Seroprevalence as an Indicator of Undercounting of COVID-19 Cases in a Large Well-Described Cohort.

Introduction: Reported confirmed cases represent a small portion of overall true cases for many infectious diseases. The undercounting of true cases can be considerable when a significant portion of infected individuals are asymptomatic or minimally symptomatic, as is the case with COVID-19. Seroprevalence studies are an efficient way to assess the extent to which true cases are undercounted during a large-scale outbreak and can inform efforts to improve case identification and reporting. Methods: A longitudinal seroprevalence study of active duty U.S. military members was conducted from May 2020 through June 2021. A random selection of service member serum samples submitted to the Department of Defense Serum Repository was analyzed for the presence of antibodies reactive to SARS-CoV-2. The monthly seroprevalence rates were compared with those of cumulative confirmed cases reported during the study period. Results: Seroprevalence was 2.3% in May 2020 and increased to 74.0% by June 2021. The estimated true case count based on seroprevalence was 9.3 times greater than monthly reported cases at the beginning of the study period and fell to 1.7 by the end of the study. Conclusions: In our sample, confirmed case counts significantly underestimated true cases of COVID-19. The increased availability of testing over the study period and enhanced efforts to detect asymptomatic and minimally symptomatic cases likely contributed to the fall in the seroprevalence to reported case ratio.

Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action.

INTRODUCTION: High quality epidemic forecasting and prediction are critical to support response to local, regional and global infectious disease threats. Other fields of biomedical research use consensus reporting guidelines to ensure standardization and quality of research practice among researchers, and to provide a framework for end-users to interpret the validity of study results. The purpose of this study was to determine whether guidelines exist specifically for epidemic forecast and prediction publications. METHODS: We undertook a formal systematic review to identify and evaluate any published infectious disease epidemic forecasting and prediction reporting guidelines. This review leveraged a team of 18 investigators from US Government and academic sectors. RESULTS: A literature database search through May 26, 2019, identified 1467 publications (MEDLINE n = 584, EMBASE n = 883), and a grey-literature review identified a further 407 publications, yielding a total 1777 unique publications. A paired-reviewer system screened in 25 potentially eligible publications, of which two were ultimately deemed eligible. A qualitative review of these two published reporting guidelines indicated that neither were specific for epidemic forecasting and prediction, although they described reporting items which may be relevant to epidemic forecasting and prediction studies. CONCLUSIONS: This systematic review confirms that no specific guidelines have been published to standardize the reporting of epidemic forecasting and prediction studies. These findings underscore the need to develop such reporting guidelines in order to improve the transparency, quality and implementation of epidemic forecasting and prediction research in operational public health.

Epidemiology of impulse control disorders and association with dopamine agonist exposure, active component, U.S. Armed Forces, 2014-2018.

Impulse control disorders (ICDs) are a group of behavioral disorders characterized by failure to resist impulsive thoughts and behaviors that can lead to significant adverse social, legal, and financial consequences. ICDs have been associated with previous diagnoses of depression, anxiety, and post-traumatic stress disorder and have been widely recognized as an adverse effect of dopamine agonist (DA) therapy. The epidemiology of these disorders in the U.S. Armed Forces is unknown. The current study evaluated the incidence of ICD diagnoses in the U.S. Armed Forces during 2014-2018. The overall incidence was 13.7 per 10,000 person-years (p-yrs), with the highest rates among females and younger personnel. The current case-control study evaluated the association between DA exposure in the year preceding an incident ICD diagnosis. Although few individuals had received DA therapy in the past year, DA therapy was independently associated with incident ICD diagnosis (adjusted odds ratio [AOR]=2.34; 95% confidence interval [CI]: 1.29-4.24, p<.0001). Previous mental health disorder diagnosis (AOR=12.0; 95% CI: 11.09-12.98, p<.0001) and fibromyalgia (AOR=1.30; 95% CI: 1.14-1.48, p<.0001) were also associated with incident ICD diagnosis. The impact of ICDs on mission readiness, medical evacuation, and deployability should be further evaluated.