Reciprocal association between voting and the epidemic spread of COVID-19: observational and dynamic modeling study.

BACKGROUND: 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. METHODS: 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. RESULTS: 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: ß = -5.36, P < 1e-9 and 2014: ß = -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. CONCLUSIONS: 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.

Predicting the propagation of COVID-19 at an international scale: extension of an SIR model.

OBJECTIVES: Several epidemiological models have been published to forecast the spread of the COVID-19 pandemic, yet many of them have proven inaccurate for reasons that remain to be fully determined. We aimed to develop a novel model and implement it in a freely accessible web application. DESIGN: We built an SIR-type compartmental model with two additional compartments: D (deceased patients); L (individuals who will die but who will not infect anybody due to social or medical isolation) and integration of a time-dependent transmission rate and a periodical weekly component linked to the way in which cases and deaths are reported. RESULTS: The model was implemented in a web application (as of 2 June 2020). It was shown to be able to accurately capture the changes in the dynamics of the pandemic for 20 countries whatever the type of pandemic spread or containment measures: for instance, the model explains 97% of the variance of US data (daily cases) and predicts the number of deaths at a 2-week horizon with an error of 1%. CONCLUSIONS: In early performance evaluation, our model showed a high level of accuracy between prediction and observed data. Such a tool might be used by the global community to follow the spread of the pandemic.

Impact of coronavirus disease 2019 (COVID-19) lockdown on in-hospital mortality and surgical activity in elective digestive resections: A nationwide cohort analysis.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) infection has led to the reorganization of hospital care in several countries. The objective was to report the postoperative mortality after elective digestive resections in a nationwide cohort during the lockdown period. METHODS: This analytic study was performed using a national billing database (the Programme de Médicalisation des Systèmes d'Informations). Patients who underwent elective digestive resections were divided in 2 groups: the lockdown group defined by hospital admissions between March 17 and May 11, 2020; and the control group, defined by hospital admissions during the corresponding period in 2019. Groups were matched on propensity score, geographical region, and surgical procedure. The primary outcome was the postoperative mortality. RESULTS: The overall population included 15,217 patients: 9,325 patients in the control group and 5,892 in the lockdown group. The overall surgical activity was decreased by 37% during the lockdown period. The overall in-hospital mortality during the hospital stay was 2.7%. After matching and adjustment, no difference in mortality between groups was reported (OR = 1.05; 95% CI: 0.83-1.34; P = .669). An asymptomatic COVID-19 infection was a risk factor for a 2-fold increased mortality, whereas a symptomatic COVID-19 infection was associated with a 10-fold increased mortality. CONCLUSION: Despite a considerable reduction in the surgical activity for elective digestive resections during the lockdown period, mortality remained stable on a nationwide scale in COVID-free patients. These findings support that systematic COVID-19 screening should be advocated before elective gastrointestinal surgery and that all efforts should be made to maintain elective surgical resection for cancer during the second wave in COVID-free patients.