TY - JOUR
T1 - A meta-meta-analysis of co-infection, secondary infections, and antimicrobial resistance in COVID-19 patients
AU - Suleiman, Adeiza Shuaibu
AU - Islam, Md Aminul
AU - Akter, Mir Salma
AU - Amin, Mohammad Ruhul
AU - Werkneh, Adhena Ayaliew
AU - Bhattacharya, Prosun
PY - 2023/10/1
Y1 - 2023/10/1
N2 - The newly discovered coronavirus SARS-CoV-2 has sparked a worldwide pandemic of COVID-19, which has caused havoc on medical infrastructures, economies, and cultures around the world. Determining the whole scenario is essential since SARS-CoV-2 variants and sub-variants keep appearing after vaccinations and booster doses. The objective of this secondary meta-analysis is to analysis co-infection, secondary infections, and antimicrobial resistance (AMR) in COVID-19 patients. This study used five significant databases to conduct a systematic review and an overlap meta-analysis to evaluate the pooled estimates of co-infections and secondary infections. The summary of the meta-analysis showed an overall co-infection effect of 26.19% (95% confidence intervals CI: 21.39–31.01, I2 =98.78, n = 14 meta-analysis) among patients with COVID-19. A coinfection effect of 11.13% (95% CI: 9.7–12.56, I2 =99.14, n = 11 meta-analysis) for bacteria; 9.69% (95% CI: 1.21–7.90, I2 =98.33) for fungal and 3.48% (95% CI: 2.15–4.81, I2 =95.84) for viruses. A secondary infection effect of 19.03% (95% CI: 9.53–28.54, I2 =85.65) was pooled from 2 meta-analyses (Ave: 82 primary studies). This is the first study that compiles the results of all the previous three years meta-analyses into a single source and offers strong proof of co-infections and secondary infections in COVID-19 patients. Early detection of co-infection and AMR is crucial for COVID-19 patients in order to effective treatment.
AB - The newly discovered coronavirus SARS-CoV-2 has sparked a worldwide pandemic of COVID-19, which has caused havoc on medical infrastructures, economies, and cultures around the world. Determining the whole scenario is essential since SARS-CoV-2 variants and sub-variants keep appearing after vaccinations and booster doses. The objective of this secondary meta-analysis is to analysis co-infection, secondary infections, and antimicrobial resistance (AMR) in COVID-19 patients. This study used five significant databases to conduct a systematic review and an overlap meta-analysis to evaluate the pooled estimates of co-infections and secondary infections. The summary of the meta-analysis showed an overall co-infection effect of 26.19% (95% confidence intervals CI: 21.39–31.01, I2 =98.78, n = 14 meta-analysis) among patients with COVID-19. A coinfection effect of 11.13% (95% CI: 9.7–12.56, I2 =99.14, n = 11 meta-analysis) for bacteria; 9.69% (95% CI: 1.21–7.90, I2 =98.33) for fungal and 3.48% (95% CI: 2.15–4.81, I2 =95.84) for viruses. A secondary infection effect of 19.03% (95% CI: 9.53–28.54, I2 =85.65) was pooled from 2 meta-analyses (Ave: 82 primary studies). This is the first study that compiles the results of all the previous three years meta-analyses into a single source and offers strong proof of co-infections and secondary infections in COVID-19 patients. Early detection of co-infection and AMR is crucial for COVID-19 patients in order to effective treatment.
KW - Antimicrobial resistant (AMR)
KW - Co-infection
KW - COVID-19
KW - Pathogens
KW - SARS-CoV-2
KW - Secondary infection
UR - https://www.scopus.com/pages/publications/85167461499
U2 - 10.1016/j.jiph.2023.07.005
DO - 10.1016/j.jiph.2023.07.005
M3 - Review article
C2 - 37572572
AN - SCOPUS:85167461499
SN - 1876-0341
VL - 16
SP - 1562
EP - 1590
JO - Journal of Infection and Public Health
JF - Journal of Infection and Public Health
IS - 10
ER -
