Title : Presymptomatic transmission as a structural limitation of symptom-based surveillance: Implications for infectious disease control, epidemic dynamics, and pandemic preparedness
Abstract:
Background: Infectious disease surveillance relies on timely detection of transmission to enable effective public health intervention. Historically, surveillance systems have been designed around the assumption that symptom onset corresponds closely with infectiousness, supporting strategies such as syndromic surveillance, symptom screening, case isolation, and contact tracing. However, pathogens capable of substantial presymptomatic transmission challenge this framework by creating a temporal gap between infectiousness and clinical recognition.
Objective: This paper examines presymptomatic transmission as a structural limitation of symptom-based surveillance systems and explores its implications for epidemic control and pandemic preparedness.
Approach: Using epidemiological transmission parameters, including the latent period, incubation period, serial interval, generation interval, and epidemic growth rate, this paper evaluates how presymptomatic infectiousness influences surveillance performance. Mathematical frameworks, including renewal equation models and extended compartmental models incorporating presymptomatic infectious states, are used to demonstrate the effects of early transmission on epidemic dynamics.
Findings: Evidence from the COVID-19 pandemic demonstrates that substantial SARS-CoV-2 transmission occurred before symptom onset, contributing to delayed detection, incomplete case ascertainment, and reduced effectiveness of symptom-triggered interventions. Mathematical modeling shows that presymptomatic transmission shortens generation intervals, accelerates epidemic growth, and reduces the available window for effective containment.
Conclusion: Presymptomatic transmission represents a fundamental challenge for conventional surveillance systems because transmission may occur before clinical recognition. Future pandemic preparedness, including readiness for emerging threats such as Disease X, requires a transition toward integrated, pathogen-agnostic surveillance systems combining clinical surveillance, laboratory networks, genomic monitoring, wastewater surveillance, community-based detection, digital epidemiology, and real-time modeling to identify transmission before widespread disease manifestation.
Keywords: Presymptomatic Transmission; Infectious Disease Surveillance; Epidemic Modeling; Generation Interval; Serial Interval; Pandemic Preparedness; Disease X
