Likely effect of the 2014 Ebola epidemic on HIV care in Liberia.

OBJECTIVE: Liberia's health system has been severely struck by the 2014 Ebola epidemic. We aimed to assess the potential effect of this epidemic on the care of HIV patient in two clinics [John F. Kennedy (JFK) and Redemption Hospitals] in Monrovia, which stayed open throughout the epidemic. DESIGN AND METHODS: A preexisting electronic database of HIV patient's follow-up visits was used to estimate three weekly parameters from January 2012 to October 2014: number of visits, number of new patient, and proportion of patients with follow-up delay. We used segmented negative binomial regressions to assess trends before and after the week of the Ebola outbreak defined in June 2014 by WHO. RESULTS: The cumulative number of patients in care comprised 5948 patients with a total of 56 287 visits between January 2012 and October 2014. From June 2014, the number of visit per week, stable since 2012, abruptly decreased (59%) in Redemption (P < 0.001) and progressively decreased by 3% per week in JFK (P < 0.001). In both the clinics, the weekly proportion of patient with follow-up delay sharply increased after the point break from June 2014 (P value < 0.001). From June 2014, a significant decrease in new patients per week occurred in both the clinics: by 57% (P value < 0.001) in Redemption and by 4.6% per week (P value < 0.001) in JFK. CONCLUSION: The Ebola epidemic had a significant effect on HIV care in Monrovia. Given the particular impact on the rate of patients with follow-up delay, a long-term impact is feared.

Improving prediction of surgical site infection risk with multilevel modeling.

BACKGROUND: Surgical site infection (SSI) surveillance is a key factor in the elaboration of strategies to reduce SSI occurrence and in providing surgeons with appropriate data feedback (risk indicators, clinical prediction rule). AIM: To improve the predictive performance of an individual-based SSI risk model by considering a multilevel hierarchical structure. PATIENTS AND METHODS: Data were collected anonymously by the French SSI active surveillance system in 2011. An SSI diagnosis was made by the surgical teams and infection control practitioners following standardized criteria. A random 20% sample comprising 151 hospitals, 502 wards and 62280 patients was used. Three-level (patient, ward, hospital) hierarchical logistic regression models were initially performed. Parameters were estimated using the simulation-based Markov Chain Monte Carlo procedure. RESULTS: A total of 623 SSI were diagnosed (1%). The hospital level was discarded from the analysis as it did not contribute to variability of SSI occurrence (p  = 0.32). Established individual risk factors (patient history, surgical procedure and hospitalization characteristics) were identified. A significant heterogeneity in SSI occurrence between wards was found (median odds ratio [MOR] 3.59, 95% credibility interval [CI] 3.03 to 4.33) after adjusting for patient-level variables. The effects of the follow-up duration varied between wards (p<10-9), with an increased heterogeneity when follow-up was <15 days (MOR 6.92, 95% CI 5.31 to 9.07]). The final two-level model significantly improved the discriminative accuracy compared to the single level reference model (p<10-9), with an area under the ROC curve of 0.84. CONCLUSION: This study sheds new light on the respective contribution of patient-, ward- and hospital-levels to SSI occurrence and demonstrates the significant impact of the ward level over and above risk factors present at patient level (i.e., independently from patient case-mix).