Estimating the Effects of Non-Pharmaceutical Interventions and Population Mobility on Daily Covid-19 Cases
Evidence from Ontario
Bibliographic Data
| ID | 11970071 |
|---|---|
| Authors | Nathaniel T Stevens (0000-0001-6149-5797, University of Waterloo, corresponding author), Anindya Sen (0000-0002-9044-2181, University of Waterloo), Francis Kiwon (University of Waterloo), Plinio Pelegrini Morita (0000-0001-9515-6478, University of Waterloo), Stefan H Steiner (0000-0002-6183-8224, University of Waterloo), Qihuang Zhang (0000-0003-1455-2159, University of Pennsylvania) |
| Year | 2021 |
| Volume | 48 |
| Issue | 1 |
| Pages | 144-161 |
| Publication date | 2021-09-23 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Canadian Public Policy (JOURNAL) |
| Journal identifiers | ISSN: 0317-0861 • E-ISSN: 1911-9917 |
| Publisher | University of Toronto Press Inc. (UTPress) (PUBLISHER) |
| DOI | 10.3138/cpp.2021-022 |
| PMID | 36039068 |
| OpenAlex | W3204721381 |
| Language | EN |
| Citations received | 3 |
| References cited | 24 |
This study uses coronavirus disease 2019 (COVID-19) case counts and Google mobility data for 12 of Ontario's largest Public Health Units from Spring 2020 until the end of January 2021 to evaluate the effects of non-pharmaceutical interventions (NPIs; policy restrictions on business operations and social gatherings) and population mobility on daily cases. Instrumental variables (IV) estimation is used to account for potential simultaneity bias, because both daily COVID-19 cases and NPIs are dependent on lagged case numbers. IV estimates based on differences in lag lengths to infer causal estimates imply that the implementation of stricter NPIs and indoor mask mandates are associated with reductions in COVID-19 cases. Moreover, estimates based on Google mobility data suggest that increases in workplace attendance are correlated with higher case counts. Finally, from October 2020 to January 2021, daily Ontario forecasts from Box-Jenkins time-series models are more accurate than official forecasts and forecasts from a susceptible-infected-removed epidemiology model
2019-20 coronavirus outbreak · Coronavirus disease 2019 (COVID-19 · Econometrics · Economics · Environmental health · Geography · Infectious disease (medical specialty · Outbreak · Pandemic · Population · Psychological intervention · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Sociology · COVID-19 epidemiological studies · COVID-19 Pandemic Impacts · Demography · Global Health Care Issues · Medicine · Nursing · Psychology · Gerontology · Internal Medicine · Virology
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JUE Insight
JUE Insight
| Unique citing works | 3 |
|---|---|
| Citations per year | 1 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |