Suchergebnisse

BACKGROUND: Travel-related arboviral infections are important preventable, emerging infectious diseases, with an estimated annual global toll of US$950 million. We investigated the burden of arboviral infections in the military health system (MHS). METHODS: KAPOS (Deployment and Travel Health: Knowledge, Attitudes, Practices, and Outcomes Study) is a multi-cohort study evaluating the burden of travel-associated diseases in the MHS. The MHS Data Repository was searched for International Classification of Diseases (ICD)-9/10 codes for arboviral infection in military beneficiaries receiving care in military treatment facilities (direct care) or civilian centers (purchased care) for fiscal years 2011-2019. Diagnostic codes were classified as Dengue, Chikungunya, Zika, or other arboviral infection. 755 outpatient charts in the direct-care system were randomly selected for diagnostic validation using Armed Forces Health Surveillance Center case definitions, and review of travel history, medical comorbidities, and pre-travel counseling. RESULTS: 11,066 unique-patient ICD codes for arboviral infections were identified; 6356 (57.4%) were direct care; 4710 (42.6%) were purchased care; 889 (8.0%) were inpatient. Median age was 31 years; 5110 (46.2%) were active duty. The most frequent ICD codes for arboviral infection were Japanese encephalitis virus (JEV) (n=4483), dengue (DENV) (n=1786), yellow fever (YF) (n=230), Zika virus (ZIKV) (n=217), West Nile virus (WNV) (n=171), and chikungunya virus (CHIKV) (n=91). DENV codes were confirmed in 166/249 (66.7%) charts; CHIKV in 23/41 (56.1%), and ZIKV in 15/129 (11.6%). No cases of JEV were confirmed in 171 encounters; all codes referred to JEV vaccine administration. 173/204 (84.8%) of confirmed arboviral cases did not undergo pre-travel counseling. CONCLUSION: Arboviral infections constitute a substantial burden of preventable infections within the MHS. Dengue contributed the largest burden of arboviral infection when corrected for accuracy. Coding for ZIKV and JEV likely ...

BACKGROUND: Increasing international travel places larger populations at risk for infections outside of their usual exposure. Deployed military personnel have unique risks for such infections. Our cohort's rates of travelers' diarrhea and influenza-like illness have been defined, but the rate of travelers with symptoms apart from a clinical syndrome has not. We present a survey of intra-travel symptoms of all travelers and confirmed diagnoses of ill-returned travelers in a cohort of military and civilian travelers. METHODS: TravMil is a prospective, multicenter observational study enrolling US military beneficiaries traveling outside the continental United States from 2010–2018; beneficiaries could also enroll after travel if they presented for a possible travel-related illness. Demographic information, intra-travel symptoms, and confirmed diagnoses were recorded. RESULTS: 2671 travelers embarked on 3050 trips: 63.1% male; median age 38 years (IQR 27, 57); median trip duration 20 days (IQR 13, 46). Common purposes of travel: military deployment (45.9%), vacation (23.7%), and visiting friends/relatives (10.9%). Ninety-seven travelers (3.2%) enrolled post-travel. Top regions of travel: Africa (31.5%), South and Central America/Caribbean (25.5%), and Southeast and North Asia/Oceania (19.4%). During travel, 56.6% experienced gastrointestinal (GI) symptoms, 11.9% respiratory symptoms, and 3.0% fever; of those, 10.3% sought medical care. Eighty returned travelers sought medical care (21 prospective enrollees vs. 59 post-travel enrollees): 5 vs. 17 malaria cases, 3 vs. 16 arbovirus infections, and 6 vs. 14 GI syndromes. All malaria cases in prospective enrollees were in military subjects. Post-travel enrollees accounted for 1 acute human immunodeficiency virus and 3 rickettsial infections. CONCLUSION: A majority of our travelers experienced symptoms during travel. Post-travel diagnoses, although uncommon, emphasize needed improvements in the application of known risk mitigation strategies. Our findings can help ...

Drive-through coronavirus disease 2019 screening can evaluate large numbers of patients while reducing healthcare exposures and personal protective equipment use. We describe the characteristics of screened individuals as well as drive-through process and outcome measures. Optimal drive-through screening involves rapid turnaround of test results and linkage to follow-up care.

Travelers are at risk for arbovirus infection. We prospectively enrolled 267 Department of Defense beneficiaries traveling to chikungunya-outbreak regions in the Americas between December 2013 and May 2015 and assessed travel characteristics and serologic exposure to chikungunya virus (CHIKV) and dengue virus (DENV). Ten ill-returning travelers were also assessed retrospectively. Self-reported mosquito exposure was common (64% of 198 evaluable travelers saw mosquitoes; 53% of 201 reported ≥ 1 bite). Increased exposure was associated with active-duty travelers (odds ratio [OR] = 2.6 [1.3–5.4] for seeing mosquitoes) or travelers visiting friends and relatives (VFR) (OR = 3.5 [1.0–10.0] for high-intensity bite exposure). Arbovirus infection was defined as seroconversion on plaque reduction neutralization testing (PRNT) of pre- and posttravel sera. For ill subjects enrolled posttravel, infection was defined by a positive convalescent PRNT and/or a positive reverse transcription polymerase chain reaction for CHIKV or DENV. We identified seven cases of arbovirus infection: four with CHIKV, five with DENV, and two with both. The composite attack rate for CHIKV and DENV infection was 3.7% of 108 evaluable, immunologically naïve, prospectively assessed travelers; there was serologic and/or polymerase chain reaction evidence of arbovirus infection in three of four evaluable (three of 10 total) ill-returning travelers. We identified both symptomatic and asymptomatic cases. Military purpose of travel and VFR travel accounted for five of seven cases. Pretravel counseling is important and should target higher risk groups. Given a shared vector between CHIKV, DENV, and Zika virus (ZIKV), this study can also help guide counseling for travelers to ZIKV-outbreak regions.

BACKGROUND: Early recognition of high-risk patients with coronavirus disease 2019 (COVID-19) may improve outcomes. Although many predictive scoring systems exist, their complexity may limit utility in COVID-19. We assessed the prognostic performance of the National Early Warning Score (NEWS) and an age-based modification (NEWS+age) among hospitalized COVID-19 patients enrolled in a prospective, multicenter US Military Health System (MHS) observational cohort study. METHODS: Hospitalized adults with confirmed COVID-19 not requiring invasive mechanical ventilation at admission and with a baseline NEWS were included. We analyzed each scoring system's ability to predict key clinical outcomes, including progression to invasive ventilation or death, stratified by baseline severity (low [0–3], medium [4–6], and high [≥7]). RESULTS: Among 184 included participants, those with low baseline NEWS had significantly shorter hospitalizations (P < .01) and lower maximum illness severity (P < .001). Most (80.2%) of low NEWS vs 15.8% of high NEWS participants required no or at most low-flow oxygen supplementation. Low NEWS (≤3) had a negative predictive value of 97.2% for progression to invasive ventilation or death; a high NEWS (≥7) had high specificity (93.1%) but low positive predictive value (42.1%) for such progression. NEWS+age performed similarly to NEWS at predicting invasive ventilation or death (NEWS+age: area under the receiver operating characteristics curve [AUROC], 0.69; 95% CI, 0.65–0.73; NEWS: AUROC, 0.70; 95% CI, 0.66–0.75). CONCLUSIONS: NEWS and NEWS+age showed similar test characteristics in an MHS COVID-19 cohort. Notably, low baseline scores had an excellent negative predictive value. Given their easy applicability, these scoring systems may be useful in resource-limited settings to identify COVID-19 patients who are unlikely to progress to critical illness.

BACKGROUND: While the majority of illness due to COVID-19 does not require hospitalization, little has been described about the host inflammatory response in the ambulatory setting. Differences in the levels of inflammatory signaling proteins between outpatient and hospitalized populations could identify key maladaptive immune responses during COVID-19. METHODS: Samples were collected from 76 participants (41% female, mean 46.8 years of age) enrolled at five military treatment facilities between March 20, 2020 and June 17, 2020 in an ongoing prospective COVID-19 cohort. This analysis was restricted to those with positive SARS-CoV-2 (severe acute respiratory syndrome–coronavirus 2) RT-PCR testing and included hospitalized (N=29; 10 requiring an ICU stay) and non-hospitalized (N=43) participants. Severity markers (IL6, D-dimer, procalcitonin, ferritin, ICAM-1, IL5, lipocalin, RAGE, TNFR, VEGFA, IFNγ, IL1β) were measured in plasma (mg/dL) using the Ella immunoassay and natural log transformed. Univariate negative binomial regression was performed to determine relative risk of hospitalization. Using the full marker panel, we performed a Principal Component Analysis (PCA) to determine directions of maximal variance in the data. Pearson's correlation coefficient was determined between analytes and each axis. RESULTS: Participants requiring ambulatory-, hospital-, and ICU-level care had samples collected at 44.0 (IQR: 35.0–51.0), 40.0 (13.0–51.0), and 47.5 (21.0–54.0) days, respectively. Higher unadjusted levels of IL6, D-dimer, procalcitonin, or ferritin were each associated with hospitalization (Table 1). The PCA showed a separation along axes between level of care and duration of symptoms (Fig 1). While significant correlations were noted with a number of biomarkers, PC1 most correlated with TNFR1 (r=0.88) and PC2 most correlated with IL6Ra (r=0.95). PC1 axis variation accounted for 36.5% of variance and the PC2 axis accounted for 20.0% of variance. Figure 1. Principal Component Analysis (PCA) of biomarkers by level ...

BACKGROUND: We evaluated clinical outcomes, functional burden, and complications 1 month after coronavirus disease 2019 (COVID-19) infection in a prospective US Military Health System (MHS) cohort of active duty, retiree, and dependent populations using serial patient-reported outcome surveys and electronic medical record (EMR) review. METHODS: MHS beneficiaries presenting at 9 sites across the United States with a positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) test, a COVID-19-like illness, or a high-risk SARS-CoV-2 exposure were eligible for enrollment. Medical history and clinical outcomes were collected through structured interviews and International Classification of Diseases–based EMR review. Risk factors associated with hospitalization were determined by multivariate logistic regression. RESULTS: A total of 1202 participants were enrolled. There were 1070 laboratory-confirmed SARS-CoV-2 cases and 132 SARS-CoV-2-negative participants. In the first month post–symptom onset among the SARS-CoV-2-positive cases, there were 212 hospitalizations, 80% requiring oxygen, 20 ICU admissions, and 10 deaths. Risk factors for COVID-19-associated hospitalization included race (increased for Asian, Black, and Hispanic compared with non-Hispanic White), age (age 45–64 and 65+ compared with <45), and obesity (BMI≥30 compared with BMI<30). Over 2% of survey respondents reported the need for supplemental oxygen, and 31% had not returned to normal daily activities at 1 month post–symptom onset. CONCLUSIONS: Older age, reporting Asian, Black, or Hispanic race/ethnicity, and obesity are associated with SARS-CoV-2 hospitalization. A proportion of acute SARS-CoV-2 infections require long-term oxygen therapy; the impact of SARS-CoV-2 infection on short-term functional status was substantial. A significant number of MHS beneficiaries had not yet returned to normal activities by 1 month.