Grant: Foundation Grant

<html> <body> <p>The global HIV response is changing. Until recently, it was often guided by where, and in whom, an estimated 2 million new HIV infections each year were occurring - not what was <em>driving</em> sustained, local transmission. To achieve its goal of zero new HIV infections, the HIV response is now looking to better address local HIV epidemic drivers.</p> <p>Disentangling epidemic drivers will help program-implementers and policy-makers choose where, what, and on whom to prioritize, and how to deliver HIV control programs to maximize health benefits at an affordable cost. Program Science involves the design, implementation, and evaluation of public health programs under a scholarly process of <em>getting research out of programs</em> as well as research into programs. Mathematical models offer an unparalleled opportunity to make the best, most efficient use of growing data from HIV programs, empirical studies, and content expertise to rigorously study the potential influence of biology, behavior, and the environment in <em>driving HIV epidemics</em>, and the potential impact of interventions on curbing HIV spread. To meet decision-makers&rsquo; needs, we have developed the first integrated laboratory in Mathematical Modeling and Epidemiology for HIV Program Science.<br> </p> <p>Our vision is to <strong>creatively explore and tease apart the HIV epidemic processes that underpin our ability to control local HIV epidemics;</strong> and to foster the next generation of <em>embedded</em> mathematical modelers in Canada and low-and middle-income countries &ndash; modelers embedded in empirical science and in the HIV programs/policies we serve to inform.<br> </p> <p>Our objectives are to:<br> </p> <p>1) <strong>Appraise HIV Epidemics (&ldquo;know your epidemic&rdquo;)</strong>: to understand why HIV epidemics establish and persist where and when they do, and what leads to differences in their trajectories, size, and characteristics across regions.<br> </p> <p>2) <strong>Maximize HIV Program Impact (&ldquo;plan the response&rdquo;)</strong>: to optimize the design and delivery of HIV programs by health-system and epidemic context.<br> </p> <p>3) <strong>Forecast Data Priorities (&ldquo;monitor and adapt the response&rdquo;)</strong>: to systematically assess the influence of data uncertainty on model projections in order to prioritize future data collection.<br> </p> <p>We will do this with (i) existing and new Canadian and international collaborations across scientific disciplines and a wealth of empirical data at multiple levels (molecular, biomedical, behavioral, social/structural, health-systems, cost); (ii) methodological and translational training and mentorship of graduate students, stakeholders, and across our interdisciplinary team; and (iii) integrated knowledge translation (KT) with stakeholders at the international, national, and local levels via iterative feedback throughout each project, research-uptake strategies, and KT products.<br> </p> <p> <strong>Potential Impacts:</strong> We will <u>produce new knowledge</u> on the key drivers of HIV epidemics across socio-cultural contexts (Sub-Saharan Africa, India, Ukraine, and Canada), thus informing the <u>re-design of HIV policies and programs</u> to better address drivers. Findings have the potential to <u>maximize the health-benefit return on investment</u>, and lead to <u>adaptive HIV programs</u> that are responsive to the evolving epidemics and program data. With cross-cutting science and stakeholder engagement, our innovative laboratory will lead a rigorous and translational research agenda to inform a targeted, more efficient HIV response that could ultimately improve the health and well-being of people with and at risk of HIV globally.</p> </body> </html>