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Age spectrometry of infant death rates as a probe of immunity: Identification of two peaks due to viral and bacterial diseases respectively

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  • Berrut, Sylvie
  • Richmond, Peter
  • Roehner, Bertrand M.

Abstract

After birth, setting up an effective immune system is a major challenge for all living organisms. In this paper we show that this process can be explored by using the age-specific infant death rate as a kind of sensor. This is made possible because, as shown by the authors in Berrut et al. (2016), between birth and a critical age tc, for all mammals the death rate decreases with age as a smooth hyperbolic function. For humans tc is equal to 10 years. It turns out that for some causes of deaths and specific ages the hyperbolic fall displays temporary spikes which, it is assumed, correspond to specific events in the organism’s response to exogenous factors. One of these spikes occurs 10 days after birth and there is another at the age of 300 days. It is shown that the first spike is related to viral infections whereas the second is related to bacterial diseases. By going back to former time periods during which infant mortality was much higher than it is currently, one gets a magnified view of these peaks. They give us useful information about how an organism adapts to new conditions. Apart from the reaction to pathogens, the same methodology can be used to study the response to changes in other external conditions, e.g. temperature or oxygen level.

Suggested Citation

  • Berrut, Sylvie & Richmond, Peter & Roehner, Bertrand M., 2017. "Age spectrometry of infant death rates as a probe of immunity: Identification of two peaks due to viral and bacterial diseases respectively," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 915-924.
    • Handle: RePEc:eee:phsmap:v:486:y:2017:i:c:p:915-924
    DOI: 10.1016/j.physa.2017.05.081
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    References listed on IDEAS

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    1. Berrut, Sylvie & Pouillard, Violette & Richmond, Peter & Roehner, Bertrand M., 2016. "Deciphering infant mortality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 400-426.
    2. Amir Bashan & Ronny P. Bartsch & Jan. W. Kantelhardt & Shlomo Havlin & Plamen Ch. Ivanov, 2012. "Network physiology reveals relations between network topology and physiological function," Nature Communications, Nature, vol. 3(1), pages 1-9, January.
    3. Richmond, Peter & Roehner, Bertrand M., 2016. "Effect of marital status on death rates. Part 1: High accuracy exploration of the Farr–Bertillon effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 748-767.
    4. Richmond, Peter & Roehner, Bertrand M., 2016. "Predictive implications of Gompertz’s law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 446-454.
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    1. Bois, Alex & Garcia-Roger, Eduardo M. & Hong, Elim & Hutzler, Stefan & Irannezhad, Ali & Mannioui, Abdelkrim & Richmond, Peter & Roehner, Bertrand M. & Tronche, Stéphane, 2020. "Congenital anomalies from a physics perspective. The key role of “manufacturing” volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).

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