A network meta-analysis of risk factors of infection among close contacts of COVID-19
Wei-wen Zhang,
Chen-xi Li,
Shu-jing Cao,
Yu-yuan Wang,
Ze-xi Lu,
Jia-lin Sun,
Ming -xia Jing
Affiliations
Wei-wen Zhang
Department of Preventive Medicine, School of Medicine, Shihezi University. Shihezi, 832003, PR China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, PR China
Chen-xi Li
Oncological Department of Oral & Maxillofacial Surgery, The First Affiliated Hospital of Xinjiang Medical University, School／Hospital of Stomatology, Xinjiang Medical University, Stomatological Research Institute of Xinjiang Uygur Autonomous Region, Urumqi, 830054, PR China
Shu-jing Cao
Department of Preventive Medicine, School of Medicine, Shihezi University. Shihezi, 832003, PR China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, PR China
Yu-yuan Wang
Department of Preventive Medicine, School of Medicine, Shihezi University. Shihezi, 832003, PR China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, PR China
Ze-xi Lu
Department of Preventive Medicine, School of Medicine, Shihezi University. Shihezi, 832003, PR China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, PR China
Jia-lin Sun
Department of Preventive Medicine, School of Medicine, Shihezi University. Shihezi, 832003, PR China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, PR China; Corresponding author.Department of Preventive Medicine, School of Medicine, Shihezi University. No.221 Beisi Road, Shihezi, 832003, PR China.
Ming -xia Jing
Department of Preventive Medicine, School of Medicine, Shihezi University. Shihezi, 832003, PR China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, PR China; Corresponding author. Department of Preventive Medicine, School of Medicine, Shihezi University. No.221 Beisi Road, Shihezi, 832003, PR China.
Objective: We aimed to use network meta-analysis to compare the impact of infection risk factors of close contacts with COVID-19, identify the most influential factors and rank their subgroups. It can provide a theoretical basis for the rapid and accurate tracking and management of close contacts. Methods: We searched nine databases from December 1, 2019 to August 2, 2023, which only took Chinese and English studies into consideration. Odd ratios (ORs) were calculated from traditional meta-estimated secondary attack rates (SARs) for different risk factors, and risk ranking of these risk factors was calculated by the surface under the cumulative ranking curve (SUCRA). Results: 25 studies with 152647 participants identified. Among all risk factors, the SUCRA of type of contact was 69.6 % and ranked first. Among six types of contact, compared with transportation contact, medical contact, social contact and other, daily contact increased risk of infection by 12.11 (OR: 12.11, 95 % confidence interval (CI): 6.51–22.55), 7.76 (OR: 7.76, 95 % CI: 4.09–14.73), 4.65 (OR: 4.65, 95 % CI: 2.66–8.51) and 8.23 OR: 8.23, 95 % CI: 4.23–16.01) times, respectively. Overall, SUCRA ranks from highest to lowest as daily contact (94.7 %), contact with pollution subjects (78.4 %), social contact (60.8 %), medical contact (31.8 %), other (27.9 %), transportation contact (6.4 %). Conclusion: The type of contact had the greatest impact on COVID-19 close contacts infection among the risk factors we included. Daily contact carried the greatest risk of infection among six types of contact, followed by contact with pollution subjects, social contact, other, medical contact and transportation contact. The results can provide scientific basis for rapid assess the risk of infection among close contacts based on fewer risk factors and pay attention to high-risk close contacts during management, thereby reducing tracking and management costs.
