Spatiotemporal Dynamics of COVID-19 epidemic in the State of Kuwait

Abstract

Objectives The prompt understanding of the temporal and spatial patterns of the epidemic on a national level is a critical step for the timely allocation of surveillance resources. Therefore, we explored the temporal and spatiotemporal dynamics of the COVID-19 epidemic in Kuwait using daily confirmed case data collected between the 23rd of February and the 7th of May, 2020. Methods We quantified the epidemic progression using the time-dependent reproductive number (R(t)), while we used the spatiotemporal scan statistic model to identify local clustering events. We accounted for the variability in the transmission dynamics within and between two socioeconomic classes, including citizens-residents and migrant workers. Results Overall, the epidemic size in Kuwait continues to grow (R(t)s  2), indicating significant ongoing spread. Significant spreading and clustering events were detected among migrant workers due to their densely populated areas and poor living conditions. However, the government's aggressive intervention measures substantially lowered epidemic growth in migrant worker areas. Yet, at a later stage of the study period, we inferred active spreading and clustering events among both socioeconomic classes. Conclusions Our analyses unveiled deeper insights into the epidemiology of COVID-19 in Kuwait and provided an important platform for rapid guidance of decisions related to intervention activities.