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Strict and repeated lockdowns have caused public fatigue regarding policy compliance and had a large impact on several countries' economies. We aimed to evaluate the effectiveness of a soft lockdown policy and the strategy of active community screening for controlling COVID-19 in Taiwan. We used village-based daily confirmed COVID-19 statistics in Taipei City and New Taipei City, between May 2, 2021, and July 17, 2021. The temporal Gi* statistic was used to compute the spatiotemporal hotspots. Simple linear regression was used to evaluate the trend of the epidemic, positivity rate from community screening, and mobility changes in COVID-19 cases and incidence before and after a level three alert in both cities. We used a Bayesian hierarchical zero-inflated Poisson model to estimate the daily infection risk. The cities accounted for 11,403 (81.17%) of 14,048 locally confirmed cases. The mean effective reproduction number (Re) surged before the level three alert and peaked on May 16, 2021, the day after the level three alert in Taipei City (Re = 3.66) and New Taipei City (Re = 3.37). Mobility reduction and a lower positive rate were positively associated with a lower number of cases and incidence. In the spatiotemporal view, seven major districts were identified with a radial spreading pattern from one hard-hit district. Villages with a higher inflow degree centrality among people aged ≥ 60 years, having confirmed cases, specific land-use types, and with a higher aging index had higher infection risks than other villages. Early soft lockdown policy and detection of infected patients showed an effective strategy to control COVID-19 in Taiwan. [ABSTRACT FROM AUTHOR]