South Oxfordshire and Vale of White Horse District Councils have awarded a new Waste Collection and Street Cleansing contract to Biffa Waste Services.

The new contract extends its 15-year success and starts next month (June). It could run for a maximum period of 16 years, costing almost £260m.

There is a minimum period of eight years and a break possible after four years to give maximum flexibility. 

While they will continue to focus on an all-in-one bin approach for recycling with the decision kept under review, they are also preparing for law changes with the national ‘Simpler Recycling’ scheme that comes into effect by March 2027, allowing residents to recycle soft plastics.

READ MORE: Petition to save free parking in Oxfordshire towns

Vale of White Horse District Council said this country-wide approach will reduce confusion.

It said: “With a single set of core materials collected kerbside, it will lead to clearer labelling for the public on packaging and greater volumes of the correct items being picked up and sorted for re-processing by the councils.”

But with no immediate changes, residents in Abingdon, Farringdon, Wantage, Dicot, Henley, Thame and Wallingford, can expect the same services until then.

Just short of half of Biffa’s fleet is either new and already in service or arriving as new vehicles within the next six months.

The remaining replacement process, pending councillor approvals, should be concluded by March 2028. 

NHS England and five of the UK’s largest hospital trusts recorded 274,620 IT incidents in 2025. Analysis of Freedom of Information data also found that major outages disrupted tens of thousands of patient interactions.

The figures cover Manchester University, Guy’s and St Thomas’, Newcastle Hospitals, Mid and South Essex, Barts Health and NHS England. They point to repeated disruption across both local systems and wider incidents, with effects ranging from cancelled operations to delayed routine appointments.

On the day of the Synnovis ransomware attack, the five trusts reported that 14,287 operations and appointments were cancelled or moved. During the global IT outage in July 2024, 12,528 patient interactions were disrupted across the same group. Another major incident in October 2025 led to 8,527 disruptions across four of the five trusts.

The data suggests routine care absorbed most of the disruption. Information from three of the five trusts showed that appointments accounted for an average of 95% of total patient disruptions, indicating that the impact extended well beyond surgical procedures.

That pattern matters for a health service already under pressure to reduce waiting lists and improve access to care. Missed or delayed appointments can affect follow-up consultations, diagnostics, preventative treatment and scheduled operations.

The findings also exposed uneven reporting across NHS organisations. Some trusts said they did not hold data linking IT incidents to patient care, while others could not provide figures on incident duration or the total number of incidents during the year.

This suggests the full effect on services may be greater than the published totals. Because the data depends on what individual organisations were able to record and return, gaps in record-keeping make it difficult to build a complete picture of where outages occur, how long they last and which services are most affected.

Reporting gaps

The variation in responses points to a wider problem in how digital disruption is measured across the health service. Without common reporting standards, comparisons between trusts are difficult and national oversight is limited.

Several of the largest disruptions were tied to events outside an individual trust’s direct control. The Synnovis incident affected pathology services in London, while the global IT outage in July 2024 hit organisations across sectors. This shows how NHS services can be exposed to problems involving suppliers and broader technology systems, as well as their own internal infrastructure.

At the same time, the aggregate total of more than 274,000 incidents in one year suggests smaller IT failures remain a frequent part of day-to-day operations. Not every incident will have led to patient harm or widespread service disruption, but the volume underlines how dependent frontline care has become on stable digital systems.

Paula Lender-Swain, regional director, public sector UK, Dynatrace, said: “The data clearly shows that NHS IT outages are a widespread issue that isn’t confined to individual trusts or one-off events. Outages are occurring at scale across multiple regions, with thousands of patient interactions affected on a single day – and not just the operations that are already being widely reported. With digital disruption now a system-wide challenge, IT outages can no longer be regarded as simply a technical issue. They have a direct and measurable impact on patients’ ability to access care when and where they need it.”

She added: “When systems go down, it’s routine services like appointments that are most affected. That not only has a direct impact on NHS waiting lists but also threatens early diagnosis and preventative treatment.”

Wider pressure

The data comes as the NHS seeks to expand its use of digital services and artificial intelligence across administration and clinical care. That ambition increases the importance of reliable infrastructure, especially in hospitals where appointments, records, diagnostics and communications depend on interconnected systems.

Lender-Swain said: “Without consistent, centralised reporting, there’s no joined-up picture of how IT outages are affecting patient care and valuable clinician time, making it harder to identify patterns, address root causes and fully understand the impact on services.”

She added: “As the NHS looks to deliver on its ambition to become one of the most AI-enabled healthcare systems in the world, it must first address these foundational gaps in visibility and resilience. Without a clear, real-time understanding of system performance and patient impact, organisations risk operating with blind spots. By strengthening observability and unifying data across systems, the NHS can move from reacting to incidents to managing them proactively – reducing disruption, supporting staff and ensuring infrastructure is ready for the next phase of digital healthcare.”

JOSEPH GABRIEL LAGONSIN

News Editor

Dojo has warned that fraudsters are using AI-generated receipts to secure refunds from retailers, with online searches for such tools rising sharply.

Data cited by the payments company showed global Google searches for “AI-generated receipts” rose by 2753% over the past year. It also referenced findings from Cifas showing that AI-manipulated documents now account for more than 20% of falsified evidence used in UK refund and chargeback disputes, where total fraud cases exceeded 444,000 last year.

The issue centres on fake proof-of-purchase documents created with generative AI tools. These can mimic real receipts with retailer logos, item lists, timestamps and transaction numbers, making them hard for frontline staff to distinguish from genuine records during refund checks.

According to the figures cited, about one in 10 UK returns is already estimated to be fraudulent. AI-generated imagery is adding pressure to return, refund and replacement processes, particularly where staff rely on uploaded documents rather than direct checks against payment records.

A Dojo spokesperson said AI receipt generators are making it easier for fraudsters to create convincing fake proof of purchase.

“With just a few clicks, they can produce receipts that mirror real store formats, complete with logos, item lists, timestamps and transaction IDs. As many return systems rely on documentation rather than transaction-level checks, these AI-generated receipts often go unnoticed, allowing fraudulent refunds to slip through even well-established defences.”

Risk areas

Several sectors appear more exposed than others. Dojo identified eCommerce and digital-only retail, fast-food and quick-service restaurants, consumer technology, ride-share and on-demand travel, food-delivery platforms, luxury goods, telecoms and financial services as industries where interest in receipt generators suggests higher fraud risk.

The assessment was based on Google search patterns for brand-specific receipt generator terms. Separate Experian data for 2025, cited by Dojo, indicated that 62% of digital-only retailers, 48% of retail banks and 44% of telecom providers reported AI-related fraud attempts.

Those sectors share several features that can make them targets for document fraud. High transaction volumes, automated customer service systems and digital templates that are relatively easy to imitate can create openings for false refund, return or reimbursement claims.

Checks advised

To limit exposure, Dojo urged businesses to verify submitted receipts against actual transaction records. Checks on timestamps, payment amounts and transaction IDs remain the most reliable way to identify fabricated documents.

It also recommended adding QR codes, barcodes or other unique markers to receipts so staff can trace a claim back to a live record in the merchant’s system. For higher-risk categories such as expensive electronics, digital-only purchases and goods commonly resold online, retailers should apply stricter refund rules and require further verification before approving a claim.

Another step is staff training. Frontline workers can be taught to spot repeated textures, irregular spacing, mismatched metadata, incorrect store formats and impossible timestamps, all of which may indicate that a receipt or supporting image has been artificially generated or altered.

Behavioural monitoring is also part of the advice. Repeated refund requests from the same device or location, multiple claims in a short period, or unusual patterns in customer activity can help investigators identify serial abuse even when the documents appear plausible.

Dojo also advised businesses to consider AI-based fraud detection systems that examine images and documents for signs of manipulation, including synthetic text, altered pixels and inconsistencies that may not be visible to staff reviewing claims manually.

The warning reflects a broader shift in fraud methods as generative AI tools become easier to access. For merchants, the challenge is no longer limited to spotting obvious forgeries, but to checking whether documents submitted in routine customer service interactions match real transaction data held in their own systems.