ArticleCureus2025
Intra- and Inter-host Transmission Dynamics of SARS-CoV-2 Through Viral Load Data Analysis.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Polymerase chain reaction (PCR) tests are the gold standard for confirming COVID-19. Test results provide the cycle threshold (Ct) value, which is correlated to the patient's viral load as well as hematological and biochemical parameters. The purpose of this study is to analyze the transmission dynamics of selected SARS-CoV-2 variants, both within hosts and between hosts, through statistics and data analysis of the Ct values and other metrics. Demographics data and Ct values from 1,041 patients with COVID-19 were collected and correlated with epidemiological indices, such as the positivity rate, hospitalizations, and deaths for each major wave of the pandemic, in Greece. The analysis showed that higher viral loads coincide with rising pandemic waves, while lower loads are observed during periods of decline. Notably, among all variants analyzed, the Delta variant, observed in mid-2021, exhibited the highest viral load values, which were associated with increased hospitalizations and mortality, despite a relatively low positivity rate. Consequently, variables associated with inter-host transmission dynamics show a significant correlation with those pertaining to intra-host dynamics. This correlation opens up the potential for predicting disease severity and forecasting the trajectory of the pandemic based on patient-related and other variables through data analysis. The analysis revealed that variations in Ct value yield valuable insights into the evolution of the pandemic and the risk stratification of patients. The study highlights that statistical measures derived from Ct values can provide insights into both intra-host and inter-host transmission dynamics, potentially supporting risk assessment and public health responses.
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