Dr. Ann Aerts Head of Novartis Foundation


Dr. Ann Aerts

Head of Novartis Foundation

Interview by Kamran Rafiq (ISNTD) & Abdullah Bhatti (ISNTD Press Corps)

After a successful career in the private and charity sectors spanning public health, critical care, cardiovascular health and tuberculosis, Dr. Ann Aerts has been leading the Novartis Foundation since January 2013, where she has played a key role in devising new policy recommendations to ensure the Novartis Foundation succeeds in expanding access to quality healthcare for patients worldwide. In this interview, we speak with Ann about the Novartis Foundation’s numerous programmes across leprosy and other diseases, both infectious and non-communicable, as well as the Foundation’s leading role in the roll-out of innovative data- and technology-driven approaches to improving disease control.

Regulating transmission can be difficult for different diseases – for example, incubation period can often vary from 2-20 years for leprosy before any symptoms appear compared with 7 days or longer for malaria. What procedures/regulations do you use to keep track of a disease with a short incubation period versus one with a longer incubation period, based on previous data collected?

Our work in disease elimination aspires to accelerate the elimination of leprosy by focusing on interventions that interrupt transmission.

Leprosy is an infectious disease caused by Mycobacterium leprae, bacteria that multiply very slowly. Once infected, the average incubation period is two to three years, although it can take between 6 months and 20 years for symptoms to appear. The challenge of covering the last mile to make leprosy history is to interrupt its transmission.

Therefore, our LPEP program (leprosy post-exposure prophylaxis) program is designed to evaluate the feasibility of contact tracing and preventative treatment with a single dose rifampicin (post-exposure prophylaxis, or PEP) for asymptomatic contact persons or prompt referral for diagnosis and treatment with multi-drug therapy (MTD) of symptomatic persons under routine conditions in pilot areas in several countries, and to determine the impact this has on leprosy incidence.

The LPEP program has been rolled out in Tanzania, Indonesia, India, Nepal, Sri Lanka, Myanmar, Cambodia and Brazil.

Digital networks have advanced quickly in the past few years, with new cloud and mobile-based technologies being utilized throughout the global health industry to help tackle issues related to data gathering and its correlation. What tool (or tools) do you use to gather & correlate data, and did it help or hinder your progress?

At the Novartis Foundation, we believe digital health tools support our programmatic and policy work to improve health outcomes in low-income settings. Therefore, we have leveraged digital health in most of our programs for the past decade, helping to empower patients and connect healthcare workers. Using digital applications also has the advantage that data can be tracked easily, to then help demonstrate the efficiency and outcomes of our health programs.

For example, the Leprosy Alert and Response Network System (LEARNS) is the Philippines’ first mobile phone-based leprosy referral system. It allows frontline health workers to send photos of suspected leprosy lesions via mobile phone to specialists in the reference centers. This contributes to accelerated diagnosis and treatment of new leprosy patients.

Are there other specific examples of how these new technologies have made it easier to gather and correlate data for the Novartis Foundation’s programmes?

Digital technology absolutely has the benefit of more quickly processing data and allowing swift feedback for decision-making; for example, together with the Swiss Tropical and Public Health Institute (Swiss TPH), the Novartis Foundation supported the development of an innovative tool for health managers to perform supportive supervision: e-TIQH (electronic Tool to Improve Quality in Health), was developed for local and regional healthcare managers to assess objective data on the performance of healthcare facilities. The tool allows for the adequate allocation of (often limited) resources and helps health managers give direct feedback to staff in the health facilities.

The quality and precision of the data gathered is also very important - for example, it’s now easier to pinpoint the exact time and place data has been gathered whilst mapping diseases and viruses on a global scale (for example, the Global Trachoma Mapping Project). What methods of data quality analysis do you use, and what is the level of precision is this data collected (i.e. time, place, level of epidemic, people affected etc.)?

We firmly believe that integration of data collection into existing health information systems is key to sustainable success. Hence, the data gathered through our leprosy-related programs are fully integrated in the information systems of the national leprosy programs where we work, and depend on the quality of those reporting systems for their speed and precision.