The reproduction number $R_t$ in structured and nonstructured populations
Using daily counts of newly infected individuals, Wallinga and Teunis (WT) introduced aconceptually simple method to estimate the number of secondary cases per primary case ($R_t$)for a given day. The method requires an estimate of the generation interval probability density function (pdf),which sp...
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AIMS Press
2009-02-01
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2009.6.239 |
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| author | Tom Burr Gerardo Chowell |
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| description | Using daily counts of newly infected individuals, Wallinga and Teunis (WT) introduced aconceptually simple method to estimate the number of secondary cases per primary case ($R_t$)for a given day. The method requires an estimate of the generation interval probability density function (pdf),which specifies the probabilities for the times between symptom onset in a primary case and symptom onset ina corresponding secondary case. Other methods to estimate $R_t$ arebased on explicit models such as the SIR model; therefore, onemight expect the WT method to be more robust to departures from SIR-type behavior.This paper uses simulated data to compare the quality of daily $R_t$ estimates based on a SIR model tothose using the WT method for both structured(classical SIR assumptions are violated) and nonstructured (classical SIR assumptions hold) populations.By using detailed simulations that record the infection day of each new infectionand the donor-recipient identities, the true $R_t$ and the generation interval pdf isknown with negligible error. We find that the generation interval pdf is timedependent in all cases, which agrees with recent results reported elsewhere.We also find that the WT method performs essentially the samein the structured populations (except for a spatial network) as it does in the nonstructured population. And,the WT method does as well or better than a SIR-model based method in three of the four structured populations.Therefore, even if the contact patterns are heterogeneous as in the structured populations evaluated here,the WT method provides reasonable estimates of $R_t$, as does the SIR method. |
| format | Article |
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| institution | Kabale University |
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| language | English |
| publishDate | 2009-02-01 |
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| spelling | doaj-art-39d4bed3b8b2473fbced0ffb0f468acb2025-01-24T01:59:06ZengAIMS PressMathematical Biosciences and Engineering1551-00182009-02-016223925910.3934/mbe.2009.6.239The reproduction number $R_t$ in structured and nonstructured populationsTom Burr0Gerardo Chowell1Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545Using daily counts of newly infected individuals, Wallinga and Teunis (WT) introduced aconceptually simple method to estimate the number of secondary cases per primary case ($R_t$)for a given day. The method requires an estimate of the generation interval probability density function (pdf),which specifies the probabilities for the times between symptom onset in a primary case and symptom onset ina corresponding secondary case. Other methods to estimate $R_t$ arebased on explicit models such as the SIR model; therefore, onemight expect the WT method to be more robust to departures from SIR-type behavior.This paper uses simulated data to compare the quality of daily $R_t$ estimates based on a SIR model tothose using the WT method for both structured(classical SIR assumptions are violated) and nonstructured (classical SIR assumptions hold) populations.By using detailed simulations that record the infection day of each new infectionand the donor-recipient identities, the true $R_t$ and the generation interval pdf isknown with negligible error. We find that the generation interval pdf is timedependent in all cases, which agrees with recent results reported elsewhere.We also find that the WT method performs essentially the samein the structured populations (except for a spatial network) as it does in the nonstructured population. And,the WT method does as well or better than a SIR-model based method in three of the four structured populations.Therefore, even if the contact patterns are heterogeneous as in the structured populations evaluated here,the WT method provides reasonable estimates of $R_t$, as does the SIR method.https://www.aimspress.com/article/doi/10.3934/mbe.2009.6.239reproduction number; generation interval; structured population. |
| spellingShingle | Tom Burr Gerardo Chowell The reproduction number $R_t$ in structured and nonstructured populations Mathematical Biosciences and Engineering reproduction number; generation interval; structured population. |
| title | The reproduction number $R_t$ in structured and nonstructured populations |
| title_full | The reproduction number $R_t$ in structured and nonstructured populations |
| title_fullStr | The reproduction number $R_t$ in structured and nonstructured populations |
| title_full_unstemmed | The reproduction number $R_t$ in structured and nonstructured populations |
| title_short | The reproduction number $R_t$ in structured and nonstructured populations |
| title_sort | reproduction number r t in structured and nonstructured populations |
| topic | reproduction number; generation interval; structured population. |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2009.6.239 |
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