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. 2022 Mar 31;8(1):8.
doi: 10.1038/s41526-022-00193-9.

Estimating medical risk in human spaceflight

Erik L Antonsen  1 , Jerry G Myers  2 , Lynn Boley  3 , John Arellano  4 , Eric Kerstman  5 , Binaifer Kadwa  6 , Daniel M Buckland  6   7 , Mary Van Baalen  6
Affiliations

Estimating medical risk in human spaceflight

Erik L Antonsen et al. NPJ Microgravity. .

Abstract

NASA and commercial spaceflight companies will soon be retuning humans to the Moon and then eventually sending them on to Mars. These distant planetary destinations will pose new risks-in particular for the health of the astronaut crews. The bulk of the evidence characterizing human health and performance in spaceflight has come from missions in Low Earth Orbit. As missions last longer and travel farther from Earth, medical risk is expected to contribute an increasing proportion of total mission risk. To date, there have been no reliable estimates of how much. The Integrated Medical Model (IMM) is a Probabilistic Risk Assessment (PRA) Monte-Carlo simulation tool developed by NASA for medical risk assessment. This paper uses the IMM to provide an evidence-based, quantified medical risk estimate comparison across different spaceflight mission durations. We discuss model limitations and unimplemented capabilities providing insight into the complexity of medical risk estimation for human spaceflight. The results enable prioritization of medical needs in the context of other mission risks. These findings provide a reasonable bounding estimate for medical risk in missions to the Moon and Mars and hold value for risk managers and mission planners in performing cost-benefit trades for mission capability and research investments.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. The IMM 4.1 Monte-Carlo simulation incorporates a mission timeline, progression-path assessment, treatment-path assessment, and event-outcome evaluation.
These are summed across all occurring conditions to provide a trial outcome and across all simulation runs to provide the simulation outcomes.
Fig. 2
Fig. 2. Total medical events predicted for the indicated mission duration and crew complement.
The results are shown by DRM across the x-axis and subdivided by the level of medical capability included in each situation. The 95% CIs is interpreted as the uncertainty estimated with respect to the data informing the 100 medical conditions and the PRA abstraction of the medical event timeline and end-states. As unaccounted uncertainties are not represented in this formulation or data representation, outcomes should be considered as representative of relative changes in risk rather than absolute risk assessments. ISS International Space Station.
Fig. 3
Fig. 3. Crew health index (CHI) predicted for the indicated mission duration and crew complement.
100 represents fully functional crew while 0 represents totally incapacitated crew. Parameters A and B are discussed in the text. The results are shown by DRM across the x-axis and subdivided by the level of medical capability included in each situation. The 95% CIs is interpreted as the uncertainty estimated with respect to the data informing the 100 medical conditions and the PRA abstraction of the medical event timeline and end-states. As unaccounted uncertainties are not represented in this formulation or data representation, outcomes should be considered as representative of relative changes in risk rather than absolute risk assessments. ISS International Space Station.
Fig. 4
Fig. 4. Calculated likelihood that crew would consider evacuation if it were available due to medical conditions experienced in-flight.
The 95% CIs is interpreted as the uncertainty estimated with respect to the data informing the 100 medical conditions and the PRA abstraction of the medical event timeline and end-states. As unaccounted uncertainties are not represented in this formulation or data representation, outcomes should be considered as representative of relative changes in risk rather than absolute risk assessments. ISS International Space Station.
Fig. 5
Fig. 5. Calculated likelihood that loss of crew life (LOCL) will occur in-mission due to medical conditions experienced in-flight.
The 95% CIs is interpreted as the uncertainty estimated with respect to the data informing the 100 medical conditions and the PRA abstraction of the medical event timeline and end-states. As unaccounted uncertainties are not represented in this formulation or data representation, outcomes should be considered as representative of relative changes in risk rather than absolute risk assessments. ISS International Space Station.
See this image and copyright information in PMC

References

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