Abstract
Dengue is an increasingly prevalent arboviral infection in tropical regions, with expanding geographic distribution and rising reports of atypical and severe manifestations, including neurological involvement. In endemic and resource-limited settings, particularly those affected by conflict, the widespread availability of rapid diagnostic tests and overlapping clinical presentations with other infectious diseases have led to a growing concern: diagnostic anchoring bias toward dengue. This bias may contribute to misdiagnosis, delayed treatment of alternative life-threatening conditions, and distorted public health data. This commentary highlights key diagnostic pitfalls, including coinfections, incidental dengue positivity, and neurological mimics, and proposes a pragmatic clinical approach to improve diagnostic accuracy and patient outcomes.
Keywords: dengue fever, dengue outbreak, diagnostic challenges, Sudan
Introduction
Dengue is a rapidly expanding global health concern, particularly in tropical and subtropical regions. While most infections are asymptomatic or mild, a subset progresses to severe disease characterized by plasma leakage, hemorrhage, and organ dysfunction. Neurological manifestations, once considered rare, are increasingly recognized and include encephalopathy, encephalitis, Guillain–Barré syndrome, and myelitis[1].
In endemic regions, such as Sudan, the diagnostic challenge is further compounded by overlapping clinical features shared with other febrile illnesses, including malaria, bacterial meningitis, and viral encephalitis. The increasing reliance on rapid diagnostic tests (e.g., NS1 antigen, IgM/IgG serology) has inadvertently contributed to diagnostic anchoring, in which clinicians prematurely attribute symptoms to dengue based on a positive test result, potentially overlooking alternative or concurrent diagnoses[2].
For example, the following hypothetical clinical vignette illustrates this scenario: a middle-aged man from a dengue-endemic region with no significant past medical history presented with acute fever, headache, and confusion. A rapid dengue NS1 test was positive in a primary healthcare facility, and the patient was then transferred and managed as severe dengue. However, his condition deteriorated, with progressive alteration in consciousness and focal neurological deficits. Upon referral, further evaluation, including neuroimaging and cerebrospinal fluid analysis, confirmed a diagnosis of herpes simplex virus type 1 encephalitis. Antiviral therapy with acyclovir was initiated late, resulting in significant neurological sequelae. This illustrative example demonstrates how diagnostic anchoring may delay recognition of alternative life-threatening conditions.
Rapid diagnostic tests, commonly used in resource-limited settings such as Sudan, demonstrate variable sensitivity and specificity depending on timing and local epidemiology. NS1 antigen testing is most sensitive during the early phase of illness (typically within the first 5 days), while its sensitivity declines thereafter. In contrast, IgM antibodies generally become detectable after 4–5 days and may persist for weeks to months, limiting their specificity for acute infection. Accordingly, false-positive results may occur, and diagnostic findings should always be interpreted in conjunction with clinical presentation and timing of illness to avoid misclassification and inappropriate clinical decisions.
Diagnostic anchoring in resource-limited and conflict settings
In conflict-affected settings, healthcare systems often face severe limitations in diagnostic capacity, workforce, and infrastructure. Under such conditions, clinicians frequently rely on rapid diagnostic tests and clinical judgment rather than comprehensive investigations. While this approach is pragmatic, it increases the risk of cognitive biases, particularly anchoring bias.
A positive dengue test may lead to premature closure of the diagnostic process, even when clinical features are atypical. This is especially problematic because dengue diagnostic tests can remain positive beyond the acute phase or detect asymptomatic infections. Consequently, incidental dengue positivity can be misinterpreted as the primary cause of illness.
In addition to anchoring bias, other cognitive biases may also contribute to diagnostic error. The widespread availability of rapid diagnostic tests during epidemics may lead to availability bias, whereby clinicians are more likely to diagnose dengue during outbreaks due to its increased visibility and perceived prevalence. Furthermore, premature closure may occur when clinicians accept an initial diagnosis without sufficient consideration of alternative possibilities. These cognitive biases may interact and reinforce one another, thereby increasing the likelihood of diagnostic error, particularly in high-pressure clinical settings.
Key diagnostic pitfalls
Coinfections and overlapping epidemiology
Dengue fever often coexists with other endemic infections such as malaria, typhoid fever, and other arboviral diseases. Reported coinfection rates vary across different settings, with studies demonstrating rates of 6.6% in eastern Sudan, 8.3% in Brazil, and 23.2% in Pakistan[3–5]. These cases are frequently associated with more severe clinical outcomes. Importantly, a positive dengue test does not exclude other infections. In malaria-endemic regions, failure to test for malaria in patients with confirmed dengue can contribute to missed or delayed treatment of a potentially fatal disease[6].
2. Incidental dengue positivity
Incidental detection of dengue markers (NS1, IgM) in patients with febrile illnesses poses a significant diagnostic challenge. This may reflect prior infection, prolonged antigenemia, or subclinical disease. Without careful clinical correlation, such findings may lead to misattribution of symptoms and inappropriate management. Importantly, cross-reactivity with other flaviviruses and prolonged persistence of IgM antibodies may complicate interpretation, particularly in endemic regions with high background dengue seroprevalence.
3. Neurological mimics
Neurological manifestations associated with dengue can closely resemble other serious conditions, including herpes simplex virus encephalitis, acute bacterial meningitis, and cerebral malaria. Patients may present with fever, altered consciousness, seizures, and focal neurological deficits. In such cases, reliance on dengue serology alone is insufficient. Cerebrospinal fluid analysis, neuroimaging, and targeted microbiological testing are essential to exclude alternative diagnoses[7].
4. Sepsis and systemic infections
Sepsis may present with fever, altered mental status, and multiorgan dysfunction, closely mimicking severe dengue. Misdiagnosis may delay the initiation of appropriate life-saving antimicrobial therapy. Therefore, sepsis should always be considered and actively ruled out in patients with suspected dengue, particularly in severe or atypical presentations.
Consequences of misdiagnosis
The consequences of diagnostic anchoring toward dengue are substantial. Clinically, diagnostic anchoring may lead to delayed or missed treatment of conditions such as bacterial meningitis, viral encephalitis, and malaria, thereby increasing morbidity and mortality. From a public health perspective, misclassification inflates dengue case numbers, distorts epidemiological data, and may obscure concurrent outbreaks of other infectious diseases.
In resource-limited settings, these effects are amplified, as healthcare systems are already strained and surveillance mechanisms may be weak. Misdiagnosis can therefore have cascading effects on healthcare planning, resource allocation, and outbreak response.
A pragmatic clinical approach
To mitigate diagnostic anchoring and improve patient outcomes, a structured approach is essential:
Maintain a broad differential diagnosis even when dengue testing is positive.
Routinely screen for malaria in endemic settings, regardless of dengue status.
Recognize clinical red flags that suggest alternative diagnoses, including focal neurological deficits, persistent shock, marked leukocytosis, or severe metabolic derangements.
Perform cerebrospinal fluid analysis and neuroimaging, when clinically indicated, in patients with neurological manifestations.
Consider empiric treatment for life-threatening conditions (e.g., bacterial meningitis or severe malaria) when diagnostic uncertainty exists.
Reassess the working diagnosis frequently, particularly in patients who fail to improve with supportive care.
Use diagnostic checklists to minimize premature closure.
Incorporate context-specific diagnostic algorithms based on local epidemiology whenever feasible.
Conclusion
Dengue remains a major public health challenge, particularly in endemic and resource-limited settings. However, the increasing reliance on rapid diagnostic tests and the overlapping clinical features of febrile illnesses have contributed to diagnostic anchoring bias. Recognizing and addressing this bias is critical to avoid misdiagnosis, ensure timely treatment for alternative conditions, and improve patient outcomes. A balanced diagnostic approach that integrates careful clinical assessment, appropriate investigations, and awareness of local epidemiology is essential, particularly in conflict-affected settings where diagnostic uncertainty is common.
Acknowledgements
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Footnotes
Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.
Contributor Information
Mumen Abdalazim Dafallah, Email: mumenabdalazim36@gmail.com.
Fatima Abdelmonem Yousif Mohamed, Email: fatimaabdelmonem91@gmail.com.
Eman Osama Mohammed Omer, Email: emanosama091@gmail.com.
Alaa Nasreldeen Yousif Ahmed, Email: alaanasreldeenyousif@gmail.com.
Eilaf AbdElmoneim Nour Elbasheir, Email: elafnour42@gmail.com.
Aya Khidir Elamin Dafaalla, Email: aya.khidir193@gmail.com.
Ibtehaj Modawi Musa Modawi, Email: eptehaj200@gmail.com.
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Author contributions
M.A.D. conceptualized the manuscript. All authors contributed equally to the writing, reviewing, and editing of the manuscript.
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Data availability statement
No new data were generated or analyzed in support of this research.
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Data Availability Statement
No new data were generated or analyzed in support of this research.
