Epidemiological Modeling to Guide Efficacy Study Design Evaluating Vaccines to Prevent Emerging Diseases An Vandebosch, PhD Joint Statistical meetings, Vancouver, July 30-2018 avandebo@its.jnj.com

Background Efficacy of prophylactic interventions is evaluated through the reduction in disease attack or infection rates between subjects receiving the intervention versus a control group Long duration: event-driven and potentially lengthy follow-up until required number of infections occurred Costly: sample size depends on the number of events and infection rate Design and sample size of the trial requires accurate assumption of the infection rate in the population under study Sample size Follow-up time Study population and study area: exposed to the infection A thorough understanding of the transmission of the infection could support study design and sample size justification

Study population and endpoint may vary in space and time Seasonal diseases Variation in annual infections, strain, severity Influenza, RSV Emerging diseases hotspots, outbreaks, epidemics Dengue, Zika, Ebola, … Finland Figure: # positive respiratory pathoghen results in Finland between 2011- 2014, Gunell. EJCMID 2016 2014-2015 Ebola outbreak West-Africa

Infectious disease transmission models Infectious disease transmission models allow to mathematically capture disease processes Evaluate short-term incidence Real-time modeling allows to characterize potential future long-term trends of an emerging epidemic Can be extended to allow evaluation of intervention strategies and/or preventive measures Metcalf and Lessler, Science 357 (2017) O'Neill, Statistics in Medicine (2010) This presentation illustrates two case studies and how information retrieved from the models was employed to guide study design and planning for efficacy trials in the context of Ebola and Dengue

Case 1 - Simulation‐guided phase 3 trial design to evaluate vaccine effectiveness to prevent Ebola virus disease infection Evaluate effectiveness of a prime-boost regimen in preventing laboratory-confirmed EVD in an outbreak setting in Sierra Leone Large-scale population-based approach: up to 400,000 prime and boost doses available  ± 160 clusters of 5000 participants Cluster-randomized controlled trial. 1:1 randomization to Immediate vaccination Control (e.g. delayed vaccination) Clusters=geographical, administrative divisions Vandebosch et al. Clinical Trials 2016

Challenges in the Tail Phase of the Epidemic Declining EVD incidence Herd immunity effect in case of mass vaccination WHO SitRep Sierra Leone up to Jan 21, 2015 Static predictions unlikely to capture epidemiological picture Spatial heterogeneity Small local outbreaks Competitive landscape

Study power and Adaptive Rules Adaptive rule to identify primary endpoint Study power and type I error maintained

Real-Time Fitting and Forecasting Situation on Feb 15, 2015

Real-Time Fitting and Forecasting Effect of the start date of the trial Cumulative number of cases for control (blue) and vaccine arms Persistence probability Situation on Feb 15, 2015

Case 2: Modeling for Dengue Prophylaxis Antiviral against dengue virus: pre-exposure prophylaxis against dengue infection in travellers and endemic populations Aim: Estimate the transmission rates and dynamics in the target study population to inform planning and design of clinical efficacy trials Collaboration with London School of Hygiene and Tropical Medicine to develop an infectious disease model to characterize dengue outbreaks geographically and over time Model designed to inform on the number and geographical spread of secondary infections following the detection of a first "index" infected case number of secondary cases that can be prevented through a prophylactic intervention by protecting individuals against infection and limiting disease transmission by age group (adults, children) and timing

Case 2: Dengue Cluster-randomized ring-prophylactic design Employs the mechanism of an infection spreading into the population Simulations to identify optimal cluster size (balance cost new cluster vs additional subject) determine sample size with geographical spread and clustering (e.g. intra-class coefficient) from disease transmission model Index case Contacts of index case Clusters randomized to intervention to control Radius of ~40m is optimal Nina D’Hollander, Joris Menten

Future for Epi Models in Support of Pharmaceutical Development Mechanistic models well established for use in evaluation of vaccination programs Implemented for trial design in 2 case studies Their use in trial design, planning, and analysis, is a relatively new and growing area of research: THANK YOU! “Rapid modeling exercises can be critical in making timely decisions and guiding interventions and field studies in a rapidly changing environment. For instance, models played a critical role in the design of vaccine trials during the Ebola outbreak (Camacho et al. Vaccine 2017). However, such real-time efforts remain sporadic and ad hoc.”