top of page

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.

With mobile and cloud based data gathering, network is required. In some environments this can be problematic. What measures do you take to ensure that the data being gathered is relayed quickly and effectively, as this is dependent on cellular and internet connectivity (in other words, when there is no cellular or internet connectivity, what do you do to get this data as quickly as possible to where it is needed and how do you safely store it before a connection is established)? The potential for harnessing the exponential growth in information and communications technology (ICT) to meet health challenges is clear. Mobile is the fastest adopted technology of all time: in 1991, mobile cellular penetration stood at less than 1%, compared to 99.7% in 2016 – and there will be an estimated 5.6 billion smartphones by 2020. Around 90% of that growth will come from low- and middle-income countries (LMICs). However 3.9 billion people still lack access to the Internet, and mobile broadband costs people in low- and middle-income countries 10 times as much as people in high income countries (as a percentage of income).

The enormous potential of digital health in both delivering healthcare and accelerating the way health data are used is in fact the topic of a digital health report the Novartis Foundation just published together with Nokia as part of the Broadband Commission for Sustainable Development.

Our research, interviews and case studies on which the report is based, lead to the identification of critical success factors for countries to maximize the potential of digital health in accelerating the achievement of SDG 3; these include the importance of senior government leadership with committed financing, effective governance mechanisms with strong cooperation between the ICT and health care sectors, well-defined roles for the different stakeholders and a national ICT framework to make sure systems are interoperable .

Only then can digital health be integrated in health systems at scale and respond to the priority health needs of the country, while ensuring long-term sustainability.

Linking data from different sectors can open up new prospects to improving health outcomes for populations. Is there an occasion where linking data helped you or others? (For example, in Durham County North Carolina, geographic pooling of census data, lead concentration in blood tests and even tax payments lead to health care authorities working with city authorities to separate risks of lead exposure in an effort to improve emergency department services. They were able to improve vastly the detection and management of childhood lead exposure at an individual level).

We absolutely see the value in multi-sector and multi-disciplinary approaches; as such we recently hosted a Novartis Foundation dialogue event to promote cross-fertilization in thinking, research, policy and operational practice for urban health in Africa.

The event aimed at bringing together experts from the areas of urban health, urban planning, education, policy makers, public and private sectors from the key disci-plines and sectors affecting the health of urban populations. As an outcome of the event, the sectors that require the most urgent interventions were beside government, the food, education and ICT sectors.

Implementing big data system in low and middle-income countries can be a challenge due to ethical, regulatory and technological issues. How do you go about making sure that when implementing data gathering system(s), you ensured that your process was ethical and of minimal risk?

It is critical for the Novartis Foundation to make sure we have the right partners on board; in all of our programs in the countries where we operate, we work closely together with the governments as well as with local implementation partners from other sectors to ensure accurate and appropriate data gathering. When collecting individual data we systematically seek IRB approval for our programs and innovative healthcare delivery models.

Where do you see the future of data sharing, gathering and correlation and do you see it link with open source data?

We strongly believe in sharing data and encourage open source platforms wherever possible.

A key ethos at the ISNTD is to support a multi-disciplinary/holistic approach in tackling global health inequalities. To foster this, we encourage working in collaboration with public-private partnerships, NGOs and governments. Is there anyone in particular you see yourself collaborating with?

Complex problems such as neglected tropical diseases (NTDs) or non-communicable diseases (NCDs) require a systems approach as opposed to a simple solution. That is why, with our new initiative “Better Hearts Better Cities”, we aim at improving cardiovascular health in low-income urban settings in a comprehensive way. We will be working with partners from across sectors, including digital technology and device companies, insurance providers and other partners from the private sector and civil society.

We believe that by bringing together global and local partners from various sectors and disciplines, we can work to address the underlying risk factors of chronic non-communicable diseases in urban settings, which often lie beyond the realm of healthcare. With their expertise in diverse fields, we hope to identify novel approaches to create robust and sustainable interventions which can have measureable impact on the health of city populations.

Collecting evidence and data on the progression, severity and natural evolution of diseases is key to help educate people and governments about the gravity of a situation of an epidemic/disease. Has the data collected by your organization affected national policy change regarding a specific disease or diseases in a country?

Only through robust data collection and evaluation can we build and grow sustainable, resilient healthcare systems. When a project is in the pilot phase, we measure its effect and potential impact. We then use this real-world data to validate our work, to inform national health policies and shape sustainable healthcare systems for the future.

For example, our Telemedicine program in Ghana successfully pioneered in the Amansie West region between 2012 and 2016. Our Telemedicine model has been selected by national health authorities (out of seven other telemedicine models) to be rolled out nationwide, thanks to the local ownership and enthusiasm of the Ghana health authorities, as well as the simplicity of the approach that is based on local realities. This model is currently being rolled-out nationally by the Ghana Health Services, with telemedicine services now covering 25 districts in five regions. In 2017, the Ghana Health Service will reach national coverage by the end of the year.

.……………………………………………………

For more information please contact:

Kiara Jade Barnes

Senior Communications Manager

Novartis Foundation Novartis Campus Forum 1-3.97 4002 Basel Switzerland Tel: +41 61 696 23 00

E: info@novartisfoundation.org

Featured articles
Recent articles
Search By Tags
Follow Us
  • Facebook Classic
  • Twitter Classic
  • Google Classic
bottom of page