A detailed analysis of the trajectory and comparison to other outbreaks;-

Introduction

A 2026 outbreak of Bundibugyo Ebola virus (BDBV) in the Democratic Republic of Congo (DRC), with spread into Uganda, has triggered a WHO Public Health Emergency of International Concern (PHEIC) (WHO, 2026; CDC, 2026). Transmission requires direct contact with infected bodily fluids and is highest in healthcare and caregiving settings. Ebola is not airborne (ECDC, 2026). These dynamics are not new; similar patterns were observed during the 2009 H1N1 pandemic and COVID 19, where workforce decisions preceded epidemiological certainty.

This BDBV outbreak does not follow the familiar Ebola playbook. There is no vaccine or established treatment, and existing countermeasures do not provide proven protection against BDBV (Reuters, 2026; Mercer, 2026):

• Material fatality risk: Mortality for Ebola typically sits at 30–50% (WHO, 2026).
• Contextual challenges: Conflict, population mobility and weak health systems amplify spread (Harvard HHI, 2026).
• Delayed detection: Early cases were not identified promptly (Lancet, 2026).

This has become a containment-dependent outbreak without a pharmaceutical safety net.

The response highlighted a familiar challenge that persists in current HCIDs – operational decisions needed to be taken before complete epidemiological clarity was available.

Workforce risk management required:

• Interpreting evolving national guidance in real time
• Translating population-level advice into organisation-specific controls
• Supporting managers to act proportionately despite uncertainty

‘Preparedness frameworks are necessary, but insufficient without the capability to apply them dynamically under conditions of incomplete information.’

Occupational Health (OH) leadership

OH leadership sits at the intersection of uncertainty and action. HCIDs do not require perfect data, but they do require proportionate judgement, applied early, particularly when workers return from travel. Swine Flu (H1N1), COVID-19 and orthovirus monkeypox (Mpox (monkeypox virus)) responses demonstrated the efficacy of risk-based decision-making at scale.

‘Occupational health must bridge the gap between public health intelligence and workplace reality, often before the data is complete.’

When workers return from travel

Infectious disease risk often manifests when workers return from travel, whether occupational or leisure. During COVID‑19, occupational health services were required to assess thousands of workers returning to work with uncertain risk profiles, often before testing or formal guidance could confirm safety.

For employers, BDBV is rarely an in-country operational problem, as the risk crystallises when workers return from travel, not when outbreaks are declared. Risk to travellers in developed regions remains low with precautions, but there are cases linked to cross-border mobility and exposure is risk higher in healthcare / close contact settings. Unforeseen and unplanned incidents, such as road traffic accidents pose the greatest risk to tourists due to the need for close contact with emergency and healthcare workers. This creates three familiar challenges:

• Exposure can precede organisational awareness
• Initial symptoms may be non-specific (NHS, 2026)
• Testing may be negative despite credible risk

‘In this context, testing becomes confirmatory, not protective.’

In practice, risk rarely presents as a clear diagnosis. During COVID‑19, employees often returned to work following exposure, symptoms, or travel, with incomplete information and evolving testing reliability. Return to work decisions relied on structured risk assessment rather than definitive results, mirroring the current challenges seen in HCIDs such as BDBV.

Experience from the Mpox (monkeypox virus) response highlighted that risk is not limited to traditional frontline roles. Non-frontline services, including community-based and outpatient settings, may present increased exposure risk where patients are infectious but undiagnosed.

The Testing Gap

Testing alone cannot determine fitness for work; the diagnostic reality is:

• Early infection may generate false negative results due to low viral load within the first 72 hours (WHO, 2026)
• Testing systems may not match or detect emerging strains (Lancet, 2026)
• False reassurance increases the risk if repeat testing is required when suspicion remains

These limitations reflect a structural gap between diagnostic capability and operational need (BMC Infectious Diseases, 2025) (Frontiers, 2023). The failure in the diagnostics model is a clear example of the unintended consequences of management systems that prioritise procedural compliance over scientific enquiry and education. This highlights the need for clear communication that a negative test does not exclude infection.

In practice, this requires adapting established models to new pathogens. During the Mpox (monkeypox virus) outbreak, existing COVID-19 risk assessment frameworks were rapidly modified to reflect different transmission routes, exposure patterns and vulnerable populations – demonstrating that structured approaches to uncertainty are transferable across HCIDs.

The exception that proves the rule

In COVID-19 and Mpox (monkeypox virus), testing became widely accessible, rapid and operationally embedded. This created an assumption: ‘If we can test, we can control risk’. This outbreak has exposed the weakness in that assumption – testing STOPS being a control when it is delayed, limited or misaligned to the pathogen. Becoming ‘the exception that proves the rule,’ BDBV is a vivid reflection of system limitations.

Even in a data-rich environment such as COVID‑19, organisations struggled to interpret testing outputs in isolation. Compliance with NHS England and HSE requirements required not just testing, but systematic individual risk assessment and consultation. One trust’s innovative online self-assessment model enabled 100% compliance with NHS England and HSE vulnerable worker risk assessment requirements.

Both COVID‑19 and Mpox (monkeypox virus) demonstrated that preparedness is not achieved through diagnostics alone, but through having adaptable frameworks, trained staff, and clear communication pathways in place before certainty emerges.

From evidence to practice: the role of structured learning

One of the consistent challenges in HCIDs is the gap between emerging global evidence and operational decision-making at local level.

During the COVID‑19 and Mpox (monkeypox virus) responses, it became clear that OH leaders need to actively engage with trusted, real-time sources of public health intelligence – not only to interpret risk, but to translate it into practical workplace guidance.

Formal learning through platforms such as OpenWHO provides an important bridge between epidemiological insight and operational application. Completion of WHO training on Mpox (monkeypox virus) epidemiology, preparedness and response highlighted principles that remain directly relevant to the current BDBV outbreak:

• The importance of early risk communication and trust, rather than reliance on definitive diagnosis alone
• The need to prioritise exposure history and population risk, particularly in rapidly evolving outbreaks
• The critical role of structured surveillance and data interpretation, even where information is incomplete
• The value of preparedness over retrospectively applied control measures

These principles closely mirror the practical experience of managing OH services during COVID‑19. At scale, effective decision-making depended on applying emerging evidence in a structured and proportionate way.

In the context of the current BDBV outbreak, this reinforces a crucial point:

The capability to interpret and apply emerging evidence is as important as the evidence itself.

Accessible, standardised training resources, particularly those developed by WHO, provide a consistent and credible foundation for this capability, supporting organisations to move beyond reactive responses and towards informed, anticipatory risk management (OpenWHO, 2022; WHO, 2022).

HCID intelligence: Data-rich vs Data-poor outbreaks

This paper proposes a practical HCID risk framework based on exposure, vulnerability, uncertainty and consequence. Traditional trajectory models assume early detection, consistent reporting and reliable diagnostics. That assumption holds for data-rich outbreaks (COVID-19, Mpox (monkeypox virus)). BDBV is a data-poor HCID because:

• Detection is retrospective
• Case counts are incomplete
• Reporting is irregular

‘Absence of data does not equal absence of risk.’

Figure 1 Data-rich v Data-poor outbreaks

In data-rich outbreaks, early and consistent testing enables smooth, interpretable trajectories. In data-poor HCIDs such as BDBV, delayed detection and limited reporting prevent this. Traditional outbreak curves assume reliable, real-time data. Note the gap before the curve at Day 14 in the current the outbreak where diagnostics have compressed early transmission into later reporting, distorting the apparent curve.

Table 1 Outbreak Patterns

‘For HCIDs, the curve is not the outbreak – the gap before the curve is.’

This framework provides a practical basis for decision-making in data-poor HCIDs, where uncertainty and consequence must be balanced in advance of reliable data.

Implications for employers and occupational health leaders

• Do not infer safety from flat curves
• Prioritise exposure history over test results
• Expect disruption before visibility
• Plan for uncertainty

‘The law of unintended consequences’

During COVID‑19, managers frequently deferred decisions pending test results. Employees remained in a ‘grey zone.’ Return-to-work and redeployment decisions were delayed. The intended control (testing) had become a driver of operational ‘vulnerability.’ OH teams had to intervene with risk-based guidance to enable safe redeployment, targeted restrictions and continuity of service delivery.

Over-reliance on testing introduces false reassurance from negative results, delayed escalation and underestimation of exposure risk where the intended control drives operational vulnerability, a pattern which has been seen repeatedly in:

• COVID-19 (first access constraints)
• Mpox (monkeypox virus) (case definition and testing lag)
• BDBV (diagnostic mismatch and delay)

The COVID-19 and Mpox (monkeypox virus) responses reinforced the importance of supporting healthcare workers facing uncertainty, including psychological impact and operational pressure. Delays, unclear guidance and evolving evidence can compound risk unless mitigated through OH initiative-taking and leadership.

We live in a global economy. People travel to increasingly remote places and on insurance policies that often do not cover cancellation unless national advice is issued against travel. National decisions must be considered pragmatically, often leading to information being issued at short notice. But the planning and logistical factors associated with this can and should be mitigated with clear and proactive occupational and travel health policies that refer to employees’ statutory duty to ‘take reasonable care for the health and safety of himself and of other persons who may be affected by his acts or omissions at work’. Workplaces are only as safe as the confidence and ease with which employees can report exposure to or symptoms of an HCID to their employer.

OH providers must get ready to be asked for guidance on ‘quarantine’ arrangements until the individual is out of the latency period. When faced with emerging evidence:

1. Do not infer safety from data: Flat curves may reflect lack of detection, not lack of transmission
2. Prioritise exposure history: Travel and contact risk outweigh single test results
3. Manage the ‘grey zone’:

• • Employees returning from travel to places with HCIDs with symptoms and / or exposure
  • Negative or pending tests require precautionary management

4. Expect disruption before clarity or operational impact will happen before:

• • Reliable data
  • Formal guidance
  • Confirmed spread

Conclusion

Protecting the public from HCIDs requires pragmatic, proportionate messaging grounded in risk—not simplified or inconsistent interventions that undermine trust. The challenge for future HCIDs is not the absence of testing, but the ability to:

• Interpret incomplete information
• Apply structured judgement
• Act proportionately in advance of confirmation
• Early application of lessons learned from the COVID-19 and Mpox (monkeypox virus) outbreaks

The question is not ‘What does the test show?’ But ‘What is the risk and how precautionary should the response be?’

‘In HCIDs, the risk is real before the data is visible – and decisions must be made accordingly.’

This requires the ability to influence across systems, often without formal authority, working alongside infectious disease, public health and operational teams to ensure that workforce risk is understood and appropriately managed.

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