Estimation of COVID-19 infections in Iraqi governorates using generalized moments method in spatial autoregressive model

Al-Temimi, S. A. S.; Al-Saffar, R. S.

At the end of 2019, a new type of virus that infects the human respiratory system was discovered in China, and it was briefly called COVID-19. In March 2020, the world Health Organization (WHO) declared Corona Virus a global pandemic. The Corona Virus is transmitted through air or through contact. The possibility of infection increases in the area or areas neighboring to the area that witnessed a community spread of the virus or when individuals return from that affected area to their areas of residence. Given the limited studies on the impact of affected neighboring areas or countries, this study focused on using the spatial autoregression model, one of the econometric models. Model parameters have been estimated using the Generalized Moment Method (GMM) which has the ability to correct the Endogeneity that occurs by the spatial regression variable as well as due to the endogenous variables. The results showed that the number of infections (Yn) of Corona epidemic increases as there are infections in the surrounding areas and vice versa. This confirms the impact of spatial neighborhood on the spread of infections among neighboring governorates. © The Author 2021. This work is licensed under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) that allows others to share and adapt the material for any purpose (even commercially), in any medium with an acknowledgement of the work's authorship and initial publication in this journal.