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P48 Predicting COVID-19 infection among older Syrian refugees in Lebanon: a multi-wave telephone survey
  1. B Abi Zeid1,2,
  2. T El Khoury1,
  3. S Abdulrahim3,
  4. H Ghattas1,2,
  5. S McCall1
  1. 1Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
  2. 2Arnold School of Public Health, University of South Carolina, Columbia, USA
  3. 3Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon

Abstract

Background Older refugees, impacted by a cluster of biological and social vulnerabilities, are more susceptible to COVID-19 infection and its complications. This study aimed to identify the socio-ecological predictors of COVID-19 infection among older Syrian refugees in Lebanon and describe the barriers to diagnostic testing among those who reported an infection.

Methods This was a cross-sectional analysis of a five-wave longitudinal study conducted in Lebanon between September 2020 and March 2022. All households that received assistance from a humanitarian organization and had a Syrian refugee aged 50 years or older were invited to participate in a telephone survey. Self-reported COVID-19 infection was the primary outcome. Candidate predictors for predicting COVID-19 infection incorporating social determinants were identified from the literature and collected through the survey. The final model was developed using adaptive LASSO regression. The calibration and discrimination of the model were assessed using the calibration slope (C-Slope) and the C-Statistic, respectively.

Results Of 2,886 participants (median [IQR] age: 56[52-62]; 52.9% males), 283 individuals (9.8%) reported a COVID-19 infection at least once. Six predictors for COVID-19 infection were identified: living outside informal tented settlements, having elementary and preparatory education or above, having chronic conditions, not receiving cash assistance, being water insecure and having unmet waste management needs. The model had moderate discrimination with a C-Statistic of 0.62 (95%CI:0.59-0.66) and good calibration with a C-Slope of 1.00 (95%CI:0.70-1.30). Nearly half of the infections were diagnosed through COVID-19 diagnostic testing (n=138 [49.1%]). The main reasons for not testing were a perception that the tests were unnecessary (n=91 [63.6%]) or unable to afford them (n=46 [32.2%]).

Discussion This study identified predictors of COVID-19 infection among Syrian refugees in Lebanon, which included social determinants. Consideration of social determinants may be important for future pandemic preparedness. COVID-19 may be underreported due to the limited diagnostic testing in this population. Yet, intensifying awareness campaigns, considering the implementation of screening measures in the community, addressing the basic needs of older refugees and ensuring coverage for hard-to-reach refugees remains essential to reduce vulnerability to infectious disease.

  • Refugee health
  • global health
  • COVID-19 infection.

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