PATH Malaria Perspectives with Belendia Serda

March 28, 2023 by PATH

When Belendia Serda began his career as a software developer, he never imagined he would eventually work on malaria elimination.

Belendia Serda has 15 years of experience as software developer. He’s one of PATH’s leading experts in malaria digital health and a PATH Digital Health Advisor in Ethiopia. Photo: Courtesy of Anne Jennings.

Belendia Serda has 15 years of experience as software developer. He’s one of PATH’s leading experts in malaria digital health and a PATH Digital Health Advisor in Ethiopia. Photo: Courtesy of Anne Jennings.

Belendia Serda began his career building software for various purposes, including library management systems and financial and customer services. But when his friend, a PATH employee, needed a software developer to program personal digital assistants—handheld computers used by health professionals to collect data—Belendia was interested.

Now, 12 years later, Belendia is one of PATH’s leading experts in malaria digital health, serving as a Digital Health Advisor in Ethiopia. In his role, he develops, customizes, deploys, and maintains data collection tools. This involves a whole range of activities, including integrating data from various sources, creating dashboards to assist health workers with malaria monitoring, and training health workers to use digital and data collection tools.

In this edition of PATH Malaria Perspectives, Belendia shares his reflections on harnessing the power of digital and data technologies to end the disease. 

Q: What challenges are you working to address in Ethiopia?

Ethiopia is a malaria-endemic country with particularly high prevalence in the western regions of the country.

One of the key challenges is that we have difficulties in sourcing reliable and accurate health-related data from the community, including malaria data. This problem is exacerbated by issues like poor internet connectivity and electricity shortages in certain remote areas.

This makes it really hard to then rely on mobile phones as data reporting tools because people can’t charge their phones in some villages. So, in some places, people are still using pen and paper to record data, which is not ideal.

Additionally, there are high rates of turnover in the health workforce in Ethiopia. We may end up training 100 health experts who, after a few months, are no longer working due to a high workload, lack of motivation, or limited opportunities to grow in their career.

Therefore, there is very limited evidence of data being used for informed action at the community level. The Digital Community Health Initiative Ethiopia digital health assessment provides more information about some of the key challenges and recommendations for Ethiopia’s digital health landscape.

Q: How can digital health improve efforts to prevent, treat, and eliminate malaria?

Right now, PATH is deploying a cloud-based Unstructured Supplementary Service Data (USSD) application that improves aggregated data collection. This data tool can be accessed on smartphones as well as older mobile phones with mechanical keyboards. As a result, health workers in areas with poor internet connectivity can report their data using their personal phones.

We are also deploying a cloud-based open-source data visualization tool. This tool will include data from the public health emergency management system as well as the health management information system, which is housed in DHIS2, an open-source health information management system developed through a global collaboration led by the University of Oslo. This tool will enable health workers to see data from both systems in one place.

We are also working closely with the Ethiopia Public Health Institute to maintain their DHIS2 server for case-based data collection. PATH is a major partner in the effort to maintain this key tool. The Ethiopian Ministry of Health, for example, uses DHIS2 to collect and analyze health data.

Q: What further investments are most needed to advance this work?

To eliminate malaria in Ethiopia, we need a strong health information system, evidence-based decision-making, and robust health service delivery. Investments are needed to scale up digital health approaches and digital tools.

We’ve made some great progress. For example, the DHIS2 server availability was successfully raised to over 99 percent through our efforts. Server availability is defined as the ability for the system to operate continuously without failing.

However, gaps still remain. We need more investment in digital health, especially at the community level, to ensure that health workers are equipped with tools such as phones and tablets.

Q: What inspires and motivates you?

I am inspired by the power of digital and data technologies. In software engineering, we face new challenges on a regular basis, and I find it very rewarding when we overcome them, especially when we can have a positive impact on public health. I find it incredibly motivating to think about the challenges we can overcome with current and future digital tools.

For example, in 2017 and 2018, there were internet blackouts in some areas of Ethiopia where we work. Without internet, we were unable to receive data from the field. To address this, we worked quickly to customize the DHIS2 application —the mobile application—to send data via SMS rather than via the internet. Once we implemented that in the reporting system, we started receiving data again.

Finally, I have amazing colleagues, and it’s a pleasure to work with them every day.  

Q: In the future, how might AI and machine learning contribute to malaria elimination efforts?

I do believe that malaria detection and treatment will improve as we continue applying new technology and innovation to the issue. AI and machine learning should become de facto tools for data analysis and visualization for effective malaria policy and interventions.

For example, imagine if a language model like ChatGPT were trained in local languages such as Amharic, Afaan Oromo, Tigrinya, Afar, and Somali. We could connect it to a health data warehouse, and it could then interact with users through social media platforms such as Telegram or WhatsApp.

This could allow health workers to query their data using their native language. The AI model could extract the data, generate a report, and even explain it to them. For example, a health worker could say, “Show me the trend of malaria in my health post,” and the system would warn them if there is an outbreak.

Wouldn’t that be amazing?