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Background: People with multiple sclerosis (MS) are a vulnerable group for severe COVID-19, particularly those taking immunosuppressive disease-modifying therapies (DMTs). We examined the characteristics of COVID-19 severity in an international sample of people with MS. Methods: Data from 12 data-sources in 28 countries were aggregated. Demographic and clinical covariates were queried, alongside COVID-19 clinical severity outcomes, hospitalisation, admission to ICU, requiring artificial ventilation, and death. Characteristics of outcomes were assessed in patients with suspected/confirmed COVID-19 using multilevel mixed-effects logistic regression. Results: 657 (28.1%) with suspected and 1,683 (61.9%) with confirmed COVID-19 were analysed. Older age, progressive MS-phenotype, and higher disability were associated with worse COVID-19 outcomes. Compared to dimethyl fumarate, ocrelizumab and rituximab were associated with hospitalisation (aOR=1.56,95%CI=1.01-2.41; aOR=2.43,95%CI=1.48-4.02) and ICU admission (aOR=2.30,95%CI=0.98-5.39; aOR=3.93,95%CI=1.56-9.89), though only rituximab was associated with higher risk of artificial ventilation (aOR=4.00,95%CI=1.54-10.39). Compared to pooled other DMTs, ocrelizumab and rituximab were associated with hospitalisation (aOR=1.75,95%CI=1.29-2.38; aOR=2.76,95%CI=1.87-4.07) and ICU admission (aOR=2.55,95%CI=1.49-4.36; aOR=4.32,95%CI=2.27-8.23) but only rituximab with artificial ventilation (aOR=6.15,95%CI=3.09-12.27). Compared to natalizumab, ocrelizumab and rituximab were associated with hospitalisation (aOR=1.86,95%CI=1.13-3.07; aOR=2.88,95%CI=1.68-4.92) and ICU admission (aOR=2.13,95%CI=0.85-5.35; aOR=3.23,95%CI=1.17-8.91), but only rituximab with ventilation (aOR=5.52,95%CI=1.71-17.84). Importantly, associations persisted on restriction to confirmed COVID-19 cases. No associations were observed between DMTs and death. Conclusions: Using the largest cohort of people with MS and COVID-19 available, we demonstrated consistent associations of rituximab with increased risk of hospitalisation, ICU admission, and requiring artificial ventilation, and ocrelizumab with hospitalisation and ICU admission, suggesting their use may be a risk factor for more severe COVID-19.
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PurposeSARS-CoV-2 infects cells via the human Angiotensin-converting enzyme 2 (ACE2) protein. The genetic variation of ACE2 function and expression across populations is still poorly understood. This study aims at better understanding the genetic basis of COVID-19 outcomes by studying association between genetic variation in ACE2 and disease severity in the Iranian population. MethodsWe analyzed two large Iranian cohorts and several publicly available human population variant databases to identify novel and previously known ACE2 exonic variants present in the Iranian population and considered those as candidate variants for association between genetic variation and disease severity. We genotyped these variants across three groups of COVID-19 patients with different clinical outcomes (mild disease, severe disease, and death) and evaluated this genetic variation with regard to clinical outcomes. ResultsWe identified 32 exonic variants present in Iranian cohorts or other public variant databases. Among those, 11 variants are novel and have thus not been described in other populations previously. Following genotyping of these 32 candidate variants, only the synonymous polymorphism (c.2247G>A) was detected across the three groups of COVID-19 patients. ConclusionGenetic variability of known and novel exonic variants was low among our COVID-19 patients. Our results do not provide support for the hypothesis that exonic variation in ACE2 has a sizeable impact on COVID-19 severity across the Iranian population.
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The current COVID-19 pandemic led to the rapid overload of Intensive Care Units (ICUs) in countries where the outbreaks was not quickly controlled. The containment measures put in place to control the outbreaks had a huge social and economic impacts, and countries are looking for strategies to relax these measures while maintaining the R0 close or below 1, in an attempt to safely reach herd immunity. In this paper we analyse the feasibility of reaching herd immunity without saturating ICUs across countries. We provide an online tool, available at www.about-the-curve.net that simulates the time required for such a scenario with a SIR model. For United States, we find that a minimum of 5 months would be required, 22 months for UK, 1 year for Italy and 9 months for Belgium. DisclaimerThe presented results are preliminary and have not been peer-reviewed.
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On March 11, 2020, the World Health Organization declared the COVID-19 outbreak, originally started in China, a global pandemic. Since then, the outbreak has indeed spread across all continents, threatening the public health of numerous countries. Although the Case Fatality Rate (CFR) of COVID-19 is relatively low when optimal level of healthcare is granted to the patients, the high percentage of severe cases developing severe pneumonia and thus requiring respiratory support is worryingly high, and could lead to a rapid saturation of Intensive Care Units (ICUs). To overcome this risk, most countries enacted COVID-19 containment measures. In this study, we use a Bayesian SEIR epidemiological model to perform a parametric regression over the COVID-19 outbreaks data in China, Italy, Belgium, and Spain, and estimate the effect of the containment measures on the basic reproduction ratio R0. We find that the effect of these measures is detectable, but tends to be gradual, and that a progressive strengthening of these measures usually reduces the R0 below 1, granting a decay of the outbreak. We also discuss the biases and inconsistencies present in the publicly available data on COVID-19 cases, providing an estimate for the actual number of cases in Italy on March 12, 2020. Lastly, despite the data and models limitations, we argue that the idea of "flattening the curve" to reach herd immunity is likely to be unfeasible.
