Simulation based adaptive vaccine delivery strategy

Inoculation is one of the most common intervention methods to mitigate the number of incidents during an outbreak. It is a crucial point to decide which age or target groups in a society are priorly vaccinated. In this study, we considered this challenge and a late vaccine distribution scenario with a new vaccine delivery strategy. A given population is divided into five age groups with different contact and transmission rates. The proposed strategy distributes weekly shots to people in an age group or groups according to results of simulation modelling different vaccination strategies for a week time horizon by considering historical incident rates of the outbreak. The method is tested against the strategy of vaccinating schoolchildren considered in many related publications in the literature. According to results, for 20 scenarios based on different contact and transmission rates and under three coverage levels, our method outperforms the benchmark strategy under 20% and 30% coverage levels for each scenario. Both strategies mostly follow same distributions and come up with same results under 10% coverage level. We can conclude that the proposed method is robust to changes in contact and transmission rates and provides superior results when coverage levels are relatively high. The method can provide effective vaccination strategies by considering disease dynamics for primarily COVID-19 and future pandemics.

Simulation based adaptive vaccine delivery strategy

Inoculation is one of the most common intervention methods to mitigate the number of incidents during an outbreak. It is a crucial point to decide which age or target groups in a society are priorly vaccinated. In this study, we considered this challenge and a late vaccine distribution scenario with a new vaccine delivery strategy. A given population is divided into five age groups with different contact and transmission rates. The proposed strategy distributes weekly shots to people in an age group or groups according to results of simulation modelling different vaccination strategies for a week time horizon by considering historical incident rates of the outbreak. The method is tested against the strategy of vaccinating schoolchildren considered in many related publications in the literature. According to results, for 20 scenarios based on different contact and transmission rates and under three coverage levels, our method outperforms the benchmark strategy under 20% and 30% coverage levels for each scenario. Both strategies mostly follow same distributions and come up with same results under 10% coverage level. We can conclude that the proposed method is robust to changes in contact and transmission rates and provides superior results when coverage levels are relatively high. The method can provide effective vaccination strategies by considering disease dynamics for primarily COVID-19 and future pandemics. (English) [ FROM AUTHOR] Aşılama, bir salgın sırasında oluşacak vaka sayısını azaltmak için kullanılan en yaygın müdahale yöntemlerinden biridir. Bir toplumda hangi yaş ve hedef gruplarının öncelikle aşılanacağına karar vermek çok önemli bir noktadır. Bu çalışmada hem bu nokta hem de geç aşı dağıtım senaryosu, yeni bir aşı dağıtma stratejisi ile düşünülmüştür. Íncelenen popülasyon farklı kontak ve bulaştırma oranları düşünülerek beş farklı gruba ayrılmıştır. Önerilen aşı dağıtma stratejisi, salgın sırasında oluşan vaka sayılarını da düşünerek, haftalık dağıtılabilecek aşıları farklı yaş gruplarında bulunan kişilere, bir hafta süre için farklı dağıtım stratejilerini modelleyen bir benzetimin sonuçlarına göre dağıtmaktadır. Bu metot, literatürdeki birçok çalışmada düşünülen okul çağındaki çocukları öncelikle aşılama stratejisine karşı test edilmiştir. Farklı kontak ve bulaştırma oranlarına göre oluşturulan 20 farklı senaryo ve 3 farklı kapsama seviyesi için elde edilen sonuçlara göre önerilen metot, %20 ve %30 kapsama seviyesi için karşılaştırılan stratejiden daha iyi sonuçlar vermiş, %10 kapsama seviyesi için de benzer sonuçlar gözlenmiştir. Sonuç olarak, kapsama seviyesinin göreceli daha yüksek olduğu durumlarda, önerilen metodun kontak ve bulaş oranlarında meydana gelen değişimlere karşı daha gürbüz olduğu ve daha iyi sonuçlar verdiği görülmüştür. Başta COVID-19 olmak üzere gelecekte yaşanabilecek salgınlarda, hastalık dinamiklerini de düşünerek, efektif aşı dağıtımlarını gerçekleştirebilecektir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Simulation based adaptive vaccine delivery strategy.

Inoculation is one of the most common intervention methods to mitigate the number of incidents during an outbreak. It is a crucial point to decide which age or target groups in a society are priorly vaccinated. In this study, we considered this challenge and a late vaccine distribution scenario with a new vaccine delivery strategy. A given population is divided into five age groups with different contact and transmission rates. The proposed strategy distributes weekly shots to people in an age group or groups according to results of simulation modelling different vaccination strategies for a week time horizon by considering historical incident rates of the outbreak. The method is tested against the strategy of vaccinating schoolchildren considered in many related publications in the literature. According to results, for 20 scenarios based on different contact and transmission rates and under three coverage levels, our method outperforms the benchmark strategy under 20% and 30% coverage levels for each scenario. Both strategies mostly follow same distributions and come up with same results under 10% coverage level. We can conclude that the proposed method is robust to changes in contact and transmission rates and provides superior results when coverage levels are relatively high. The method can provide effective vaccination strategies by considering disease dynamics for primarily COVID-19 and future pandemics. (English) [ FROM AUTHOR] Aşılama, bir salgın sırasında oluşacak vaka sayısını azaltmak için kullanılan en yaygın müdahale yöntemlerinden biridir. Bir toplumda hangi yaş ve hedef gruplarının öncelikle aşılanacağına karar vermek çok önemli bir noktadır. Bu çalışmada hem bu nokta hem de geç aşı dağıtım senaryosu, yeni bir aşı dağıtma stratejisi ile düşünülmüştür. Íncelenen popülasyon farklı kontak ve bulaştırma oranları düşünülerek beş farklı gruba ayrılmıştır. Önerilen aşı dağıtma stratejisi, salgın sırasında oluşan vaka sayılarını da düşünerek, haftalık dağıtılabilecek aşıları farklı yaş gruplarında bulunan kişilere, bir hafta süre için farklı dağıtım stratejilerini modelleyen bir benzetimin sonuçlarına göre dağıtmaktadır. Bu metot, literatürdeki birçok çalışmada düşünülen okul çağındaki çocukları öncelikle aşılama stratejisine karşı test edilmiştir. Farklı kontak ve bulaştırma oranlarına göre oluşturulan 20 farklı senaryo ve 3 farklı kapsama seviyesi için elde edilen sonuçlara göre önerilen metot, %20 ve %30 kapsama seviyesi için karşılaştırılan stratejiden daha iyi sonuçlar vermiş, %10 kapsama seviyesi için de benzer sonuçlar gözlenmiştir. Sonuç olarak, kapsama seviyesinin göreceli daha yüksek olduğu durumlarda, önerilen metodun kontak ve bulaş oranlarında meydana gelen değişimlere karşı daha gürbüz olduğu ve daha iyi sonuçlar verdiği görülmüştür. Başta COVID-19 olmak üzere gelecekte yaşanabilecek salgınlarda, hastalık dinamiklerini de düşünerek, efektif aşı dağıtımlarını gerçekleştirebilecektir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Simulation based adaptive vaccine delivery strategy

Inoculation is one of the most common intervention methods to mitigate the number of incidents during an outbreak. It is a crucial point to decide which age or target groups in a society are priorly vaccinated. In this study, we considered this challenge and a late vaccine distribution scenario with a new vaccine delivery strategy. A given population is divided into five age groups with different contact and transmission rates. The proposed strategy distributes weekly shots to people in an age group or groups according to results of simulation modelling different vaccination strategies for a week time horizon by considering historical incident rates of the outbreak. The method is tested against the strategy of vaccinating schoolchildren considered in many related publications in the literature. According to results, for 20 scenarios based on different contact and transmission rates and under three coverage levels, our method outperforms the benchmark strategy under 20% and 30% coverage levels for each scenario. Both strategies mostly follow same distributions and come up with same results under 10% coverage level. We can conclude that the proposed method is robust to changes in contact and transmission rates and provides superior results when coverage levels are relatively high. The method can provide effective vaccination strategies by considering disease dynamics for primarily COVID-19 and future pandemics. (English) [ FROM AUTHOR]

Simulation based adaptive vaccine delivery strategy

Inoculation is one of the most common intervention methods to mitigate the number of incidents during an outbreak. It is a crucial point to decide which age or target groups in a society are priorly vaccinated. In this study, we considered this challenge and a late vaccine distribution scenario with a new vaccine delivery strategy. A given population is divided into five age groups with different contact and transmission rates. The proposed strategy distributes weekly shots to people in an age group or groups according to results of simulation modelling different vaccination strategies for a week time horizon by considering historical incident rates of the outbreak. The method is tested against the strategy of vaccinating schoolchildren considered in many related publications in the literature. According to results, for 20 scenarios based on different contact and transmission rates and under three coverage levels, our method outperforms the benchmark strategy under 20% and 30% coverage levels for each scenario. Both strategies mostly follow same distributions and come up with same results under 10% coverage level. We can conclude that the proposed method is robust to changes in contact and transmission rates and provides superior results when coverage levels are relatively high. The method can provide effective vaccination strategies by considering disease dynamics for primarily COVID-19 and future pandemics.

Deep Reinforcement Learning-based Vaccine Distribution Strategies

The rapid development of artificial intelligence techniques is significantly promoting the resolution of various important decision-making issues such as material distribution, generation line optimization scheduling, and path planning. Currently, SARS-CoV-2 is raging over the world, and it is valuable to propose a vaccine distribution strategy to utilize limited vaccine resources rationally. In this paper, we aim to propose an optimal vaccine distribution strategy based on deep reinforcement learning(DRL) approaches. An End-to-End vaccine distribution model is proposed by combining the Deep Reinforcement Learning model and LinUCB algorithm to get an optimistic strategy of allocation. Experiment results demonstrated that vaccine distribution strategies based on this model show a strong capacity to control the epidemic and ensure stable government revenue compared with baseline strategies. © 2021 IEEE.