Estimating generation time of SARS-CoV-2 variants in Italy from the daily incidence rate
Abstract The identification of the transmission parameters of a virus is fundamental to identify the optimal public health strategy. These parameters can present significant changes over time caused by genetic mutations or viral recombination, making their continuous monitoring fundamental. Here we...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-07-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-38327-y |
| _version_ | 1797774249530753024 |
|---|---|
| author | Eugenio Lippiello Giuseppe Petrillo Silvio Baccari Lucilla de Arcangelis |
| author_facet | Eugenio Lippiello Giuseppe Petrillo Silvio Baccari Lucilla de Arcangelis |
| author_sort | Eugenio Lippiello |
| collection | DOAJ |
| description | Abstract The identification of the transmission parameters of a virus is fundamental to identify the optimal public health strategy. These parameters can present significant changes over time caused by genetic mutations or viral recombination, making their continuous monitoring fundamental. Here we present a method, suitable for this task, which uses as unique information the daily number of reported cases. The method is based on a time since infection model where transmission parameters are obtained by means of an efficient maximization procedure of the likelihood. Applying the method to SARS-CoV-2 data in Italy, we find an average generation time $${\overline{z}}=3.2 \pm 0.8$$ z ¯ = 3.2 ± 0.8 days, during the temporal window when the majority of infections can be attributed to the Omicron variants. At the same time we find a significantly larger value $${\overline{z}}=6.2\pm 1.1$$ z ¯ = 6.2 ± 1.1 days, in the temporal window when spreading was dominated by the Delta variant. We are also able to show that the presence of the Omicron variant, characterized by a shorter $${{\overline{z}}}$$ z ¯ , was already detectable in the first weeks of December 2021, in full agreement with results provided by sequences of SARS-CoV-2 genomes reported in national databases. Our results therefore show that the novel approach can indicate the existence of virus variants, resulting particularly useful in situations when information about genomic sequencing is not yet available. At the same time, we find that the standard deviation of the generation time does not significantly change among variants. |
| first_indexed | 2024-03-12T22:18:16Z |
| format | Article |
| id | doaj.art-d3ddd96079fa47b6b8631d84f90b6807 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-12T22:18:16Z |
| publishDate | 2023-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-d3ddd96079fa47b6b8631d84f90b68072023-07-23T11:13:46ZengNature PortfolioScientific Reports2045-23222023-07-011311710.1038/s41598-023-38327-yEstimating generation time of SARS-CoV-2 variants in Italy from the daily incidence rateEugenio Lippiello0Giuseppe Petrillo1Silvio Baccari2Lucilla de Arcangelis3Department of Mathematics and Physics, University of Campania “L. Vanvitelli”The Institute of Statistical Mathematics, Research Organization of Information and SystemsDepartment of Mathematics and Physics, University of Campania “L. Vanvitelli”Department of Mathematics and Physics, University of Campania “L. Vanvitelli”Abstract The identification of the transmission parameters of a virus is fundamental to identify the optimal public health strategy. These parameters can present significant changes over time caused by genetic mutations or viral recombination, making their continuous monitoring fundamental. Here we present a method, suitable for this task, which uses as unique information the daily number of reported cases. The method is based on a time since infection model where transmission parameters are obtained by means of an efficient maximization procedure of the likelihood. Applying the method to SARS-CoV-2 data in Italy, we find an average generation time $${\overline{z}}=3.2 \pm 0.8$$ z ¯ = 3.2 ± 0.8 days, during the temporal window when the majority of infections can be attributed to the Omicron variants. At the same time we find a significantly larger value $${\overline{z}}=6.2\pm 1.1$$ z ¯ = 6.2 ± 1.1 days, in the temporal window when spreading was dominated by the Delta variant. We are also able to show that the presence of the Omicron variant, characterized by a shorter $${{\overline{z}}}$$ z ¯ , was already detectable in the first weeks of December 2021, in full agreement with results provided by sequences of SARS-CoV-2 genomes reported in national databases. Our results therefore show that the novel approach can indicate the existence of virus variants, resulting particularly useful in situations when information about genomic sequencing is not yet available. At the same time, we find that the standard deviation of the generation time does not significantly change among variants.https://doi.org/10.1038/s41598-023-38327-y |
| spellingShingle | Eugenio Lippiello Giuseppe Petrillo Silvio Baccari Lucilla de Arcangelis Estimating generation time of SARS-CoV-2 variants in Italy from the daily incidence rate Scientific Reports |
| title | Estimating generation time of SARS-CoV-2 variants in Italy from the daily incidence rate |
| title_full | Estimating generation time of SARS-CoV-2 variants in Italy from the daily incidence rate |
| title_fullStr | Estimating generation time of SARS-CoV-2 variants in Italy from the daily incidence rate |
| title_full_unstemmed | Estimating generation time of SARS-CoV-2 variants in Italy from the daily incidence rate |
| title_short | Estimating generation time of SARS-CoV-2 variants in Italy from the daily incidence rate |
| title_sort | estimating generation time of sars cov 2 variants in italy from the daily incidence rate |
| url | https://doi.org/10.1038/s41598-023-38327-y |
| work_keys_str_mv | AT eugeniolippiello estimatinggenerationtimeofsarscov2variantsinitalyfromthedailyincidencerate AT giuseppepetrillo estimatinggenerationtimeofsarscov2variantsinitalyfromthedailyincidencerate AT silviobaccari estimatinggenerationtimeofsarscov2variantsinitalyfromthedailyincidencerate AT lucilladearcangelis estimatinggenerationtimeofsarscov2variantsinitalyfromthedailyincidencerate |