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Volume 18, Issue 3 (2026)
3 2026, 18(3): 1001-1011 |
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Received: 2026/09/10 | Accepted: 2026/09/19 | Published: 2026/09/19
Received: 2026/09/10 | Accepted: 2026/09/19 | Published: 2026/09/19
How to cite this article
Al-Eqabi Q.A.K.. Technology-Enabled Infection Risk Surveillance among Accidents-Affected Clients: The Mediating Role of Community Health Workers' Early Threat Detection Capacity. 3 2026; 18 (3) :1001-1011
URL: http://ijwph.daneshafarand.org/article-3-87226-en.html
URL: http://ijwph.daneshafarand.org/article-3-87226-en.html
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Abstract (14 Views)
Background: Increased incidence of infectious diseases and disruptions of existing health systems are likely to occur among populations living in or affected by accident and disaster affected areas, where exposure risks may be elevated. This study aimed to examine the role of technology-enabled risk-surveillance in infection surveillance by assessing the mediating effect of early threat detection capacity.
Methods: A quantitative cross-sectional study was conducted among 250 Community Health Workers in Kut City; Iraq in 2026. Data where collected wsing established measures of technology enabled infection risk surveillance, early threat detection capacity, and infection risk surveillance. Pearson correlation, multiple linear regression, and Hayes PROCESS macro Model 4 with 5000 bootstrap samples were applied.
Results: Technology- enabled surveillance was positively and significantly associated with early threat detection capacity (r = .62, p < .001) and risk for detecting infections (r = .58, p < .001). There was also a strong association between the capacity for detecting potential threats early and infection risk surveillance (r = .65, p < .001). In the multiple linear regression model, technology-enabled surveillance was independently associated with infection risk surveillance ( B= .39, p < .001). Mediation analysis indicated a significant indirect effect (B = 0.30, 95% bootstrap CI: 0.20-0.42), supporting partial mediation.
Conclusion: Technology-enabled surveillance was associated with higher levels of infection risk surveillance, with early threat-detection capacity partially accounting for this association. The combination of digital surveillance technologies with training of health workers and emergency readiness could better support community-based infection surveillance.
Methods: A quantitative cross-sectional study was conducted among 250 Community Health Workers in Kut City; Iraq in 2026. Data where collected wsing established measures of technology enabled infection risk surveillance, early threat detection capacity, and infection risk surveillance. Pearson correlation, multiple linear regression, and Hayes PROCESS macro Model 4 with 5000 bootstrap samples were applied.
Results: Technology- enabled surveillance was positively and significantly associated with early threat detection capacity (r = .62, p < .001) and risk for detecting infections (r = .58, p < .001). There was also a strong association between the capacity for detecting potential threats early and infection risk surveillance (r = .65, p < .001). In the multiple linear regression model, technology-enabled surveillance was independently associated with infection risk surveillance ( B= .39, p < .001). Mediation analysis indicated a significant indirect effect (B = 0.30, 95% bootstrap CI: 0.20-0.42), supporting partial mediation.
Conclusion: Technology-enabled surveillance was associated with higher levels of infection risk surveillance, with early threat-detection capacity partially accounting for this association. The combination of digital surveillance technologies with training of health workers and emergency readiness could better support community-based infection surveillance.