2SIR-VD Model to Compare Idealized COVID-19 Vaccine Distribution Strategies in the Philippines
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Abstract
COVID-19 is a novel respiratory disease first identified in Wuhan, China, that is caused by the novel coronavirus, SARS-CoV-2. It has triggered a global pandemic of historic proportions. The government of the Philippines began its national vaccine drive on 01 Mar 2021, with the goal of vaccinating 70 million of its citizens by the end of the calendar year. To determine the optimum geographical distribution strategy in the Philippines for the limited supply of vaccines that is currently available, we developed and adapted a basic SIR (susceptible-infected-recovered) model that allows us to understand the evolution of a pandemic when public health authorities are vaccinating two susceptible populations within a country with different vaccine rates. Our analysis with our 2SIR-VD (two-population susceptible-infected-recovered-vaccinated-deceased) model of an idealized pandemic scenario revealed that prioritizing vaccine deployment to the National Capital Region (NCR) of the Philippines minimized the number of COVID-19 cases in the country. We, therefore, recommend deploying 80–90% of the available vaccine supply to the NCR to mitigate viral transmission there. The remaining doses would allow the rest of the archipelago to vaccinate all of their medical frontliners, senior citizens, and adults with comorbidities – thus shielding this vulnerable population against severe disease and death from COVID-19.
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SciScore for 10.1101/2021.05.20.21257556: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The fourth-order Runge-Kutta technique was used in integrating the systems of differential equations implemented in Microsoft Excel, with small temporal steps undertaken to assure numerical stability. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)To determine the final and converged rate constant values, the in-house Microsoft Excel Solver add-in’s Nonlinear Generalized Reduced Gradient method was used. Microsoft Excel Solversuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when …
SciScore for 10.1101/2021.05.20.21257556: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The fourth-order Runge-Kutta technique was used in integrating the systems of differential equations implemented in Microsoft Excel, with small temporal steps undertaken to assure numerical stability. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)To determine the final and converged rate constant values, the in-house Microsoft Excel Solver add-in’s Nonlinear Generalized Reduced Gradient method was used. Microsoft Excel Solversuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Because of the shortcomings and limitations of the available COVID-19 pandemic data provided by the Department of Health of the Philippines, we decided to construct a basic compartmental model with the minimum number of compartments that would allow us to test different vaccine deployment strategies that prioritized different geographical regions of the country. To evaluate the quality and forecasting potential of our 2SIR-VD model, we began by comparing simulations of the pandemic at the beginning of the second surge of COVID-19 in the Philippines to the data made available by the Department of Health (DOH). As shown in Figure 1, our model accurately simulated the growth of the pandemic in the country as well as in the National Capital Region (NCR). Since the second surge of the pandemic was concentrated in the NCR, it is not surprising that the country-wide curve and the capital-only curve were similar in form and shape. Once we had determined that our model accurately simulated the growth of the pandemic during the second surge of COVID-19 in the Philippines, we used it to interrogate the impact of vaccinations on the dynamics of the pandemic. We chose to model the impact of a single-dose vaccine that conferred full protection against COVID-19. This is clearly an idealized scenario for the COVID-19 pandemic where most of the available vaccines require two doses separated by different periods of time, with different reported efficacy rates, but we believe that the model is ...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a protocol registration statement.
Results from scite Reference Check: We found no unreliable references.
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