The Role of Mortality Estimation in Project Evaluation: Findings from a Household Survey in Dembo and Beboro Health Zones, Chad

In the vast, often overlooked corners of the world where humanitarian aid operates, the most critical question is not just how many people are being helped, but whether those efforts are actually saving lives. To answer this, health workers rely on a specific kind of measurement: counting deaths. This is not about tallying a body count in a grim sense, but about establishing a baseline of how many people are dying in a community over a specific time. When this number rises sharply above the normal background rate, it signals a crisis that demands immediate, large-scale intervention. In places where official records are missing or unreliable, researchers must go door-to-door, asking families about births, deaths, and illnesses to build a clear picture of population health. Without these estimates, aid organizations might believe they are succeeding when, in reality, the people they serve are still dying in alarming numbers.

In the remote, rural health zones of Dembo and Beboro in Chad, Médecins Sans Frontières (MSF) had been working for years to support local health services and distribute malaria medication. Despite these efforts, the organization decided to pause and take a hard look at the true state of the population. They conducted a massive survey, sending teams into the field to speak with thousands of households. The goal was simple yet profound: to find out if the people living in these hard-to-reach areas were actually safer than before, or if a silent crisis was unfolding right under their noses.

The researchers chose a method that allowed them to reach deep into the landscape. They did not just visit the main towns; they used a map of every building roof in the area to randomly select starting points, ensuring they captured a true cross-section of life in these zones. From these points, they walked to nearby homes, interviewing representatives from nearly 1,744 households. They asked about the last eight months of life in the family: who had been born, who had died, who had moved away, and who had arrived. They asked specifically about the causes of death and whether the family had sought medical help. This process covered over 10,000 people, a sample large enough to reveal patterns that smaller checks might miss.

The results painted a stark picture of a population in acute distress. In the Dembo zone, the number of deaths was shockingly high. For every 10,000 people living there, nearly one person died every single day. Among children under five, the rate was even more severe, with nearly two deaths per 10,000 children daily. This meant that for every 1,000 babies born, more than 229 would not survive to their fifth birthday. In the neighboring Beboro zone, the numbers were slightly lower but still alarmingly high, with nearly one death per 10,000 people daily and about one child death per 1,000 births. These figures were not just slightly above average; they were more than double, and in some cases triple, the rates seen in the wider region and the rest of sub-Saharan Africa.

When the researchers looked at who was dying, a troubling pattern emerged, particularly in Beboro. While the overall death rates were high, the data suggested that the true burden of death was being hidden. In Beboro, for every female child under five who was reported to have died, more than four male children were reported to have died. This extreme imbalance did not match the actual population, where boys and girls are born in roughly equal numbers. The researchers concluded that this was likely not a biological phenomenon, but a reporting one. It suggested that families were under-reporting the deaths of girls, perhaps due to cultural biases or the way information was gathered. If these missing female deaths were counted, the true death rate in Beboro would be even higher, revealing a crisis that was even deeper than the initial numbers showed.

The causes of death pointed directly to the region's most persistent threats. Malaria was the leading killer in both zones, responsible for a significant portion of the deaths, especially during the rainy season when mosquitoes are most active. In Dembo, complications from birth and the first few weeks of life were also major drivers of mortality. The survey revealed that while most families did seek care before a death occurred, many of those deaths happened at home or at local health centers that lacked the capacity to treat severe cases. In Dembo, the situation was compounded by geography; the area is separated from the main hospital by a river that can only be crossed by a ferry that frequently breaks down, leaving residents stranded without access to emergency care during critical times.

The study did not just identify problems; it challenged the assumption that existing aid programs were sufficient. The researchers found that despite years of support, including seasonal malaria prevention and maternal health services, the mortality rates remained dangerously high. This suggested that the current model of care was not reaching everyone who needed it, or that the scale of the crisis had outpaced the resources available. The data showed that the community was facing a perfect storm of high disease transmission, food insecurity, and difficult access to medical facilities.

Following the release of these findings, the aid organization did not simply file the report away. They used the evidence to fundamentally change their approach. They held meetings with community leaders to understand the barriers to care, increased supervision of local health centers to improve the quality of treatment, and began planning a follow-up survey to see if these new measures would save lives. The study served as a vital reality check, proving that even in areas where aid workers are present, the true extent of a crisis can remain invisible without rigorous, on-the-ground measurement.

Ultimately, this work highlights the power of counting the dead to save the living. In a region where data is scarce and needs are immense, the simple act of asking families about their losses provided the clarity needed to direct resources where they were most desperately required. It demonstrated that mortality estimation is not just a statistical exercise, but a critical tool for ensuring that humanitarian programs are actually meeting the needs of the people they aim to serve. Without this kind of honest, difficult accounting, the most vulnerable populations risk being left behind, their suffering unmeasured and their needs unmet.