Factors associated with delayed presentation to healthcare facilities for Lassa fever cases, Nigeria 2019: a retrospective cohort study

Background Large outbreaks of Lassa fever (LF) occur annually in Nigeria. The case fatality rate among hospitalised cases is ~ 20%. The antiviral drug ribavirin along with supportive care and rehydration are the recommended treatments but must be administered early (within 6 days of symptom onset) for optimal results. We aimed to identify factors associated with late presentation of LF cases to a healthcare facility to inform interventions. Methods We undertook a retrospective cohort study of all laboratory confirmed LF cases reported in Nigeria from December 2018 to April 2019. We performed descriptive epidemiology and a univariate Cox proportional-hazards regression analysis to investigate the effect of clinical (symptom severity), epidemiological (age, sex, education, occupation, residential State) and exposure (travel, attendance at funeral, exposure to rodents or confirmed case) factors on time to presentation. Results Of 389 cases, median presentation time was 6 days (IQR 4–10 days), with 53% attending within 6 days. There were no differences in presentation times by sex but differences were noted by age-group; 60+ year-olds had the longest delays while 13–17 year-olds had the shortest. By sex and age, there were differences seen among the younger ages, with 0–4-year-old females presenting earlier than males (4 days and 73% vs. 10 days and 30%). For 5–12 and 13–17 year-olds, males presented sooner than females (males: 5 days, 65% and 3 days, 85% vs. females: 6 days, 50% and 5 days, 61%, respectively). Presentation times differed across occupations 4.5–9 days and 20–60%, transporters (people who drive informal public transport vehicles) had the longest delays. Other data were limited (41–95% missing). However, the Cox regression showed no factors were statistically associated with longer presentation time. Conclusions Whilst we observed important differences in presentation delays across factors, our sample size was insufficient to show any statistically significant differences that might exist. However, almost half of cases presented after 6 days of onset, highlighting the need for more accurate and complete surveillance data to determine if there is a systemic or specific cause for delays, so to inform, monitor and evaluate public health strategies and improve outcomes.