Therefore, knowledge of the most effective NPIs would allow stakeholders to judiciously and timely implement a specific sequence of key interventions to combat a resurgence of COVID-19 or any other future respiratory outbreak. Government interventions may cause substantial economic and social costs 5 while affecting individuals’ behaviour, mental health and social security 6. Decisions had to be taken under rapidly changing epidemiological situations, despite (at least at the very beginning of the epidemic) a lack of scientific evidence on the individual and combined effectiveness of these measures 2, 3, 4, degree of compliance of the population and societal impact. In the absence of vaccines and antiviral medication, non-pharmaceutical interventions (NPIs) implemented in response to (emerging) epidemic respiratory viruses are the only option available to delay and moderate the spread of the virus in a population 1.Ĭonfronted with the worldwide COVID-19 epidemic, most governments have implemented bundles of highly restrictive, sometimes intrusive, NPIs. Using country-specific ‘what-if’ scenarios, we assess how the effectiveness of NPIs depends on the local context such as timing of their adoption, opening the way for forecasting the effectiveness of future interventions. Less disruptive and costly NPIs can be as effective as more intrusive, drastic, ones (for example, a national lockdown). Our results indicate that a suitable combination of NPIs is necessary to curb the spread of the virus. We validate our findings with two external datasets recording 42,151 additional NPIs from 226 countries. We propose a modelling approach that combines four computational techniques merging statistical, inference and artificial intelligence tools. Here we quantify the impact of 6,068 hierarchically coded NPIs implemented in 79 territories on the effective reproduction number, R t, of COVID-19. Learn more about The Times count by reading this list of frequently asked questions or by reading this interview with members of our team.Assessing the effectiveness of non-pharmaceutical interventions (NPIs) to mitigate the spread of SARS-CoV-2 is critical to inform future preparedness response plans. The data collection effort is done in partnership with journalists at the San Francisco Chronicle, the San Diego Union-Tribune, KQED, KPCC, CapRadio, Calmatters and Stanford’s Big Local News. The files will be updated daily at /datadesk/california-coronavirus-data. The Times database is available to the public on Github, a popular website for hosting data and computer code. and Puerto Rico are collected by researchers at the Johns Hopkins University Center for Systems Science and Engineering.Ĭounties are organized into regions using the groupings developed by the state health department. Nursing home totals include skilled-nursing facilities tracked by the state public health department, as well as assisted-living facilities monitored by the California Department of Social Services.ĭata from other states, Washington, D.C. The number of people who have recovered from a coronavirus infection is an estimate, created by a model described in our FAQ. Data on hospitalizations, tests, demographics and reopening plans also come from the state health department. Numbers are gathered and posted each day. State and county totals come from the California Department of Public Health. This page was created by Swetha Kannan, Casey Miller, Sean Greene, Lorena Iñiguez Elebee, Rong-Gong Lin II, Ryan Murphy, Melody Gutierrez, Priya Krishnakumar, Sandhya Kambhampati, Maloy Moore, Jennifer Lu, Aida Ylanan, Vanessa Martínez, Ryan Menezes, Thomas Suh Lauder, Andrea Roberson, Ben Poston, Nicole Santa Cruz, Iris Lee, Rahul Mukherjee, Jaclyn Cosgrove, Anthony Pesce, Paul Duginski, Phi Do, Alejandro Maciel, Matt Stiles and Gabrielle LaMarr LeMee.
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