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 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 Non-compulsory measures sufficiently reduced human mobility in Tokyo during the COVID-19 epidemic

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Takahiro Yabe ◽  
Kota Tsubouchi ◽  
Naoya Fujiwara ◽  
Takayuki Wada ◽  
Yoshihide Sekimoto ◽  
...  
Keyword(s):  
Large Scale ◽  
Human Mobility ◽  
Social Contact ◽  
Mobility Patterns ◽  
State Of Emergency ◽  
Social Contacts ◽  
Policy Makers ◽  
Mobility Data ◽  
Contact Rates ◽  
Mobility Behavior

Abstract While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo. The analysis concludes that by April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the strong relationships with non-compulsory measures. Furthermore, the reduction in data-driven human mobility metrics showed correlation with the decrease in estimated effective reproduction number of COVID-19 in Tokyo. Such empirical insights could inform policy makers on deciding sufficient levels of mobility reduction to contain the disease.

scholarly journals The association of cultural and contextual factors with social contact avoidance during the COVID-19 pandemic

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261858
Author(s):  
Wolfgang Messner
Keyword(s):  
Public Health ◽  
International Business ◽  
Future Orientation ◽  
Power Distance ◽  
Social Contact ◽  
First Line ◽  
Social Contacts ◽  
High Social Support ◽  
High Power Distance ◽  
Pathogen Exposure

As a first line of defense to the COVID-19 pandemic in 2020, people reduced social contacts to avoid pathogen exposure. Using a panel of countries, this research suggests that this was amplified in societies characterized by high social support and future orientation. People reacted more strongly in dense environments; government orders had more effect in high power distance societies. Conversely, a focus on accomplishments was associated with lower changes. Understanding people’s actual behaviors in response to health threats across societies is of great importance for epidemiology, public health, international business, and for the functioning of humanity as a whole.

scholarly journals The impact of dengue illness on social distancing and caregiving behavior

2021 ◽  
Vol 15 (7) ◽  
pp. e0009614
Author(s):  
Kathryn L. Schaber ◽  
Amy C. Morrison ◽  
William H. Elson ◽  
Helvio Astete-Vega ◽  
Jhonny J. Córdova-López ◽  
...  
Keyword(s):  
Human Mobility ◽  
Social Contact ◽  
Febrile Illness ◽  
Well Being ◽  
Denv Infection ◽  
Transmission Dynamics ◽  
Mobility Patterns ◽  
Social Contacts ◽  
Infectious Individual ◽  
The Impact

Background Human mobility among residential locations can drive dengue virus (DENV) transmission dynamics. Recently, it was shown that individuals with symptomatic DENV infection exhibit significant changes in their mobility patterns, spending more time at home during illness. This change in mobility is predicted to increase the risk of acquiring infection for those living with or visiting the ill individual. It has yet to be considered, however, whether social contacts are also changing their mobility, either by socially distancing themselves from the infectious individual or increasing contact to help care for them. Social, or physical, distancing and caregiving could have diverse yet important impacts on DENV transmission dynamics; therefore, it is necessary to better understand the nature and frequency of these behaviors including their effect on mobility. Methodology and principal findings Through community-based febrile illness surveillance and RT-PCR infection confirmation, 67 DENV positive (DENV+) residents were identified in the city of Iquitos, Peru. Using retrospective interviews, data were collected on visitors and home-based care received during the illness. While 15% of participants lost visitors during their illness, 22% gained visitors; overall, 32% of all individuals (particularly females) received visitors while symptomatic. Caregiving was common (90%), particularly caring by housemates (91%) and caring for children (98%). Twenty-eight percent of caregivers changed their behavior enough to have their work (and, likely, mobility patterns) affected. This was significantly more likely when caring for individuals with low “health-related quality of well-being” during illness (Fisher’s Exact, p = 0.01). Conclusions/Significance Our study demonstrates that social contacts of individuals with dengue modify their patterns of visitation and caregiving. The observed mobility changes could impact a susceptible individual’s exposure to virus or a presymptomatic/clinically inapparent individual’s contribution to onward transmission. Accounting for changes in social contact mobility is imperative in order to get a more accurate understanding of DENV transmission.

Estimating the Effects of Non-Pharmaceutical Interventions (NPIs) and Population Mobility on Daily COVID-19 Cases: Evidence from Ontario

2020 ◽  
Vol COVID-19 ◽  
pp. e2021022
Author(s):  
Nathaniel T. Stevens ◽  
Anindya Sen ◽  
Francis Kiwon ◽  
Plinio P. Morita ◽  
Stefan H. Steiner ◽  
...  
Keyword(s):  
Public Health ◽  
Time Series ◽  
Instrumental Variables ◽  
Time Series Models ◽  
Population Mobility ◽  
Simultaneity Bias ◽  
Mobility Data ◽  
Business Operations ◽  
Iv Estimation ◽  
Pharmaceutical Interventions

This study employs COVID-19 case counts and Google mobility data for twelve of Ontario’s largest Public Health Units from Spring 2020 until the end of January 2021 to evaluate the effects of Non-Pharmaceutical Interventions (NPIs: policy restrictions on business operations and social gatherings) and population mobility on daily cases. Instrumental Variables (IV) estimation is used to account for potential simultaneity bias, as both daily COVID-19 cases and NPIs are dependent on lagged case numbers. IV estimates based on differences in lag lengths to infer causal estimates, imply that the implementation of stricter NPIs and indoor mask mandates are associated with COVID-19 case reductions. Further, estimates based on Google mobility data suggest that increases in workplace attendance are correlated with higher case counts. Finally, from October 2020 to January 2021, daily Ontario forecasts from Box-Jenkins time-series models are more accurate than official forecasts and forecasts from a Susceptible-Infected-Removed (SIR) epidemiology model.

scholarly journals Household Members Do Not Contact Each Other at Random: Implications for Infectious Disease Modelling

2017 ◽  
Author(s):  
Nele Goeyvaerts ◽  
Eva Santermans ◽  
Gail Potter ◽  
Andrea Torneri ◽  
Kim Van Kerckhove ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Social Contact ◽  
Household Contact ◽  
Disease Spread ◽  
Contact Density ◽  
Social Contacts ◽  
Contact Networks ◽  
Epidemic Simulation ◽  
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 in infectious disease spread and control, typically rely on the assumption of random mixing within households. Until now there was 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) in 2010-2011. We analyzed data from 318 households totaling 1266 individuals with household sizes ranging from 2 to 7 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 father and child is smaller than for any other pair except for older siblings. 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 simulation. However, ignoring the contact density when inferring from an epidemic model will result in biased estimates of within-household transmission rates. Further research on the implementation of within-household contact networks in epidemic models is necessary.Significance StatementHouseholds have a pivotal role in the spread of airborne infectious diseases. Households are bridging units between schools and workplaces, and social contacts within households are frequent and intimate, allowing for rapid disease spread. Infectious disease models typically assume that members of a household contact each other randomly. Until now there was no direct empirical evidence to support this assumption. In this paper, we present the first social contact survey specifically designed to study contact networks within households with young children. We investigate which factors drive contacts between household members on one particular day by means of a statistical model. Our results suggest the importance of connectedness within households over heterogeneity in number of contacts.

scholarly journals Single mothers' contact frequency with family and non-family members

2020 ◽  
Vol 32 (1) ◽  
pp. 25-44
Author(s):  
Hannah Zagel
Keyword(s):  
Single Mothers ◽  
Fixed Effects ◽  
Family Members ◽  
Social Contact ◽  
Single Motherhood ◽  
Cross Sectional ◽  
Social Contacts ◽  
Contact Frequency ◽  
Contact Data ◽  
Structural Isolation

Existing studies on single mothers’ social contacts often examine small selective samples and are mostly cross-sectional. The lack of high-quality longitudinal survey data on this subject constrains the possibility to draw more generalizable conclusions. This paper exploits panel data to investigate whether transitions to single motherhood affect contact frequency. Fixed-effects models are used on the six waves of the German ‘Socio-economic Panel’ survey that contain social contact data (1990, 1995, 1998, 2003, 2008, 2013) for analyzing whether single motherhood is associated with changes in contact frequency with family and non-family members. Findings show that women transitioning to single motherhood maintain contact with family and non-family members. Single motherhood is unlikely to cause mothers’ structural isolation. However, the absence of a second parent in the household neither seems to be connected with an increase in contact frequency with others. Providing a more generalised account of single mothers’ social contacts over time than previous research, the present study does not find evidence for a disintegrative effect of single motherhood.

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.

COVID-19, Security Threats and Public Opinions

2020 ◽  
Vol 26 (3) ◽  
Author(s):  
Vincenzo Bove ◽  
Riccardo Di Leo
Keyword(s):  
Public Health ◽  
Survey Data ◽  
Human Agency ◽  
Public Health Emergency ◽  
Terrorist Attacks ◽  
Critical Event ◽  
Political Leader ◽  
Security Threats ◽  
Public Opinions ◽  
Terrorist Violence

AbstractThroughout the coronavirus outbreak, politicians and commentators have often adopted a war-like rhetoric, invoking a language more often associated to terrorist violence, rather than epidemics. Although COVID-19 represents primarily a public health emergency, not inflicted by human agency, there are similarities in the type and scope of regulations governments have introduced to tackle the virus and to respond to terrorist attacks. In this article, we first ask what we can learn from the extant studies on the attitudinal and emotional consequences of terrorism, relating it to recent research on public opinions in the wake of COVID-19, in order to better understand and predict how the pandemic will influence public sentiments. We then analyze how attitudes can shift when a critical event not only threatens the population of a country as a whole, but directly affects its political leader. Leveraging recently released survey data, we show how the announcement of Angela Merkel’s quarantine significantly dampened the trust in and the credibility of her government, although this effect was short-lived.

scholarly journals SARS-CoV-2 shifting transmission dynamics and hidden reservoirs potentially limit efficacy of public health interventions in Italy

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Marta Giovanetti ◽  
Eleonora Cella ◽  
Francesca Benedetti ◽  
Brittany Rife Magalis ◽  
Vagner Fonseca ◽  
...  
Keyword(s):  
Public Health ◽  
Epidemiological Data ◽  
Health Interventions ◽  
Transmission Dynamics ◽  
Public Health Interventions ◽  
Viral Spread ◽  
Three Phase ◽  
Phylodynamic Analysis ◽  
Epidemic Wave ◽  
Over Time

AbstractWe investigated SARS-CoV-2 transmission dynamics in Italy, one of the countries hit hardest by the pandemic, using phylodynamic analysis of viral genetic and epidemiological data. We observed the co-circulation of multiple SARS-CoV-2 lineages over time, which were linked to multiple importations and characterized by large transmission clusters concomitant with a high number of infections. Subsequent implementation of a three-phase nationwide lockdown strategy greatly reduced infection numbers and hospitalizations. Yet we present evidence of sustained viral spread among sporadic clusters acting as “hidden reservoirs” during summer 2020. Mathematical modelling shows that increased mobility among residents eventually catalyzed the coalescence of such clusters, thus driving up the number of infections and initiating a new epidemic wave. Our results suggest that the efficacy of public health interventions is, ultimately, limited by the size and structure of epidemic reservoirs, which may warrant prioritization during vaccine deployment.

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