Psychiatric manifestations and associated risk factors among hospitalised patients with COVID-19 in Edo State, Nigeria: a cross-sectional study.

OBJECTIVE: To estimate the prevalence of depression and anxiety and identify associated risk factors in hospitalised persons with confirmed COVID-19 in Edo, Nigeria. DESIGN: A multicentre cross-sectional survey. SETTING: Patients with COVID-19 hospitalised at the three government-designated treatment and isolation centres in Edo State, Nigeria. PARTICIPANTS: The study was conducted from 15 April to 11 November 2020 among 489 patients with confirmed COVID-19 and in treatment and isolation centres in Edo State, Nigeria. The mean age of participants was 43.39 (SD=16.94) years. Male participants were 252 (51.5%) and female were 237 (48.5%). MAIN OUTCOME MEASURES: The nine-item Patient Health Questionnaire for depression, (total score: 0-27, depression ≥10), Generalized Anxiety Disorder-7 for anxiety (total score: 0-21, anxiety ≥10), and social demographic and clinical characteristics for associated risk factors. RESULTS: Of the 489 participants, 49.1% and 38.0% had depressive and anxiety symptoms, respectively. The prevalence rates of depression, anxiety and combination of both were 16.2%, 12.9% and 9.0%, respectively. Moderate-severe symptoms of COVID-19, ≥14 days in isolation, worrying about the outcome of infection and stigma increased the risk of having depression and anxiety. Additionally, being separated/divorced increased the risk of having depression and having comorbidity increased the risk of having anxiety. CONCLUSION: A substantial proportion of our participants experienced depression, anxiety and a combination of both especially in those who had the risk factors we identified. The findings underscore the need to address modifiable risk factors for psychiatric manifestations early in the course of the disease and integrate mental health interventions and psychosocial support into COVID-19 management guidelines.

The Origins and Future of Sentinel: An Early-Warning System for Pandemic Preemption and Response.

While investigating a signal of adaptive evolution in humans at the gene LARGE, we encountered an intriguing finding by Dr. Stefan Kunz that the gene plays a critical role in Lassa virus binding and entry. This led us to pursue field work to test our hypothesis that natural selection acting on LARGE-detected in the Yoruba population of Nigeria-conferred resistance to Lassa Fever in some West African populations. As we delved further, we conjectured that the "emerging" nature of recently discovered diseases like Lassa fever is related to a newfound capacity for detection, rather than a novel viral presence, and that humans have in fact been exposed to the viruses that cause such diseases for much longer than previously suspected. Dr. Stefan Kunz's critical efforts not only laid the groundwork for this discovery, but also inspired and catalyzed a series of events that birthed Sentinel, an ambitious and large-scale pandemic prevention effort in West Africa. Sentinel aims to detect and characterize deadly pathogens before they spread across the globe, through implementation of its three fundamental pillars: Detect, Connect, and Empower. More specifically, Sentinel is designed to detect known and novel infections rapidly, connect and share information in real time to identify emerging threats, and empower the public health community to improve pandemic preparedness and response anywhere in the world. We are proud to dedicate this work to Stefan Kunz, and eagerly invite new collaborators, experts, and others to join us in our efforts.