Characteristics and prognostic factors of COVID-19 among infected cases: a nationwide Tunisian analysis

Abstract

Background: The outbreak of coronavirus disease (COVID-19) continues to constitute an international public health concern. Few data are available on the duration and prognostic factors of the disease. We aimed to study the recovery time among a Tunisian cohort of COVID-19 confirmed patients and identify the prognostic factors. Methods: A retrospective, nationwide study was conducted from March 2 to May 8, 2020, recruiting all patients who were diagnosed with COVID-19, by RT-PCR methods, in Tunisia. Data were collected via phone call interview. Kaplan-Meir Methods and Cox proportional hazards regression models were, respectively, used to study the recovery time and estimate its prognostic factors. Results: One thousand and thirty patients with COVID-19 (aged 43.2 ± 18.2 years, 526 female (51.1%)) were enrolled. Among them 141 (14.8%) were healthcare professionals. Out of 173 patients (17.8%) admitted to the hospital, 47 were admitted in an intensive care unit. Among 827 patients who didn’t require specialized care, 55.5% were self-isolated at home, while the rest were in specialized centers. Six hundred and two patients were symptomatic. A total of 634 (61.6%) patients have recovered and 45 (4.4%) patients died. The median duration of illness was estimated to be 31 days (95% CI: [29–32]). Older age (HR = 0.66, CI:[0.46–0.96], P = 0.031) and symptoms (HR = 0.61, CI:[0.43–0.81], P = 0.021) were independently associated with a delay in recovery time. Being a healthcare professional (HR = 1.52, CI: [1.10–2.08], P = 0.011) and patients in home isolation compared to isolation centers (HR = 2.99, CI: [1.85–4.83], P < 10¯3) were independently associated with faster recovery time. Conclusion: The duration of illness was estimated to be 1 month. However, this long estimated duration of illness may not equate to infectiousness. A particular attention must to be paid to elderly and symptomatic patients with closer monitoring.