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Transmission of SARS-CoV-2 between ferrets in presence of pre-existing immunity
Chong Wang1,2, Lei Shuai1,2, Gongxun Zhong1,2
1State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, People's Republic of China.
Abstract:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19), is characterized by its high contagiousness. The COVID-19 pandemic has exerted profound impacts on human society. The persistent circulation of SARS-CoV-2 in human populations continues to pose re-exposure risks for both vaccinated individuals and those with prior natural infection. Against this epidemiological background, there is an urgent need to characterize the transmission dynamics of SARS-CoV-2 in the context of pre-existing immunity. Using a ferret infection model, this study systematically addresses critical scientific questions, including viral transmission efficiency, temporal patterns of transmissibility, and the ability of pre-existing immunity to mitigate reinfection and viral shedding. The findings provide robust experimental evidence for elucidating the transmission mechanisms of SARS-CoV-2 and offer scientific insights to inform the rational design of optimized antiviral strategies.IMPORTANCEIn this study, a ferret infection model was used to systematically investigate SARS-CoV-2's in vivo transmission dynamics and modes with pre-existing immunity. By characterizing viral transmission efficiency, temporal shedding patterns, and immunity's role in mitigating re-infection severity and dissemination, it provides direct evidence for understanding SARS-CoV-2 spread in immune-exposed hosts. It quantifies how humoral immunity modulates viral load (primary/secondary infections) and ferret contact transmission. Findings establish a key SARS-CoV-2 transmission framework-pre-existing immunity shortens shedding, reduces secondary attack rates but retains residual transmissibility-fill knowledge gaps, guide vaccine/herd immunity/public health measures, and lay a foundation for predicting real-world transmission and antiviral policies via integrated endpoints.
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