Study population and setting
This study of SARS-CoV-2 spread within mainland China from December 1, 2019 to April 30, 2020 used mobile phone (i.e., smartphone) data on inter-city and inner-city population movement from three sources: aggregated inflow and outflow data from 340 cities in China, a historical city-specific relative movement matrix from 2014-2015, and county-level daily population movement data used to estimate within-city travel. Additionally, the interval between illness onset to case confirmation was estimated at the county level. The authors used these data different data sources to assess impact of three groups of non-pharmaceutical interventions (NPIs): 1) prohibition of travel between cities to prevent intercity viral spread, 2) early identification and isolation of cases through contact tracing, and 3) contact restrictions and social distancing measures. A susceptible-exposed-infection-removed (SEIR) model was used to simulate viral spread between and within cities in China, accounting for observed changes in contact rates due to travel restrictions and social distancing (estimated from mobile phone data) and reductions in the infectious period due to contact tracing (estimated from data on delay from illness onset to case detection). The impacts of individual NPIs and their timing were assessed by simulating different scenarios.
Summary of Main Findings
Joint implementation of all three classes of NPIs had the largest estimated effect in terms of case counts. Of the three types of NPIs assessed, early detection and isolation of cases had the greatest individual impact on the reduction in total number of cases. Inter-city travel bans were implemented after the virus had already spread outside of Hubei; these had the smallest impact on the case count of the three classes of NPIs. Simulations showed substantial impacts on case counts by varying the timing of NPI implementation in either direction; even a single week’s delay in implementation would have increased the number of new infections by threefold.
This study used comprehensive mobile data on population movements (>7 billion position requests per day) at the city level to assess changes in contact patterns following travel restrictions between provinces and the implementation of social distancing measures.
In part because of the near-simultaneous implementation of NPI measures in China, the interventions assessed are broad aggregates of multiple individual interventions: for example, “contact restrictions and social distancing” comprise many distinct measures that include school closures, bans on gatherings, etc. Similarly, case detection and isolation comprise a suite of linked public health measures, some of which may be replicable outside China and some which may not. The impact of travel restrictions and social distancing may be different outside of China. The study assumes once cases are detected, they are effectively isolated with no subsequent onward transmission; thus, the study may overestimate the impact of case detection and isolation. The estimated number of cases implies that China detected over half of all cases of SARS-CoV-2, which may considerably underestimate the size of the epidemic.
This is one of the first studies to disaggregate the impact of individual NPIs and to compare their individual versus combined effectiveness.