SummaryBackgroundCountries around the globe have implemented unprecedented mitigation measures to mitigate the coronavirus disease 2019 (COVID-19) pandemic. We aim to predict COVID-19 cases and compare effectiveness of mitigation measures across countries to inform policy decision making.MethodsWe propose a survival-convolution model for predicting key statistics of COVID-19 epidemics (daily new cases). We account for transmission during a presymptomatic incubation period and use a time-varying reproduction number (Rt) to reflect the temporal trend of transmission and change in response to an intervention. We estimate the intervention effect on reducing the infection rate and quantify uncertainty by permutation.FindingsOur model adequately estimated observed daily new cases and could predict the entire disease epidemic using data from the early phase. A fast rate of decline in Rt was observed in China and South Korea. In Italy, Rt decreased at a slower rate and did not change significantly before the nation-wide lockdown and two-weeks after. In the United States (US), there was a significant change in Rt before and after the declaration of national emergency.InterpretationAdopting mitigation strategies early in the epidemic is effective in reducing the infection rate. The lockdown in Italy did not further accelerate the speed at which the infection rate decreases and the epidemic is not yet under control. If the current trend continues in the US, COVID-19 may be controlled by May 24 (CI: May 15 to Jun 9). However, relaxing mitigation measures could delay the end date of the epidemic as long as 42 days.FundingUS National Institutes of Health.Research in contextEvidence before this studyThe COVID-19 has created major health crisis around the world. As countries respond to the pandemic, it is urgent to predict disease epidemic and compare containment and mitigation efforts between countries to investigate their impacts on infection rates. We searched PubMed for studies published in English up to April 2020, with the terms “COVID-19”, “coronavirus”, “SARS-CoV-2”,”2019-nCoV” AND “transmission”, “dynamics”, “model”, “estimate”, “forecast”, “intervention”, “control measures”. We found several infectious disease models for epidemic in China, other Asian countries, and Europe, and predictions of mortality rate and hospital demands in United Kingdom and United States. A few studies have investigated the impact of control measures based on simulations. However, existing models for COVID-19 are based on susceptible-exposed-infected-removed (SEIR) models for prior influenza and SARS epidemics, which involve a large number of parameters and may susceptible to perturbation in parameters. No published work has used a parsimonious survival model to directly predict daily new case or use natural experiment design to estimate intervention effect.Added value of this studyWe present a parsimonious and robust survival convolution model to predict daily new cases and daily hidden latent cases with a few model parameters and assumptions, and estimate intervention effects across countries under longitudinal pre-post quasi-experimental. Our model may provide narrower confidence intervals and more accurate prediction than existing methods based on SEIR models. In China and South Korea, we predict the entire disease epidemic using only data two to three weeks after the outbreak. In Italy, there was no significant effect of national-wide lockdown measured by the difference in the trend of Rt. In the US, series of response measures implemented across states before March 13 has made a significant impact on changing Rt. Early response measures implemented in China and South Korea have reduced the infection rate faster than Italy and the US. Italy’s Rt has remained around 1·0 for more than two weeks since March 26, while in the US Rt continues to decrease.Implications of all the available evidenceImplementing response measures earlier in the disease epidemic reduces the disease transmission measured by Rt at a faster speed. Thus, for regions at early stage of disease epidemic (e.g., South America), mitigation measures should be introduced early. Nation-wide lockdown may not further reduce the speed of Rt reduction compared to regional quarantine measures. In countries where disease transmission has slowed down, lifting of quarantine measures may lead to a persistent infection rate delaying full control of epidemic and thus should be implemented with caution.
An Examination of People’s Privacy Concerns, Perceptions of Social Benefits, and Acceptance of COVID-19 Mitigation Measures That Harness Location Information: A Comparative Study of the U.S. and South Korea
