COVID-19 in Veterans: A Narrative Review

Impact of COVID-19 on the veteran population: evidence from the Trends in Scottish Veterans Health study

INTRODUCTION

There have been few epidemiological studies on the impact of the SARS-CoV-2 (COVID-19) pandemic on the veteran population, other than on specific aspects such as mental health, and none in the UK. We used data from the Trends in Scottish Veterans Health cohort to explore the risk of hospitalisation and death associated with COVID-19 in veterans resident in Scotland in comparison with matched non-veterans.

METHODS

Retrospective cohort study of 71 000 veterans and a comparison group of 230 000 non-veterans matched for age, sex and geography, using Cox proportional hazard analysis to explore the risk of hospitalisation with COVID-19 and COVID-19-associated death overall and by birth cohort, sex and length of military service.

RESULTS

Between 1 January 2020 and 31 December 2021, 564 (0.79%) veterans had been hospitalised with COVID-19 compared with 1728 (0.75%) non-veterans. The Cox model showed no significant difference overall, HR 0.99, 95% CIs 0.90 to 1.11, p=0.800. Subgroup analysis showed increased risk in older, short-serving (<20 weeks) Early Service Leavers (ESL). There was no overall difference in COVID-19-associated deaths, HR 0.99, 95% CI 0.79 to 1.23, p=0.993, but subgroup analysis showed a non-significant reduced risk of death in veterans aged 61-70 years, and a 38% higher risk in veterans aged over 70 years which almost reached statistical significance, p=0.054. This was only partially explained by socioeconomic factors and common comorbidities, although we had no data on domestic circumstances or care home residence.

CONCLUSIONS

Overall, military service was not a risk factor for either hospitalisation or death associated with COVID-19. Older ESLs were at increased risk compared with non-veterans, but military service is unlikely to have been causal. The risk of death was increased in the oldest veterans and further studies are needed to explain this once census data become available for linkage.

Synthetic Health Data Can Augment Community Research Efforts to Better Inform the Public During Emerging Pandemics

The COVID-19 pandemic had disproportionate effects on the Veteran population due to the increased prevalence of medical and environmental risk factors. Synthetic electronic health record (EHR) data can help meet the acute need for Veteran population-specific predictive modeling efforts by avoiding the strict barriers to access, currently present within Veteran Health Administration (VHA) datasets. The U.S. Food and Drug Administration (FDA) and the VHA launched the precisionFDA COVID-19 Risk Factor Modeling Challenge to develop COVID-19 diagnostic and prognostic models; identify Veteran population-specific risk factors; and test the usefulness of synthetic data as a substitute for real data. The use of synthetic data boosted challenge participation by providing a dataset that was accessible to all competitors. Models trained on synthetic data showed similar but systematically inflated model performance metrics to those trained on real data. The important risk factors identified in the synthetic data largely overlapped with those identified from the real data, and both sets of risk factors were validated in the literature. Tradeoffs exist between synthetic data generation approaches based on whether a real EHR dataset is required as input. Synthetic data generated directly from real EHR input will more closely align with the characteristics of the relevant cohort. This work shows that synthetic EHR data will have practical value to the Veterans' health research community for the foreseeable future.