I shouldn’t be alive… and yet here I am

 By: Dr. Ismael Perdomo

Medical Doctor – Pediatrician – Epidemiologist

At 45 years of age, a question arose that seemed simple on the surface but ended up transforming the way I see existence: ¿what has been the cumulative probability of my death up to today?. Until that moment, I had devoted my professional life to evaluating other people’s risks: in specific patients, in vulnerable populations, in infant mortality curves, and in epidemiological models. I had never considered myself a statistical case worthy of study. And yet something clicked. If life is so fragile, if so many things can go wrong at any second, why am I still here? As a pediatrician, I have accompanied the beginning of life and witnessed its extreme vulnerability; as an epidemiologist, I know that survival can be represented as a mathematical function and that intuition fails us when it faces small probabilities and chained events; as a person, I have come to understand that my existence defies any simple calculation when one rigorously adds up all the risks overcome.

This article is the result of a personal inquiry guided by solid scientific evidence, seeking to answer an uncomfortable question: “human life is statistically improbable.” If we could stop the clock at any given moment and calculate the probability of having overcome all prior risks, the resulting number would be so low that awe would be the only honest reaction. Today, at 47, I can say that if life were a purely mathematical bet, I would have lost millions of times. And yet, I am still here. What follows is my scientific, epidemiological, and philosophical analysis of how I exist—against all statistical logic.

Before existing, it was already practically impossible to exist

To exist is the favorable outcome of an immense chain of unstable events, each with a relatively low individual probability of success. Let us begin with the oocyte. Human oogenesis is not a “clean” process: it is an intricate dance, prone to chromosomal recombination errors that favor aneuploidy. Various studies show that a nontrivial percentage of oocytes present recombination abnormalities that predispose to chromosomal segregation errors in meiosis; that fragility explains why aneuploidy is the leading cause of human reproductive loss. This is not a guess: contemporary repositories linked to massive series of evaluated embryos corroborate that maternal meiotic failures are associated with a significant risk of aneuploidy, with PLK4 and other genes of the meiotic machinery among the usual suspects.

To this we must add the “lottery” of the sperm: one out of 200 to 500 million will manage to fertilize the oocyte. Converted to probability, that founding episode of our personal biography is 1 in hundreds of millions. But even if fertilization occurs, the true filter is only beginning. Early embryonic mortality is high: the total loss between fertilization and birth ranges, in conservative estimates, between 40% and 60%, including losses prior to implantation and in the first weeks of development. In other words, the rule is to disappear, not to keep going. This view is supported by reanalyses of hCG data and critical reviews that temper some exaggerated claims in the classical literature yet still conclude that natural loss is high and that most conceptions do not reach term.

That first stretch of my life—even before my mother knew she was pregnant—was decided on a violently selective biological frontier. Every micro-decision at implantation (trophoblastic adhesion, hormonal signaling, immune tolerance, endometrial angiogenesis) had to occur with precision. A delay of milliseconds, an imbalanced cytokine, an error in cell-to-cell communication, and my story would have ended without a trace. When we add to this the organogenesis of the first weeks—neural tube closure, cardiac septation, left-right patterning, cellular migrations—it is easy to see why, from a risk perspective, I was an outlier before I even had a name.

Every cell division: endless biological dice rolls

Let us suppose I made it past fertilization and implantation. Then comes a phase we often forget: trillions of coordinated cell divisions during gestation and childhood, each with the potential to introduce lethal errors. DNA replication must copy more than 3.2 billion nucleotides per cell; the repair systems and cell-cycle checkpoints, while extraordinary, are not infallible. Even so, life “persists” thanks to molecular surveillance.

The accumulated evidence of the last decade is compelling: healthy human tissues harbor thousands of somatic mutations that accumulate with age. In 36 human tissues analyzed from individuals without apparent disease, hundreds of thousands of somatic variants have been cataloged; many are transient, others clone silently, and a few, under the right context, can become the first step toward cancer. This landscape of “normal” mutations shows that the organism coexists with error without collapsing.

Furthermore, the rate at which these mutations appear is not trivial. Recent estimates place ~9 to 56 new mutations per cell per year, depending on tissue and age; inter-tissue variation is wide and suggests that the architecture of damage and repair is profoundly specific. Intuition suggests that, with so much mutational “noise,” disorganization should be the most likely outcome; observation shows the opposite: the body encapsulates entropy. And when we compare species, an elegant pattern emerges: in mammals, the annual somatic mutation rate correlates inversely with longevity; in some way, evolution calibrated the “speed of error” so that the final mutation burden at the end of life is comparable across species with very different lifespans—reinforcing the idea that to age is, in part, to accumulate errors.

The first-person clinical question is simple and brutal: why didn’t I develop a lethal cancer in childhood, when the rate of cell division was maximal? The statistical answer is that each division was a bet against destruction—and I won them all.

Birth: the physiological decompression that puts life to the test

The uterus is a perfect support ecosystem; the outside world is a hostile ocean. Birth imposes, within minutes, physiological changes that in an adult would be incompatible with life: functional and then anatomical closure of the ductus arteriosus, a drop in pulmonary resistance with alveolar opening, the establishment of breathing, a radical shift in metabolism (from a continuous maternal glucose flow to self-regulation), accelerated microbial colonization, and activation of the innate immune system. If any of these transitions fails for even seconds, the outcome can be fatal.

Even when pregnancy reaches term, the finish line guarantees nothing: global figures show that the start of extrauterine life remains a high-risk zone. In population terms, international surveillance systems estimate substantial perinatal and neonatal death burdens, and, in aggregate, mortality associated with that “bridge” period continues to be a crucial component of under-five mortality, which—though historically reduced—still claims millions of lives each year. Read from my personal case, the message is simple: my first cry was a physiological feat.

Childhood: an invisible minefield of everyday risks

Childhood is not a valley of invulnerability; it is a period of trial and error where each discovery entails risk. The child explores, runs, climbs, swallows, leans over water, touches surfaces, and experiences infections that train (or overwhelm) the immune system. Globally, millions of deaths in under-five children remain associated with preventable and treatable causes—prematurity, intrapartum complications, pneumonia, diarrhea, malaria, malnutrition. At the global scale, curves have fallen sharply in three decades, but the absolute number remains high, with tens of thousands of deaths every week. That backdrop reminds us that having made it through childhood in acceptable health is, statistically, an achievement.

There is also a component of banal risks which we should translate into understandable probabilities. As a pediatrician, I often tell parents that “crossing the street” is not a military operation, but neither is it innocuous: pedestrians pay a real mortality toll. At the country level (U.S.), 7,314 pedestrians died in 2023—a figure that has grown compared with past decades and represents about 18% of all traffic deaths. By itself, that statistic does not yield the individual probability, but it does set the environmental baseline risk to which anyone—including a child walking to school—is exposed.

Adulthood: surviving internal collapse

Adulthood does not mean the absence of danger; it means danger becomes internalized. The adult body fights, minute by minute, molecular erosion: reactive oxygen species oxidize proteins and lipids; telomeres shorten with each division; mitochondria lose efficiency; proteins undergo glycation; the epigenome “drifts”; and—most importantly—precancerous cells appear and must be silently detected and eliminated by the immune system. The surveillance-apoptosis-repair circuit acts like a firewall that, if it lowers its guard for one single day, may allow the start of a malignant clone.

In real-world oncology, one name summarizes that frontier: TP53, the “guardian of the genome.” Its inactivation is implicated in a large share of human tumors and, in analyses of large cohorts, around one-third of cancers harbor somatic TP53 mutations; other papers speak of “half” of all cancers if multiple inactivation mechanisms are counted, not only coding mutations. Whether 35% or 50% depending on the method, the message is the same: when TP53 falls, cancer advances. The fact that in 47 years none of my cells has won that devastating lottery—or, if it did, that my immune system eliminated it—is yet another everyday statistical victory.

But adult life also adds the layer of cumulative everyday risks. Let us translate them into lifetime odds so the brain can grasp the scale: dying in a motor-vehicle crash over a lifetime is on the order of 1 in 93; from an accidental fall, 1 in 102; from drowning, 1 in 1,006; as a pedestrian struck, 1 in 543; from accidental opioid overdose (a growing number), 1 in 57. By contrast, death in commercial air travel is extraordinarily rare; estimates based on historical series put it around 1 in several hundred million; still, it is “not zero”: it exists. These values are not uniform across countries or cohorts, but they help us calibrate something we forget: our daily life is immersed in real probabilities of termination.

When one overlays these probabilities across 47 years of personal trajectories—driving, walking, traveling, working—one understands that each sunrise is the outcome of multiple roulettes which, against intuition, tip toward life.

Everyday life: playing with statistics without noticing

In public health, the epidemiologist knows that death is not an extraordinary event: mathematically, it is the most probable long-term outcome. What is extraordinary is postponing it. Hence the technical language distinguishes between “instantaneous risk” and “cumulative probability.” Someone who drives to work today might think “nothing will happen,” but a small daily risk repeated thousands of times becomes a non-trivial cumulative probability of a fatal outcome. Put differently: even if today’s risk is minuscule, multiplying it across days, months, and years makes it substantive.

Consider a few examples. Driving to work adds a small increment to the probability of death by crash; walking as a pedestrian near poor-visibility intersections adds another; showering while half asleep adds another via falls; eating and choking, another; exposure to a winter respiratory infection, another; flying once or twice a year, a tiny one. Everyday life is a vector of tiny risks that, when accumulated, are not trivial. And yet, for most of us, those probabilities resolve in favor of survival thousands of times in a row. If we think about it seriously, that is astounding. (To calibrate the environmental baseline: in the U.S. alone, pedestrians represented 18% of all traffic deaths in 2023; translated into individual probability, even if you do not drive, simply walking entails real risk.)

At the same time, the global macro-statistics add their own context: in 2023, 4.8 million children under five died; far fewer than in 1990 (12.8 million), but still far too many. In probability terms, this translates into a differential probability—depending on country and development level—that a newborn will not reach age five. To have been born in a particular context and, moreover, to have survived that context is not an anecdote; it is a realization of probability.

The cumulative probability of death: the clinical case of my own life

After two years of mulling over these chained data, I built a concept to think about myself: Cumulative Probability of Death (CPD). The idea is simple: if each life stage has a death risk Rᵢ greater than zero (conception, implantation, fetal development, birth, neonatal period, childhood, adolescence, adulthood, aging, environmental exposure, accidents, cancer, cardiovascular disease…), then my probability of survival at 47 is the product of the probabilities of surviving each stage:

Survival at 47 = ∏ (1 – Rᵢ).

Basic arithmetic teaches that the product of fractions less than 1 tends toward zero. The more stages are chained, the more the product approaches zero. The qualitative result is clear: by pure mathematics, I should not be alive. This intuition becomes more graphic when I compare it to a game everyone understands: the lottery. The probability of winning one Mega Millions drawing is about 1 in 302.6 million. Winning five in a row is on the order of 1 in 2.4 × 10³⁸. In my reflection—after aggregating biological, perinatal, childhood, environmental, and adult risks—I reached a conclusion that may sound provocative but that I consider honest: being alive this second feels more improbable than winning five multimillion-dollar lotteries in a row. It is not an exact comparison—the events are neither independent nor equiprobable—but it is a useful quantitative metaphor to communicate the chasm between what “should” have happened and what did happen.

Here the philosophical crack opens: if statistics “expects” me to be dead, yet I am alive, what variable is missing from the equation?

If life is statistically impossible… what sustains my existence?

I have avoided hasty conclusions and let biology, genetics, epidemiology, and probability speak for themselves. The verdict is uncomfortable: life does not sustain itself from a statistical standpoint—or at least, not only with what we measure. The CPD is not a clinical tool, but as a metaphor and an intellectual experiment it has forced me to take the brutality of the numbers seriously. Paradoxically, the more honest I am with them, the harder it is to claim that I am alive by chance. I do not deny chance—that would be absurd; I deny that chance, by itself, explains 47 years of consecutive victories against so many simultaneous roulettes.

Some will say this is survivorship bias—and there is some of that: only those who survive can tell the story. But the objection does not erase the magnitude of the phenomenon we are trying to explain. The bias accounts for my point of view; it does not account for my existence.

So I return to the question: what sustains the anomaly of my survival?

Life is an impossible bet… won by grace

In theology and philosophy, there is a famous reflection by Blaise Pascal known as Pascal’s Wager. Simplified, it says that if God does not exist, believing in Him carries no eternal harm; but if He does exist, denying Him carries the worst possible consequence. From the standpoint of rational decision-making under uncertainty, believing would be the optimal choice. I recognize the strength of that argument, but my personal and scientific journey takes me one step further: my entire life is already an impossible bet won over and over. If everything above is true—if each stage offered me small probabilities of moving forward and I overcame them all—then the question is no longer “should I believe just in case?” but “why am I alive when I shouldn’t be?”

Science offers a partial answer: I am improbable.

Faith offers a complete answer: I am loved.

The cumulative probability of death says my story should have ended long ago.

The love of God and the grace of Jesus Christ say my story is just beginning.

Why has God insisted on keeping me alive for 47 years?

Not by merit. Not by chance. Not by statistics.

By grace.

To offer me the gift that surpasses biology: eternal life in Jesus Christ. If He keeps my heart beating today, it is so I can take His hand and live what was designed before the foundation of the world.

I have beaten death thousands of times without realizing it.

Today I understand why: God has never stopped sustaining my life.

Although I was born into a Catholic home—like most Colombians—and was raised under conservative Christian principles, it was not until 2015 that I had a personal encounter with Jesus and decided to open my heart for Him to dwell in me. The Bible, which is God’s Word, tells us: “Look at the birds of the air; they do not sow or reap or store away in barns, and yet your heavenly Father feeds them. Are you not much more valuable than they?” Matthew 6:26 (NIV). This verse reminds us of God’s profound love for His children and shows His fatherly protection and life-sustaining care.

Thank you, God, for sustaining these 47 years of statistical miracle.

Thank you, Jesus, for securing for me an eternity no mathematics can measure.

Bibliografía

Biología reproductiva y pérdidas tempranas

1. Jarvis GE. Early embryo mortality in natural human reproduction: What the data say. F1000Research. 2017;6:111. Disponible en PubMed/PMC. 

2. Jarvis GE. Misjudging early embryo mortality in natural human reproduction. F1000Research. 2020;9:702. (Revisión crítica de rangos 40–60% del total de pérdidas). 

3. Ivanova A, et al. The chromosomal challenge of human embryos. HGG Advances (Cell Press). 2025. (Errores meióticos, genes TUBB8, MEI1, PLK4). 

4. Carioscia SA, et al. Common variation in meiosis genes shapes human aneuploidy and recombination. (Base de datos masiva de PGT; aneuploidía como causa líder de pérdida). 

Mutaciones somáticas y envejecimiento

5. García-Nieto PE, et al. The somatic mutation landscape of the human body. Genome Biology. 2019;20:275. (Mutaciones en 36 tejidos sanos). 

6. Martincorena I. Somatic mutation and clonal expansions in human tissues. Genome Medicine. 2019. (Clones mutantes en epitelios normales). 

7. Cagan A, et al. Somatic mutation rates scale with lifespan across mammals. Nature. 2022;604:517–24. (Tasa somática anual inversamente correlacionada con longevidad). 

Oncogénesis y TP53

8. Sinkala M, et al. Mutational landscape of cancer-driver genes across human cancers. Scientific Reports. 2023. (TP53 mutado ~36.6% global). 

9. Olivier M, et al. TP53 mutations in human cancers: origins, consequences, and clinical use. Cold Spring Harbor Perspectives / Oncogene (revisión clásica; Li-Fraumeni). 

Mortalidad infantil y neonatal (OMS/UNICEF)

10. WHO Global Health Observatory. Child mortality and causes of death. (Baja de 12,8 M en 1990 a 4,8 M en 2023; NMR y U5MR). 

11. UNICEF Data. Under-five mortality. (4,8 M muertes U5 en 2023; ≈13.100 diarias). 

Riesgos cotidianos, peatones, conducción, probabilidades vitales

12. National Safety Council (NSC). Injury Facts – Odds of Dying (2023 Data): lifetime odds por causa (accidente automovilístico ~1/93; caídas ~1/102; peatón ~1/543; ahogamiento ~1/1.006; sobredosis opioides ~1/57). 

13. NHTSA. Traffic Safety Facts 2023 – Pedestrians. (7.314 peatones muertos; ≈18% de muertes viales en 2023). 

14. NHTSA. Pedestrian Safety – Overview. (Tendencias y proporción de muertes de peatones). 

Notas sobre aviación (Contexto divulgativo): múltiples resúmenes de riesgo de aviación comercial citan probabilidades muy bajas (del orden de 1 en varios cientos de millones); aunque no existe un consenso único metodológico, la comparación relativa con conducción es clara: volar comercial es órdenes de magnitud más seguro que conducir la misma distancia. (Para el lector, prioricé la NSC y la NHTSA como fuentes oficiales para probabilidades comparativas de la vida real).