Human mobility triggers how fast and where infectious diseases spread and modelling community flows helps assess the impact of social distancing policies and advance our understanding of community behaviour in such circumstances. This study investigated the relationship between human mobility and the surging incidence of COVID-19 in India. We performed a generalised estimating equation with a Poisson log-linear model to analyse the daily mobility rate and new cases of COVID-19 between 14 March and 11 September 2020. We found that mobility to grocery and retail locations was significantly associated (p < 0.01) with the incidence of COVID-19, these being crowded and unorganised in most parts of India. In contrast, visits to parks, workplaces, and transit stations did not considerably affect the changing COVID-19 cases over time. In particular, workplaces equipped with social distancing protocols or low-density open spaces are much less susceptible to the spread of the virus. These findings suggest that human mobility data, geographic information, and health geography modelling have significant potential to inform strategic decision-making during pandemics because they provide actionable knowledge of when and where communities might be exposed to the disease.
ASJC Scopus subject areas
- Geography, Planning and Development
- Urban Studies