COVID-19 vaccination policies under uncertain transmission characteristics using stochastic programming.
We develop a new stochastic programming methodology for determining optimal vaccination policies for a multi-community heterogeneous population. An optimal policy provides the minimum number of vaccinations required to drive post-vaccination reproduction number to below one at a desired reliability...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0270524&type=printable |
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| _version_ | 1850023664058105856 |
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| author | Krishna Reddy Gujjula Jiangyue Gong Brittany Segundo Lewis Ntaimo |
| author_facet | Krishna Reddy Gujjula Jiangyue Gong Brittany Segundo Lewis Ntaimo |
| author_sort | Krishna Reddy Gujjula |
| collection | DOAJ |
| description | We develop a new stochastic programming methodology for determining optimal vaccination policies for a multi-community heterogeneous population. An optimal policy provides the minimum number of vaccinations required to drive post-vaccination reproduction number to below one at a desired reliability level. To generate a vaccination policy, the new method considers the uncertainty in COVID-19 related parameters such as efficacy of vaccines, age-related variation in susceptibility and infectivity to SARS-CoV-2, distribution of household composition in a community, and variation in human interactions. We report on a computational study of the new methodology on a set of neighboring U.S. counties to generate vaccination policies based on vaccine availability. The results show that to control outbreaks at least a certain percentage of the population should be vaccinated in each community based on pre-determined reliability levels. The study also reveals the vaccine sharing capability of the proposed approach among counties under limited vaccine availability. This work contributes a decision-making tool to aid public health agencies worldwide in the allocation of limited vaccines under uncertainty towards controlling epidemics through vaccinations. |
| format | Article |
| id | doaj-art-a3fcbe280feb4b14a8ab6df81af7e350 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-a3fcbe280feb4b14a8ab6df81af7e3502025-08-20T03:01:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01177e027052410.1371/journal.pone.0270524COVID-19 vaccination policies under uncertain transmission characteristics using stochastic programming.Krishna Reddy GujjulaJiangyue GongBrittany SegundoLewis NtaimoWe develop a new stochastic programming methodology for determining optimal vaccination policies for a multi-community heterogeneous population. An optimal policy provides the minimum number of vaccinations required to drive post-vaccination reproduction number to below one at a desired reliability level. To generate a vaccination policy, the new method considers the uncertainty in COVID-19 related parameters such as efficacy of vaccines, age-related variation in susceptibility and infectivity to SARS-CoV-2, distribution of household composition in a community, and variation in human interactions. We report on a computational study of the new methodology on a set of neighboring U.S. counties to generate vaccination policies based on vaccine availability. The results show that to control outbreaks at least a certain percentage of the population should be vaccinated in each community based on pre-determined reliability levels. The study also reveals the vaccine sharing capability of the proposed approach among counties under limited vaccine availability. This work contributes a decision-making tool to aid public health agencies worldwide in the allocation of limited vaccines under uncertainty towards controlling epidemics through vaccinations.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0270524&type=printable |
| spellingShingle | Krishna Reddy Gujjula Jiangyue Gong Brittany Segundo Lewis Ntaimo COVID-19 vaccination policies under uncertain transmission characteristics using stochastic programming. PLoS ONE |
| title | COVID-19 vaccination policies under uncertain transmission characteristics using stochastic programming. |
| title_full | COVID-19 vaccination policies under uncertain transmission characteristics using stochastic programming. |
| title_fullStr | COVID-19 vaccination policies under uncertain transmission characteristics using stochastic programming. |
| title_full_unstemmed | COVID-19 vaccination policies under uncertain transmission characteristics using stochastic programming. |
| title_short | COVID-19 vaccination policies under uncertain transmission characteristics using stochastic programming. |
| title_sort | covid 19 vaccination policies under uncertain transmission characteristics using stochastic programming |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0270524&type=printable |
| work_keys_str_mv | AT krishnareddygujjula covid19vaccinationpoliciesunderuncertaintransmissioncharacteristicsusingstochasticprogramming AT jiangyuegong covid19vaccinationpoliciesunderuncertaintransmissioncharacteristicsusingstochasticprogramming AT brittanysegundo covid19vaccinationpoliciesunderuncertaintransmissioncharacteristicsusingstochasticprogramming AT lewisntaimo covid19vaccinationpoliciesunderuncertaintransmissioncharacteristicsusingstochasticprogramming |