The public health work nobody sees
Every day, experts detect and investigate potential public health threats that never become headline news.
Consider 2026 alone. The CDC reported six U.S. outbreaks as of July this year1, representing a fraction of what surveillance systems actually track.
Most people only learn of a public health event once it reaches national attention, whether that’s a contamination incident, a disease outbreak, or an emerging toxic exposure. In reality, surveillance is a continuous process. It involves numerous organizations and experts working behind the scenes.
National surveillance relies on collaboration between poison centers, public health agencies, epidemiologists, toxicologists, and healthcare professionals who monitor signals that may indicate an emerging concern. Much of this work involves identifying patterns within large volumes of seemingly unrelated data, determining whether a signal is meaningful, and deciding when escalation is warranted.
For every public health event that makes national headlines, countless others are investigated behind the scenes to determine their public health significance.
Surveillance depends on rapid coding and human judgement
Technology supports surveillance, but humans identify what matters.
Effective surveillance relies on specialized data collection methods and tools that enable consistent monitoring, to track incidence, severity, and outcomes.
An example of this includes human experts across America’s Poison Centers who continuously monitor trends and investigate signals that may represent events of public health significance. Communication across organizations is key, and fast allocation of a product code to log cases against, as a threat grows, can make all the difference when new threats emerge.
Behind that speed sits a dedicated partnership. America’s Poison Center coding committees partner with toxicology experts at Micromedex. Together, they deploy and activate new product codes, giving surveillance teams a consistent way to track emerging cases that carry public health implications.
When a new threat emerges, you can’t track what you can’t identify. Rapid coding transforms isolated cases into actionable intelligence.
Ahead of the World Cup 2026, the committee created a dedicated product code before the tournament began, enabling proactive monitoring of exposure-related events at one of the largest international sports events. Another example is when the teams quickly activated a code to track infant botulism concerns linked to ByHeart infant formula. And who remembers Diamond Shruumz-brand chocolate bars? They were tied to serious illness and found to contain psychoactive substances that never appeared on the label. Each case looked different. Each demanded the same rapid, coordinated response.
From detection to action: Decisions need data
Once a threat has been identified, the priority shifts from detection to response, and information becomes critical.
Toxicologists, poison center staff and public health professionals need immediate access to trusted information, as do first responders and emergency department staff. Evidence-based toxicology knowledge becomes critical for informed decision-making during rapidly evolving situations.
These emerging events often require quick answers to highly specific clinical and toxicology questions. This is where a trusted, expert-curated source of toxicology-specific clinical information is critical. 100% of U.S. Poison Centers and many healthcare providers worldwide rely on the most trusted clinical decision support system for instant, actionable treatment protocols and management strategies. That exposure coverage spans more than 470,000 commercial products, chemicals, drugs, plants, and animals.
The exposure situations can vary widely. Substance abuse and overdose events. Train derailments and chemical spills. Mass exposure incidents involving pesticides or organophosphates. Different scenarios, the same urgent need for reliable answers.
In accessing data for urgent cases, every second counts
Artificial intelligence can help locate critical information faster when time is limited.
With advances in machine learning and large language models, artificial intelligence (AI) has already been applied to trusted toxicology databases, giving specialists another route to time-sensitive answers.
The benefit is practical. Users can ask questions in plain language rather than mapping how the data is organized in the system, which lowers cognitive load during high-pressure cases. AI narrows extensive information quickly, so teams in poison centers and emergency medicine can focus on decisions rather than digging for data. And when a database provides full citations and hyperlinks to the supporting evidence, every source can be traced, streamlining fact-checking and supporting confident decisions.
However, data integrity and relevance is key. The effectiveness of AI tools in clinical toxicology depends first on the level of detailed and specialized toxicology content the AI models have access to, and second on the quality of that data. Does it include clinical and adverse effects, range of toxicity, expected symptoms following chemical releases or spills, antidote recommendations, and detailed treatment guidelines? Has it been validated by experts?
For AI to be a reliable tool for accessing information on drug toxicity or poisoning and its effect on human health, it must be built on toxicology-specific, high-quality, evidence-based, and meticulously curated clinical content.
Closing thought
So, when the next public health event makes the evening news, know that the work of protection began long before the headlines. Behind every coordinated response is a network of experts, agencies, and curated intelligence working together to identify risks, interpret signals, and act before harm spreads. That’s not coincidence. It’s preparation.
Learn more about the clinical decision support used by 100% of U.S. Poison Centers and many healthcare providers worldwide.
