Observational studyFrontiers in public health2025
Comparing SARS-CoV-2 infections in the US Military Health System and national data: opportunities for future pandemic surveillance.
Observational study in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The Military Health System offers geographically distributed SARS-CoV-2 incidence estimates to support critical national pandemic surveillance, but this has not been previously assessed. The objective was to identify confirmed, probable, and possible SARS-CoV-2 infections with laboratory and clinical evidence and compare cumulative incidence to the general United States population. Methods: An observational, retrospective epidemiologic study using medical records from the United States Military Health System (inclusive of active duty) collected from outpatient and inpatient facilities worldwide, both United States Military and non-military treatment facilities. Direct standardization to the general US population was used to calculate sex-adjusted cumulative incidence, stratified by age, for 10 Health and Human Services regions for active duty and non-active duty beneficiary populations, with Spearman's rho correlations for age and region strata. Results: Among Military Health System beneficiaries, 2,219,987 cases were identified, with 27.4% laboratory-confirmed cases alongside 35.0% probable and 37.6% possible cases identified using clinical ICD-10-CM evidence. Peaks in cases occurred November 2020-January 2021, August 2021-September 2021, and January 2022. Age-stratified and sex-adjusted cumulative incidence across 10 geographical regions reflected these temporal patterns among both active duty (90% of age and region-specific correlation coefficients >0.7) and non-active duty beneficiaries (80% of age and region-specific correlation coefficients >0.7). Cumulative incidence was higher among active duty beneficiaries compared to the United States general population, particularly those ages 18-49 years, with adjusted cumulative incidence ratios consistently greater than 1. The cumulative incidence ratios for non-active duty beneficiaries were more consistent and closer to 1. The sensitivity analysis of laboratory-confirmed cases among active duty personnel demonstrated consistently lower adjusted cumulative incidence than United States general population. Conclusion: Temporal patterns in cases among Military Health System beneficiaries reflect cases measured nationally by the Centers for Disease Control and Prevention. Applying a comprehensive algorithm of clinical and laboratory data from a large electronic health system, such as the Military Health System, may improve case capture during an emergent epidemic providing incidence estimates and regional impact in support of U. S. national surveillance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.