Suchergebnisse

Human T-cell lymphotropic virus type 1 (HTLV-1) was the first human retrovirus to be reported and is associated with neoplastic, neurological, autoimmune, and infectious complications. HTLV-1 is endemic in Peru, with the highest prevalence reported among commercial sex workers. Seroprevalence data collected from Peruvian female sex workers (FSWs) working in Callao over three study periods between 1993 and 2010 were used to examine the secular trend in HTLV-1 prevalence. Between 1993 and 2010, the prevalence of HTLV-1 decreased significantly from 14.5% to 3.1% (P 0.07). There were no cases of HTLV-1 detected among FSW born after 1979 (N = 224). Participant characteristics associated with HTLV-1 seropositivity were birth in the Andes Mountains region, age, increased time in sex work, younger age of starting sex work, and human immunodeficiency virus (HIV) seropositivity. The secular trend in declining prevalence persisted after adjustment for age, time in sex work, place of birth, and HIV serostatus, with the odds of HTLV-1 infection decreasing approximately 16% per year (adjusted odds ratio = 0.84, 95% confidence interval = 0.78, 0.90). The increasing use of condoms by later birth cohorts noted in our analysis, as well as the increasing availability of free condoms provided by the Peruvian government—which started in the late 1980s before this study— may have been responsible for declining HTLV seroprevalence.

Understanding the burden and risk factors of dengue virus (DENV) infection in Puerto Rico is important for the prevention of dengue in local, traveler and military populations. Using sera from the Department of Defense Serum Repository, we estimated the prevalence and predictors of DENV seropositivity in those who had served in Puerto Rico, stratified by birth or prior residence ("birth/residence") in dengue-endemic versus non-endemic regions. We selected sera collected in early 2015 from 500 U.S. military members, a time-point also permitting detection of early cryptic Zika virus (ZIKV) circulation. 87.2% were born or resided in a DENV-endemic area before their military service in Puerto Rico. A high-throughput, flow-cytometry-based neutralization assay was employed to screen sera for ZIKV and DENV neutralizing antibodies, and confirmatory testing was done by plaque-reduction neutralization test (PRNT). We identified one Puerto Rico resident who seroconverted to ZIKV by June 2015, suggesting cryptic ZIKV circulation in Puerto Rico at least 4 months before the first reported cases. A further six PRNT-positive presumptive ZIKV infections which were resolved as DENV infections only by the use of paired sera. We noted 66.8% of the total study sample was DENV seropositive by early 2015. Logistic regression analysis indicated that birth/residence in a dengue non-endemic region (before military service in Puerto Rico) was associated with a lower odds of DENV exposure by January—June 2015 (aOR = 0.28, p = 0.001). Among those with birth/residence in a non-endemic country, we noted moderate evidence to support increase in odds of DENV exposure for each year of military service in Puerto Rico (aOR = 1.58, p = 0.06), but no association with age. In those with birth/residence in dengue-endemic regions (before military service in Puerto Rico), we noted that age (aOR = 1.04, p = 0.02), rather than duration of Puerto Rico service, was associated with dengue seropositivity, suggesting earlier lifetime DENV exposure. Our ...

Epidemics of emerging and re-emerging infectious diseases are a danger to civilian and military populations worldwide. Health security and mitigation of infectious disease threats is a priority of the United States Government and the Department of Defense (DoD). Next generation sequencing (NGS) and Bioinformatics (BI) enhances traditional biosurveillance by providing additional data to understand transmission, identify resistance and virulence factors, make predictions, and update risk assessments. As more and more laboratories adopt NGS and BI technologies they encounter challenges in building local capacity. In addition to choosing the right sequencing platform and approach, considerations must also be made for the complexity of bioinformatics analyses, data storage, as well as personnel and computational requirements. To address these needs, a comprehensive training program was developed covering wet lab and bioinformatics approaches to NGS. The program is meant to be modular and adaptive to meet both common and individualized needs of medical research and public health laboratories across the DoD. The training program was first deployed internationally to the Basic Science Laboratory of the US Army Medical Research Directorate-Africa in Kisumu, Kenya, which is an overseas Lab of the Walter Reed Army Institute of Research (WRAIR). A week-long workshop with intensive focus on targeted sequencing and the bioinformatics of genome assembly (n = 24 participants) was held. Post-workshop self-assessment (completed by 21 participants) noted significant median gains in knowledge domains related to NGS targeted sequencing, bioinformatics for genome assembly, and sequence quality assessment. The participants also reported that the information on study design, sample preparation, sequencing quality control, data quality assessment, reporting, and basic and advanced bioinformatics analysis were the most useful information presented in the training. While longer-term evaluations are planned, the training resulted in ...

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.

NGR reports funding by NIGMS grant R35GM119582. BMA is supported by Bill and Melinda Gates Foundation through the Global Good Fund. SP and IMB were funded by the Armed Forces Health Surveillance Branch (GEIS: P0116_19_WR_03.11). ; 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. ; Publisher PDF ; Peer reviewed

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.

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.

BACKGROUND: mRNA COVID-19 vaccines are playing a key role in controlling the COVID-19 pandemic. The relationship between post-vaccination symptoms and strength of antibody responses is unclear. OBJECTIVE: To determine whether adverse effects caused by vaccination with the Pfizer/BioNTech BNT162b2 vaccine are associated with the magnitude of vaccine-induced antibody levels. DESIGN: Single center, prospective, observational cohort study. SETTING: Participants worked at Walter Reed National Military Medical Center and were seen monthly at the Naval Medical Research Center Clinical Trials Center. PARTICIPANTS: Generally healthy adults that were not severely immunocompromised, had no history of COVID-19, and were seronegative for SARS-CoV-2 spike protein prior to vaccination. MEASURES: Severity of vaccine-associated symptoms was obtained through participant completed questionnaires. Testing for IgG antibodies against SARS-CoV-2 spike protein and receptor binding domain was conducted using microsphere-based multiplex immunoassays. RESULTS: 206 participants were evaluated (69.4% female, median age 41.5 years old). We found no correlation between vaccine-associated symptom severity scores and vaccine-induced antibody titers one month after vaccination. We also observed that 1) post-vaccination symptoms were inversely correlated with age and weight and more common in women, 2) systemic symptoms were more frequent after the second vaccination, 3) high symptom scores after first vaccination were predictive of high symptom scores after second vaccination, and 4) older age was associated with lower titers. LIMITATIONS: Study only observes antibody responses and consists of healthy participants. CONCLUSIONS: Lack of post-vaccination symptoms following receipt of the BNT162b2 vaccine does not equate to lack of vaccine-induced antibodies one month after vaccination. This study also suggests that it may be possible to design future mRNA vaccines that confer robust antibody responses with lower frequencies of vaccine-associated ...

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.