ABSTRACT:
Background;In low- and middle-income countries (LMICs), emerging pathogens often pose the greatest risk when they circulate unnoticed within health systems already strained by large outbreaks1. Arboviral diseases are particularly vulnerable to misclassification due to overlapping clinical features and shared vectors, especially when surveillance systems are organised around single-pathogen priorities2. During a major dengue surge in Khyber Pakhtunkhwa, Pakistan, chikungunya transmission remained undetected within routine dengue surveillance, delaying recognition of an imported outbreak with implications for early warning and equitable response3. Methods;Targeted field epidemiological investigations were conducted among suspected dengue cases, including household interviews, review of clinical records, and assessment of rapid diagnostic testing results. Travel histories were systematically examined to identify epidemiological linkages. Serum samples were referred to the National Institute of Health (NIH), Pakistan, for confirmatory testing. Vector presence and ecological suitability for onward transmission were assessed to inform public health risk4. Results;Eighteen epidemiologically linked cases were identified among travellers returning from Karachi, an urban centre with documented arboviral transmission3. All cases presented during peak dengue season with acute febrile illness and dengue-compatible symptoms. Despite this, all tested negative for dengue NS1 antigen, dengue IgM/IgG, and malaria rapid diagnostic tests. Uniform dengue test negativity, combined with recent travel exposure, prompted investigation beyond routine surveillance algorithms2. The cluster occurred in an area with established Aedes albopictus populations, indicating a credible risk of local transmission had detection remained delayed4. Conclusion;This event demonstrates how emerging pathogens can remain effectively invisible when surveillance systems prioritise individual diseases rather than people, exposure pathways, and concurrent risks1. In Aedes-endemic LMIC settings, diagnostic bias and narrowly defined alert thresholds disproportionately delay recognition among mobile and underserved populations, undermining equitable outbreak response2. Sustainable preparedness requires surveillance models that integrate systematic travel history, multi-pathogen testing strategies, and alert frameworks capable of detecting overlapping outbreaks within routine health systems1