Phenomenology of infant death rates. Identification of the peaks of viral and bacterial diseases

TL;DR

This paper uses age-specific infant death rates as sensors to identify peaks related to viral and bacterial infections, revealing insights into immune system development and responses to external factors across different historical periods.

Contribution

It introduces a novel methodology to analyze infant mortality data as a sensor for immune response peaks, linking specific age-related spikes to pathogens and external environmental factors.

Findings

Identified peaks at 10 days and 300 days linked to viral and bacterial infections.

Historical data magnifies these peaks, providing deeper insights into immune adaptation.

Methodology applicable to studying responses to various external conditions.

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 t_c, for all mammals the death rate decreases with age as an hyperbolic function. For humans t_c is equal to 10 years. At some ages the hyperbolic fall displays 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 about 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 currently, it is possible to get a magnified view of these peaks which in turn may give us useful information about how an organism adapts to new conditions. Apart from pathogens, the same methodology can be used to study the response to changes in other external conditions, e.g. supply of food, temperature or oxygen level.