scholarly journals Individual social contact data and population mobility data as early markers of SARS-CoV-2 transmission dynamics during the first wave in Germany—an analysis based on the COVIMOD study

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Damilola Victoria Tomori ◽  
Nicole Rübsamen ◽  
Tom Berger ◽  
Stefan Scholz ◽  
Jasmin Walde ◽  
...  
Keyword(s):  
Survey Data ◽  
Social Contact ◽  
Transmission Dynamics ◽  
Relative Reduction ◽  
Population Mobility ◽  
Mobility Data ◽  
Infection Dynamics ◽  
Contact Data ◽  
The One ◽  
Contact Survey

Abstract Background The effect of contact reduction measures on infectious disease transmission can only be assessed indirectly and with considerable delay. However, individual social contact data and population mobility data can offer near real-time proxy information. The aim of this study is to compare social contact data and population mobility data with respect to their ability to reflect transmission dynamics during the first wave of the SARS-CoV-2 pandemic in Germany. Methods We quantified the change in social contact patterns derived from self-reported contact survey data collected by the German COVIMOD study from 04/2020 to 06/2020 (compared to the pre-pandemic period from previous studies) and estimated the percentage mean reduction over time. We compared these results as well as the percentage mean reduction in population mobility data (corrected for pre-pandemic mobility) with and without the introduction of scaling factors and specific weights for different types of contacts and mobility to the relative reduction in transmission dynamics measured by changes in R values provided by the German Public Health Institute. Results We observed the largest reduction in social contacts (90%, compared to pre-pandemic data) in late April corresponding to the strictest contact reduction measures. Thereafter, the reduction in contacts dropped continuously to a minimum of 73% in late June. Relative reduction of infection dynamics derived from contact survey data underestimated the one based on reported R values in the time of strictest contact reduction measures but reflected it well thereafter. Relative reduction of infection dynamics derived from mobility data overestimated the one based on reported R values considerably throughout the study. After the introduction of a scaling factor, specific weights for different types of contacts and mobility reduced the mean absolute percentage error considerably; in all analyses, estimates based on contact data reflected measured R values better than those based on mobility. Conclusions Contact survey data reflected infection dynamics better than population mobility data, indicating that both data sources cover different dimensions of infection dynamics. The use of contact type-specific weights reduced the mean absolute percentage errors to less than 1%. Measuring the changes in mobility alone is not sufficient for understanding the changes in transmission dynamics triggered by public health measures.

scholarly journals Individual social contact data reflected SARS-CoV-2 transmission dynamics during the first wave in Germany better than population mobility data - an analysis based on the COVIMOD study

2021 ◽  
Author(s):  
Damilola Victoria Tomori ◽  
Nicole Ruebsamen ◽  
Tom Berger ◽  
Stefan Scholz ◽  
Jasmin Walde ◽  
...  
Keyword(s):  
Public Health ◽  
Survey Data ◽  
Social Contact ◽  
Transmission Dynamics ◽  
Population Mobility ◽  
Social Contacts ◽  
Mobility Data ◽  
Contact Data ◽  
Contact Survey ◽  
T Values

Background The effect of contact reduction measures on infectious disease transmission can only be assessed indirectly and with considerable delay. However, individual social contact data and population mobility data can offer near real-time proxy information. Aim To compare social contact data and population mobility data with respect to their ability to predict transmission dynamics during the first wave of the SARS-CoV-2 pandemic in Germany. Methods We quantified the change in social contact patterns derived from self-reported contact survey data collected by the German COVIMOD study from 04/2020-06/2020 (compared to the pre-pandemic period), and estimated the percentage mean reduction in the effective reproduction number R(t) over time. We compared these results to the ones based on R(t) estimates from open-source mobility data and to R(t) values provided by the German Public Health Institute. Results We observed the largest reduction in social contacts (90%, compared to pre-pandemic data) in late April corresponding to the strictest contacts reduction measures. Thereafter, the reduction in contacts dropped continuously to a minimum of 73% in late June. R(t) estimates based on social contacts underestimated measured R(t) values slightly in the time of strictest contact reduction measures but predicted R(t) well thereafter. R(t) estimates based on mobility data overestimated R(t) considerably throughout the study. Conclusions R(t) prediction accuracy based on contact survey data was superior to the one based on population mobility data, indicating that measuring changes in mobility alone is not sufficient for understanding changes in transmission dynamics triggered by public health measures.

scholarly journals Phylogenomic Evidence of Reinfection and Persistence of SARS-CoV-2: First Report from Colombia

Vaccines ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 282
Author(s):  
Juan David Ramírez ◽  
Marina Muñoz ◽  
Nathalia Ballesteros ◽  
Luz H. Patiño ◽  
Sergio Castañeda ◽  
...  
Keyword(s):  
Viral Persistence ◽  
Transmission Dynamics ◽  
Polymorphism Analysis ◽  
Rt Pcr ◽  
Paired Samples ◽  
Infection Dynamics ◽  
Oxford Nanopore ◽  
Novel Variants ◽  
First Time ◽  
Oxford Nanopore Technologies

The continuing evolution of SARS-CoV-2 and the emergence of novel variants have raised concerns about possible reinfection events and potential changes in the coronavirus disease 2019 (COVID-19) transmission dynamics. Utilizing Oxford Nanopore technologies, we sequenced paired samples of three patients with positive RT-PCR results in a 1–2-month window period, and subsequent phylogenetics and genetic polymorphism analysis of these genomes was performed. Herein, we report, for the first time, genomic evidence of one case of reinfection in Colombia, exhibiting different SARS-CoV-2 lineage classifications between samples (B.1 and B.1.1.269). Furthermore, we report two cases of possible viral persistence, highlighting the importance of deepening our understanding on the evolutionary intra-host traits of this virus throughout different timeframes of disease progression. These results emphasize the relevance of genomic surveillance as a tool for understanding SARS-CoV-2 infection dynamics, and how this may translate effectively to future control and mitigations efforts, such as the national vaccination program.

scholarly journals A data-driven metapopulation model for the Belgian COVID-19 epidemic: assessing the impact of lockdown and exit strategies

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pietro Coletti ◽  
Pieter Libin ◽  
Oana Petrof ◽  
Lander Willem ◽  
Steven Abrams ◽  
...  
Keyword(s):  
Phase 1 ◽  
Leisure Activities ◽  
National Level ◽  
Social Contact ◽  
Exit Strategy ◽  
Initial Wave ◽  
Contact Data ◽  
Stochastic Data ◽  
The Impact ◽  
Second Wave

Abstract Background In response to the ongoing COVID-19 pandemic, several countries adopted measures of social distancing to a different degree. For many countries, after successfully curbing the initial wave, lockdown measures were gradually lifted. In Belgium, such relief started on May 4th with phase 1, followed by several subsequent phases over the next few weeks. Methods We analysed the expected impact of relaxing stringent lockdown measures taken according to the phased Belgian exit strategy. We developed a stochastic, data-informed, meta-population model that accounts for mixing and mobility of the age-structured population of Belgium. The model is calibrated to daily hospitalization data and is able to reproduce the outbreak at the national level. We consider different scenarios for relieving the lockdown, quantified in terms of relative reductions in pre-pandemic social mixing and mobility. We validate our assumptions by making comparisons with social contact data collected during and after the lockdown. Results Our model is able to successfully describe the initial wave of COVID-19 in Belgium and identifies interactions during leisure/other activities as pivotal in the exit strategy. Indeed, we find a smaller impact of school re-openings as compared to restarting leisure activities and re-openings of work places. We also assess the impact of case isolation of new (suspected) infections, and find that it allows re-establishing relatively more social interactions while still ensuring epidemic control. Scenarios predicting a second wave of hospitalizations were not observed, suggesting that the per-contact probability of infection has changed with respect to the pre-lockdown period. Conclusions Contacts during leisure activities are found to be most influential, followed by professional contacts and school contacts, respectively, for an impending second wave of COVID-19. Regular re-assessment of social contacts in the population is therefore crucial to adjust to evolving behavioral changes that can affect epidemic diffusion.

scholarly journals COVID-19, Urbanization Pattern and Economic Recovery: An Analysis of Hubei, China

2020 ◽  
Vol 17 (24) ◽  
pp. 9577
Author(s):  
Wenyi Yang ◽  
Xueli Wang ◽  
Keke Zhang ◽  
Zikan Ke
Keyword(s):  
Rapid Development ◽  
Generalized Method Of Moments ◽  
Economic Recovery ◽  
Population Mobility ◽  
Economic Resilience ◽  
Economic Resource ◽  
Large Cities ◽  
Impact Of Urbanization ◽  
The One ◽  
The Impact

In the context of the rapid development of urbanization and increasing population mobility in China, the outbreak of COVID-19 has had a significant impact on China’s economy and society. This article uses China UnionPay transaction data and takes Hubei, the worst-hit region by COVID-19 in China, as an example, to conduct empirical analysis using the generalized method of moments (GMM) of the impact of current urbanization patterns on the spread of the epidemic and economic recovery from the perspectives of time, industry, and regional differences. The study found that during the different stages of COVID-19, including discovery, outbreak, and subsidence, the overall impact of urbanization on the economy in Hubei Province was first positive, then became negative, and finally gradually increased. This process had significant industrial and urban heterogeneity, which was mainly manifested in losses in tourism and catering industries that were significantly greater than those in the audio-visual entertainment and digital office industries. Similarly, the recovery speed of large cities was lower than that of small and medium-sized cities. The main reason for these differences is that the one-sided problem of urbanization is more obvious in areas with higher urbanization rates. COVID-19 has drawn attention to the development of urbanization in the future, that is, the development path of one-sided economic resource agglomeration and scale expansion should be abandoned, with greater attention paid to the improvement of service functions and the development of amenities. This transformation is necessary to enhance urban economic resilience and reduce public health risks.

scholarly journals Modelling Representative Population Mobility for COVID-19 Spatial Transmission in South Africa

2021 ◽  
Vol 4 ◽  
Author(s):  
A. Potgieter ◽  
I. N. Fabris-Rotelli ◽  
Z. Kimmie ◽  
N. Dudeni-Tlhone ◽  
J. P. Holloway ◽  
...  
Keyword(s):  
Human Mobility ◽  
Data Sources ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Mobility Data ◽  
The World ◽  
Spatial Weight ◽  
Data Source ◽  
Reduced Mobility ◽  
Spatial Transmission

The COVID-19 pandemic starting in the first half of 2020 has changed the lives of everyone across the world. Reduced mobility was essential due to it being the largest impact possible against the spread of the little understood SARS-CoV-2 virus. To understand the spread, a comprehension of human mobility patterns is needed. The use of mobility data in modelling is thus essential to capture the intrinsic spread through the population. It is necessary to determine to what extent mobility data sources convey the same message of mobility within a region. This paper compares different mobility data sources by constructing spatial weight matrices at a variety of spatial resolutions and further compares the results through hierarchical clustering. We consider four methods for constructing spatial weight matrices representing mobility between spatial units, taking into account distance between spatial units as well as spatial covariates. This provides insight for the user into which data provides what type of information and in what situations a particular data source is most useful.

scholarly journals Modeling infection dynamics and mitigation strategies to support K-6 in-person instruction during the COVID-19 pandemic

2021 ◽  
Author(s):  
Douglas E. Morrison ◽  
Roch Nianogo ◽  
Vladimir Manuel ◽  
Onyebuchi A. Arah ◽  
Nathaniel Anderson ◽  
...  
Keyword(s):  
School Attendance ◽  
Secondary Infection ◽  
Mitigation Strategies ◽  
Transmission Dynamics ◽  
Model Parameters ◽  
Safety Education ◽  
Vaccination Rates ◽  
Health Authorities ◽  
Infection Dynamics ◽  
Public Health Authorities

AbstractObjectiveTo support safer in-person K-6 instruction during the coronavirus disease 2019 (COVID- 19) pandemic by providing public health authorities and school districts with a practical model of transmission dynamics and mitigation strategies.MethodsWe developed an agent-based model of infection dynamics and preventive mitigation strategies such as distancing, health behaviors, surveillance and symptomatic testing, daily symptom and exposure screening, quarantine policies, and vaccination. The model parameters can be updated as the science evolves and are adjustable via an online user interface, enabling users to explore the effects of interventions on outcomes of interest to states and localities, under a variety of plausible epidemiological and policy assumptions.ResultsUnder default assumptions, secondary infection rates and school attendance are substantially affected by surveillance testing protocols, vaccination rates, class sizes, and effectiveness of safety education.ConclusionsOur model helps policymakers consider how mitigation options and the dynamics of school infection risks affect outcomes of interest. The model’s parameters can be immediately updated in response to changes in epidemiological conditions, science of COVID-19 transmission dynamics, testing and vaccination resources, and reliability of mitigation strategies.

scholarly journals The first 100 days of SARS-CoV-2 control in Vietnam

2020 ◽  
Author(s):  
Thai Quang Pham ◽  
Maia Rabaa ◽  
Luong Huy Duong ◽  
Tan Quang Dang ◽  
Quang Dai Tran ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Severe Disease ◽  
Steering Committee ◽  
International Travel ◽  
Control Measures ◽  
Contact Tracing ◽  
Population Mobility ◽  
Early Introduction ◽  
Mobility Data ◽  
Travel Restrictions

Background: One hundred days after SARS-CoV-2 was first reported in Vietnam on January 23rd, 270 cases have been confirmed, with no deaths. We describe the control measures used and their relationship with imported and domestically-acquired case numbers. Methods: Data on the first 270 SARS-CoV-2 infected cases and the timing and nature of control measures were captured by Vietnam's National Steering Committee for COVID-19 response. Apple and Google mobility data provided population movement proxies. Serial intervals were calculated from 33 infector-infectee pairs and used to estimate the proportion of pre-symptomatic transmission events and time-varying reproduction numbers. Results: After the first confirmed case on January 23rd, the Vietnamese Government initiated mass communications measures, contact tracing, mandatory 14-day quarantine, school and university closures, and progressive flight restrictions. A national lockdown was implemented between April 1st and 22nd. Around 200,000 people were quarantined and 266,122 RT-PCR tests conducted. Population mobility decreased progressively before lockdown. 60% (163/270) of cases were imported; 43% (89/208) of resolved infections were asymptomatic. 21 developed severe disease, with no deaths. The serial interval was 3.24 days, and 27.5% (95% confidence interval, 15.7%-40.0%) of transmissions occurred pre-symptomatically. Limited transmission amounted to a maximum reproduction number of 1.15 (95% confidence interval, 0.37-2.36). No community transmission has been detected since April 15th. Conclusions: Vietnam has controlled SARS-CoV-2 spread through the early introduction of communication, contact-tracing, quarantine, and international travel restrictions. The value of these interventions is supported by the high proportion of asymptomatic cases and imported cases, and evidence for substantial pre-symptomatic transmission.

scholarly journals Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study

BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e047227
Author(s):  
Xiaoming Cui ◽  
Lin Zhao ◽  
Yuhao Zhou ◽  
Xin Lin ◽  
Runze Ye ◽  
...  
Keyword(s):  
Close Contact ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Population Mobility ◽  
Wholesale Market ◽  
The People ◽  
Spatiotemporal Analyses ◽  
Epidemiological Characteristics ◽  
Pharmaceutical Interventions ◽  
Modelling Study

ObjectiveTo evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions.DesignDescriptive and modelling study based on surveillance data of COVID-19 in Beijing.SettingOutbreak in Beijing.ParticipantsThe database included 335 confirmed cases of COVID-19.MethodsTo conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing.ResultsWe found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect.ConclusionsThe non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection.

scholarly journals SOCRATES: An online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19

2020 ◽  
Author(s):  
Lander Willem ◽  
Thang Van Hoang ◽  
Sebastian Funk ◽  
Pietro Coletti ◽  
Philippe Beutels ◽  
...  
Keyword(s):  
Data Sharing ◽  
Social Contact ◽  
School Closure ◽  
Mitigation Strategies ◽  
Online Application ◽  
Online Tool ◽  
R Shiny ◽  
Contact Data ◽  
Considerable Impact ◽  
Disease Specific

AbstractObjectiveEstablishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19.ResultsWe organized data sharing of published social contact surveys via online repositories and formatting guidelines. We analyzed this social contact data in terms of weighted social contact matrices, next generation matrices, relative incidence and R0. We incorporated location-specific isolation measures (e.g. school closure or telework) and capture their effect on transmission dynamics. All methods have been implemented in an online application based on R Shiny and applied to COVID-19 with age-specific susceptibility and infectiousness. Using our online tool with the available social contact data, we illustrate that social distancing could have a considerable impact on reducing transmission for COVID-19. The effect itself depends on assumptions made about disease-specific characteristics and the choice of intervention(s).

scholarly journals Household members do not contact each other at random: implications for infectious disease modelling

2018 ◽  
Vol 285 (1893) ◽  
pp. 20182201 ◽  
Author(s):  
Nele Goeyvaerts ◽  
Eva Santermans ◽  
Gail Potter ◽  
Andrea Torneri ◽  
Kim Van Kerckhove ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Social Contact ◽  
Household Contact ◽  
Epidemic Models ◽  
Disease Spread ◽  
Contact Density ◽  
Contact Networks ◽  
Household Transmission ◽  
Household Members ◽  
Contact Survey

Airborne infectious diseases such as influenza are primarily transmitted from human to human by means of social contacts, and thus easily spread within households. Epidemic models, used to gain insight into infectious disease spread and control, typically rely on the assumption of random mixing within households. Until now, there has been no direct empirical evidence to support this assumption. Here, we present the first social contact survey specifically designed to study contact networks within households. The survey was conducted in Belgium (Flanders and Brussels) from 2010 to 2011. We analysed data from 318 households totalling 1266 individuals with household sizes ranging from two to seven members. Exponential-family random graph models (ERGMs) were fitted to the within-household contact networks to reveal the processes driving contact between household members, both on weekdays and weekends. The ERGMs showed a high degree of clustering and, specifically on weekdays, decreasing connectedness with increasing household size. Furthermore, we found that the odds of a contact between older siblings and between father and child are smaller than for any other pair. The epidemic simulation results suggest that within-household contact density is the main driver of differences in epidemic spread between complete and empirical-based household contact networks. The homogeneous mixing assumption may therefore be an adequate characterization of the within-household contact structure for the purpose of epidemic simulations. However, ignoring the contact density when inferring based on an epidemic model will result in biased estimates of within-household transmission rates. Further research regarding the implementation of within-household contact networks in epidemic models is necessary.

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