Each animal in the Darwinian theater is exposed to a number of abiotic and biotic risk factors causing mortality. Several of these risk factors are intimately associated with the act of energy acquisition as such and with the amount of reserve the organism has available from this acquisition for overcoming temporary distress. Because a considerable fraction of an individual’s lifetime energy acquisition is spent on somatic maintenance, there is a close link between energy expenditure on somatic maintenance and mortality risk. Here, we show, by simple life-history theory reasoning backed up by empirical cohort survivorship data, how reduction of mortality risk might be achieved by restraining allocation to somatic maintenance, which enhances lifetime fitness but results in aging. Our results predict the ubiquitous presence of senescent individuals in a highly diverse group of natural animal populations, which may display constant, increasing, or decreasing mortality with age. This suggests that allocation to somatic maintenance is primarily tuned to expected life span by stabilizing selection and is not necessarily traded against reproductive effort or other traits. Due to this ubiquitous strategy of modulating the somatic maintenance budget so as to increase fitness under natural conditions, it follows that individuals kept in protected environments with very low environmental mortality risk will have their expected life span primarily defined by somatic damage accumulation mechanisms laid down by natural selection in the wild.
While invasive social distancing measures have proven efficient to control the spread of pandemics in the absence of a vaccine, they carry vast societal costs.
Guided by the finding that large households function as hubs for the propagation of COVID-19, we developed a data-driven individual-based epidemiological network-model to assess the intervention efficiency of targeted testing of large households.
For an outbreak with reproductive numbers R between 1.1 and 2, our results suggest that the intervention effect of weekly pooled testing of the 10% largest households in an urban area is on par with the effect of imposing strict lockdown measures.
By testing no more than 20% of households every 4 days, the model predicts that one can reduce R from 1.6 to below unity over a few weeks, lowering the prevalence by 75%.
Pooled household testing appears to be a powerful alternative to more invasive measures as a localized early response to contain epidemic outbreaks.
With limited availability of vaccines, an efficient use of the limited supply of vaccines in order to achieve herd immunity will be an important tool to combat the wide-spread prevalence of COVID-19. Here, we propose a targeted vaccination approach (EHR) that provides a significant reduction in the necessary number of doses needed achieve herd immunity compared to age-prioritized and random selection vaccination schemes. Using high-fidelity individual-based computer simulations with Oslo, Norway as an example, we find that for a community reproductive number in a setting where R=1.4 without population immunity, the EHR method reaches herd immunity at only 15% of the population vaccinated, whereas the common age-prioritized approach needs 40%. With R=1.9 in the absence of immunity, EHR needs 30% and age-prioritized needs 52%.
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