The trade-off between mobility and vaccination for COVID-19 control: a metapopulation modelling approach

November 2020 received a string of encouraging results from leading vaccine developers raising hopes for the imminent availability of an effective and safe vaccine against the SARS-CoV-2. In the present work, we discuss the theoretical impact of introducing a vaccine across a range of scenarios. In particular, we investigate how vaccination coverage, efficacy and delivery time affect the control of the transmission dynamics in comparison to mobility restrictions. The analysis is based on a metapopulation epidemic model structured by risk. We perform a global sensitivity analysis using the Sobol method. Our analysis suggest that the reduction of mobility among patches plays a significant role in the mitigation of the disease close to the effect of immunization coverage of 30% achieved in four months. Moreover, for an immunization coverage between 20% and 50% achieved in the first half of 2021 with a vaccine efficacy between 70% and 95%, the percentage reduction in the total number of SARS-CoV-2 infections is between 30% and 50% by the end of 2021 in comparison with the no vaccination scenario.

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The trade-off between mobility and vaccination for COVID-19 control: a metapopulation modeling approach

10.1101/2020.12.09.20246538 ◽

2020 ◽

Author(s):

Fernando Saldana ◽

Jorge X. Velasco-Hernandez

Keyword(s):

Sensitivity Analysis ◽

Epidemic Model ◽

Global Sensitivity Analysis ◽

Immunization Coverage ◽

Transmission Dynamics ◽

Percentage Reduction ◽

Delivery Time ◽

Trade Off ◽

Global Sensitivity ◽

Safe Vaccine

November 2020 received a string of encouraging results from leading vaccine developers raising hopes for the imminent availability of an effective and safe vaccine against the SARS-CoV-2. In the present work, we discuss the theoretical impact of introducing a vaccine across a range of scenarios . In particular, we investigate how vaccination coverage, efficacy, and delivery time affect the control of the transmission dynamics in comparison to mobility restrictions. The analysis is based on a metapopulation epidemic model structured by risk. We perform a global sensitivity analysis using the Sobol method. Our analysis suggest that the reduction of mobility among patches play a significant role in the mitigation of the disease close to the effect of immunization coverage of 30\% achieved in 4 months. Moreover, for an immunization coverage between 20\%-50\% achieved in the first half of 2021 with a vaccine efficacy between 70\%-95\%, the percentage reduction in the total number of SARS-CoV-2 infections is between 30\%-50\% by the end of 2021 in comparison with the no vaccination scenario.

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Stability and global sensitivity analysis of the transmission dynamics of malaria with relapse and ignorant infected humans

Physica Scripta ◽

10.1088/1402-4896/ac4862 ◽

2022 ◽

Author(s):

Yves Tinda Mangongo ◽

Joseph-Désiré Kyemba Bukweli ◽

Justin Dupar Busili Kampempe ◽

Rostin Matendo Mabela ◽

Justin Manango Wazute Munganga

Keyword(s):

Sensitivity Analysis ◽

Recovery Rate ◽

Global Sensitivity Analysis ◽

Rank Correlation ◽

Latin Hypercube Sampling ◽

Transmission Dynamics ◽

Asymptotically Stable ◽

Globally Asymptotically Stable ◽

Global Sensitivity ◽

Partial Rank Correlation

Abstract In this paper we present a more realistic mathematical model for the transmission dynamics of malaria by extending the classical SEIRS scheme and the model of Hai-Feng Huo and Guang-Ming Qiu [21] by adding the ignorant infected humans compartment. We analyze the global asymptotically stabilities of the model by the use of the basic reproduction number R_0 and we prove that when R_0≦1, the disease-free equilibrium is globally asymptotically stable. That is malaria dies out in the population. When R_0>1, there exists a co-existing unique endemic equilibrium which is globally asymptotically stable. The global sensitivity analysis have been done through the partial rank correlation coefficient using the samples generated by the use of latin hypercube sampling method and shows that the most influence parameters in the spread of malaria are the proportion θ of infectious humans who recover and the recovery rate γ of infectious humans. In order to eradicate malaria, we have to decrease the number of ignorant infected humans by testing peoples and treat them. Numerical simulations show that malaria can be also controlled or eradicated by increasing the recovery rate γ of infectious humans, decreasing the number of ignorant infected humans and decreasing the average number n of mosquito bites.

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