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Estimating direct and spill-over impacts of political elections on COVID-19 transmission using synthetic control methods

Authors :
Jue Tao Lim
Joel Ruihan Koo
Sok Teng Tan
Jane Mingjie Lim
Ken Wei Tan
Alex R. Cook
Kenwin Maung
Borame L Dickens
Minah Park
Suan Ee Ong
Haoyang Sun
Joanne Yoong
Source :
PLoS Computational Biology, Vol 17, Iss 5, p e1008959 (2021), PLoS Computational Biology
Publication Year :
2021
Publisher :
Public Library of Science (PLoS), 2021.

Abstract

Mass gathering events have been identified as high-risk environments for community transmission of coronavirus disease 2019 (COVID-19). Empirical estimates of their direct and spill-over effects however remain challenging to identify. In this study, we propose the use of a novel synthetic control framework to obtain causal estimates for direct and spill-over impacts of these events. The Sabah state elections in Malaysia were used as an example for our proposed methodology and we investigate the event’s spatial and temporal impacts on COVID-19 transmission. Results indicate an estimated (i) 70.0% of COVID-19 case counts within Sabah post-state election were attributable to the election’s direct effect; (ii) 64.4% of COVID-19 cases in the rest of Malaysia post-state election were attributable to the election’s spill-over effects. Sensitivity analysis was further conducted by examining epidemiological pre-trends, surveillance efforts, varying synthetic control matching characteristics and spill-over specifications. We demonstrate that our estimates are not due to pre-existing epidemiological trends, surveillance efforts, and/or preventive policies. These estimates highlight the potential of mass gatherings in one region to spill-over into an outbreak of national scale. Relaxations of mass gathering restrictions must therefore be carefully considered, even in the context of low community transmission and enforcement of safe distancing guidelines.<br />Author summary Mass gathering events have been identified as high-risk environments for community transmission of coronavirus disease 2019 (COVID-19). Empirical estimates of their direct and spill-over effects however remain limited. We frame the Sabah state election in Malaysia as a natural experiment to investigate the event’s spatial and temporal impacts on COVID-19 transmission. We estimate the direct and spill-over impact of the elections through a synthetic control methodology. Results indicate an estimated (i) 70.0% of COVID-19 case counts within Sabah post-state election were attributable to the election’s direct effect; (ii) 64.4% of COVID-19 cases in the rest of Malaysia post-state election were attributable to the election’s spill-over effects. We demonstrate that our estimates are not due to pre-existing epidemiological trends, surveillance efforts, and/or preventive policies. These estimates highlight the potential of mass gatherings in one region to spill-over into an outbreak of national scale. Relaxations of mass gathering restrictions must therefore be carefully considered, even in the context of low community transmission and enforcement of safe distancing guidelines.

Details

ISSN :
15537358
Volume :
17
Database :
OpenAIRE
Journal :
PLOS Computational Biology
Accession number :
edsair.doi.dedup.....30039260b2b5826252c483387e83ede9
Full Text :
https://doi.org/10.1371/journal.pcbi.1008959