Artificial intelligence in public health: the potential of epidemic early warning systems.

The use of artificial intelligence (AI) to generate automated early warnings in epidemic surveillance by harnessing vast open-source data with minimal human intervention has the potential to be both revolutionary and highly sustainable. AI can overcome the challenges faced by weak health systems by detecting epidemic signals much earlier than traditional surveillance. AI-based digital surveillance is an adjunct to-not a replacement of-traditional surveillance and can trigger early investigation, diagnostics and responses at the regional level. This narrative review focuses on the role of AI in epidemic surveillance and summarises several current epidemic intelligence systems including ProMED-mail, HealthMap, Epidemic Intelligence from Open Sources, BlueDot, Metabiota, the Global Biosurveillance Portal, Epitweetr and EPIWATCH. Not all of these systems are AI-based, and some are only accessible to paid users. Most systems have large volumes of unfiltered data; only a few can sort and filter data to provide users with curated intelligence. However, uptake of these systems by public health authorities, who have been slower to embrace AI than their clinical counterparts, is low. The widespread adoption of digital open-source surveillance and AI technology is needed for the prevention of serious epidemics.

Analysis of metatranscriptomic methods to enable wastewater-based biosurveillance of all infectious diseases.

Introduction: Wastewater-based surveillance emerged during the COVID-19 pandemic as an efficient way to quickly screen large populations, monitor infectious disease transmission over time, and identify whether more virulent strains are becoming more prevalent in the region without burdening the health care system with individualized testing. Ohio was one of the first states to implement wastewater monitoring through its Ohio Coronavirus Wastewater Monitoring Network (OCWMN), originally tracking the prevalence of COVID-19 by quantitative qPCR from over 67 sites across the state. The OCWMN evolved along with the pandemic to include sequencing the SARS-CoV-2 genome to assess variants of concern circulating within the population. As the pandemic wanes, networks such as OCWMN can be expanded to monitor other infectious diseases and outbreaks of interest to the health department to reduce the burden of communicable diseases. However, most surveillance still utilizes qPCR based diagnostic tests for individual pathogens, which is hard to scale for surveillance of multiple pathogens. Methods: Here we have tested several genomic methods, both targeted and untargeted, for wastewater-based biosurveillance to find the most efficient procedure to detect and track trends in reportable infectious diseases and outbreaks of known pathogens as well as potentially novel pathogens or variants on the rise in our communities. RNA extracts from the OCWMN were provided weekly from 10 sites for 6 weeks. Total RNA was sequenced from the samples on the Illumina NextSeq and on the MinION to identify pathogens present. The MinION long read platform was also used to sequence SARS-CoV-2 with the goal of reducing the complexity of variant calling in mixed populations as occurs with short Illumina reads. Finally, a targeted hybridization approach was tested for compatibility with wastewater RNA samples. Results and discussion: The data analyzed here provides a baseline assessment that demonstrates that wastewater is a rich resource for infectious disease epidemiology and identifies technology gaps and potential solutions to enable this resource to be used by public health laboratories to monitor the infectious disease landscape of the regions they serve.

Can Water-Only DNA Extraction Reduce the Logistical Footprint of Biosurveillance and Planetary Health Diagnostics? Toward a New Method.

The coronavirus disease-2019 (COVID-19) pandemic has raised the stakes for planetary health diagnostics. Because pandemics pose enormous burdens on biosurveillance and diagnostics, reduction of the logistical burdens of pandemics and ecological crises is essential. Moreover, the disruptive effects of catastrophic bioevents impact the supply chains in both highly populated urban centers and rural communities. One "upstream" focus of methodological innovation in biosurveillance is the footprint of Nucleic Acid Amplification Test (NAAT)-based assays. We report in this study a water-only DNA extraction, as an initial step in developing future protocols that may require few expendables, and with low environmental footprints, in terms of wet and solid laboratory waste. In the present work, boiling-hot distilled water was used as the main cell lysis agent for direct polymerase chain reactions (PCRs) on crude extracts. After evaluation (1) in blood and mouth swabs for human biomarker genotyping, and (2) in mouth swabs and plant tissue for generic bacterial or fungal detection, and using different combinations of extraction volume, mechanical assistance, and extract dilution, we found the method to be applicable in low-complexity samples, but not in high-complexity ones such as blood and plant tissue. In conclusion, this study examined the doability of a lean approach for template extraction in the case of NAAT-based diagnostics. Testing our approach with different biosamples, PCR settings, and instruments, including portable ones for COVID-19 or dispersed applications, warrant further research. Minimal resources analysis is a concept and practice, vital and timely for biosurveillance, integrative biology, and planetary health in the 21st century.

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.