Biosurveillance of Drug Overdoses and Substance Misuse Treated in Selected Emergency Departments in Minnesota, 2017-2020.

OBJECTIVES: Increasing knowledge about the toxicology of drug overdose and substance misuse (DOSM) is important in improving our understanding of the epidemic. We describe the Minnesota Drug Overdose and Substance Use Pilot Surveillance Activity, which started collecting data on emergency department (ED) visits attributable to DOSM in 2017, with a focus on the toxicology results of a subset of clinical encounters. METHODS: From November 1, 2017, through January 30, 2020, we collected near-real-time data on DOSM-related ED encounters. The Minnesota Department of Health Public Health Laboratory tested leftover clinical specimens (blood and/or urine) for the presence of various substances for patients who died, were hospitalized, had an atypical clinical presentation, or were part of a local drug overdose cluster. Testing looked for >250 drugs or their metabolites, including those commonly misused (eg, methamphetamine, cocaine), prescription medications, synthetic cannabinoids and cathinones, and opioids. We describe characteristics of the overall group and a subgroup of clinical encounters with toxicology results. RESULTS: Specimens submitted from 6 EDs during the study period represented 239 clinical encounters. Methamphetamine was the most frequently detected substance (67.4%) but was suspected in only 45.6% of encounters. At least 1 opioid was detected in 42.5% of encounters but suspected in only 29.7%. Testing also detected potential adulterants and additives (eg, fentanyl, fentanyl analogues, levamisole) and showed frequent patient exposure to substances not reported by patients or suspected by clinicians. Nearly half (44.4%) of clinical encounters had >1 substance detected. CONCLUSIONS: ED surveillance for DOSM encounters, enhanced by toxicology testing, can provide local situational awareness on overdoses, prevent potential mischaracterization of the true drug overdose epidemic, and inform harm reduction and drug overdose prevention efforts.

Fast, Scalable, and Practical: An Alkaline DNA Extraction Pipeline for Emergency Microbiomics Biosurveillance.

Pandemics and environmental crises evident from the first two decades of the 21st century call for methods innovation in biosurveillance and early detection of risk signals in planetary ecosystems. In crises conditions, conventional methods in public health, biosecurity, and environmental surveillance do not work well. In addition, the standard laboratory amenities and procedures may become unavailable, irrelevant, or simply not feasible, for example, owing to disruptions in logistics and process supply chains. The COVID-19 pandemic has been a wakeup call in this sense to reintroduce point-of-need diagnostics with an eye to limited resource settings and biosurveillance solutions. We report here a methodology innovation, a fast, scalable, and alkaline DNA extraction pipeline for emergency microbiomics biosurveillance. We believe that the presented methodology is well poised for effective, resilient, and anticipatory responses to future pandemics and ecological crises while contributing to microbiome science and point-of-need diagnostics in nonelective emergency contexts. The alkaline DNA extraction pipeline can usefully expand the throughput in emergencies by deployment or to allow backup in case of instrumentation failure in vital facilities. The need for distributed public health genomics surveillance is increasingly evident in the 21st century. This study makes a contribution to these ends broadly, and for future pandemic preparedness in particular. We call for innovation in biosurveillance methods that remain important existentially on a planet under pressure from unchecked human growth and breach of the boundaries between human and nonhuman animal habitats.

Mosquito Identification From Bulk Samples Using DNA Metabarcoding: a Protocol to Support Mosquito-Borne Disease Surveillance in Canada.

Approximately 80 species of mosquitoes (Diptera: Culicidae) have been documented in Canada. Exotic species such as Aedes albopictus (Skuse) (Diptera: Culicidae) are becoming established. Recently occurring endemic mosquito-borne diseases (MBD) in Canada including West-Nile virus (WNV) and Eastern Equine Encephalitis (EEE) are having significant public health impacts. Here we explore the use of DNA metabarcoding to identify mosquitoes from CDC light-trap collections from two locations in eastern Canada. Two primer pairs (BF2-BR2 and F230) were used to amplify regions of the cytochrome c oxidase subunit I (CO1) gene. High throughput sequencing was conducted using an Illumina MiSeq platform and GenBank-based species identification was applied using a QIIME 1.9 bioinformatics pipeline. From a site in southeastern Ontario, Canada, 26 CDC light trap collections of 72 to >300 individual mosquitoes were used to explore the capacity of DNA metabarcoding to identify and quantify captured mosquitoes. The DNA metabarcoding method identified 33 species overall while 24 species were identified by key. Using replicates from each trap, the dried biomass needed to identify the majority of species was determined to be 76 mg (equivalent to approximately 72 mosquitoes), and at least two replicates from the dried biomass would be needed to reliably detect the majority of species in collections of 144-215 mosquitoes and three replicates would be advised for collections with >215 mosquitoes. This study supports the use of DNA metabarcoding as a mosquito surveillance tool in Canada which can help identify the emergence of new mosquito-borne disease potential threats.

Multichart Schemes for Detecting Changes in Disease Incidence.

Several methods have been proposed in open literatures for detecting changes in disease outbreak or incidence. Most of these methods are likelihood-based as well as the direct application of Shewhart, CUSUM and EWMA schemes. We use CUSUM, EWMA and EWMA-CUSUM multi-chart schemes to detect changes in disease incidence. Multi-chart is a combination of several single charts that detects changes in a process and have been shown to have elegant properties in the sense that they are fast in detecting changes in a process as well as being computationally less expensive. Simulation results show that the multi-CUSUM chart is faster than EWMA and EWMA-CUSUM multi-charts in detecting shifts in the rate parameter. A real illustration with health data is used to demonstrate the efficiency of the schemes.

Implementation System of a Biosurveillance System in the Republic of Korea and Its Legal Ramifications.

Laws are fundamental tools that regulate and manage various issues to protect the rights of the people in a society. Legislation on disease surveillance enables agencies to regulate and manage public health, including preventing the spread of infectious diseases. We assessed the Infectious Disease Prevention and Control Act of Korea (IDPCA) through the lens of biosurveillance to understand its effectiveness in protecting public health. In addition, the relevant legislation and regulations of the United States and the World Health Organization were examined. The evaluation concludes that the current IDPCA is limited in terms of providing guidance for early detection of and response to hazards using integrated data and an information-sharing system. Further revision of the laws is needed to enable early detection and warning of potential threats to public health.

A new statistical early outbreak detection method for biosurveillance and performance comparisons.

Biosurveillance for rapid detection of epidemics of diseases is a challenging area of endeavor in many respects. Hence, this area is in need of development of methodology and opens to novel methods of detection. In this study, a new simple statistical early outbreak detection approach is proposed to detect outbreaks of diseases in real time. The new approach is called LWMAT since it is based on linearly weighted moving average. Furthermore, it does not require a long baseline and partly takes into account of likely features of biosurveillance data such as nonstationary and overdispersion to some extent. Moreover, this newly proposed method is easily adapted to automated use in public health surveillance systems to monitor simultaneously large number time series of indicators associated with the relevant diseases. To compare the performance of the new method with those of some well-known outbreak detection methods, semisynthetic data with outbreaks of various magnitudes and durations are simulated by considering the weekly number of outpatient visits for influenza-like illness for the influenza seasons 2014-2015 through 2017-2018 at Centers for Disease Control and Prevention (CDC) in the United States. Under the conditions of the simulation studies, Serfling regression and Farrington flexible seem to be preferable methods for monitoring the weekly influenza data at CDC in terms of early identification of influenza outbreaks with a high probability. In addition, the newly proposed LWMAT-type methods appear to be promising and useful methods in the case of small magnitude outbreaks with a short duration.

Next-Generation Sequencing for Biodefense: Biothreat Detection, Forensics, and the Clinic.

BACKGROUND: Next-generation sequencing (NGS) is revolutionizing a variety of molecular biology fields including bioforensics, biosurveillance, and infectious disease diagnostics. For pathogen detection, the ability to sequence all nucleic acids in a sample allows near limitless multiplexability, free from a priori knowledge regarding an etiologic agent as is typically required for targeted molecular assays such as real-time PCR. Furthermore, sequencing capabilities can generate in depth genomic information, allowing detailed molecular epidemiological studies and bioforensics analysis, which is critical for source agent identification in a biothreat outbreak. However, lack of analytical specificity, inherent to NGS, presents challenges for regulated applications such as clinical diagnostics and molecular attribution. CONTENT: Here, we discuss NGS applications in the context of preparedness and biothreat readiness. Specifically, we investigate current and future applications of NGS technologies to affect the fields of biosurveillance, bioforensics, and clinical diagnostics with specific focus on biodefense. SUMMARY: Overall, there are many advantages to the implementation of NGS for preparedness and readiness against biowarfare agents, from forensics to diagnostics. However, appropriate caveats must be associated with any technology. This includes NGS. While NGS is not the panacea replacing all molecular techniques, it will greatly enhance the ability to detect, characterize, and diagnose biowarfare agents, thus providing an excellent addition to the biodefense toolbox of biosurveillance, bioforensics, and biothreat diagnosis.

Humanome Versus Microbiome: Games of Dominance and Pan-Biosurveillance in the Omics Universe.

Global governance of pathogens such as Ebola virus and infectious diseases is central to global health, and to innovation in systems medicine. Worrisomely, the gaps in human immunity and healthcare services combined with novel pathogens emerging by travel, biotechnological advances, or the rupture of the host-species barrier challenge infectious diseases' global governance. Such biorisks and biothreats may scale up to global catastrophic biological risks (GCBRs) spatiotemporally, either as individual or as collective risks. The scale and intensity of such threats challenge current thinking on surveillance, and calls for a move toward pan-biosurveillance. New multilayered, cross-sectoral, and adaptable strategies of prevention and intervention on GCBRs should be developed, considering human hosts in entirety, and in close relationship with other hosts (plants and animals). This also calls for the "Humanome," which we introduce in this study as the totality of human subjects plus any directly dependent biological or nonbiological entities (products, constructs, and interventions). Surveillance networks should be implemented by integrating communications, diagnostics, and robotics/aeronautics technologies. Suppression of pathogens must be enforced both before and during an epidemic outbreak, the former allowing more drastic measures before the pathogens harbor the host. We propose in this expert review that microbiome-level intervention might particularly prove as an effective solution in medical and environmental scales against traditional, currently emerging, and future infectious threats. We conclude with a discussion on the ways in which the humanome and microbiome contest and cooperate, and how this knowledge might usefully inform in addressing the GCBRs, bioterrorism, and associated threats in the pursuit of pan-biosurveillance.

Unbiased Strain-Typing of Arbovirus Directly from Mosquitoes Using Nanopore Sequencing: A Field-forward Biosurveillance Protocol.

The future of infectious disease surveillance and outbreak response is trending towards smaller hand-held solutions for point-of-need pathogen detection. Here, samples of Culex cedecei mosquitoes collected in Southern Florida, USA were tested for Venezuelan Equine Encephalitis Virus (VEEV), a previously-weaponized arthropod-borne RNA-virus capable of causing acute and fatal encephalitis in animal and human hosts. A single 20-mosquito pool tested positive for VEEV by quantitative reverse transcription polymerase chain reaction (RT-qPCR) on the Biomeme two3. The virus-positive sample was subjected to unbiased metatranscriptome sequencing on the Oxford Nanopore MinION and shown to contain Everglades Virus (EVEV), an alphavirus in the VEEV serocomplex. Our results demonstrate, for the first time, the use of unbiased sequence-based detection and subtyping of a high-consequence biothreat pathogen directly from an environmental sample using field-forward protocols. The development and validation of methods designed for field-based diagnostic metagenomics and pathogen discovery, such as those suitable for use in mobile "pocket laboratories", will address a growing demand for public health teams to carry out their mission where it is most urgent: at the point-of-need.

Internet-based biosurveillance methods for vector-borne diseases: Are they novel public health tools or just novelties?

Internet-based surveillance methods for vector-borne diseases (VBDs) using "big data" sources such as Google, Twitter, and internet newswire scraping have recently been developed, yet reviews on such "digital disease detection" methods have focused on respiratory pathogens, particularly in high-income regions. Here, we present a narrative review of the literature that has examined the performance of internet-based biosurveillance for diseases caused by vector-borne viruses, parasites, and other pathogens, including Zika, dengue, other arthropod-borne viruses, malaria, leishmaniasis, and Lyme disease across a range of settings, including low- and middle-income countries. The fundamental features, advantages, and drawbacks of each internet big data source are presented for those with varying familiarity of "digital epidemiology." We conclude with some of the challenges and future directions in using internet-based biosurveillance for the surveillance and control of VBD.

Web-Based Surveillance of Illness in Childcare Centers.

School absenteeism is an inefficient and unspecific metric for measuring community illness and does not provide surveillance during summertime. Web-based biosurveillance of childcare centers may represent a novel way to efficiently monitor illness outbreaks year-round. A web-based biosurveillance program ( sickchildcare.org ) was created and implemented in 4 childcare centers in a single Michigan county. Childcare providers were trained to report sick children who required exclusion or had parent-reported absences due to illness. Deidentified data on age range, number of illnesses, and illness categories were collected. Weekly electronic reports were sent to the county public health department. Data for reports were gathered beginning in December 2013 and were summarized using descriptive statistics. A total of 385 individual episodes of illness occurred during the study period. Children with reported illness were infants (16%, n = 61), toddlers (38%, n = 148), and preschoolers (46%, n = 176). Illness categories included: fever (30%, n = 116), gastroenteritis (30%, n = 115), influenzalike illness (8%, n = 32), cold without fever (13%, n = 51), rash (7%, n = 26), conjunctivitis (1%, n = 3), ear infection (1%, n = 5), and other (10%, n = 37). The majority of reports were center exclusions (55%, n = 214); others were absences (45%, n = 171). The detection of a gastroenteritis outbreak by web-based surveillance during winter 2013-14 preceded county health reports by 3 weeks; an additional outbreak of hand-foot-mouth disease was detected during June 2014 when standard school-based surveillance was not available. Web-based biosurveillance of illness in childcare centers represents a novel and feasible method to detect disease trends earlier and year-round compared to standard school-based disease surveillance.

An extensible framework and database of infectious disease for biosurveillance.

Biosurveillance, a relatively young field, has recently increased in importance because of increasing emphasis on global health. Databases and tools describing particular subsets of disease are becoming increasingly common in the field. Here, we present an infectious disease database that includes diseases of biosurveillance relevance and an extensible framework for the easy expansion of the database.

Empirical Study on the Impact of a Tactical Biosurveillance Information Visualization on Users' Situational Awareness.

Decisions on antibiotic-resistant infection (ARI) prevention in dynamic health care settings should be agile and target the right process at the right time. Health information technologies can aid the recognition of high-risk situations for ARI transmission and timely facilitate operators' situational awareness (SA) in various military and civilian health care locations or transport platforms. High SA is one of the significant predictors of better performance. The objective of this study was to evaluate the impact of the developed health information visualization (VIZ) on the users' SA regarding situations when risks of ARI transmission and exposure are high. The enrolled 19 subjects assessed the proposed VIZ artifacts representing 1 scenario, compared the VIZ effectiveness against the currently employed local methods, and reported their SA (perception and comprehension) with the use of a pre- and post-self-rating questionnaire. The results showed that the VIZ significantly increased SA in the study subjects and revealed the importance of communicating the risk of exposure to ARIs. The VIZ enabled the participants to quickly acknowledge the high-risk individuals (super-spreaders), locations (hot spots), and biosafety (deficient infection prevention). The study concluded that SA-oriented technologies may be promising for promoting better infection prevention practices.

Expanding veterinary biosurveillance in Washington, DC: The creation and utilization of an electronic-based online veterinary surveillance system.

OBJECTIVES: To enhance the early detection of emerging infectious diseases and bioterrorism events using companion animal-based surveillance. METHODS: Washington, DC, small animal veterinary facilities (n=17) were surveyed to determine interest in conducting infectious disease surveillance. Using these results, an electronic-based online reporting system was developed and launched in August 2015 to monitor rates of canine influenza, canine leptospirosis, antibiotic resistant infections, canine parvovirus, and syndromic disease trends. RESULTS: Nine of the 10 facilities that responded expressed interest conducting surveillance. In September 2015, 17 canine parvovirus cases were reported. In response, a campaign encouraging regular veterinary preventative care was launched and featured on local media platforms. Additionally, during the system's first year of operation it detected 5 canine leptospirosis cases and 2 antibiotic resistant infections. No canine influenza cases were reported and syndromic surveillance compliance varied, peaking during National Special Security Events. CONCLUSIONS: Small animal veterinarians and the general public are interested in companion animal disease surveillance. The system described can serve as a model for establishing similar systems to monitor disease trends of public health importance in pet populations and enhance biosurveillance capabilities.