Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel

Abstract Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequence 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. We find that travelers returning from the United States of America significantly contributed to viral spread in Israel, more than their proportion in incoming infected travelers. Using phylodynamic analysis, we estimate that the basic reproduction number of the virus was initially around 2.5, dropping by more than two-thirds following the implementation of social distancing measures. We further report high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 2-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings demonstrate the effectiveness of social distancing measures for reducing viral spread.

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Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel

10.1101/2020.05.21.20104521 ◽

2020 ◽

Cited By ~ 16

Author(s):

Danielle Miller ◽

Michael A Martin ◽

Noam Harel ◽

Talia Kustin ◽

Omer Tirosh ◽

...

Keyword(s):

Reproduction Number ◽

Full Genome ◽

Viral Pathogens ◽

Social Distancing ◽

Viral Spread ◽

Geographic Spread ◽

Secondary Infections ◽

Viral Sequences ◽

Phylodynamic Analysis ◽

Local Transmission

Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequenced 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. A phylogenetic analysis including thousands of globally sampled sequences allowed us to infer multiple independent introductions into Israel, followed by local transmission. Returning travelers from the U.S. contributed dramatically more to viral spread relative to their proportion in incoming infected travelers. Using phylodynamic analysis, we estimated that the basic reproduction number of the virus was initially around ~2.0-2.6, dropping by two-thirds following the implementation of social distancing measures. A comparison between reported and model-estimated case numbers indicated high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 1-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings underscore the ability of this virus to efficiently transmit between and within countries, as well as demonstrate the effectiveness of social distancing measures for reducing its spread.

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Public Compliance With Social Distancing Measures and SARS-CoV-2 Spread

Public Health Reports ◽

10.1177/00333549211011254 ◽

2021 ◽

pp. 003335492110112

Author(s):

Hongjie Liu ◽

Chang Chen ◽

Raul Cruz-Cano ◽

Jennifer L. Guida ◽

Minha Lee

Keyword(s):

Growth Rate ◽

Reproduction Number ◽

Early Stage ◽

Human Mobility ◽

The United States ◽

Density Change ◽

Regression Coefficients ◽

Daily Growth Rate ◽

Daily Growth ◽

Social Distancing

Objective We quantified the association between public compliance with social distancing measures and the spread of SARS-CoV-2 during the first wave of the epidemic (March–May 2020) in 5 states that accounted for half of the total number of COVID-19 cases in the United States. Methods We used data on mobility and number of COVID-19 cases to longitudinally estimate associations between public compliance, as measured by human mobility, and the daily reproduction number and daily growth rate during the first wave of the COVID-19 epidemic in California, Illinois, Massachusetts, New Jersey, and New York. Results The 5 states mandated social distancing directives during March 19-24, 2020, and public compliance with mandates started to decrease in mid-April 2020. As of May 31, 2020, the daily reproduction number decreased from 2.41-5.21 to 0.72-1.19, and the daily growth rate decreased from 0.22-0.77 to –0.04 to 0.05 in the 5 states. The level of public compliance, as measured by the social distancing index (SDI) and daily encounter-density change, was high at the early stage of implementation but decreased in the 5 states. The SDI was negatively associated with the daily reproduction number (regression coefficients range, –0.04 to –0.01) and the daily growth rate (from –0.009 to –0.01). The daily encounter-density change was positively associated with the daily reproduction number (regression coefficients range, 0.24 to 1.02) and the daily growth rate (from 0.05 to 0.26). Conclusions Social distancing is an effective strategy to reduce the incidence of COVID-19 and illustrates the role of public compliance with social distancing measures to achieve public health benefits.

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Second waves, social distancing, and the spread of COVID-19 across America

Wellcome Open Research ◽

10.12688/wellcomeopenres.15986.1 ◽

2020 ◽

Vol 5 ◽

pp. 103 ◽

Cited By ~ 8

Author(s):

Karl J. Friston ◽

Thomas Parr ◽

Peter Zeidman ◽

Adeel Razi ◽

Guillaume Flandin ◽

...

Keyword(s):

United States ◽

Effective Connectivity ◽

The United States ◽

Parameter Estimates ◽

Key Factors ◽

Strategic Responses ◽

Social Distancing ◽

Viral Spread ◽

Single Region ◽

Dynamic Causal Model

We recently described a dynamic causal model of a COVID-19 outbreak within a single region. Here, we combine several of these (epidemic) models to create a (pandemic) model of viral spread among regions. Our focus is on a second wave of new cases that may result from loss of immunity—and the exchange of people between regions—and how mortality rates can be ameliorated under different strategic responses. In particular, we consider hard or soft social distancing strategies predicated on national (Federal) or regional (State) estimates of the prevalence of infection in the population. The modelling is demonstrated using timeseries of new cases and deaths from the United States to estimate the parameters of a factorial (compartmental) epidemiological model of each State and, crucially, coupling between States. Using Bayesian model reduction, we identify the effective connectivity between States that best explains the initial phases of the outbreak in the United States. Using the ensuing posterior parameter estimates, we then evaluate the likely outcomes of different policies in terms of mortality, working days lost due to lockdown and demands upon critical care. The provisional results of this modelling suggest that social distancing and loss of immunity are the two key factors that underwrite a return to endemic equilibrium.

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Real-Time Estimation of Rt for Supporting Public-Health Policies Against COVID-19

Frontiers in Public Health ◽

10.3389/fpubh.2020.556689 ◽

2020 ◽

Vol 8 ◽

Author(s):

Sebastián Contreras ◽

H. Andrés Villavicencio ◽

David Medina-Ortiz ◽

Claudia P. Saavedra ◽

Álvaro Olivera-Nappa

Keyword(s):

Public Health ◽

Real Time ◽

Reproduction Number ◽

Case Reports ◽

Mathematical Formulation ◽

Time Estimation ◽

Consensus Protocol ◽

Viral Spread ◽

Effective Interventions ◽

Secondary Infections

In the absence of a consensus protocol to slow down the spread of SARS-CoV-2, policymakers need real-time indicators to support decisions in public health matters. The Effective Reproduction Number (Rt) represents the number of secondary infections generated per each case and can be dramatically modified by applying effective interventions. However, current methodologies to calculate Rt from data remain somewhat cumbersome, thus raising a barrier between its timely calculation and application by policymakers. In this work, we provide a simple mathematical formulation for obtaining the effective reproduction number in real-time using only and directly daily official case reports, obtained by modifying the equations describing the viral spread. We numerically explore the accuracy and limitations of the proposed methodology, which was demonstrated to provide accurate, timely, and intuitive results. We illustrate the use of our methodology to study the evolution of the pandemic in different iconic countries, and to assess the efficacy and promptness of different public health interventions.

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Revealing fine-scale spatiotemporal differences in SARS-CoV-2 introduction and spread

Nature Communications ◽

10.1038/s41467-020-19346-z ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

Gage K. Moreno ◽

Katarina M. Braun ◽

Kasen K. Riemersma ◽

Michael A. Martin ◽

Peter J. Halfmann ◽

...

Keyword(s):

Public Health ◽

United States ◽

The United States ◽

Health Interventions ◽

Evidence Based ◽

Full Genome ◽

Public Health Interventions ◽

Viral Spread ◽

Milwaukee County ◽

Local Patterns

Abstract Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties following the statewide “Safer at Home” order, which went into effect 25 March 2020. Our results suggest patterns of SARS-CoV-2 transmission may vary substantially even in nearby communities. Understanding these local patterns will enable better targeting of public health interventions.

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Social Media as an Early Proxy for Social Distancing Indicated by the COVID-19 Reproduction Number: Observational Study (Preprint)

10.2196/preprints.21340 ◽

2020 ◽

Author(s):

Joseph Younis ◽

Harvy Freitag ◽

Jeremy S Ruthberg ◽

Jonathan P Romanes ◽

Craig Nielsen ◽

...

Keyword(s):

United States ◽

Social Media ◽

Observational Study ◽

Social Mobility ◽

Reproduction Number ◽

The United States ◽

Google Trends ◽

Basic Reproductive Number ◽

Social Distancing ◽

Google Search

BACKGROUND The magnitude and time course of the COVID-19 epidemic in the United States depends on early interventions to reduce the basic reproductive number to below 1. It is imperative, then, to develop methods to actively assess where quarantine measures such as social distancing may be deficient and suppress those potential resurgence nodes as early as possible. OBJECTIVE We ask if social media is an early indicator of public social distancing measures in the United States by investigating its correlation with the time-varying reproduction number (Rt) as compared to social mobility estimates reported from Google and Apple Maps. METHODS In this observational study, the estimated Rt was obtained for the period between March 5 and April 5, 2020, using the EpiEstim package. Social media activity was assessed using queries of “social distancing” or “#socialdistancing” on Google Trends, Instagram, and Twitter, with social mobility assessed using Apple and Google Maps data. Cross-correlations were performed between Rt and social media activity or mobility for the United States. We used Pearson correlations and the coefficient of determination (ρ) with significance set to P<.05. RESULTS Negative correlations were found between Google search interest for “social distancing” and Rt in the United States (P<.001), and between search interest and state-specific Rt for 9 states with the highest COVID-19 cases (P<.001); most states experienced a delay varying between 3-8 days before reaching significance. A negative correlation was seen at a 4-day delay from the start of the Instagram hashtag “#socialdistancing” and at 6 days for Twitter (P<.001). Significant correlations between Rt and social media manifest earlier in time compared to social mobility measures from Google and Apple Maps, with peaks at –6 and –4 days. Meanwhile, changes in social mobility correlated best with Rt at –2 days and +1 day for workplace and grocery/pharmacy, respectively. CONCLUSIONS Our study demonstrates the potential use of Google Trends, Instagram, and Twitter as epidemiological tools in the assessment of social distancing measures in the United States during the early course of the COVID-19 pandemic. Their correlation and earlier rise and peak in correlative strength with Rt when compared to social mobility may provide proactive insight into whether social distancing efforts are sufficiently enacted. Whether this proves valuable in the creation of more accurate assessments of the early epidemic course is uncertain due to limitations. These limitations include the use of a biased sample that is internet literate with internet access, which may covary with socioeconomic status, education, geography, and age, and the use of subtotal social media mentions of social distancing. Future studies should focus on investigating how social media reactions change during the course of the epidemic, as well as the conversion of social media behavior to actual physical behavior.

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The Association of Social Distancing, Population Density, and Temperature with the SARS-CoV-2 Instantaneous Reproduction Number in Counties Across the United States

10.1101/2020.05.08.20094474 ◽

2020 ◽

Author(s):

David Rubin ◽

Jing Huang ◽

Brian T. Fisher ◽

Antonio Gasparrini ◽

Vicky Tam ◽

...

Keyword(s):

United States ◽

Population Density ◽

Reproduction Number ◽

Multivariable Analysis ◽

The United States ◽

Fatality Rate ◽

Social Distancing ◽

Specific Factors ◽

Lower Population ◽

Lower Population Density

AbstractImportanceThe Covid-19 pandemic has been marked by considerable heterogeneity in outbreaks across the United States. Local factors that may be associated with variation in SARS-CoV-2 transmission have not been well studied.ObjectiveTo examine the association of county-level factors with variation in the SARS-CoV-2 reproduction number over time.DesignObservational studySetting211 counties in 46 states and the District of Columbia between February 25, 2020 and April 23, 2020.ParticipantsResidents within the counties (55% of the US population)ExposuresSocial distancing as measured by percent change in visits to non-essential businesses, population density, lagged daily wet bulb temperatures.Main Outcomes and MeasuresThe instantaneous reproduction number (Rt) which is the estimated number of cases generated by one case at a given time during the pandemic.ResultsMedian case incidence was 1185 cases and fatality rate was 43.7 deaths per 100,000 people for the top decile of 21 counties, nearly ten times the incidence and fatality rate in the lowest density quartile. Average Rt in the first two weeks was 5.7 (SD 2.5) in the top decile, compared to 3.1 (SD 1.2) in the lowest quartile. In multivariable analysis, a 50% decrease in visits to non-essential businesses was associated with a 57% decrease in Rt (95% confidence interval, 56% to 58%). Cumulative temperature effects over 4 to 10 days prior to case incidence were nonlinear; relative Rt decreased as temperatures warmed above 32°F to 53°F, which was the point of minimum Rt, then increased between 53°F and 66°F, at which point Rt began to decrease. At 55°F, and with a 70% reduction in visits to non-essential business, 96% of counties were estimated to fall below a threshold Rt of 1.0, including 86% of counties among the top density decile and 98% of counties in the lowest density quartile.Conclusions and RelevanceSocial distancing, lower population density, and temperate weather change were associated with a decreased SARS-Co-V-2 Rt in counties across the United States. These relationships can inform selective public policy planning in communities during the SARS-CoV-2 pandemic.Key PointsQuestionHow is the instantaneous reproduction number (Rt) of SARS-CoV-2 influenced by local area effects of social distancing, wet bulb temperature, and population density in counties across the United States?FindingsSocial distancing, temperate weather, and lower population density were associated with a decrease in Rt. Of these county-specific factors, social distancing appeared to be the most significant in reducing SARS-CoV-2 transmission.MeaningRt varies significantly across counties. The relationship between Rt and county-specific factors can inform policies to reduce SARS-CoV-2 transmission in selective and heterogeneous communities.

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Distinct patterns of SARS-CoV-2 transmission in two nearby communities in Wisconsin, USA

10.1101/2020.07.09.20149104 ◽

2020 ◽

Cited By ~ 1

Author(s):

Gage Kahl Moreno ◽

Katarina M Braun ◽

Kasen K Riemersma ◽

Michael A Martin ◽

Peter J Halfmann ◽

...

Keyword(s):

Public Health ◽

United States ◽

The United States ◽

Viral Transmission ◽

Evidence Based ◽

Full Genome ◽

Present Evidence ◽

Viral Spread ◽

Milwaukee County ◽

At Home

Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties, and limited viral transmission between counties, following the statewide Safer-at-Home public health order, which went into effect 25 March 2020. Our results suggest that early containment efforts suppressed the spread of SARS-CoV-2 within Wisconsin.

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Social Media as an Early Proxy for Social Distancing Indicated by the COVID-19 Reproduction Number: Observational Study

JMIR Public Health and Surveillance ◽

10.2196/21340 ◽

2020 ◽

Vol 6 (4) ◽

pp. e21340 ◽

Cited By ~ 1

Author(s):

Joseph Younis ◽

Harvy Freitag ◽

Jeremy S Ruthberg ◽

Jonathan P Romanes ◽

Craig Nielsen ◽

...

Keyword(s):

United States ◽

Social Media ◽

Observational Study ◽

Social Mobility ◽

Reproduction Number ◽

The United States ◽

Google Trends ◽

Basic Reproductive Number ◽

Social Distancing ◽

Google Search

Background The magnitude and time course of the COVID-19 epidemic in the United States depends on early interventions to reduce the basic reproductive number to below 1. It is imperative, then, to develop methods to actively assess where quarantine measures such as social distancing may be deficient and suppress those potential resurgence nodes as early as possible. Objective We ask if social media is an early indicator of public social distancing measures in the United States by investigating its correlation with the time-varying reproduction number (Rt) as compared to social mobility estimates reported from Google and Apple Maps. Methods In this observational study, the estimated Rt was obtained for the period between March 5 and April 5, 2020, using the EpiEstim package. Social media activity was assessed using queries of “social distancing” or “#socialdistancing” on Google Trends, Instagram, and Twitter, with social mobility assessed using Apple and Google Maps data. Cross-correlations were performed between Rt and social media activity or mobility for the United States. We used Pearson correlations and the coefficient of determination (ρ) with significance set to P<.05. Results Negative correlations were found between Google search interest for “social distancing” and Rt in the United States (P<.001), and between search interest and state-specific Rt for 9 states with the highest COVID-19 cases (P<.001); most states experienced a delay varying between 3-8 days before reaching significance. A negative correlation was seen at a 4-day delay from the start of the Instagram hashtag “#socialdistancing” and at 6 days for Twitter (P<.001). Significant correlations between Rt and social media manifest earlier in time compared to social mobility measures from Google and Apple Maps, with peaks at –6 and –4 days. Meanwhile, changes in social mobility correlated best with Rt at –2 days and +1 day for workplace and grocery/pharmacy, respectively. Conclusions Our study demonstrates the potential use of Google Trends, Instagram, and Twitter as epidemiological tools in the assessment of social distancing measures in the United States during the early course of the COVID-19 pandemic. Their correlation and earlier rise and peak in correlative strength with Rt when compared to social mobility may provide proactive insight into whether social distancing efforts are sufficiently enacted. Whether this proves valuable in the creation of more accurate assessments of the early epidemic course is uncertain due to limitations. These limitations include the use of a biased sample that is internet literate with internet access, which may covary with socioeconomic status, education, geography, and age, and the use of subtotal social media mentions of social distancing. Future studies should focus on investigating how social media reactions change during the course of the epidemic, as well as the conversion of social media behavior to actual physical behavior.

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How the Affective Quality of Day-to-Day Social Connections May Contribute to Public Health: Prosocial Tendencies Account for the Links Between Positivity Resonance and Behaviors that Reduce the Spread of COVID-19

10.31234/osf.io/x5rfz ◽

2020 ◽

Author(s):

Taylor Nicole West ◽

Khoa D. Le Nguyen ◽

Jieni Zhou ◽

Michael Prinzing ◽

Jenna C. Wells ◽

...

Keyword(s):

Positive Affect ◽

Affective State ◽

The United States ◽

Political Orientation ◽

Sensitivity Analyses ◽

Social Connections ◽

Mediation Effects ◽

Social Distancing ◽

Viral Spread ◽

Prosocial Tendencies

Although simple behaviors such as handwashing, mask wearing and social distancing are known to limit viral spread, early in the COVID-19 pandemic, many individuals in the United States did not adopt them. The Positivity Resonance Theory of collective positive affect holds that shared pleasant states that include the key features of mutual care and a sense of oneness through behavioral synchrony, function to build self-transcendent prosocial tendencies (Fredrickson, 2016). We tested the theory-driven hypothesis that prosocial tendencies (e.g., positive, other-oriented dispositions of felt unity, empathy, altruism and general positivity toward humanity) are associated with high-quality day-to-day social connections characterized by the affective state of positivity resonance, and in turn account for simple behaviors to slow the spread of COVID-19. We measured positivity resonance at the level of social episodes either during (Study 1, N = 1059, April-May 2020) or before the COVID-19 pandemic (Study 2, N = 227, March-November 2019). Across both studies, results suggest that positivity resonance had a positive indirect effect on self-reported COVID-19-related hygienic (e.g., handwashing & mask-wearing) and charitable behaviors, which was mediated by a latent index of prosocial tendencies. Sensitivity analyses confirmed these mediation effects to be independent of overall positive and negative affect, the frequency of social interaction, political orientation, and concern for one’s own health. Effects for social distancing were mixed. Overall, findings are consistent with the view that positivity resonance, a subtype of collective positive affect, builds self-transcendent prosocial tendencies that motivate simple behaviors to protect community health.

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