Centre d'Epidémiologie Clinique, Hôtel Dieu Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France.
Department of Gastroenterology and Nutrition, Hôpital Saint-Antoine, Assistance Publique-Hôpitaux de Paris, Paris, France.
Eur J Public Health. 2021 Dec 1;31(6):1265-1270. doi: 10.1093/eurpub/ckab140.
Whether voting is a risk factor for epidemic spread is unknown. Reciprocally, whether an epidemic can deter citizens from voting has not been often studied. We aimed to investigate such relationships for France during the coronavirus disease 19 (COVID-19) epidemic.
We performed an observational study and dynamic modelling using a sigmoidal mixed effects model. All hospitals with COVID-19 patients were included (18 March 2020-17 April 2020). Abstention rate of a concomitant national election was collected.
Mean abstention rate in 2020 among departments was 52.5% ± 6.4% and had increased by a mean of 18.8% as compared with the 2014 election. There was a high degree of similarity of abstention between the two elections among the departments (P < 0.001). Among departments with a high outbreak intensity, those with a higher participation were not affected by significantly higher COVID-19 admissions after the elections. The sigmoidal model fitted the data from the different departments with a high degree of consistency. The covariate analysis showed that a significant association between participation and number of admitted patients was observed for both elections (2020: β = -5.36, P < 1e-9 and 2014: β = -3.15, P < 1e-6) contradicting a direct specific causation of the 2020 election. Participation was not associated with the position of the inflexion point suggesting no effect in the speed of spread.
Our results suggest that the surrounding intensity of the COVID-19 epidemic in France did not have any local impact on participation to a national election. The level of participation had no impact on the spread of the pandemic.
投票是否是疫情传播的一个风险因素尚不清楚。相反，疫情是否会阻止公民投票也没有得到经常研究。我们旨在研究法国在 2019 冠状病毒病（COVID-19）疫情期间的这种关系。
我们使用了一个 S 型混合效应模型进行了观察性研究和动态建模。所有有 COVID-19 患者的医院都被纳入（2020 年 3 月 18 日至 4 月 17 日）。同时进行的全国选举的弃权率被收集。
2020 年，各部门的平均弃权率为 52.5%±6.4%，与 2014 年选举相比，平均增加了 18.8%。在各部门中，两次选举的弃权率非常相似（P<0.001）。在疫情强度较高的部门中，那些参与度较高的部门在选举后，COVID-19 入院人数的增加并没有显著影响。S 型模型高度一致地拟合了不同部门的数据。协变量分析显示，在两次选举中，参与率与入院人数之间存在显著的关联（2020 年：β=-5.36，P<1e-9；2014 年：β=-3.15，P<1e-6），这与选举对 COVID-19 的直接特定因果关系相矛盾。参与率与拐点位置无关，表明其对传播速度没有影响。
我们的结果表明，法国 COVID-19 疫情的周围强度对全国选举的参与没有任何局部影响。参与率对大流行的传播没有影响。
