Parents in north London have been told their children could be excluded from school if they are not fully vaccinated against measles amid an outbreak of the highly-contagious disease. Unvaccinated pupils identified as close contacts of people with measles could be excluded for 21 days in accordance with national guidelines, Enfield Council said in a letter to all parents in the borough in late January. At least 34 children have contracted measles in Enfield so far this year, the UK Health Security Agency (UKHSA) has said, and a number sent to hospital. A local health chief meanwhile told the BBC: We are worried because actually, this is a significantly increased number than what we're used to. Asking unvaccinated, close contacts of measles cases to stay off school is fairly standard practice when there are local outbreaks.

The specialized crops could save farmers millions. A swarm of desert locusts fly after an aircraft sprayed pesticide in Meru, Kenya in 2021. Breakthroughs, discoveries, and DIY tips sent six days a week. Swarms of locusts devouring a farmer's livelihood might sound apocalyptic, but major locust infestations are a regular problem in agricultural communities around the world. These locust swarms--dense, droning packs of certain grasshopper species--can cover hundreds of square miles, and the insects consume vast amounts of vegetation and threaten global agriculture.

This review explores the integration of Artificial Intelligence into Horizon Scanning, focusing on identifying and responding to emerging threats and opportunities linked to Infectious Diseases. We examine how AI tools can enhance signal detection, data monitoring, scenario analysis, and decision support. We also address the risks associated with AI adoption and propose strategies for effective implementation and governance. The findings contribute to the growing body of Foresight literature by demonstrating the potential and limitations of AI in Public Health preparedness.

They might be the smallest falcon, but American kestrels still intimidate other birds. Breakthroughs, discoveries, and DIY tips sent every weekday. No one wants poop on their cherries . Farmers in northern Michigan could get some help on this fecal matter from some feathered allies. Small falcons called the American kestrel help deter smaller birds that like to snack on the fruit when it is growing.

Responding to disease outbreaks requires close surveillance of their trajectories, but outbreak detection is hindered by the high noise in epidemic time series. Aggregating information across data sources has shown great denoising ability in other fields, but remains underexplored in epidemiology. Here, we present LRTrend, an interpretable machine learning framework to identify outbreaks in real time. LRTrend effectively aggregates diverse health and behavioral data streams within one region and learns disease-specific epidemic networks to aggregate information across regions. We reveal diverse epidemic clusters and connections across the United States that are not well explained by commonly used human mobility networks and may be informative for future public health coordination. We apply LRTrend to 2 years of COVID-19 data in 305 hospital referral regions and frequently detect regional Delta and Omicron waves within 2 weeks of the outbreak's start, when case counts are a small fraction of the wave's resulting peak.

Employees at the company's Chelsea campus were told to stay home after exterminators found "credible evidence" of an infestation. Google's New York office is shown in lower Manhattan. Google employees working at the company's Chelsea campus in New York City received a notice on Sunday alerting them to a possible bed bug outbreak at the office. Exterminators arrived at the scene with a sniffer dog "and found credible evidence of their presence," according to an email obtained by WIRED. The email was sent to all Google employees in New York on behalf of the company's environmental, health, and safety team.

Large-scale outbreaks of epidemics, misinformation, or other harmful contagions pose significant threats to human society, yet the fundamental question of whether an emerging outbreak will escalate into a major epidemic or naturally die out remains largely unaddressed. This problem is challenging, partially due to inadequate data during the early stages of outbreaks and also because established models focus on average behaviors of large epidemics rather than the stochastic nature of small transmission chains. Here, we introduce the first systematic framework for forecasting whether initial transmission events will amplify into major outbreaks or fade into extinction during early stages, when intervention strategies can still be effectively implemented. Using extensive data from stochastic spreading models, we developed a deep learning framework that predicts early-stage spreading outcomes in real-time. Validation across Erdős-Rényi and Barabási-Albert networks with varying infectivity levels shows our method accurately forecasts stochastic spreading events well before potential outbreaks, demonstrating robust performance across different network structures and infectivity scenarios.To address the challenge of sparse data during early outbreak stages, we further propose a pretrain-finetune framework that leverages diverse simulation data for pretraining and adapts to specific scenarios through targeted fine-tuning. The pretrain-finetune framework consistently outperforms baseline models, achieving superior performance even when trained on limited scenario-specific data. To our knowledge, this work presents the first framework for predicting stochastic take-off versus die-out. This framework provides valuable insights for epidemic preparedness and public health decision-making, enabling more informed early intervention strategies.

Things to Do in L.A. Tap to enable a layout that focuses on the article. California has a strict vaccine mandate. Will it survive the Trump administration? Dr. Neville Anderson, right, tries to distract Perry Roj, 4, while nurse Breanna Kirby gives her a DTaP polio vaccination. Her mom, Devin Homsey, holds her tight at Larchmont Pediatrics.

Speaking at a WIRED event Tuesday, Moderna CEO Stéphane Bancel said he was "encouraged" by the company's dialogue with the FDA--but acknowledged recent setbacks. Moderna CEO Stéphane Bancel prepares to testify before the Senate on March 22, 2023 in Washington, DC. At the WIRED Health summit on Tuesday, Moderna CEO Stéphane Bancel said the recent changes to Covid-19 vaccine policy made by Health and Human Services secretary Robert F. Kennedy, Jr. are a "step backward." Moderna is one of the manufacturers of mRNA-based Covid-19 vaccines, and last month the company received approval from the Food and Drug Administration for an updated version of the shot . But as part of that approval, the FDA imposed new restrictions on who can receive the vaccine.

The rapid evolution of artificial intelligence (AI), together with the increased availability of social media and news for epidemiological surveillance, are marking a pivotal moment in epidemiology and public health research. Leveraging the power of generative AI, we use an ensemble approach which incorporates multiple Large Language Models (LLMs) to extract valuable actionable epidemiological information from the World Health Organization (WHO) Disease Outbreak News (DONs). DONs is a collection of regular reports on global outbreaks curated by the WHO and the adopted decision-making processes to respond to them. The extracted information is made available in a daily-updated dataset and a knowledge graph, referred to as eKG, derived to provide a nuanced representation of the public health domain knowledge. We provide an overview of this new dataset and describe the structure of eKG, along with the services and tools used to access and utilize the data that we are building on top. These innovative data resources open altogether new opportunities for epidemiological research, and the analysis and surveillance of disease outbreaks.