Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Using Spatial Patterns of COVID-19 to Build a Framework for Economic Reactivation

Version 1 : Received: 20 July 2021 / Approved: 21 July 2021 / Online: 21 July 2021 (18:27:42 CEST)

How to cite: Quiliche, R.; Renteria-Ramos, R.; Junior, I.D.B.; Luna, A.; Chong, M. Using Spatial Patterns of COVID-19 to Build a Framework for Economic Reactivation. Preprints 2021, 2021070504 (doi: 10.20944/preprints202107.0504.v1). Quiliche, R.; Renteria-Ramos, R.; Junior, I.D.B.; Luna, A.; Chong, M. Using Spatial Patterns of COVID-19 to Build a Framework for Economic Reactivation. Preprints 2021, 2021070504 (doi: 10.20944/preprints202107.0504.v1).

Abstract

In this article we propose an application of humanitarian logistics theory to build a supportive framework for economic reactivation and pandemic management based on province vulnerability against COVID-19. The main research question is: which factors are related to COVID-19 mortality between Peruvian provinces? We conduct a spatial regression analysis to explore which factors determines the differences in COVID-19 cumulative mortality rates for 189 Peruvian provinces up to December 2020. The most vulnerable provinces are characterized by having low outcomes of long-run poverty and high population density. Low poverty means a high economic activity that leads to more deaths of COVID-19. There is a lack of supply of a set of relief goods defined as Pandemic Response and Recovery Supportive Goods and Services (PRRSGS). These goods must be delivered in order to mitigate the risk associated to COVID-19. A supportive framework for economic reactivation can be built based on regression results and a delivery strategy can be discussed according to the spatial patterns that we found for mortality rates.

Subject Areas

humanitarian logistics; pandemic; economic reactivation; spatial modelling

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