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1.
Preprint in English | medRxiv | ID: ppmedrxiv-22278458

ABSTRACT

The direct and indirect impact of the COVID-19 pandemic on population-level mortality is of concern to public health but challenging to quantify. We modelled excess mortality and the direct and indirect effects of the pandemic on mortality in Switzerland. We analyzed yearly population data and weekly all-cause deaths by age, sex, and canton 2010-2019 and all-cause and laboratory-confirmed COVID-19 deaths from February 2020 to April 2022 (study period). Bayesian models predicted the expected number of deaths. A total of 13,130 laboratory-confirmed COVID-19 deaths were reported. The model estimated that COVID-19-related mortality was underestimated by a factor of 0.72 [95% Credible Interval: 0.46-0.78] resulting in 18,140 [15,962-20,174] excess deaths. After accounting for COVID-19 deaths, the observed mortality was 3% [-1-7] lower than expected, corresponding to a deficit of 4,406 deaths, with a wide credibility interval [-1,776-10,700]. Underestimation of COVID-19 deaths was greatest for ages 70 years and older; the mortality deficit was most pronounced in age groups 40 to 69 years. We conclude that shortcomings in testing caused underestimation of COVID-19-related deaths in Switzerland, particularly in older people. Although COVID-19 control measures may have negative effects (e.g., delays in seeking care or mental health impairments), after subtracting COVID-19 deaths, there were fewer deaths in Switzerland during the pandemic than expected, suggesting that any negative effects of control measures on mortality were offset by the positive effects. These results have important implications for the ongoing debate about the appropriateness of COVID-19 control measures.

2.
Preprint in English | medRxiv | ID: ppmedrxiv-22269581

ABSTRACT

BACKGROUNDDebate about the level of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection continues. The amount of evidence is increasing and study designs have changed over time. We updated a living systematic review to address three questions: (1) Amongst people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? (2) What is the infectiousness of asymptomatic and presymptomatic, compared with symptomatic, SARS-CoV-2 infection? (3) What proportion of SARS-CoV-2 transmission in a population is accounted for by people who are asymptomatic or presymptomatic? METHODS AND FINDINGSThe protocol was first published on 1 April 2020 and last updated on 18 June 2021. We searched PubMed, Embase, bioRxiv and medRxiv, aggregated in a database of SARS-CoV-2 literature, most recently on 6 July 2021. Studies of people with PCR-diagnosed SARS-CoV-2, which documented symptom status at the beginning and end of follow-up, or mathematical modelling studies were included. Studies restricted to people already diagnosed, of single individuals or families, or without sufficient follow-up were excluded. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with a bespoke checklist and modelling studies with a published checklist. All data syntheses were done using random effects models. Review question (1): We included 130 studies. Heterogeneity was high so we did not estimate a mean proportion of asymptomatic infections overall (interquartile range 14-50%, prediction interval 2-90%), or in 84 studies based on screening of defined populations (interquartile range 20-65%, prediction interval 4-94%). In 46 studies based on contact or outbreak investigations, the summary proportion asymptomatic was 19% (95% CI 15-25%, prediction interval 2-70%). (2) The secondary attack rate in contacts of people with asymptomatic infection compared with symptomatic infection was 0.32 (95% CI 0.16-0.64, prediction interval 0.11-0-95, 8 studies). (3) In 13 modelling studies fit to data, the proportion of all SARS-CoV-2 transmission from presymptomatic individuals was higher than from asymptomatic individuals. Limitations of the evidence include high heterogeneity and high risks of selection and information bias in studies that were not designed to measure persistently asymptomatic infection, and limited information about variants of concern or in people who have been vaccinated. CONCLUSIONSBased on studies published up to July 2021, most SARS-CoV-2 infections were not persistently asymptomatic and asymptomatic infections were less infectious than symptomatic infections. Summary estimates from meta-analysis may be misleading when variability between studies is extreme and prediction intervals should be presented. Future studies should determine the asymptomatic proportion of SARS-CoV-2 infections caused by variants of concern and in people with immunity following vaccination or previous infection. Without prospective longitudinal studies with methods that minimise selection and measurement biases, further updates with the study types included in this living systematic review are unlikely to be able to provide a reliable summary estimate of the proportion of asymptomatic infections caused by SARS-CoV-2. REVIEW PROTOCOLOpen Science Framework (https://osf.io/9ewys/) AUTHOR SUMMARYO_ST_ABSWhy was this study done?C_ST_ABS{blacksquare} The proportion of people who will remain asymptomatic throughout the course of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (covid-19), is debated. {blacksquare}Studies that assess people at just one time point overestimate the proportion of true asymptomatic infection because those who go on to develop covid-19 symptoms will be wrongly classified as asymptomatic, but other types of study might underestimate the proportion if, for example, people with symptoms are more likely to be included in a study population. {blacksquare}The number of published studies about SARS-CoV-2 is increasing continuously, types of studies are changing and, since 2021, vaccines have become available, and variants of concern have emerged. What did the researchers do and find?{blacksquare} We updated a living systematic review through 6 July 2021, using automated workflows that speed up the review processes, and allow the review to be updated when relevant new evidence becomes available. {blacksquare}In 130 studies, we found an interquartile range of 14-50% (prediction interval 2-90%) of people with SARS-CoV-2 infection that was persistently asymptomatic; owing to heterogeneity, we did not estimate a summary proportion. {blacksquare}Contacts of people with asymptomatic SARS-CoV-2 infection are less likely to become infected than contacts of people with symptomatic infection (risk ratio 0.38, 95% CI 0.16-0.64, prediction interval 0.11-0.95, 8 studies). What do these findings mean?O_LI{blacksquare} Up to mid-2021, most people with SARS-CoV-2 were not persistently asymptomatic and asymptomatic infection was less infectious than symptomatic infection. C_LIO_LI{blacksquare} In the presence of high between-study variability, summary estimates from meta-analysis may be misleading and prediction intervals should be presented. C_LIO_LI{blacksquare} Future studies about asymptomatic SARS-CoV-2 infections caused by variants of concern and in people with immunity following vaccination or previous infection should be specifically designed, using methods to minimise biases in the selection of study participants and in ascertainment, classification and follow-up of symptom status. C_LI

3.
Preprint in English | medRxiv | ID: ppmedrxiv-21267513

ABSTRACT

Neutralizing antibodies are considered a key correlate of protection by current SARS-CoV-2 vaccines. The ability of antibody-based therapies, including convalescent plasma, to affect established disease remains to be elucidated. Only few monoclonal therapies and only when used at a very early stage of infection have shown efficacy. Here, we conducted a proof-of-principle study of convalescent plasma therapy in a phase I trial in 30 COVID-19 patients including immunocompromised individuals hospitalized early after onset of symptoms. A comprehensive longitudinal monitoring of the virologic, serologic, and disease status of recipients in conjunction with detailed post-hoc seroprofiling of transfused convalescent plasma, allowed deciphering of parameters on which plasma therapy efficacy depends. Plasma therapy was safe and had a significant effect on viral clearance depending on neutralizing and spike SARS-CoV-2 antibody levels in the supplied convalescent plasma. Endogenous immunity had strong effects on virus control. Lack of endogenous neutralizing activity at baseline was associated with a higher risk of systemic viremia. The onset of endogenous neutralization had a noticeable effect on viral clearance but, importantly, even after adjusting for their endogenous neutralization status recipients benefitted from therapy with high neutralizing antibody containing plasma. In summary, our data demonstrate a clear impact of exogenous antibody therapy on the rapid clearance of viremia in the early stages of infection and provide directions for improved efficacy evaluation of current and future SARS-CoV-2 therapies beyond antibody-based interventions. Incorporating an assessment of the endogenous immune response and its dynamic interplay with viral production is critical for determining therapeutic effects. One Sentence SummaryThis study demonstrates the impact of exogenous antibody therapy by convalescent plasma containing high neutralizing titers on the rapid clearance of viremia in the early stages of SARS-CoV-2 infection.

4.
Preprint in English | medRxiv | ID: ppmedrxiv-20158014

ABSTRACT

AIMIn late February and early March 2020, Switzerland experienced rapid growth of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections with 30,243 confirmed cases and 1,860 deaths as of 10 May 2020. The sequential introduction of non-pharmaceutical interventions (NPIs) resulted in successful containment of the epidemic. A better understanding of how the timing of implementing NPIs influences the dynamics and outcome of SARS-CoV-2 epidemics will be crucial for the management of a potential resurgence in Switzerland. METHODSWe developed a dynamic transmission model that describes infection, hospitalization, recovery and death due to SARS-CoV-2 in Switzerland. Using a maximum likelihood framework, we fitted the model to aggregated daily numbers of hospitalized patients, ICU occupancy and death from 25 February to 10 May 2020. We estimated critical parameters of SARS-CoV-2 transmission in Switzerland and explored counterfactual scenarios of an earlier and later implementation of NPIs. RESULTSWe estimated the basic reproduction number R0 = 2.61 (95% compatibility interval, CI: 2.51-2.71) during the early exponential phase of the SARS-CoV-2 epidemic in Switzerland. After the implementation of NPIs, the effective reproduction number approached Re = 0.64 (95% CI: 0.61-0.66). Based on the observed doubling times of the epidemic before and after the implementation of NPIs, we estimated that one week of early exponential spread required 3.1 weeks (95% CI: 2.8-3.3 weeks) of lockdown to reduce the number of infections to the same level. Introducing the same sequence of NPIs one week earlier or later would have resulted in substantially lower (399, 95% prediction interval, PI: 347-458) and higher (8,683, 95% PI: 8,038-9,453) numbers of deaths, respectively. CONCLUSIONSThe introduction of NPIs in March 2020 prevented thousands of SARS-CoV-2-related deaths in Switzerland. Early implementation of NPIs during SARS-CoV-2 outbreaks can reduce the number of deaths and the necessary duration of strict control measures considerably.

5.
Preprint in English | medRxiv | ID: ppmedrxiv-20129213

ABSTRACT

AO_SCPLOWBSTRACTC_SCPLOWA key parameter in epidemiological modeling which characterizes the spread of an infectious disease is the mean serial interval. There is increasing evidence supporting a prolonged viral shedding window for COVID-19, but the transmissibility in this phase is unclear. Based on this, we build a model including an additional compartment of infectious individuals who stay infectious for a longer duration than the reported serial interval, but with infectivity reduced to varying degrees. We find that such an assumption also yields a plausible model in explaining the data observed so far, but has different implications for the future predictions in case of a gradual easing on the lockdown measures. Considering the role of modeling in important decisions such as easing lockdown measures and adjusting hospital capacity, we believe that it is critically important to consider a chronically infectious population as an alternative modeling approach to better interpret the transmission dynamics of COVID-19.

6.
Preprint in English | medRxiv | ID: ppmedrxiv-20031104

ABSTRACT

BackgroundAs of 16 May 2020, more than 4.5 million cases and more than 300,000 deaths from disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported. Reliable estimates of mortality from SARS-CoV-2 infection are essential to understand clinical prognosis, plan health care capacity and for epidemic forecasting. The case fatality ratio (CFR), calculated from total numbers of reported cases and reported deaths, is the most commonly reported metric, but can be a misleading measure of overall mortality. The objectives of this study were to: 1) simulate the transmission dynamics of SARS-CoV-2 using publicly available surveillance data; 2) infer estimates of SARS-CoV-2 mortality adjusted for biases and examine the CFR, the symptomatic case fatality ratio (sCFR) and the infection fatality ratio (IFR) in different geographic locations. Method and FindingsWe developed an age-stratified susceptible-exposed-infected-removed (SEIR) compartmental model describing the dynamics of transmission and mortality during the SARS-CoV-2 epidemic. Our model accounts for two biases: preferential ascertainment of severe cases and right-censoring of mortality. We fitted the transmission model to surveillance data from Hubei province, China and applied the same model to six regions in Europe: Austria, Bavaria (Germany), Baden-Wurttemberg (Germany), Lombardy (Italy), Spain and Switzerland. In Hubei, the baseline estimates were: CFR 2.4% (95% credible interval [CrI]: 2.1-2.8%), sCFR 3.7% (3.2-4.2%) and IFR 2.9% (2.4-3.5%). Estimated measures of mortality changed over time. Across the six locations in Europe estimates of CFR varied widely. Estimates of sCFR and IFR, adjusted for bias, were more similar to each other but still showed some degree of heterogeneity. Estimates of IFR ranged from 0.5% (95% CrI 0.4-0.6%) in Switzerland to 1.4% (1.1-1.6%) in Lombardy, Italy. In all locations, mortality increased with age. Among 80+ year olds, estimates of the IFR suggest that the proportion of all those infected with SARS-CoV-2 who will die ranges from 20% (95% CrI: 16-26%) in Switzerland to 34% (95% CrI: 28-40%) in Spain. A limitation of the model is that count data by date of onset are required and these are not available in all countries. ConclusionsWe propose a comprehensive solution to the estimation of SARS-Cov-2 mortality from surveillance data during outbreaks. The CFR is not a good predictor of overall mortality from SARS-CoV-2 and should not be used for evaluation of policy or comparison across settings. Geographic differences in IFR suggest that a single IFR should not be applied to all settings to estimate the total size of the SARS-CoV-2 epidemic in different countries. The sCFR and IFR, adjusted for right-censoring and preferential ascertainment of severe cases, are measures that can be used to improve and monitor clinical and public health strategies to reduce the deaths from SARS-CoV-2 infection. Author summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIReliable estimates of measures of mortality from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are needed to understand clinical prognosis, plan health care capacity and for epidemic forecasting. C_LIO_LIThe case fatality ratio (CFR), the number of reported deaths divided by the number of reported cases at a specific time point, is the most commonly used metric, but is a biased measure of mortality from SARS-CoV-2 infection. C_LIO_LIThe symptomatic case fatality ratio (sCFR) and overall infection fatality ratio (IFR) are alternative measures of mortality with clinical and public health relevance, which should be investigated further in different geographic locations. C_LI What did the researchers do and find?O_LIWe developed a mathematical model that describes infection transmission and death during a SARS-CoV-2 epidemic. The model takes into account the delay between infection and death and preferential ascertainment of disease in people with severe symptoms, both of which affect the assessment of mortality. C_LIO_LIWe applied the model to data from Hubei province in China, which was the first place affected by SARS-CoV-2, and to six locations in Europe: Austria, Bavaria (Germany), Baden-Wurttemberg (Germany), Lombardy (Italy), Spain and Switzerland, to estimate the CFR, the sCFR and the IFR. C_LIO_LIEstimates of sCFR and IFR, adjusted for bias, were similar to each other and varied less geographically than the CFR. IFR was lowest in Switzerland (0.5%) and highest in Hubei province (2.9%). The IFR increased with age; among 80+ year olds, estimates ranged from 20% in Switzerland to 34% in Spain. C_LI What do these findings mean?O_LIThe CFR does not predict overall mortality from SARS-CoV-2 infection well and should not be used for the evaluation of policy or for making comparisons between geographic locations. C_LIO_LIThere are geographic differences in the IFR of SARS-CoV-2, which could result from differences in factors including emergency preparedness and response, and health service capacity. C_LIO_LISARS-CoV-2 infection results in substantial mortality. Further studies should investigate ways to reduce death from SARS-CoV-2 in older people and to understand the causes of the differences between countries. C_LI

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