Armed Forces Health Surveillance Center

Adenocarcinoma of the lung is the leading cause of cancer death worldwide. Here we report molecular profiling of 230 resected lung adenocarcinomas using messenger RNA, microRNA and DNA sequencing integrated with copy number, methylation and proteomic analyses. High rates of somatic mutation were seen (mean 8.9 mutations per megabase). Eighteen genes were statistically significantly mutated, including RIT1 activating mutations and newly described loss-of-function MGA mutations which are mutually exclusive with focal MYC amplification. EGFR mutations were more frequent in female patients, whereas mutations in RBM10 were more common in males. Aberrations in NF1, MET, ERBB2 and RIT1 occurred in 13% of cases and were enriched in samples otherwise lacking an activated oncogene, suggesting a driver role for these events in certain tumours. DNA and mRNA sequence from the same tumour highlighted splicing alterations driven by somatic genomic changes, including exon 14 skipping in MET mRNA in 4% of cases. MAPK and PI(3)K pathway activity, when measured at the protein level, was explained by known mutations in only a fraction of cases, suggesting additional, unexplained mechanisms of pathway activation. These data establish a foundation for classification and further investigations of lung adenocarcinoma molecular pathogenesis. An integrated transcriptome, genome, methylome and proteome analysis of over 200 lung adenocarcinomas reveals high rates of somatic mutations, 18 statistically significantly mutated genes including RIT1 and MGA, splicing changes, and alterations in MAPK and PI(3)K pathway activity. This report from The Cancer Genome Atlas Research Network presents molecular profiling of 230 resected untreated lung adenocarcinomas. Integrated analyses of transcriptome, genome, methylome and proteome collectively identify high rates of somatic mutation, significantly mutated genes including RIT1 and MGA, splicing alterations driven by somatic genomic changes, and point to as yet unidentified lesions that alter MAPK and PI(3)K pathway activity. These data establish a foundation for classification and further investigations of the leading cause of cancer death worldwide.

Deaths during the 1918-19 influenza pandemic have been attributed to a hypervirulent influenza strain. Hence, preparations for the next pandemic focus almost exclusively on vaccine prevention and antiviral treatment for infections with a novel influenza strain. However, we hypothesize that infections with the pandemic strain generally caused self-limited (rarely fatal) illnesses that enabled colonizing strains of bacteria to produce highly lethal pneumonias. This sequential-infection hypothesis is consistent with characteristics of the 1918-19 pandemic, contemporaneous expert opinion, and current knowledge regarding the pathophysiologic effects of influenza viruses and their interactions with respiratory bacteria. This hypothesis suggests opportunities for prevention and treatment during the next pandemic (e.g., with bacterial vaccines and antimicrobial drugs), particularly if a pandemic strain-specific vaccine is unavailable or inaccessible to isolated, crowded, or medically underserved populations.

Bacterial vaginosis (BV) is a common vaginal disorder in women of reproductive age. Since the initial work of Leopoldo in 1953 and Gardner and Dukes in 1955, researchers have not been able to identify the causative etiologic agent of BV. There is increasing evidence, however, that BV occurs when Lactobacillus spp., the predominant species in healthy vaginal flora, are replaced by anaerobic bacteria, such as Gardenella vaginalis, Mobiluncus curtisii, M. mulieris, other anaerobic bacteria and/or Mycoplasma hominis. Worldwide, it estimated that 20-30 % of women of reproductive age attending sexually transmitted infection (STI) clinics suffer from BV, and that its prevalence can be as high as 50-60 % in high-risk populations (e.g., those who practice commercial sex work (CSW). Epidemiological data show that women are more likely to report BV if they: 1) have had a higher number of lifetime sexual partners; 2) are unmarried; 3) have engaged in their first intercourse at a younger age; 4) have engaged in CSW, and 5) practice regular douching. In the past decade, several studies have provided evidence on the contribution of sexual activity to BV. However, it is difficult to state that BV is a STI without being able to identify the etiologic agent. BV has also emerged as a public health problem due to its association with other STIs, including: human immunodeficiency virus (HIV), herpes simplex virus type 2 (HSV-2), Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG). The most recent evidence on the association between BV and CT/NG infection comes from two secondary analyses of cohort data conducted among women attending STI clinics. Based on these studies, women with BV had a 1.8 and 1.9-fold increased risk for NG and CT infection, respectively. Taken together, BV is likely a risk factor or at least an important contributor to subsequent NG or CT infection in high-risk women. Additional research is required to determine whether this association is also present in other low-risk sexually active populations, such as among women in the US military. It is essential to conduct large scale cross-sectional or population-based case-control studies to investigate the role of BV as a risk factor for CT/NG infections. These studies could lead to the development of interventions aimed at reducing the burden associated with bacterial STIs worldwide.

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.

Forecasts of influenza activity in human populations could help guide key preparedness tasks. We conducted a scoping review to characterize these methodological approaches and identify research gaps. Adapting the PRISMA methodology for systematic reviews, we searched PubMed, CINAHL, Project Euclid, and Cochrane Database of Systematic Reviews for publications in English since January 1, 2000 using the terms "influenza AND (forecast* OR predict*)", excluding studies that did not validate forecasts against independent data or incorporate influenza-related surveillance data from the season or pandemic for which the forecasts were applied. We included 35 publications describing population-based (N = 27), medical facility-based (N = 4), and regional or global pandemic spread (N = 4) forecasts. They included areas of North America (N = 15), Europe (N = 14), and/or Asia-Pacific region (N = 4), or had global scope (N = 3). Forecasting models were statistical (N = 18) or epidemiological (N = 17). Five studies used data assimilation methods to update forecasts with new surveillance data. Models used virological (N = 14), syndromic (N = 13), meteorological (N = 6), internet search query (N = 4), and/or other surveillance data as inputs. Forecasting outcomes and validation metrics varied widely. Two studies compared distinct modeling approaches using common data, 2 assessed model calibration, and 1 systematically incorporated expert input. Of the 17 studies using epidemiological models, 8 included sensitivity analysis. This review suggests need for use of good practices in influenza forecasting (e.g., sensitivity analysis); direct comparisons of diverse approaches; assessment of model calibration; integration of subjective expert input; operational research in pilot, real-world applications; and improved mutual understanding among modelers and public health officials.

Abstract Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015–2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14–81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5–28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p < 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p < 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.

Next generation sequencing (NGS) combined with bioinformatics has successfully been used in a vast array of analyses for infectious disease research of public health relevance. For instance, NGS and bioinformatics approaches have been used to identify outbreak origins, track transmissions, investigate epidemic dynamics, determine etiological agents of a disease, and discover novel human pathogens. However, implementation of high-quality NGS and bioinformatics in research and public health laboratories can be challenging. These challenges mainly include the choice of the sequencing platform and the sequencing approach, the choice of bioinformatics methodologies, access to the appropriate computation and information technology infrastructure, and recruiting and retaining personnel with the specialized skills and experience in this field. In this review, we summarize the most common NGS and bioinformatics workflows in the context of infectious disease genomic surveillance and pathogen discovery, and highlight the main challenges and considerations for setting up an NGS and bioinformatics-focused infectious disease research public health laboratory. We describe the most commonly used sequencing platforms and review their strengths and weaknesses. We review sequencing approaches that have been used for various pathogens and study questions, as well as the most common difficulties associated with these approaches that should be considered when implementing in a public health or research setting. In addition, we provide a review of some common bioinformatics tools and procedures used for pathogen discovery and genome assembly, along with the most common challenges and solutions. Finally, we summarize the bioinformatics of advanced viral, bacterial, and parasite pathogen characterization, including types of study questions that can be answered when utilizing NGS and bioinformatics.

PURPOSE: To assess the radioprotective potential of gamma-tocotrienol. MATERIALS AND METHODS: To optimise its dose and time regimen, gamma-tocotrienol (GT3) was injected subcutaneously (SC) at different doses into male CD2F1 mice [LD(50/30) (lethal radiation dose that results in the mortality of 50% mice in 30 days) radiation dose of 8.6 Gy with vehicle]. The mice were given 10.5, 11 and 11.5 Gy cobalt-60 radiation, and 30-day survival-protection was determined. Time optimisation was done by SC administration of GT3 at different intervals before irradiation. Dose reduction factor (DRF) was determined by probit analysis using mortality as the end point at six radiation doses. Protection from radiation induced pancytopenia was determined by enumerating peripheral blood cells from mice given GT3 and irradiated at 7 Gy. RESULTS: At an optimal dose of 200 mg/kg given SC 24 h before irradiation, GT3 had a DRF of 1.29. GT3 accelerated the recovery of total white blood cells, neutrophils, monocytes, platelets, and reticulocytes in irradiated mice, compared to vehicle-injected, irradiated controls. CONCLUSION: GT3 is a radioprotectant having a higher DRF than any other tocols. The protection it provides close to the gastro-intestinal range indicate that GT3 can be considered as an ideal radioprotectant meriting further drug development stages for the ultimate use in humans.

We conducted a longitudinal observational study of 533 patients presenting to two hospitals in the Ecuadorean Amazon basin with acute undifferentiated febrile illness (AUFI) from 2001 through 2004. Viral isolation, reverse transcription-polymerase chain reaction (RT-PCR), IgM seroconversion, and malaria smears identified pathogens responsible for fever in 122 (40.1%) of 304 patients who provided both acute and convalescent blood samples. Leptospirosis was found in 40 (13.2%), malaria in 38 (12.5%), rickettsioses in 18 (5.9%), dengue fever in 16 (5.3%), Q fever in 15 (4.9%), brucellosis in 4 (1.3%), Ilhéus infection in 3 (1.0%), and Venezuelan equine encephalitis (VEE), Oropouche, and St. Louis encephalitis virus infections in less than 1% of these patients. Viral isolation and RT-PCR on another 229 participants who provided only acute samples identified 3 cases of dengue fever, 2 of VEE, and 1 of Ilhéus. None of these pathogens, except for malaria, had previously been detected in the study area.

BACKGROUND: The Department of Defense Military Health System operates a syndromic surveillance system that monitors medical records at more than 450 non-combat Military Treatment Facilities (MTF) worldwide. The Electronic Surveillance System for Early Notification of Community-based Epidemics (ESSENCE) uses both temporal and spatial algorithms to detect disease outbreaks. This study focuses on spatial detection and attempts to improve the effectiveness of the ESSENCE implementation of the spatial scan statistic by increasing the spatial resolution of incidence data from zip codes to street address level. METHODS: Influenza-Like Illness (ILI) was used as a test syndrome to develop methods to improve the spatial accuracy of detected alerts. Simulated incident clusters of various sizes were superimposed on real ILI incidents from the 2008/2009 influenza season. Clusters were detected using the spatial scan statistic and their displacement from simulated loci was measured. Detected cluster size distributions were also evaluated for compliance with simulated cluster sizes. RESULTS: Relative to the ESSENCE zip code based method, clusters detected using street level incidents were displaced on average 65% less for 2 and 5 mile radius clusters and 31% less for 10 mile radius clusters. Detected cluster size distributions for the street address method were quasi normal and sizes tended to slightly exceed simulated radii. ESSENCE methods yielded fragmented distributions and had high rates of zero radius and oversized clusters. CONCLUSIONS: Spatial detection accuracy improved notably with regard to both location and size when incidents were geocoded to street addresses rather than zip code centroids. Since street address geocoding success rates were only 73.5%, zip codes were still used for more than one quarter of ILI cases. Thus, further advances in spatial detection accuracy are dependant on systematic improvements in the collection of individual address information.

BACKGROUND: In late 2011, after a 12-year hiatus, oral vaccines against adenovirus types 4 (Ad4) and 7 (Ad7) were again produced and administered to US military recruits. This study examined the impact of the new adenovirus vaccines on febrile respiratory illness (FRI) and adenovirus rates and investigated if new serotypes emerged. FRI rates and their associated hospitalizations had markedly risen since vaccine production ceased in 1999. METHODS: From 1996 to 2013, the Naval Health Research Center conducted FRI surveillance at 8 military recruit training centers in the United States. During this period, 58 103 FRI pharyngeal swab specimens were studied, yielding 37 048 adenovirus-positive cases, among which 64% were typed. RESULTS: During the 2 years after reintroduction of the vaccines, military trainees experienced a 100-fold decline in adenovirus disease burden (from 5.8 to 0.02 cases per 1000 person-weeks, P < .0001), without evidence that vaccine pressure had increased the impact of adenovirus types other than Ad4 and Ad7. Although the percentage of type 14 increased following reintroduction of the vaccination, the actual number of cases decreased. We estimate that the vaccines prevent approximately 1 death, 1100-2700 hospitalizations, and 13 000 febrile adenovirus cases each year among the trainees. CONCLUSIONS: These data strongly support the continued production and use of Ad4 and Ad7 vaccines in controlling FRI among US military trainees. Continued surveillance for emerging adenovirus subtypes is warranted.

As of November 2015, the Ebola virus disease (EVD) epidemic that began in West Africa in late 2013 is waning. The human toll includes more than 28,000 EVD cases and 11,000 deaths in Guinea, Liberia, and Sierra Leone, the most heavily-affected countries. We reviewed 66 mathematical modeling studies of the EVD epidemic published in the peer-reviewed literature to assess the key uncertainties models addressed, data used for modeling, public sharing of data and results, and model performance. Based on the review, we suggest steps to improve the use of modeling in future public health emergencies.

Infectious disease modeling has played a prominent role in recent outbreaks, yet integrating these analyses into public health decision-making has been challenging. We recommend establishing ‘outbreak science’ as an inter-disciplinary field to improve applied epidemic modeling.

BACKGROUND: Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya. METHODS AND FINDINGS: We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004-2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3-4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall. CONCLUSIONS/SIGNIFICANCE: Extremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecological drivers of vector-borne diseases is critical in long-range planning of appropriate disease and disease-vector response, control, and mitigation strategies.

Adult Aedes aegypti (Linnaeus) (Diptera: Culicidae) were previously recovered from emergence traps on septic tanks in southeastern Puerto Rico. In this study we quantified immature mosquito abundance and its relationship with structural variables of the septic tanks and chemical properties of the water containing raw sewage. A miniaturized floating funnel trap was used to sample 89 septic tanks for larvae in the Puerto Rican community of Playa-Playita. Aedes aegypti larvae were recovered from 18% of the sampled tanks (10.3 larvae per septic tank per day). Larval presence was positively associated with cracking of the septic tank walls and uncovered access ports. Larval abundance was positively associated with cracking of the septic tank walls and larger tank surface areas, and inversely associated with the total dissolved solids (TDS). Culex quinquefasciatus (Say) larvae were also recovered from 74% of the septic tanks (129.6 larvae per septic tank per day). Larval presence was negatively associated with TDS in the water and larval abundance was positively associated with cracking of the septic tank walls. A screened, plastic emergence trap was used to sample 93 septic tanks within the community for Ae. aegypti and Cx. quinquefasciatus adults. Aedes aegypti adults were recovered from 49% of the sampled tanks (8.7 adults per septic tank per day) and Cx. quinquefasciatus adults were recovered from 97% of the sampled tanks (155.5 adults per septic tank per day). Aedes aegypti adult presence was positively associated with cracking, uncapped openings and septic water pH. The Ae. aegypti adult counts were positively associated with cracking and inversely associated with TDS and conductivity. This study marks the first published record of the recovery of Ae. aegypti larvae from holding tanks containing raw sewage in the Caribbean region. Our study indicates that Ae. aegypti larvae are present in sewage water and that septic tanks have at least the potential to maintain dengue transmission during the dry season.

This comprehensive review outlines the impact of military-relevant respiratory infections, with special attention to recruit training environments, influenza pandemics in 1918 to 1919 and 2009 to 2010, and peacetime operations and conflicts in the past 25 years. Outbreaks and epidemiologic investigations of viral and bacterial infections among high-risk groups are presented, including (i) experience by recruits at training centers, (ii) impact on advanced trainees in special settings, (iii) morbidity sustained by shipboard personnel at sea, and (iv) experience of deployed personnel. Utilizing a pathogen-by-pathogen approach, we examine (i) epidemiology, (ii) impact in terms of morbidity and operational readiness, (iii) clinical presentation and outbreak potential, (iv) diagnostic modalities, (v) treatment approaches, and (vi) vaccine and other control measures. We also outline military-specific initiatives in (i) surveillance, (ii) vaccine development and policy, (iii) novel influenza and coronavirus diagnostic test development and surveillance methods, (iv) influenza virus transmission and severity prediction modeling efforts, and (v) evaluation and implementation of nonvaccine, nonpharmacologic interventions.

BACKGROUND: Carrion's disease affects small Andean communities in Peru, Colombia and Ecuador and is characterized by two distinct disease manifestations: an abrupt acute bacteraemic illness (Oroya fever) and an indolent cutaneous eruptive condition (verruga Peruana). Case fatality rates of untreated acute disease can exceed 80% during outbreaks. Despite being an ancient disease that has affected populations since pre-Inca times, research in this area has been limited and diagnostic and treatment guidelines are based on very low evidence reports. The apparently limited geographical distribution and ecology of Bartonella bacilliformis may present an opportunity for disease elimination if a clear understanding of the epidemiology and optimal case and outbreak management can be gained. METHODS: All available databases were searched for English and Spanish language articles on Carrion's disease. In addition, experts in the field were consulted for recent un-published work and conference papers. The highest level evidence studies in the fields of diagnostics, treatment, vector control and epidemiology were critically reviewed and allocated a level of evidence, using the Oxford Centre for Evidence-Based Medicine (CEBM) guidelines. RESULTS: A total of 44 studies were considered to be of sufficient quality to be included in the analysis. The majority of these were level 4 or 5 (low quality) evidence and based on small sample sizes. Few studies had been carried out in endemic areas. CONCLUSIONS: Current approaches to the diagnosis and management of Carrion's disease are based on small retrospective or observational studies and expert opinion. Few studies take a public health perspective or examine vector control and prevention. High quality studies performed in endemic areas are required to define optimal diagnostic and treatment strategies.

Popular running magazines and running shoe companies suggest that imprints of the bottom of the feet (plantar shape) can be used as an indication of the height of the medial longitudinal foot arch and that this can be used to select individually appropriate types of running shoes. This study examined whether or not this selection technique influenced injury risk during United States Army Basic Combat Training (BCT). After foot examinations, BCT recruits in an experimental group (E: n = 1,079 men and 451 women) selected motion control, stability, or cushioned shoes for plantar shapes judged to represent low, medium, or high foot arches, respectively. A control group (C: n = 1,068 men and 464 women) received a stability shoe regardless of plantar shape. Injuries during BCT were determined from outpatient medical records. Other previously known injury risk factors (e.g., age, fitness, and smoking) were obtained from a questionnaire and existing databases. Multivariate Cox regression controlling for other injury risk factors showed little difference in injury risk between the E and C groups among men (risk ratio (E/C) = 1.01; 95% confidence interval = 0.88-1.16; p = 0.87) or women (risk ratio (E/C) = 1.07; 95% confidence interval = 0.91-1.25; p = 0.44). In practical application, this prospective study demonstrated that selecting shoes based on plantar shape had little influence on injury risk in BCT. Thus, if the goal is injury prevention, this selection technique is not necessary in BCT.

The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program's ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia.

In order to explore a priori hypotheses about drug-induced Stevens-Johnson Syndrome (SJS), a case-control study was initiated using data from COMPASS, a computerized data base consisting of Medicaid claims data. The records of 3.8 million patients in five U.S. states were searched to identify patients with an inpatient diagnosis of ICD-9-CM code 695.1 (erythema multiforme-EM). Out of the total of 367 cases that were identified, primary medical records for 249 were sought and 128 (51.4 per cent) of these were obtained. The remainder could not be obtained because: in 36 (29.8 per cent) the hospital refused to provide medical records; in 33 (27.3 per cent) there were transcription errors; in 20 (16.5 per cent) the state could not translate the identification number, primarily because the patients lost Medicaid eligibility too long before our request; in 27 (22.3 per cent) the hospital could not locate the patient's record; and in 5 (4.1 per cent) there were other reasons. Of those with a medical record, 121 (94.5 per cent) had a skin diagnosis and 109 (85.2 per cent) had a diagnosis compatible with ICD-9-CM code 695.1 specified on their discharge summary. However, in 35 (27.3 per cent) an expert reviewer felt that the discharge diagnosis was incorrect. In 50 (39 per cent) the computer diagnosis was incorrect. Only 19 (14.8 per cent) were judged by the expert reviewer to truly have Stevens-Johnson Syndrome, and an additional 37 (28.9 per cent) were judged to have erythema multiforme minor. Thus, the computerized diagnosis agreed very well with the diagnoses specified on the discharge summary. However, EM is frequently misdiagnosed, ICD-9-CM code 695.1 contains multiple other diagnoses which are not EM, and much of hospitalized EM is EM minor. Thus, studies of SJS cannot be performed except in patients whose medical records are available.