Multi-objective Risk-based Resource Allocation for Urban Pandemic Preparedness: The COVID-19 Case in Bogotá, Colombia
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Abstract
Determining how best to allocate resources to be used during a pandemic is a strategic decision that directly affects the success of pandemic response operations. However, government agencies have finite resources, so they can’t monitor everything all of the time: they have to decide how best to allocate their scarce resources (i.e., budget for antivirals and preventive vaccinations, Intensive Care Unit (ICU), ventilators, non-intensive Care Unit (non-ICU), doctors) across a broad range of risk exposures (i.e., geographic spread, routes of transmission, overall poverty, medical preconditions). This paper establishes a comprehensive risk-based emergency management framework that could be used by decision-makers to determine how best to manage medical resources, as well as suggest patient allocation among hospitals and alternative healthcare facilities. A set of risk indexes are proposed by modeling the randomness and uncertainty of allocating resources in a pandemic. The city understudy is modeled as a Euclidean complex network, where depending on the neighborhood influence of allocating a resource in a demand point (i.e., informing citizens, limit social contact, allocate a new hospital) different network configurations are proposed. Finally, a multi-objective risk-based resource allocation (MoRRA) framework is proposed to optimize the allocation of resources in pandemics. The applicability of the framework is shown by the identification of high-risk areas where to prioritize the resource allocation during the current COVID-19 pandemic in Bogotá, Colombia.
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SciScore for 10.1101/2021.02.24.21252407: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results 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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar …
SciScore for 10.1101/2021.02.24.21252407: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results 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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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.
- No protocol registration statement was detected.
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