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Abstract Background Attrition in cohort studies challenges causal inference. Although inverse probability weighting (IPW) has been proposed to handle attrition in association analyses, its relevance has been little studied in this context. We aimed to investigate its ability to correct for selection bias in exposure-outcome estimation by addressing an important methodological issue: the specification of the response model. Methods A simulation study compared the IPW method with complete-case analysis (CCA) for nine response-mechanism scenarios (3 missing at random – MAR and 6 missing not at random - MNAR). Eighteen response models differing by the type of variables included were assessed. Results The IPW method was equivalent to CCA in terms of bias and consistently less efficient in all scenarios, regardless of the response model tested. The most effective response model included only the confounding factors of the association model. Conclusion Our study questions the ability of the IPW method to correct for selection bias in situations of attrition leading to missing outcomes. If the method is to be used, we encourage including only the confounding variables of the association of interest in the response model.

Background: Attrition in cohort studies challenges causal inference. Although inverse probability weighting (IPW) has been proposed to handle attrition in association analyses, its relevance has been little studied in this context. We aimed to investigate its ability to correct for selection bias in exposure-outcome estimation by addressing an important methodological issue: the specification of the response model.Methods: A simulation study compared the IPW method with complete-case analysis (CCA) for nine response-mechanism scenarios (3 missing at random - MAR and 6 missing not at random - MNAR). Eighteen response models differing by the type of variables included were assessed.Results: The IPW method was equivalent to CCA in terms of bias and consistently less efficient in all scenarios, regardless of the response model tested. The most effective response model included only the confounding factors of the association model.Conclusion: Our study questions the ability of the IPW method to correct for selection bias in situations of attrition leading to missing outcomes. If the method is to be used, we encourage including only the confounding variables of the association of interest in the response model. [ABSTRACT FROM AUTHOR]

Background: The French syndromic surveillance (SyS) system, SurSaUD®, was one of the systems used to monitor the COVID-19 outbreak. Aim: This study described the epidemiological characteristics of COVID-19-related visits to both emergency departments (EDs) and the network of emergency general practitioners known as SOS Médecins (SOSMed) in France from 17 February to 28 June 2020. Methods: Data on all visits to 634 EDs and 60 SOSMed associations were collected daily. COVID-19-related visits were identified using ICD-10 codes after coding recommendations were sent to all ED and SOSMed doctors. The time course of COVID-19-related visits was described by age group and region. During the lockdown period, the characteristics of ED and SOSMed visits and hospitalisations after visits were described by age group and gender. The most frequent diagnoses associated with COVID-19-related visits were analysed. Results: COVID-19 SyS was implemented on 29 February and 4 March for EDs and SOSMed, respectively. A total of 170,113 ED and 59,087 SOSMed visits relating to COVID-19 were recorded, representing 4.0% and 5.6% of the overall coded activity with a peak in late March representing 22.5% and 25% of all ED and SOSMed visits, respectively. COVID-19-related visits were most frequently reported for women and those aged 15–64 years, although patients who were subsequently hospitalised were more often men and persons aged 65 years and older. Conclusion: SyS allowed for population health monitoring of the COVID-19 epidemic in France. As SyS has more than 15 years of historical data with high quality and reliability, it was considered sufficiently robust to contribute to defining the post-lockdown strategy. [ABSTRACT FROM AUTHOR]