Gender and health data on the Venezuelan migrant population in Colombia


This is the tenth blogpost 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. 

In this blog post, Sandra Patricia Martínez-Cabezas reflects on her research in the COLEV project, which focused on using responsible AI and data science to address COVID-19 challenges in Colombia. She recounts how her research team used health records of Venezuelan migrant populations crossing into Colombia to capture their health issues in national responses. In applying a gender lens, she explored the incompleteness of the data, how it was heavily skewed towards women and children and neglected men’s health. She emphasizes the need to consider gender biases in health data to ensure equitable interventions for vulnerable populations.

I started working as a researcher on the COLEV project in 2021. COLEV, which stands for Colombia Evidencia, studied how to ethically use AI and data science to respond to COVID-19 related challenges in Colombia by tailoring the public health measures to regional contexts and vulnerable populations in different local health ecosystems.

As a researcher in a middle-income country, I feel a need to help our populations, no matter their country of origin. That is my contribution; that is how I can help. I found a particular affinity for research questions related to the health of vulnerable populations. As a researcher in health and demography, I thought it would be interesting to know what had happened to the health of the Venezuelan migrant population in Colombia during the COVID-19 pandemic, so I decided that it was necessary to begin with an exploration of the data that gave us an account of the health records of this group.

Why was it important to know what was happening?

In recent years, Colombia has been the main receiving territory of the Venezuelan migrant population. Venezuelan refugees have been leaving their nation in droves, due to political turmoil, socio-economic instability and humanitarian crises. Between 2015 and 2019, more than two million people arrived in Colombia with multiple needs, including health.

Now, in the midst of the pandemic, it was important to know what was happening to their health. Based on the experience of other migrant populations in other parts of the world, I expected to see that Venezuela migrants, especially those in transit at the border, would have poorer health than Colombians.

And the drama began…

I already knew that the data I was going to face would not be good quality. Currently, Colombia doesn’t even have good records of its own population, much less of other groups. It became clear that health records of migrants were incomplete, with even the most basic information missing, such as age or ethnicity.

I immediately noticed several elements that caught my attention. The first was that most of the medical records were related to childbirth or postpartum care. The second was the low proportion of diseases such as cardiovascular diseases, anxiety or depression.

The third element that grabbed my attention was the low proportion of records for the male population. This did not initially surprise me. For the general population of many nations, research shows that men are less likely to go to a doctor than women. But the gender disparity for migrants in Colombia was even more pronounced than I anticipated. Among the migrant population in Colombia, I noticed that 70 percent of all health care records—from interactions with medical personnel—were of Venezuelan migrant women receiving health care.

Where were the men?

© iStock.

Gender and data

Were these findings not expected? In a certain way, yes. I expected this gender difference in the use of health care services, since many single mothers have migrated with their children without their husbands or partners, and suspected that this would be reflected in Colombia’s health records. Health interventions by the health care system and international aid organizations in the migrant population would, naturally, largely focus on women and children.

To try to understand this data more deeply, we started working collaboratively with an international cooperation agency to find out if the same situation was occurring with their health records of Venezuelan migrants. When we analyzed this data, we found the same thing: most of the records concentrated on women and were related to sexual and reproductive health; there were few records about men’s health.

In one of our work meetings with the COLEV gender team, I mentioned that I had found a pattern that was basically making men invisible in the health records. An uninformed person could easily think that migrant men do not get sick. On the other hand, the number of women who were seen for contraceptive services was very high compared to men. Practically all contraception fell on migrant women.

I asked myself, why is sexual health the responsibility of women? Why does my country not collect information about migrant men?

The importance of an interdisciplinary team

The discussions about this data in our gender group led us to research how migrant health data is collected and produced.

Two anthropologist researchers of the team suggested investigating in greater depth. To this end, we decided to carry out an ethnographic study in a city on the Colombian-Venezuelan border. During the fieldwork, we identified different actors related to the production of migrant health data, among them the international cooperation agencies present in the region and the local directorates and health institutions. We discovered that data revealed a very complex situation. International agencies, who are especially active at the border, collect information for their databases. But they do not share this nominal information with the national health system. This makes the migrant data fragmented and incomplete.

And what did we find?

We identified that there was no certainty about the condition of men’s health in general because the priority populations were pregnant women and children. In fact, once we consulted the government’s Health Sector Response Plan to the Migratory Phenomenon we understood why: Colombia’s national health plan for migrant populations prioritizes those groups. Practically everything revolves around women’s sexual and reproductive health. So it was a vicious circle, as the overrepresentation of women in the data encouraged health interventions for women and their health issues.

Now, it is totally understandable that women and children were prioritized, since Venezuela was going through a humanitarian crisis and these groups needed medical attention. But why wasn’t men’s health being promoted? Why was contraception a women’s only issue?

And what was the point of this work?

Sometimes, without noticing, we exclude population groups that also have health needs. A gender perspective makes it possible to identify the bias in the health care of the Venezuelan migrant population in Colombia, and allows the formulation of research questions on how health data on the Venezuelan migrant population in Colombia is produced. This approach provided me and the COLEV project team many lessons on gender and data in vulnerable populations. At first I wanted to know what was happening with health in Venezuelan migrants, but finally our research work allowed us to think in greater depth about the health data that was produced.

Today, one year after conducting fieldwork and multiple sessions in the COLEV gender group, we have published an article that compiles our research in which we argue how the representation of migrants in health metrics is permeated by different forms of inclusion and exclusion, which impacts inequalities in access to health care for this population.

I learned that data is not neutral. As researchers, it is important to ask how data is produced to avoid biases that can affect interventions in vulnerable populations.

This blog post was written by Sandra Patricia Martínez-Cabezas, Ms.c. Ph.D, & is licensed under a CC BY 4.0 license. © 2023 Sandra Patricia Martínez-Cabezas.

Sandra Patricia is a demographer, an epidemiologist, and a researcher at the Universidad de los Andes, Colombia. Her research is related to health demography, mortality, maternal health, infectious diseases COVID-19, acute respiratory infections and vector-borne diseases. You can find her on LinkedIn.

Curious to read more reflections on gender inequality, exclusions, & AI? Read the other blog posts from this series here.

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