COVID-19 in Space: Possible Health Risks and Preparedness Guidelines
Bibliographic record
Abstract
Abstract Background The COVID-19 pandemic of 2020 resulted in over 705 million infections and more than 7 million deaths worldwide. The virus primarily spreads through aerosol droplets released during breathing, coughing, or sneezing, leading to symptoms ranging from mild fever and cough to severe outcomes, including death. Given the high risk associated with COVID-19, understanding its behaviour in diverse geographical and environmental conditions is critical. Space exploration and tourism represent an emerging industry, projected to reach a market value of $1.8 trillion. With numerous space missions planned by space agencies such as NASA, SpaceX, and ISRO, it is vital to address potential health risks for astronauts and space tourists. Objective With the expansion of human exploration into space, there is an urgent need to assess the risks posed by COVID-19 in extraterrestrial environments. This study reviews existing literature on airborne infections in space, identifies key knowledge gaps, and enhances preparedness for potential COVID-19 outbreaks during space missions. Methods A systematic literature review was conducted to identify studies examining airborne infectious diseases in space and their health effects under microgravity. Databases searched included PubMed and NASA’s Open Data Portal. To compare these findings with Earth-based data, additional systematic reviews were performed to analyze the known effects of these diseases on Earth, using Pathogen Safety Data Sheets. A separate systematic review was conducted using PubMed to explore similarities between COVID-19 and the selected airborne infectious diseases. Using a comparative approach, disease effects observed on Earth and in space were analyzed to predict COVID-19’s potential behavior in microgravity. Existing guidelines for managing airborne diseases in space and on Earth were reviewed and compared to develop a set of preparedness recommendations for COVID-19 in space. Results The airborne infectious diseases occurring in space found in this study include Aspergillus fumigatus, Beauveria bassiana , Epstein-Barr Virus (EBV), Escherichia coli, Klebsiella pneumoniae infections , Pseudomonas aeruginosa , Roseolovirus (Human Herpesvirus 6 & 7), Salmonella Typhimurium infection , Serratia marcescens infection , Staphylococcus aureus, Staphylococcus epidermidis , and Varicella-Zoster Virus (VZV). The relationship between the aforementioned diseases and COVID-19 was used in regard to theorizing the effects of COVID-19 in space. Six Tentative effects of COVID-19 in a microgravity environment could be theorized in this study. Along with that, recommendations to improve the current space travel health guidelines have also been referred to. Conclusion The results of this study will change the course of human space exploration by assisting in the protection of space travelers and guiding the development of new designs for spacecraft that include extra safety features.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.123 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".