Application of a VP4/VP2-inferred transmission clusters in estimating the impact of interventions on rhinovirus transmission

应用基于VP4/VP2推断的传播簇来评估干预措施对鼻病毒传播的影响

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Abstract

BACKGROUND: Despite the clinical burden attributable to rhinovirus (RV) infections, the RV transmission dynamics and the impact of interventions on viral transmission remain elusive. METHODS: A total of 3,935 nasopharyngeal specimens were examined, from which the VP4/VP2 gene was sequenced and genotyped. RV transmission clusters were reconstructed using the genetic threshold of 0.005 substitutions/site, estimated from the global VP4/VP2 sequences. A transmission cluster is characterized by the presence of at least two individuals (represent by nodes), whose viral sequences are genetically linked (represent by undirected edges) at the estimated genetic distance threshold supported by bootstrap value of ≥ 90%. To assess the impact of facemask, pleconaril and social distancing on RV transmission clusters, trials were simulated for interventions with varying efficacy and were evaluated based on the reduction in the number of infected patients (nodes) and the reduction in the number of nodes-connecting edges. The putative impact of intervention strategies on RV transmission clusters was evaluated through 10,000 simulations. RESULTS: A substantial clustering of 168 RV transmission clusters of varying sizes were observed. This suggests that RV disease burden observed in the population was largely due to multiple sub-epidemics, predominantly driven by RV-A, followed by RV-C and -B. No misclassification of RV species and types were observed, suggesting the specificity and sensitivity of the analysis. Through 10,000 simulations, it was shown that social distancing may be effective in decelerating RV transmission, by removing more than 95% of nodes and edges within the RV transmission clusters. However, facemask removed less than 8% and 66% of nodes and edges, respectively, conferring moderate advantage in limiting RV transmission. CONCLUSION: Here, we presented a network-based approach of which the degree of RV spread that fuel disease transmission in the region was mapped for the first time. The utilization of RV transmission clusters in assessing the putative impact of interventions on disease transmission at the population level was demonstrated.

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