Direct and indirect effects of the COVID-19 pandemic on mortality in Switzerland: A population-based study

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.

Continued Emergence and Evolution of Omicron in South Africa: New BA.4 and BA.5 lineages

South Africas fourth COVID-19 wave was driven predominantly by three lineages (BA.1, BA.2 and BA.3) of the SARS-CoV-2 Omicron variant of concern. We have now identified two new lineages, BA.4 and BA.5. The spike proteins of BA.4 and BA.5 are identical, and comparable to BA.2 except for the addition of 69-70del, L452R, F486V and the wild type amino acid at Q493. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure with the TaqPath COVID-19 qPCR assay. BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa from the first week of April 2022 onwards. Using a multinomial logistic regression model, we estimate growth advantages for BA.4 and BA.5 of 0.08 (95% CI: 0.07 - 0.09) and 0.12 (95% CI: 0.09 - 0.15) per day respectively over BA.2 in South Africa.

Replacement of the Gamma by the Delta variant in Brazil: impact of lineage displacement on the ongoing pandemic

The COVID-19 epidemic in Brazil was driven mainly by the spread of Gamma (P.1), a locally emerged Variant of Concern (VOC) that was first detected in early January 2021. This variant was estimated to be responsible for more than 96% of cases reported between January and June 2021, being associated with increased transmissibility and disease severity, a reduction in neutralization antibodies and effectiveness of treatments or vaccines, as well as diagnostic detection failure. Here we show that, following several importations predominantly from the USA, the Delta variant rapidly replaced Gamma after July 2021. However, in contrast to what was seen in other countries, the rapid spread of Delta did not lead to a large increase in the number of cases and deaths reported in Brazil. We suggest that this was likely due to the relatively successful early vaccination campaign coupled with natural immunity acquired following prior infection with Gamma. Our data reinforces reports of the increased transmissibility of the Delta variant and, considering the increasing concern due to the recently identified Omicron variant, argues for the necessity to strengthen genomic monitoring on a national level to quickly detect and curb the emergence and spread of other VOCs that might threaten global health.

Quantification of the spread of SARS-CoV-2 variant B.1.1.7 in Switzerland

BackgroundIn December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now named B.1.1.7. Based on initial data from the UK and later data from other countries, this variant was estimated to have a transmission fitness advantage of around 40-80% [1, 2, 3]. AimThis study aims to estimate the transmission fitness advantage and the effective reproductive number of B.1.1.7 through time based on data from Switzerland. MethodsWe generated whole genome sequences from 11.8% of all confirmed SARS-CoV-2 cases in Switzerland between 14 December 2020 and 11 March 2021. Based on these data, we determine the daily frequency of the B.1.1.7 variant and quantify the variants transmission fitness advantage on a national and a regional scale. ResultsWe estimate B.1.1.7 had a transmission fitness advantage of 43-52% compared to the other variants circulating in Switzerland during the study period. Further, we estimate B.1.1.7 had a reproductive number above 1 from 01 January 2021 until the end of the study period, compared to below 1 for the other variants. Specifically, we estimate the reproductive number for B.1.1.7 was 1.24 [1.07-1.41] from 01 January until 17 January 2021 and 1.18 [1.06-1.30] from 18 January until 01 March 2021 based on the whole genome sequencing data. From 10 March to 16 March 2021, once B.1.1.7 was dominant, we estimate the reproductive number was 1.14 [1.00-1.26] based on all confirmed cases. For reference, Switzerland applied more non-pharmaceutical interventions to combat SARS-CoV-2 on 18 January 2021 and lifted some measures again on 01 March 2021. ConclusionThe observed increase in B.1.1.7 frequency in Switzerland during the study period is as expected based on observations in the UK. In absolute numbers, B.1.1.7 increased exponentially with an estimated doubling time of around 2-3.5 weeks. To monitor the ongoing spread of B.1.1.7, our plots are available online.

The role of the SwissCovid digital contact tracing app during the pandemic response: results for the Canton of Zurich

ImportanceDigital proximity tracing (DPT) apps were released in several countries to help interrupt SARS-CoV-2 transmission chains in the population. However, the impact of DPT on pandemic mitigation still remains to be demonstrated. ObjectiveTo estimate key populations and performance indicators along the DPT app notification cascade in a clearly defined regional (Canton of Zurich, using all of Switzerland as a comparison) and temporal context (September/October 2020). DesignPublicly available administrative and research data, including key DPT performance indicators, SARS-CoV-2 testing statistics, infoline call statistics, and observational study data, were compiled. A model of the DPT notification cascade was developed and key performance indicators for DPT processes were defined. Subpopulation sizes at each cascade step were estimated using data triangulation. Resulting estimates were systematically checked for internal consistency and consistency with other up- or downstream estimates in the cascade. Stochastic simulations were performed to explore robustness of results. ResultsFor the Canton of Zurich, we estimate that 537 app users received a positive SARS-CoV-2 test in September 2020, of whom 324 received and entered a CovidCode. This triggered an app notification for an estimated 1374 proximity contacts and led to 722 infoline calls. In total, 170 callers received a quarantine recommendation, and 30 app users tested positive for SARS-CoV-2 after an app notification, reflecting a performance above the national level. Based on this quantification, key performance indicators were evaluated. For September 2020, these analyses suggest that SwissCovid triggered quarantine recommendations in the equivalent of 5% of all exposed contacts placed in quarantine by manual contact tracing. Per 11 CovidCodes entered in the app, we estimate that almost 1 contact tested positive for SARS-CoV-2 upon app notification. However, longitudinal indicator analyses demonstrate bottlenecks in the notification cascade, as capacity limits were reached due to large increases in SARS-CoV-2 incidence in October 2020. ConclusionAlthough requiring confirmation, our estimations on the number of notified proximity contacts receiving quarantine recommendations or testing positive after notification suggest relevant contributions to mitigating the pandemic. Increasing SwissCovid app uptake and improving notification cascade performance may further enhance its impact. Key pointsO_ST_ABSQuestionC_ST_ABSWhat is the real-life impact of Digital proximity tracing (DPT) apps on interrupting SARS-CoV-2 transmission chains? FindingsThis data-informed simulation study found that, in the canton of Zurich, the number of app notified persons receiving a quarantine recommendation corresponds to the equivalent of up to 5% of all mandatory quarantined contacts identified by manual contact tracing. Furthermore, about 1 in 11 notification triggers led to SARS-CoV-2 testing of an exposed proximity contact who was consecutively tested positive. MeaningDPT apps exert a measurable impact that will further scale as more persons use the apps.

Quantifying superspreading for COVID-19 using Poisson mixture distributions

The number of secondary cases is an important parameter for the control of infectious diseases. When individual variation in disease transmission is present, like for COVID-19, the number of secondary cases is often modelled using a negative binomial distribution. However, this may not be the best distribution to describe the underlying transmission process. We propose the use of three other offspring distributions to quantify heterogeneity in transmission, and we assess the possible bias in estimates of the offspring mean and its overdispersion when the data generating distribution is different from the one used for inference. We find that overdispersion estimates may be biased when there is a substantial amount of heterogeneity, and that the use of other distributions besides the negative binomial should be considered. We revisit three previously analysed COVID-19 datasets and quantify the proportion of cases responsible for 80% of transmission, p80%, while acknowledging the variation arising from the assumed offspring distribution. We find that the number of secondary cases for these datasets is better described by a Poisson-lognormal distribution.

Emergence and spread of a SARS-CoV-2 variant through Europe in the summer of 2020

Following its emergence in late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic resulting in unprecedented efforts to reduce transmission and develop therapies and vaccines (WHO Emergency Committee, 2020; Zhu et al., 2020). Rapidly generated viral genome sequences have allowed the spread of the virus to be tracked via phylogenetic analysis (Worobey et al., 2020; Hadfield et al., 2018; Pybus et al., 2020). While the virus spread globally in early 2020 before borders closed, intercontinental travel has since been greatly reduced, allowing continent-specific variants to emerge. However, within Europe travel resumed in the summer of 2020, and the impact of this travel on the epidemic is not well understood. Here we report on a novel SARS-CoV-2 variant, 20E (EU1), that emerged in Spain in early summer, and subsequently spread to multiple locations in Europe. We find no evidence of increased transmissibility of this variant, but instead demonstrate how rising incidence in Spain, resumption of travel across Europe, and lack of effective screening and containment may explain the variants success. Despite travel restrictions and quarantine requirements, we estimate 20E (EU1) was introduced hundreds of times to countries across Europe by summertime travellers, likely undermining local efforts to keep SARS-CoV-2 cases low. Our results demonstrate how a variant can rapidly become dominant even in absence of a substantial transmission advantage in favorable epidemiological settings. Genomic surveillance is critical to understanding how travel can impact SARS-CoV-2 transmission, and thus for informing future containment strategies as travel resumes. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the first pandemic where the spread of a viral pathogen has been globally tracked in near real-time using phylogenetic analysis of viral genome sequences (Worobey et al., 2020; Hadfield et al., 2018; Pybus et al., 2020). SARS-CoV-2 genomes continue to be generated at a rate far greater than for any other pathogen and more than 500,000 full genomes are available on GISAID as of February 2020 (Shu and McCauley, 2017). In addition to tracking the viral spread, these genome sequences have been used to monitor mutations which might change the transmission, pathogenesis, or anti-genic properties of the virus. One mutation in particular, D614G in the spike protein, has received much attention. This variant (Nextstrain clade 20A) seeded large outbreaks in Europe in early 2020 and subsequently dominated the outbreaks in the Americas, thereby largely replacing previously circulating lineages. This rapid rise led to the suggestion that this variant is more transmissible, which has since been corroborated by phylogenetic (Korber et al., 2020; Volz et al., 2020) and experimental evidence (Plante et al., 2020; Yurkovetskiy et al., 2020). Following the global dissemination of SARS-CoV-2 in early 2020 (Worobey et al., 2020), intercontinental travel dropped dramatically. Within Europe, however, travel and in particular holiday travel resumed in summer (though at lower levels than in previous years) with largely uncharacterized effects on the pandemic. Here we report on a novel SARS-CoV-2 variant 20E (EU1) (S:A222V) that emerged in early summer 2020, presumably in Spain, and subsequently spread to multiple locations in Europe. Over the summer, it rose in frequency in parallel in multiple countries. As we report here, this variant, 20E (EU1), and a second variant 20A.EU2 with mutation S477N in the spike protein accounted for the majority of sequences in Europe in the autumn of 2020.

Early Evidence of Effectiveness of Digital Contact Tracing for SARS-CoV-2 in Switzerland

In the wake of the pandemic of coronavirus disease 2019 (COVID-19), contact tracing has become a key element of strategies to control the spread of severe acute respiratory syndrome coronavirus 2019 (SARS-CoV-2). Given the rapid and intense spread of SARS-CoV-2, digital contact tracing has emerged as a potential complementary tool to support containment and mitigation efforts. Early modelling studies highlighted the potential of digital contact tracing to break transmission chains, and Google and Apple subsequently developed the Exposure Notification (EN) framework, making it available to the vast majority of smartphones. A growing number of governments have launched or announced EN-based contact tracing apps, but their effectiveness remains unknown. Here, we report early findings of the digital contact tracing app deployment in Switzerland. We demonstrate proof-of-principle that digital contact tracing reaches exposed contacts, who then test positive for SARS-CoV-2. This indicates that digital contact tracing is an effective complementary tool for controlling the spread of SARS-CoV-2. Continued technical improvement and international compatibility can further increase the efficacy, particularly also across country borders.

Time is of the essence: containment of the SARS-CoV-2 epidemic in Switzerland from February to May 2020

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.

Population-wide evolution of SARS-CoV-2 immunity tracked by a ternary immunoassay

Effective public-health measures and vaccination campaigns against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against the ectodomain and the receptor-binding domain of the spike protein as well as the nucleocapsid protein of SARS-CoV-2. We used TRABI for continuous seromonitoring of hospital patients and healthy blood donors (n=72222) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). Seroprevalence peaked in May 2020 and rose again in November 2020 in both cohorts. Validations of results included antibody diffusional sizing and Western Blotting. Using an extended Susceptible-Exposed-Infectious-Removed model, we found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020 in the population of the canton of Zurich. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19 and up to the timepoint of survey participation. Crucially, we found no evidence for a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2- infected subjects represents a resource for the study of chronic and possibly unexpected sequelae.

Adjusted age-specific case fatality ratio during the COVID-19 epidemic in Hubei, China, January and February 2020

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

Pattern of early human-to-human transmission of Wuhan 2019-nCoV

On December 31, 2019, the World Health Organization was notified about a cluster of pneumonia of unknown aetiology in the city of Wuhan, China. Chinese authorities later identified a new coronavirus (2019-nCoV) as the causative agent of the outbreak. As of January 23, 2020, 655 cases have been confirmed in China and several other countries. Understanding the transmission characteristics and the potential for sustained human-to-human transmission of 2019-nCoV is critically important for coordinating current screening and containment strategies, and determining whether the outbreak constitutes a public health emergency of international concern (PHEIC). We performed stochastic simulations of early outbreak trajectories that are consistent with the epidemiological findings to date. We found the basic reproduction number, R0, to be around 2.2 (90% high density interval 1.4--3.8), indicating the potential for sustained human-to-human transmission. Transmission characteristics appear to be of a similar magnitude to severe acute respiratory syndrome-related coronavirus (SARS-CoV) and the 1918 pandemic influenza. These findings underline the importance of heightened screening, surveillance and control efforts, particularly at airports and other travel hubs, in order to prevent further international spread of 2019-nCoV.