A Biostatistician’s Personal Journey through Gender Bias

This is the sixth blog post of the AI Research and COVID: Journeys to Gender Equality and Inclusion series. This blog series emerged from the “writeshop” organized by Gender at Work as part of the Data Science and Artificial Intelligence Research Program to Combat COVID-19, also known as AI4COVID, financed by the International Development Research Centre (IDRC) and Swedish International Development Cooperation Agency (SIDA). The initiative was part of the final Gender Action Learning workshop held in Nairobi, Kenya in February 2023.

July 28, 2023

In this blog post, Sylvia Kiwuwa Muyingo reflects on her early fieldwork collecting health information from HIV-affected communities in Uganda and how this experience motivates her focus on vulnerable communities and appreciation of women’s unpaid caregiving roles. She discusses her current work in using data science and AI tools to address health disparities and biases in public health decision making during COVID-19, and the promotion of gender and intersectionality sensitivity in AI models and algorithms.

Early fieldwork: Grief, loss and gender roles

I started my career as a biostatistician working in the field with vulnerable communities affected and infected with HIV disease. In Uganda in the early 2000s, HIV was a major threat to the general population, with 7% of the citizens having contracted the virus. In 1999 alone, approximately 100,000 people are believed to have died from AIDS related illnesses, 1.4 million were living with HIV, and at least 1 million children were orphaned.

I landed a fieldwork job that involved navigating dusty murram roads and moving from house to house in the scorching heat. My job was to engage residents of communities affected by HIV and collect health information and blood specimens for testing. This was my first real fieldwork experience and one of the busiest. The job impacted my life profoundly, teaching me how to thrive during adversity, and how to adapt and problem solve using local knowledge. This led to important personal and professional growth. I became more effective as a researcher at delivering valuable insights and solutions.

My role involved developing research tools with my team to document participant behaviour, interviewing families, programming laboratory machines to produce HIV test results for participants, and supervising field teams. Communicating with field teams from distant fieldwork locations over radio call (radiotelephone) with voice overtones was such an intriguing experience in the absence of mobile phones. For the participants, however, coming to their homes from the clinic put a human face to the disease. This experience solidified my resolve to work among vulnerable communities. I was willing to do anything to learn as much as possible on a deep level from this experience and benefit from my education.

Blasting off

When I finally got into the field, I felt as if it was blasting off to the moon.

Each day, I would travel at least 50 miles to visit up to 15 homesteads. The first stop would be in a fieldwork car provided by the project, then subsequent stops might have been on foot or by motorbike. The roads would rise and wind through dark thickets and green gardens. Somewhere along that steep hillside of 10 miles would be around five houses. After a few miles, I would find a stopping place and make a visit to a family. I then would remount my motorbike and travel to my next stopping place. Were it not for gardens and labourers going down the road, the solitude would have been awful.

A typical day’s visit as an interviewer in a household began with my arrival at the house to find the resident(s) either looking after someone sick or out in the garden. I would joyfully exchange greetings with them, then have a cordial conversation about their health in general and what challenges were present and pressing at the moment. I asked myself how we could be a source of information and how this would help in identifying resources for health. I would introduce work we were undertaking and tell them how they were free to take part in the study to support the development of drugs in Africa. The visit was a balance of mind, heart and spirit as I tried to empathize with the family and also give them a sense of hope―even though it was far from within reach for them, given the community perception that once infected with HIV it meant the end of life.

Amidst all the caregiving work, behind the scenes were families affected by grief or loss of loved ones.  As part of my visit, from the religious and cultural perspectives in African tradition, it became imperative for one to console the bereaved, even if some of their beliefs about the loss were different from my personal beliefs. In many sub-Saharan communities, norms and culture compel women to sacrifice their personal ambitions and pleasure. My experience of working within these communities exposed me to the realities of gender biases in our society, where young girls have to give up schooling to take on care jobs or are caregivers in the home. Because of the work of these girls, most homesteads were still well looked after, with fire burning and/or coal in the outdoor kitchens.


The more I visited these homes, the more I realized that inequalities and lack of economic empowerment can have significant health implications that are still central to the spread of HIV and other diseases. In many homes affected by HIV, children were orphaned or had to take on caregiver jobs to look after the sick. Girls were more likely to drop out of school, but also took on the leadership roles in the households.

We visited households annually over a period of about three to four years. I saw that girls and boys grew up in their role. The reality was, if they survived the ‘harsh tones’—if they managed to overcome the challenges posed by the combination of HIV infection and cultural practices like child marriage, polygamy, and widow inheritance, and endured their new roles as caregivers—then they’d find greater hope and strength to weather the storms to come. When drugs for HIV treatment became available, stigma was reduced; then came better drugs, support groups and social systems; then moving from highly specialized medical care to primary health care.

The new challenge came when the boys and girls started their own relationships as young adults. They faced challenges about disclosure of their HIV status if they got infected and around compliance with their treatment plan, which requires going to regular medical appointments, taking medications and following other medical advice—all of which can be influenced by stigma around infection, as the fear of being discriminated against may impact their willingness to engage in HIV care. They worried about how society would view them as being resilient, but at the same time disown them.

My own personal experience with gender

In contrast to the power and privilege in patriarchal society that I saw during my field work, I grew up in a large family that champions both men and women in many ways, from their roles in the home to their level of education. So when I turned 18, I was excited to register and vote and do my civic duty. I still remember voting for clan leadership for the first time and my uncle took me to the polling place.

As I also lived through a civil war in Uganda, life was centred around women. During the war, women were at the forefront, having to flee with their children to seek safety in remote places. I too had to go to a remote village with my mother and my siblings. I watched mothers as caregivers. Somehow I did not have a clue of how to support them when I started work so many years ago. Based on my experience, I now realize that, unlike men, women in our society rely on greater social support due to the cultural and gender roles specific to the challenges they face. This may come from family, friends, community networks and is vital for emotional, practical and sometimes financial reasons.

Today in 2023, I face the same reality in a caregiver role with my parents, and struggle with the cultural norms around women as caregivers while juggling work. I was also confronted with my late husband’s incurable cancer. Adapting to this process of caregiving, I learned that my experience in the field made me more resilient, to some extent, and again required a balance of states of mind, body and spirit. I now have the ability to navigate the ups and downs of life with greater resilience, to promote well-being and to maintain a positive outlook, even during difficult times.

My research journey

When I joined the field of research as a biostatistician, my vision was to unpack the realities communities face, and deepen my understanding of health disparities and their impact on health outcomes. I would contribute to solutions by applying statistical tools to public health problems within communities we live in.

Since 2019, when I joined the African Population and Health Research Center (APHRC), my role has been to contribute to understanding and promoting inclusive and equitable solutions to public health problems, to support evidence-based policy decision making, and to improve lives in Africa through the use of data science applications and tools. In my current role at the Center, where I shifted to a regional setting, I am able to gather information from various vulnerable communities and incorporate local knowledge. This enables more robust evidence to build consensus or influence among stakeholders for more inclusive practices and targeted policies. 

When the COVID-19 pandemic broke out, health systems generated data on a massive scale and there was a need to respond rapidly, which necessitated the use of AI. In my experience working with HIV and COVID-19, both infectious diseases have greatly affected global health and vulnerable communities, and have been associated with gender-specific challenges, stigma and discrimination. In the context of COVID-19, the utilization of AI has played a crucial role and was leveraged by improvements in computational capacity and technology developments. Unlike my radiotelephone experience, this is a much more efficient improvement in technology for communication.

For our Global South AI4COVID project, my team harnessed heterogeneous COVID-19 data to build a data hub, and applied AI and data science to support public health and economic decision making in Kenya and Malawi. I learned much more about the biases in AI and biases around gender and intersectionality through our Gender Action Learning project. The implementation of this project has yielded tangible outcomes, including the creation of a valuable toolkit. The toolkit informs formal rules that guide AI models and algorithms to be gender and intersectionality sensitive. It also makes stakeholder data more available to address what’s missing, to inform actions and guide policy, and to increase the visibility and impact of their data.

The goal remains to find solutions to public health problems. It is said that ‘a journey of 1000 miles begins with one step’―even if that journey involves navigating dusty roads in the scorching heat or traveling treacherous mountain roads to deliver those solutions.

This blog post was written by Sylvia Kiwuwa Muyingo & is licensed under a CC BY 4.0 license. © 2023 Sylvia Kiwuwa Muyingo. 

Sylvia is an Associate Research Scientist/Biostatistician at APHRC, Data, Synergy and Evaluations Unit with a focus on Gender and Intersectionality in the design and application of data science tools to studies in Africa to improve lives in communities we live in, promoting equitable and responsible data access, as well as evidence decision making. You can find Sylvia on LinkedIn & Twitter.

Curious to read more reflections on AI, gender inequality and exclusions? Read the first blog posts from this series here: Amelia Taylor’s Can AI have its cake and eat it too?; Michelle Mbuthia’s Cook, Clean, Plan: A case for more gender-responsive policymaking, Meghan Malaatjie’s Are women programmed to think less and do more?Jim Todd’s Break out of your siloandMahlet Hailemariam’s Why are you talking to a blank screen?.