Stage 4 | Stage 5 | |||
Present study (2021) | Observational | - | 215 | 25 (11.6%) | 39 (18.1%) | 74 (34.4%) | 68 (31.6%) | 9 (4.2%) |
Thiam et al. (2021) [24] | Retrospective | 6 | 26 | 3 (11.5%) | 6 (23.1%) | 4 (15.4%) | 8 (30.8%) | 5 (19.2%) |
Tan-Loh & Cheong (2021) [26] | Retrospective | 6 | 46 | 12 (26.1%) | 24 (52.2%) | 7 (15.2%) | 1 (2.2%) | 2 (4.3%) |
Tan et al. (2021) [23] | Retrospective | 8 | 199 | 93 (46.7%) | 79 (39.7%) | 22 (11.1%) | 3 (1.5%) | 2 (1.0%) |
Sim et al. (2020) [25] | Observational | 7 | 5889 | 2956 (50.2%) | 1859 (31.6%) | 801 (13.6%) | 210 (3.6%) | 63 (1.1%) |
Subgroup | Prevalence Rate (95% CI) | Number of Studies | Heterogeneity | Model | Egger’s Test t; p | |
---|---|---|---|---|---|---|
I2 (%) | Q-Test | |||||
Stage 1 | 0.278 (0.152–0.452) | 5 | 96.4 | <0.001 | Random | 2.271; 0.108 |
Stage 2 | 0.320 (0.240–0.412) | 5 | 87.7 | <0.001 | Random | 0.044; 0.967 |
Stage 3 | 0.171 (0.098–0.281) | 5 | 94.1 | <0.001 | Random | 0.676; 0.548 |
Stage 4 | 0.076 (0.017–0.284) | 5 | 98.5 | <0.001 | Random | 0.588; 0.598 |
Stage 5 | 0.034 (0.010–0.103) | 5 | 92.0 | <0.001 | Random | 1.699; 0.188 |
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Ng, J.W.; Chong, E.T.J.; Tan, Y.A.; Lee, H.G.; Chan, L.L.; Lee, Q.Z.; Saw, Y.T.; Wong, Y.; Zakaria, A.A.B.; Amin, Z.B.; et al. Prevalence of Coronavirus Disease 2019 (COVID-19) in Different Clinical Stages before the National COVID-19 Vaccination Programme in Malaysia: A Systematic Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2022, 19, 2216. https://doi.org/10.3390/ijerph19042216
Ng JW, Chong ETJ, Tan YA, Lee HG, Chan LL, Lee QZ, Saw YT, Wong Y, Zakaria AAB, Amin ZB, et al. Prevalence of Coronavirus Disease 2019 (COVID-19) in Different Clinical Stages before the National COVID-19 Vaccination Programme in Malaysia: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health. 2022; 19(4):2216. https://doi.org/10.3390/ijerph19042216
Chicago/Turabian StyleNg, Jun Wei, Eric Tzyy Jiann Chong, Yee Ann Tan, Heng Gee Lee, Lan Lan Chan, Qin Zhi Lee, Yen Tsen Saw, Yiko Wong, Ahmad Aizudeen Bin Zakaria, Zarina Binti Amin, and et al. 2022. "Prevalence of Coronavirus Disease 2019 (COVID-19) in Different Clinical Stages before the National COVID-19 Vaccination Programme in Malaysia: A Systematic Review and Meta-Analysis" International Journal of Environmental Research and Public Health 19, no. 4: 2216. https://doi.org/10.3390/ijerph19042216