Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk
Abstract Background Non-pharmaceutical interventions (NPIs) implemented in one place can affect neighboring regions by influencing people’s behavior. However, existing epidemic models for NPIs evaluation rarely consider such spatial spillover effects, which may lead to a biased assessment of policy...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-06-01
|
| Series: | International Journal of Health Geographics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12942-023-00335-6 |
| _version_ | 1827928486695665664 |
|---|---|
| author | Keli Wang Xiaoyi Han Lei Dong Xiao-Jian Chen Gezhi Xiu Mei-po Kwan Yu Liu |
| author_facet | Keli Wang Xiaoyi Han Lei Dong Xiao-Jian Chen Gezhi Xiu Mei-po Kwan Yu Liu |
| author_sort | Keli Wang |
| collection | DOAJ |
| description | Abstract Background Non-pharmaceutical interventions (NPIs) implemented in one place can affect neighboring regions by influencing people’s behavior. However, existing epidemic models for NPIs evaluation rarely consider such spatial spillover effects, which may lead to a biased assessment of policy effects. Methods Using the US state-level mobility and policy data from January 6 to August 2, 2020, we develop a quantitative framework that includes both a panel spatial econometric model and an S-SEIR (Spillover-Susceptible-Exposed-Infected-Recovered) model to quantify the spatial spillover effects of NPIs on human mobility and COVID-19 transmission. Results The spatial spillover effects of NPIs explain $$61.2\%$$ 61.2 % [ $$95\%$$ 95 % credible interval: 52.8- $$84.4\%$$ 84.4 % ] of national cumulative confirmed cases, suggesting that the presence of the spillover effect significantly enhances the NPI influence. Simulations based on the S-SEIR model further show that increasing interventions in only a few states with larger intrastate human mobility intensity significantly reduce the cases nationwide. These region-based interventions also can carry over to interstate lockdowns. Conclusions Our study provides a framework for evaluating and comparing the effectiveness of different intervention strategies conditional on NPI spillovers, and calls for collaboration from different regions. |
| first_indexed | 2024-03-13T06:08:21Z |
| format | Article |
| id | doaj.art-5d3d6b00ce2a482181dfc0097b9070b6 |
| institution | Directory Open Access Journal |
| issn | 1476-072X |
| language | English |
| last_indexed | 2024-03-13T06:08:21Z |
| publishDate | 2023-06-01 |
| publisher | BMC |
| record_format | Article |
| series | International Journal of Health Geographics |
| spelling | doaj.art-5d3d6b00ce2a482181dfc0097b9070b62023-06-11T11:24:23ZengBMCInternational Journal of Health Geographics1476-072X2023-06-0122111610.1186/s12942-023-00335-6Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic riskKeli Wang0Xiaoyi Han1Lei Dong2Xiao-Jian Chen3Gezhi Xiu4Mei-po Kwan5Yu Liu6Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking UniversityThe Wang Yanan Institute for Studies in Economics (WISE), Xiamen UniversityInstitute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking UniversityInstitute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking UniversityInstitute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking UniversityInstitute of Space and Earth Information Science, The Chinese University of Hong KongInstitute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking UniversityAbstract Background Non-pharmaceutical interventions (NPIs) implemented in one place can affect neighboring regions by influencing people’s behavior. However, existing epidemic models for NPIs evaluation rarely consider such spatial spillover effects, which may lead to a biased assessment of policy effects. Methods Using the US state-level mobility and policy data from January 6 to August 2, 2020, we develop a quantitative framework that includes both a panel spatial econometric model and an S-SEIR (Spillover-Susceptible-Exposed-Infected-Recovered) model to quantify the spatial spillover effects of NPIs on human mobility and COVID-19 transmission. Results The spatial spillover effects of NPIs explain $$61.2\%$$ 61.2 % [ $$95\%$$ 95 % credible interval: 52.8- $$84.4\%$$ 84.4 % ] of national cumulative confirmed cases, suggesting that the presence of the spillover effect significantly enhances the NPI influence. Simulations based on the S-SEIR model further show that increasing interventions in only a few states with larger intrastate human mobility intensity significantly reduce the cases nationwide. These region-based interventions also can carry over to interstate lockdowns. Conclusions Our study provides a framework for evaluating and comparing the effectiveness of different intervention strategies conditional on NPI spillovers, and calls for collaboration from different regions.https://doi.org/10.1186/s12942-023-00335-6COVID-19Non-pharmaceutical interventionsSpatial spillover effectsSEIRHuman mobility |
| spellingShingle | Keli Wang Xiaoyi Han Lei Dong Xiao-Jian Chen Gezhi Xiu Mei-po Kwan Yu Liu Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk International Journal of Health Geographics COVID-19 Non-pharmaceutical interventions Spatial spillover effects SEIR Human mobility |
| title | Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk |
| title_full | Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk |
| title_fullStr | Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk |
| title_full_unstemmed | Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk |
| title_short | Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk |
| title_sort | quantifying the spatial spillover effects of non pharmaceutical interventions on pandemic risk |
| topic | COVID-19 Non-pharmaceutical interventions Spatial spillover effects SEIR Human mobility |
| url | https://doi.org/10.1186/s12942-023-00335-6 |
| work_keys_str_mv | AT keliwang quantifyingthespatialspillovereffectsofnonpharmaceuticalinterventionsonpandemicrisk AT xiaoyihan quantifyingthespatialspillovereffectsofnonpharmaceuticalinterventionsonpandemicrisk AT leidong quantifyingthespatialspillovereffectsofnonpharmaceuticalinterventionsonpandemicrisk AT xiaojianchen quantifyingthespatialspillovereffectsofnonpharmaceuticalinterventionsonpandemicrisk AT gezhixiu quantifyingthespatialspillovereffectsofnonpharmaceuticalinterventionsonpandemicrisk AT meipokwan quantifyingthespatialspillovereffectsofnonpharmaceuticalinterventionsonpandemicrisk AT yuliu quantifyingthespatialspillovereffectsofnonpharmaceuticalinterventionsonpandemicrisk |