Human Mobility Patterns and Its Cross-Correlation with the COVID-19 Transmission in Jakarta, Indonesia

Abstract

The novel coronavirus disease (COVID-19) has been rapidly spreading and causing a severe health crisis in Indonesia. In the absence of medically proven vaccines, official authorities commonly adopt a social control approach under the strict public order. The Indonesian Government is no different, which imposed a large scale social restriction as an intervention strategy in Jakarta and other major cities. In this paper, we aim to quantify the correlation between human mobility and the daily new cases of COVID-19 which are further divided into two main distinct patterns: weekdays and weekends. We utilized the big data sources presented by reputable online service providers include Apple, Waze, and Google in terms of the reported daily mobility patterns. The mobility patterns include driving and walking activities as well as the movement trends across different public places such as retail and recreation, pharmacies, groceries, parks, etc from March 1 to July 31, 2020. To capture the real growth rate of COVID-19, we use the official data reported by Governmental Disease Response Acceleration Task Force. Our cross-correlation analysis revealed that in Jakarta (province-level) and Indonesia (country-level), the COVID-19 case daily growth rate is correlated with the human mobility patterns of driving and walking activities on both weekends and weekdays time. Our work put the additional insight in supporting the importance of social distancing as an effective mitigation strategy to combat the coronavirus outbreak.