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on Economic Geography |
| By: | Chen, Xiao; Huang, Hanwei; Ju, Jiandong; Sun, Ruoyan; Zhang, Jialiang |
| Abstract: | We study infectious diseases using a Susceptible-Infected-Recovered-Deceased model with endogenous cross-region human mobility. Individuals weigh the risk of infection against economic opportunities when moving across regions. The model predicts that the mobility rate of susceptible individuals declines with a higher infection rate at the destination. With cross-region mobility, a decrease in the transmission rate or an increase in the removal rate of the virus in any region reduces the global basic reproduction number (R0). Global R0 falls between the minimum and maximum of local R0s. A new method of Normalized Hat Algebra is developed to solve the model dynamics. Simulations indicate that a decrease in global R0 does not always imply a lower cumulative infection rate. Local and central governments may prefer different mobility control policies. |
| Keywords: | SIRD model; spatial economy; endogenous mobility; basic reproduction number; normalized hat algebra |
| JEL: | C61 C68 I18 J61 R13 |
| Date: | 2022–07–13 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:117907&r=geo |
| By: | Rosina Moreno (AQR-IREA, University of Barcelona.); Esther Vayá (AQR-IREA, University of Barcelona.) |
| Abstract: | This paper pursues a deep insight in the evolution of the spatial distribution of the pandemic in the Spanish provinces along the six waves. Through the use of spatial exploratory techniques, we observe that the geographical spread of the COVID-19 has been changing considerably so that the conclusions obtained for specific points in time are not transferable to other moments of the pandemic. We also take into consideration the changes in the determinants of the spread of the pandemic across waves while considering the possibility of external effects across provinces through the estimation of spatial regressions. |
| Keywords: | COVID-19, Pandemic, Spatial analysis, Temperature, Non-climate factors, Spanish provinces. JEL classification: H75, R58. |
| Date: | 2023–01 |
| URL: | http://d.repec.org/n?u=RePEc:ira:wpaper:202301&r=geo |