A retrospective cross-sectional study of risk factors for communicable disease diagnoses among refugees in mainland Greek camps, 2016-2017.

Communicable disease risk is high in refugee camps and reception centers. To better understand the risks for communicable disease diagnoses among refugees and asylum seekers, this study assesses individual- and camp-level risk factors among individuals utilizing Médecins du Monde clinics in four large refugee camps-Elliniko, Malakasa, Koutsochero, and Raidestos-on mainland Greece between July 2016 and May 2017. Descriptive statistics are reported for the demographic characteristics of the study population and for communicable disease burdens within the four camps-Elliniko, Malakasa, Raidestos, and Koutsochero. A hierarchical generalized linear model was used to assess risk factors for communicable disease diagnoses while accounting for individual-level clustering. This study shows marginal patterns in risk factors for communicable disease. Males had marginally higher risk of communicable disease diagnosis than females (OR = 1.12; 95% CI 0.97-1.29), and increased age was more protective against communicable disease for females (OR = 0.957; 95% CI 0.953-0.961) than for males (OR = 0.963; 95% CI 0.959-0.967). Communicable disease risk was significantly different between camps, with Elliniko (OR = 1.58; 95% CI 1.40-1.79) and Malakasa (OR = 1.43; 95% CI 1.25-1.63) having higher odds of communicable disease than Raidestos. The demographic and epidemiologic profiles of displaced populations differ across settings, and epidemiologic baselines for displaced populations are fundamental to evidence-informed provision of humanitarian aid. Further, while influences and risks for negative health outcomes in complex emergencies are broadly, the causal mechanisms that underpin these relationships are not as well understood. Both practitioners and researchers should engage with further research to elucidate the mechanisms through which these risks operate among displaced populations, including multilevel analyses.