Immune Heterogeneity and Epistasis Explain Punctuated Evolution of SARS-CoV-2

Identifying drivers of viral diversity is key to understanding the evolutionary as well as epidemiological dynamics of the COVID-19 pandemic. Using rich viral genomic data sets, we show that periods of steadily rising diversity have been punctuated by sudden, enormous increases followed by similarly abrupt collapses of diversity. We introduce a mechanistic model of saltational evolution with epistasis and demonstrate that these features parsimoniously account for the observed temporal dynamics of inter-genomic diversity. Our results provide support for recent proposals that saltational evolution may be a signature feature of SARS-CoV-2, allowing the pathogen to more readily evolve highly transmissible variants. These findings lend theoretical support to a heightened awareness of biological contexts where increased diversification may occur. They also underline the power of pathogen genomics and other surveillance streams in clarifying the phylodynamics of emerging and endemic infections. In public health terms, our results further underline the importance of equitable distribution of up-to-date vaccines.

Direct and indirect mortality impacts of the COVID-19 pandemic in the US, March 2020-April 2021

Excess mortality studies provide crucial information regarding the health burden of pandemics and other large-scale events. Here, we used time series approaches to separate the direct contribution of SARS-CoV-2 infections on mortality from the indirect consequences of pandemic interventions and behavior changes in the United States. We estimated deaths occurring in excess of seasonal baselines stratified by state, age, week and cause (all causes, COVID-19 and respiratory diseases, Alzheimers disease, cancer, cerebrovascular disease, diabetes, heart disease, and external causes, including suicides, opioids, accidents) from March 1, 2020 to April 30, 2021. Our estimates of COVID-19 excess deaths were highly correlated with SARS-CoV-2 serology, lending support to our approach. Over the study period, we estimate an excess of 666,000 (95% Confidence Interval (CI) 556000, 774000) all-cause deaths, of which 90% could be attributed to the direct impact of SARS-CoV-2 infection, and 78% were reflected in official COVID-19 statistics. Mortality from all disease conditions rose during the pandemic, except for cancer. The largest direct impacts of the pandemic were seen in mortality from diabetes, Alzheimers, and heart diseases, and in age groups over 65 years. In contrast, the largest indirect consequences of the pandemic were seen in deaths from external causes, which increased by 45,300 (95% CI 30,800, 59,500) and were statistically linked to the intensity of non-pharmaceutical interventions. Within this category, increases were most pronounced in mortality from accidents and injuries, drug overdoses, and assaults and homicides, while the rate of death from suicides remained stable. Younger age groups suffered the brunt of these indirect effects. Overall, on a national scale, the largest consequences of the COVID-19 pandemic are attributable to the direct impact of SARS-CoV-2 infections; yet, the secondary impacts dominate among younger age groups, in periods of stricter interventions, and in mortality from external causes. Further research on the drivers of indirect mortality is warranted to optimize interventions in future pandemics.

Testing Denmark: A Danish nationwide surveillance study of COVID-19

BackgroundNational data on the spread of SARS-CoV-2 infection and knowledge on associated risk factors are important for understanding the course of the pandemic. "Testing Denmark" is a national large-scale epidemiological surveillance study of SARS-CoV-2 in the Danish population. MethodsBetween September and October 2020, approximately 1.3 million of 5.8 million Danish citizens (age > 15 years) were randomly invited to fill in an electronic questionnaire covering COVID-19 exposures and symptoms. The prevalence of SARS-CoV-2 antibodies was determined by Point-of Care rapid Test (POCT) distributed to participants home addresses. FindingsIn total 318,552 participants (24.5% invitees) completed the questionnaire and provided the result of the POCT. Of these, 2,519 (0.79%) were seropositive (median age 55 years) and women were more often seropositive than men, interquartile range (IQR) 42-64, 40.2% males. Of participants with a prior positive Polymerase Chain Reaction (PCR) test (n=1,828), 29.1% were seropositive in the POCT. Seropositivity increased with age irrespective of sex. Elderly participants (>61 years) reported less symptoms and had less frequently been tested for SARS-CoV-2 compared to younger participants. Seropositivity was associated with physical contact with SARS-CoV-2 infected individuals (Risk ratio (RR) 7.43, 95% CI: 6.57-8.41) and in particular household members (RR 17.70, 95% CI: 15.60-20.10). Home care workers had a higher risk of seropositivity (RR 2.09 (95% CI: 1.58-2.78) as compared to office workers. Geographic population density was not associated to seropositivity. A high degree of compliance with national preventive recommendations was reported (e.g., > 80% use of face masks), but no difference was found between seropositive and seronegative participants. InterpretationThis study provides insight into the immunity of the Danish population seven to eight months after the first COVID-19 case in Denmark. The seroprevalence was lower than expected probably due to a low sensitivity of the POCT used or due to challenges relating to the reading of test results. Occupation or exposure in local communities were major routes of infection. As elderly participants were more often seropositive despite fewer symptoms and less PCR tests performed, more emphasis should be placed on testing this age group.

Lockdowns exert selection pressure on overdispersion of SARS-CoV-2 variants

The SARS-CoV-2 ancestral strain has caused pronounced super-spreading events, reflecting a disease characterized by overdispersion, where about 10% of infected people causes 80% of infections. New variants of the disease have different person-to-person variations in viral load, suggesting for example that the Alpha (B.1.1.7) variant is more infectious but relatively less prone to superspreading. Meanwhile, mitigation of the pandemic has focused on limiting social contacts (lockdowns, regulations on gatherings) and decreasing transmission risk through mask wearing and social distancing. Using a mathematical model, we show that the competitive advantage of disease variants may heavily depend on the restrictions imposed. In particular, we find that lockdowns exert an evolutionary pressure which favours variants with lower levels of overdispersion. We find that overdispersion is an evolutionarily unstable trait, with a tendency for more homogeneously spreading variants to eventually dominate. SignificanceOne of the most important and complex properties of viral pathogens is their ability to mutate. The SARS-CoV-2 pandemic has been characterized by overdispersion - a propensity for superspreading, which means that around 10% of those who become infected cause 80% of infections. However, evidence is mounting that this is not a stable property of the virus and that the Alpha variant spreads more homogeneously. We use a mathematical model to show that lockdowns exert a selection pressure, driving the pathogen towards more homogeneous transmission. In general, we highlight the importance of understanding how non-pharmaceutical interventions exert evolutionary pressure on pathogens. Our results imply that overdispersion should be taken into account when assessing the transmissibility of emerging variants.

SARS-CoV-2 antibody prevalence among homeless people, sex workers and shelter workers in Denmark: a nationwide cross-sectional study

BackgroundPeople experiencing homelessness (PEH) and associated shelter workers may be at higher risk of infection with "Severe acute respiratory syndrome coronavirus 2" (SARS-CoV-2). The aim of this study was to determine the prevalence of SARS-CoV-2 among PEH and shelter workers in Denmark. Design and methodsIn November 2020, we conducted a nationwide cross-sectional seroprevalence study among PEH and shelter workers at 21 recruitment sites in Denmark. The assessment included a point-of-care test for antibodies against SARS-CoV-2, followed by a questionnaire. The seroprevalence was compared to that of geographically matched blood donors considered as a proxy for the background population, tested using a total Ig ELISA assay. ResultsWe included 827 participants in the study, of whom 819 provided their SARS-CoV-2 antibody results. Of those, 628 were PEH (median age 50.8 (IQR 40.9-59.1) years, 35.5% female) and 191 were shelter workers (median age 46.6 (IQR 36.1-55.0) years and 74.5% female). The overall seroprevalence was 6.7% and was similar among PEH and shelter workers (6.8% vs 6.3%, p=0.87); and 12.2% among all participants who engaged in sex work. The overall participant seroprevalence was significantly higher than that of the background population (2.9%, p <0.001). When combining all participants who reported sex work or were recruited at designated safe havens, we found a significantly increased risk of seropositivity compared to other participants (RR 2.1, 95% CI 1.16-3.75, p=0.02). Seropositive and seronegative participants reported a similar presence of at least one SARS-CoV-2 associated symptom (49% and 54%, respectively). InterpretationsThe prevalence of SARS-CoV-2 antibodies was more than twice as high among PEH and associated shelter workers, compared to the background population. The subset of the study participants who were also sex workers were at particularly high risk of COVID-19 infection. FundingTrygFonden and HelseFonden.

Seroprevalence of SARS-CoV-2 antibodies in social housing areas in Denmark

BackgroundCOVID-19 is suggested to be more prevalent among ethnic minorities and individuals with low socioeconomic status. We aimed to investigate the prevalence of SARS-CoV-2 antibodies during the COVID-19 pandemic among citizens 15 years or older in Denmark living in social housing (SH) areas. MethodsAs part of "Testing Denmark", a nationwide sero-epidemiological surveillance survey, we conducted a study between January 8th and January 31st, 2021 with recruitment in 13 selected SH areas in Denmark. Participants were offered a point-of-care rapid SARS-CoV-2 IgM and IgG antibody test and a questionnaire concerning previous testing (viral throat- and nasopharyngeal swab or antibody test), test results for COVID-19, demographics, household characteristics, employment, risk factors for SARS-CoV-2 infection and history of symptoms associated with COVID-19. Data on seroprevalence from Danish blood donors in same period using a total Ig ELISA assay were used as a proxy for the general Danish population. FindingsOf the 13,279 included participants, 2,296 (17.3%) were seropositive (mean age 46.6 (SD 16.4) years, 54.2% female), which was 3 times higher than in the general Danish population (mean age 41.7 (SD 14.1) years, 48.5% female) in the same period (5.8%, risk ratios (RR) 2.96, 95% CI 2.78-3.16, p>0.001). Seropositivity was higher among males than females (RR 1.1, 95% CI 1.05-1.22%, p=0.001) and increased with age, with an OR seropositivity of 1.03 for each 10-year increase in age (95% CI 1.00-1.06, p=0.031). Close contact with COVID-19-infected individuals was associated with a higher risk of infection, especially among members of the same households (OR 5.0, 95% CI 4.1-6.2 p<0,001). Adjusted for age, gender and region living at least 4 people in a household significantly increased the OR of seropositivity (OR 1.3, 95% CI 1.1-1.6, p=0.02) as did living in a multi-generational household (OR 1.3 per generation, 95% CI 1.1-1.5, p=0.007). Only 1.6% of participants reported not following any of the national COVID-19 recommendations. Anosmia (RR 3.2 95% CI 2.8-3.7, p<0.001) and ageusia (RR 3.3, 95% CI 2.9-3.8, p<0.001) were strongest associated with seropositivity. InterpretationDanish citizens living in SH areas of low socioeconomic status had a three times higher SARS-CoV-2 seroprevalence compared to the general Danish population. The seroprevalence was significantly higher in males and increased with age. Living in multiple generations or more than four persons in a household was an independent risk factor for being seropositive. Results of this study can be used for future consideration of the need for preventive measures in the populations living in SH areas.

Heterogeneity is essential for contact tracing

Contact tracing is suggested as an effective strategy for controlling an epidemic without severely limiting personal mobility. Here, we explore how social structure affects contact tracing of COVID-19. Using smartphone proximity data, we simulate the spread of COVID-19 and find that heterogeneity in the social network and activity levels of individuals decreases the severity of an epidemic and improves the effectiveness of contact tracing. As a mitigation strategy, contact tracing depends strongly on social structure and can be remarkably effective, even if only frequent contacts are traced. In perspective, this highlights the necessity of incorporating social heterogeneity into models of mitigation strategies. O_TEXTBOXSignificance StatementThe COVID-19 epidemic has put severe limitations on individual mobility in the form of lockdowns and closed national borders. Mitigation strategies permitting individual mobility while limiting disease spreading are needed, and contact tracing is a potentially effective example of such a strategy. We use smartphone proximity data to monitor contacts between people, and find that contact tracing is highly dependent on social structure, being very effective on real contact networks. This shows that mitigation of COVID-19 may be possible with contact tracing, and that epidemiological models must incorporate social network structure. C_TEXTBOX

Impact of Superspreaders on dissemination and mitigation of COVID-19

BackgroundThe draconian measures used to control COVID-19 dissemination have been highly effective but only at enormous socioeconomic cost. Evidence suggests that "superspreaders" who transmit the virus to a large number of people, play a substantial role in transmission; recent estimates suggest that about 1-20% of people with the virus are the source for about 80% of infections. We used an agent-based model to explore the interplay between social structure, mitigation and superspreading. MethodsWe developed an agent-based model with a subset of "superspreader" agents that transmit disease far more efficiently. These agents act in a social network that allows transmission during contacts in three sectors: "home," "work/school" and "other". We simulated the effect of various mitigation strategies that limit contacts in each of these sectors, and used the model to fit COVID-19 mortality data from Sweden. FindingsReducing contacts in the "other" sector had a far greater impact on epidemic trajectory than did reducing "home" or "work/school" contacts; this effect was substantially enhanced when the infectivity of children was reduced relative to that of adults. The model fit Swedish hospitalization data with reasonable assumptions about the effect of Swedens mitigation policies on contacts in the different sectors. InterpretationOur results suggest COVID-19 could be controlled by limiting large gatherings and other opportunities for contacts between people in restaurants, sporting events, concerts and worship services) while still allowing regular contacts in the home or at work and school. O_TEXTBOXResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSSuperspreading events have long been known to be important in the epidemiology of many infectious diseases, including tuberculosis, measles, Ebola and SARS. Since the emergence of SARS-CoV-2, epidemiologic analyses have inferred substantial individual-level variation in transmissibility, with an estimated 1% to 20% of infected persons causing about 80% of all COVID-19 cases. Added value of this studyWe developed an agent-based socially structured model to simulate the effect of superspreaders in COVID-19 transmission in the context of country-wide "lockdown" policies. These simulations indicate that COVID-19 can be effectively mitigated by limiting contacts between people who otherwise rarely meet, while allowing home and most work/school contacts to continue. Implications of all available evidenceIt is crucial to include heterogeneity in individual infectiousness when modeling the impact of mitigation strategies on observed COVID-19 epidemic patterns. Reducing opportunities for superspreading by limiting random contacts outside home and work could be the most effective way to control COVID-19. Our findings suggest why the epidemic has continued to decline following re-opening of work and school in European countries. The superspreader phenomenon may also explain the variability in COVID-19 incidence in rural and urban areas within a country. C_TEXTBOX

Estimating the early death toll of COVID-19 in the United States

BackgroundEfforts to track the severity and public health impact of the novel coronavirus, COVID-19, in the US have been hampered by testing issues, reporting lags, and inconsistency between states. Evaluating unexplained increases in deaths attributed to broad outcomes, such as pneumonia and influenza (P&I) or all causes, can provide a more complete and consistent picture of the burden caused by COVID-19. MethodsWe evaluated increases in the occurrence of deaths due to P&I above a seasonal baseline (adjusted for influenza activity) or due to any cause across the United States in February and March 2020. These estimates are compared with reported deaths due to COVID-19 and with testing data. ResultsThere were notable increases in the rate of death due to P&I in February and March 2020. In a number of states, these deaths pre-dated increases in COVID-19 testing rates and were not counted in official records as related to COVID-19. There was substantial variability between states in the discrepancy between reported rates of death due to COVID-19 and the estimated burden of excess deaths due to P&I. The increase in all-cause deaths in New York and New Jersey is 1.5-3 times higher than the official tally of COVID-19 confirmed deaths or the estimated excess death due to P&I. ConclusionsExcess P&I deaths provide a conservative estimate of COVID-19 burden and indicate that COVID-19-related deaths are missed in locations with inadequate testing or intense pandemic activity. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSDeaths due to the novel coronavirus, COVID-19, have been increasing sharply in the United States since mid-March. However, efforts to track the severity and public health impact of COIVD-19 in the US have been hampered by testing issues, reporting lags, and inconsistency between states. As a result, the reported number of deaths likely represents an underestimate of the true burden. Added Value of this studyWe evaluate increases in deaths due to pneumonia across the United States and relate these increases to the number of reported deaths due to COVID-19 in different states and evaluate the trajectories of these increases in relation to the volume of testing and to indicators of COVID-19 morbidity. This provides a more complete picture of mortality due to COVID-19 in the US and demonstrates how delays in testing led to many coronavirus deaths not being counted in certain states. Implications of all the available evidenceThe number of deaths reported to be due to COVID-19 represents just a fraction of the deaths linked to the pandemic. Monitoring trends in deaths due to pneumonia and all-causes provides a more complete picture of the tool of the disease.

Epidemic doubling time of the 2019 novel coronavirus outbreak by province in mainland China

COVID-19 epidemic doubling time by Chinese province was increasing from January 20 through February 9, 2020. The harmonic mean of the arithmetic mean doubling time estimates ranged from 1.4 (Hunan, 95% CI, 1.2-2.0) to 3.1 (Xinjiang, 95% CI, 2.1-4.8), with an estimate of 2.5 days (95% CI, 2.4-2.6) for Hubei.