Social Contact Patterns Research Articles

Increased urbanization reduced the effectiveness of school closures on seasonal influenza epidemics in China

BackgroundSchool closure is a common mitigation strategy during severe influenza epidemics and pandemics. However, the effectiveness of this strategy remains controversial. In this study, we aimed to explore the effectiveness of school closure on seasonal influenza epidemics in provincial-level administrative divisions (PLADs) with varying urbanization rates in China.MethodsThis study analyzed influenza surveillance data between 2010 and 2019 provided by the Chinese National Influenza Center. Taking into consideration the climate, this study included a region with 3 adjacent PLADs in Northern China and another region with 4 adjacent PLADs in Southern China. The effect of school closure on influenza transmission was evaluated by the reduction of the effective reproductive number of seasonal influenza during school winter breaks compared with that before school winter breaks. An age-structured Susceptible-Infected-Recovered-Susceptible (SIRS) model was built to model influenza transmission in different levels of urbanization. Parameters were determined using the surveillance data via robust Bayesian method.ResultsBetween 2010 and 2019, in the less urbanized provinces: Hebei, Zhejiang, Jiangsu and Anhui, during school winter breaks, the effective reproductive number of seasonal influenza epidemics reduced 14.6% [95% confidential interval (CI): 6.2–22.9%], 9.6% (95% CI: 2.5–16.6%), 7.3% (95% CI: 0.1–14.4%) and 8.2% (95% CI: 1.1–15.3%) respectively. However, in the highly urbanized cities: Beijing, Tianjin and Shanghai, it reduced only 5.2% (95% CI: -0.7–11.2%), 4.1% (95% CI: -0.9–9.1%) and 3.9% (95% CI: -1.6–9.4%) respectively. In China, urbanization is associated with decreased proportion of children and increased social contact. According to the SIRS model, both factors could reduce the impact of school closure on seasonal influenza epidemics, and the proportion of children in the population is thought to be the dominant influencing factor.ConclusionsEffectiveness of school closure on the epidemics varies with the age structure in the population and social contact patterns. School closure should be recommended in the low urbanized regions in China in the influenza seasons.Graphical abstract

Individual social contact data and population mobility data as early markers of SARS-CoV-2 transmission dynamics during the first wave in Germany\u2014an analysis based on the COVIMOD study

BackgroundThe 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.MethodsWe 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.ResultsWe 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.ConclusionsContact 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.

Differential impact of physical distancing strategies on social contacts relevant for the spread of SARS-CoV-2: evidence from a cross-national online survey, March–April 2020

ObjectivesWe investigate changes in social contact patterns following the gradual introduction of non-pharmaceutical interventions and their implications for infection transmission in the early phase of the pandemic.Design, setting and participantsWe...

Two-Age-Structured COVID-19 Epidemic Model: Estimation of Virulence Parameters to Interpret Effects of National and Regional Feedback Interventions and Vaccination

The COVID-19 epidemic has recently led in Italy to the implementation of different external strategies in order to limit the spread of the disease in response to its transmission rate: strict national lockdown rules, followed first by a weakening of the social distancing and contact reduction feedback interventions and finally the implementation of coordinated intermittent regional actions, up to the application, in this last context, of an age-stratified vaccine prioritization strategy. This paper originally aims at identifying, starting from the available age-structured real data at the national level during the specific aforementioned scenarios, external-scenario-dependent sets of virulence parameters for a two-age-structured COVID-19 epidemic compartmental model, in order to provide an interpretation of how each external scenario modifies the age-dependent patterns of social contacts and the spread of COVID-19.

Analyzing the demographic, spatial, and temporal factors influencing social contact patterns in U.S. and implications for infectious disease spread

BackgroundDiseases such as COVID-19 are spread through social contact. Reducing social contacts is required to stop disease spread in pandemics for which vaccines have not yet been developed. However, existing data on social contact patterns in the United States (U.S.) is limited.MethodWe use American Time Use Survey data from 2003–2018 to describe and quantify the age-pattern of disease-relevant social contacts. For within-household contacts, we construct age-structured contact duration matrices (who spends time with whom, by age). For both within-household and non-household contacts, we also estimate the mean number and duration of contact by location. We estimate and test for differences in the age-pattern of social contacts based on demographic, temporal, and spatial characteristics.ResultsThe mean number and duration of social contacts vary by age. The biggest gender differences in the age-pattern of social contacts are at home and at work; the former appears to be driven by caretaking responsibilities.Non-Hispanic Blacks have a shorter duration of contact and fewer social contacts than non-Hispanic Whites. This difference is largely driven by fewer and shorter contacts at home. Pre-pandemic, non-Hispanic Blacks have shorter durations of work contacts. Their jobs are more likely to require close physical proximity, so their contacts are riskier than those of non-Hispanic Whites. Hispanics have the highest number of household contacts and are also more likely to work in jobs requiring close physical proximity than non-Hispanic Whites.With the exceptions of work and school contacts, the duration of social contact is higher on weekends than on weekdays. Seasonal differences in the total duration of social contacts are driven by school-aged respondents who have significantly shorter contacts during the summer months. Contact patterns did not differ by metro status. Age patterns of social contacts were similar across regions.ConclusionSocial contact patterns differ by age, race and ethnicity, and gender. Other factors besides contact patterns may be driving seasonal variation in disease incidence if school-aged individuals are not an important source of transmission. Pre-pandemic, there were no spatial differences in social contacts, but this finding has likely changed during the pandemic.

Using wearable proximity sensors to characterize social contact patterns in a village of rural Malawi

Measuring close proximity interactions between individuals can provide key information on social contacts in human communities and related behaviours. This is even more essential in rural settings in low- and middle-income countries where there is a need to understand contact patterns for the implementation of strategies for social protection interventions. We report the quantitative assessment of contact patterns in a village in rural Malawi, based on proximity sensors technology that allows for high-resolution measurements of social contacts. Our results revealed that the community structure of the village was highly correlated with the household membership of the individuals, thus confirming the importance of the family ties within the village. Social contacts within households occurred mainly between adults and children, and adults and adolescents and most of the inter-household social relationships occurred among adults and among adolescents. At the individual level, age and gender social assortment were observed in the inter-household network, and age disassortativity was instead observed in intra-household networks. Moreover, we obtained a clear trend of the daily contact activity of the village. Family members congregated in the early morning, during lunch time and dinner time. In contrast, inter-household contact activity displayed a growth from the morning, reaching a maximum in the afternoon.The proximity sensors technology used in this study provided high resolution temporal data characterized by timescales comparable with those intrinsic to social dynamics and it thus allowed to have access to the level of information needed to understand the social context of the village.

Inter‐Group Social Behavior, Contact Patterns and Risk for Pathogen Transmission in Cape Buffalo Populations

ABSTRACTIn social species, the transmission and maintenance of infectious diseases depends on the contact patterns between individuals within groups and on the interactions between groups. In southern Africa, the Cape buffalo (Syncerus caffer caffer) is a vector for many pathogens that can infect sympatric livestock. Although intra‐group contact patterns of Cape buffalo have been relatively well described, how groups interact with each other and risks for pathogen transmission remain poorly understood. We identified and compared spatial behavior and contact patterns between neighboring groups of Cape buffalo under contrasting environments: within the seasonally flooded environment of the Okavango Delta in Botswana and the semi‐arid environment of northern Kruger National Park in South Africa. We used telemetry data collected between 2007 and 2015 from 10 distinct groups. We estimated seasonal overlap and proximity between home ranges of pairwise neighboring groups, and we quantified seasonal contact patterns between these groups. We defined contact patterns within variable spatiotemporal windows compatible with the transmission of diseases carried by the Cape buffalo: bovine tuberculosis, brucellosis, and Rift Valley fever (mosquito‐borne transmission). We examined the effects of habitat and distance to water on contact location. In both study populations, neighboring buffalo groups were highly spatially segregated in the dry and rainy seasons. Inter‐group contact patterns were characterized by very few direct and short‐term indirect (within 0–2 days) contacts, lasting on average 1 hour and 2 hours, respectively. Contact patterns were generally consistent across populations and seasons, suggesting species‐specific behavior. In the drier study site, the probability of indirect and vector‐borne contacts generally decreased during the dry season with increasing distance to water. In the seasonally flooded area, only the probability of vector‐borne contact decreased with increasing distance to water. Our results highlight the importance of dry season water availability in influencing the dynamics of indirectly transmitted Cape buffalo pathogens but only in areas with low water availability. The results from this study have important implications for future modeling of pathogen dynamics in a single host, and the ecology and management of Cape buffalo at the landscape level. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.

Daily Social Life of Older Adults and Vulnerabilities During the COVID-19 Pandemic.

Introduction: The social integration of older adults is crucial for understanding their risk of infection and mental health during the COVID-19 pandemic. However, the social lives of older adults differ, which means they are not all vulnerable to COVID-19 in the same way. This study analyzes everyday time use and social contacts of older adults to inform discussions of their vulnerabilities during the pandemic.Methods: Using the 2019 American time use survey (N = 4,256, aged 55 and older), hurdle model regressions were used to examine the relationship between age, gender, and six indicators of the degree of social contact and time use, including (1) time alone, (2) time spent with family members, (3) time spent with non-family members, (4) time spent with people in the same household, (5) number of public spaces visited, and (6) time spent in public spaces.Results: Results showed substantial heterogeneity in everyday time use and social contacts. Time in public places gradually decreased from the oldest-old (85 years or older), old-old (75–84 years), to mid-life (55–64 years) adults. The gaps were not explained by age differences in sociodemographic characteristics and social roles. Compared with mid-life adults, time with family members of the young-old and old-old adults decreased, but time with non-family members increased. Age differences in social roles over the life course partially explained the differences.Conclusions: Should these patterns of time use and social contacts persist during COVID-19; then, such variations in the organization of social life may create different exposure contexts and vulnerabilities to social distancing measures among older adults; such information could help inform interventions to better protect this population.

Rapid Review of Social Contact Patterns During the COVID-19 Pandemic.

Physical distancing measures aim to reduce person-to-person contact, a key driver of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. In response to unprecedented restrictions on human contact during the coronavirus disease 2019 (COVID-19) pandemic, studies measured social contact patterns under the implementation of physical distancing measures. This rapid review synthesizes empirical data on the changing social contact patterns during the COVID-19 pandemic. We conducted a systematic review using PubMed, Medline, Embase, and Google Scholar following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We descriptively compared the distribution of contacts observed during the pandemic to pre-COVID data across countries to explore changes in contact patterns during physical distancing measures. We identified 12 studies reporting social contact patterns during the COVID-19 pandemic. Eight studies were conducted in European countries and eleven collected data during the initial mitigation period in the spring of 2020 marked by government-declared lockdowns. Some studies collected additional data after relaxation of initial mitigation. Most study settings reported a mean of between 2 and 5 contacts per person per day, a substantial reduction compared to pre-COVID rates, which ranged from 7 to 26 contacts per day. This reduction was pronounced for contacts outside of the home. Consequently, levels of assortative mixing by age substantially declined. After relaxation of initial mitigation, mean contact rates increased but did not return to pre-COVID levels. Increases in contacts post-relaxation were driven by working-age adults. Information on changes in contact patterns during physical distancing measures can guide more realistic representations of contact patterns in mathematical models for SARS-CoV-2 transmission.

A modified age-structured SIR model for COVID-19 type viruses

We present a modified age-structured SIR model based on known patterns of social contact and distancing measures within Washington, USA. We find that population age-distribution has a significant effect on disease spread and mortality rate, and contribute to the efficacy of age-specific contact and treatment measures. We consider the effect of relaxing restrictions across less vulnerable age-brackets, comparing results across selected groups of varying population parameters. Moreover, we analyze the mitigating effects of vaccinations and examine the effectiveness of age-targeted distributions. Lastly, we explore how our model can applied to other states to reflect social-distancing policy based on different parameters and metrics.

Estimation of the main conditions in (SARS-CoV-2) Covid-19 patients that increase the risk of death using Machine learning, the case of Mexico

Nowadays, society faces a catastrophic problem related to respiratory syndrome due to the coronavirus SARS-CoV-2: the Covid-19 disease. This virus has changed our coexistence rules and, in consequence, has reshaped the daily activities in modern societies. Thus, there are many efforts to understand the virus behaviour in order to reduce its negative impact, and these efforts produce an incredible amount of information and data sources every week. Data scientists, which use techniques such as Machine learning, are focusing their abilities to develop mathematical models for analysing this critical situation. This paper uses Machine Learning techniques as tools to help understand some specific new patterns in Covid patients that arise from unknown complex interactions in the transmission-dynamic models of the SARS-CoV-2 virus, and their relation with the corresponding social contact patterns which are often known or can be inferred from populations variables. One of the main motivations of this research is to find the diseases that cause an increase in the risk of death in infected people with the Covid-19 virus. Mexico is the case of study in this research. The general conditions of health that cause death are well known generally in the world. However, these conditions in each country can differ depending on different factors such as the general health status of people. The results show that the principal causes of death in Mexico are related to age, bad eating habits, chronic diseases, and contact with infected people having not proper care. Results from the analysis show a remarkable accuracy of 87%, which is considered satisfactory.

Social contact patterns among employees in 3 U.S. companies during early phases of the COVID-19 pandemic, April to June 2020

We measured contact patterns using online diaries for 304 employees of 3 U.S. companies working remotely. The median number of daily contacts was 2 (IQR 1-4); majority were conversation (55 %), occurred at home (64 %) and lasted >4 h (38 %). These data are crucial for modeling outbreak control among the workforces.

Limits of lockdown: characterising essential contacts during strict physical distancing

Background: Coronavirus disease 2019 (COVID-19) has exposed health inequalities within countries and globally. The fundamental determining factor behind an individual’s risk of infection is the number of social contacts they make. In many countries, physical distancing measures have been implemented to control transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), reducing social contacts to a minimum. We characterise social contacts to understand the drivers and inequalities behind differential risks for aiding in planning SARS-CoV-2 mitigation programmes. Methods: We utilised an existing longitudinal birth cohort (n=6807) to explore social contact patterns and behaviours when strict physical distancing measures were in place during the UK’s first lockdown in March-May 2020. We used an online questionnaire to capture information on participant contact patterns, health, SARS-CoV-2 exposure, behaviours and impacts resulting from COVID-19. We quantified daily contacts and examined the association between covariates and numbers of daily total contacts using a negative binomial regression model. Results: A daily average of 3.7 [standard deviation = 10.6] total contacts outside the household were reported. Essential workers, specifically those in healthcare, had 4.5 times as many contacts as non-essential workers [incident rate ratio = 4.42 (95% CI: 3.88–5.04)], whilst essential workers in other sectors, mainly teaching and the police force had three times as many contacts [IRR = 2.84 (2.58–3.13)]. The number of individuals in a household, which largely reflects number of children, increases essential social contacts by 40%. Self-isolation effectively reduces numbers of contacts outside of the home, but not entirely. Conclusions: Contextualising contact patterns has highlighted the health inequalities exposed by COVID-19, as well as potential sources of infection risk and transmission. Together, these findings will aid the interpretation of epidemiological data and impact the design of effective control strategies for SARS-CoV-2, such as vaccination, testing and contact tracing.

Cooperative coinfection dynamics on clustered networks.

Coinfection is the process by which a host that is infected with a pathogen becomes infected by a second pathogen at a later point in time. An immunosuppressant host response to a primary disease can facilitate spreading of a subsequent emergent pathogen among the population. Social contact patterns within the substrate populace can be modeled using complex networks and it has been shown that contact patterns vastly influence the emergent disease dynamics. In this paper, we consider the effect of contact clustering on the coinfection dynamics of two pathogens spreading over a network. We use the generating function formulation to describe the expected outbreak sizes of each pathogen and numerically study the threshold criteria that permit the coexistence of each strain among the network. We find that the effects of clustering on the levels of coinfection are governed by the details of the contact topology.

Modeling the interplay between demography, social contact patterns, and SARS-CoV-2 transmission in the South West Shewa Zone of Oromia Region, Ethiopia

BackgroundCOVID-19 spread may have a dramatic impact in countries with vulnerable economies and limited availability of, and access to, healthcare resources and infrastructures. However, in sub-Saharan Africa, a low prevalence and mortality have been observed so far.MethodsWe collected data on individuals’ social contacts in the South West Shewa Zone (SWSZ) of Ethiopia across geographical contexts characterized by heterogeneous population density, work and travel opportunities, and access to primary care. We assessed how socio-demographic factors and observed mixing patterns can influence the COVID-19 disease burden, by simulating SARS-CoV-2 transmission in remote settlements, rural villages, and urban neighborhoods, under school closure mandate.ResultsFrom national surveillance data, we estimated a net reproduction number of 1.62 (95% CI 1.55–1.70). We found that, at the end of an epidemic mitigated by school closure alone, 10–15% of the population residing in the SWSZ would have been symptomatic and 0.3–0.4% of the population would require mechanical ventilation and/or possibly result in a fatal outcome. Higher infection attack rates are expected in more urbanized areas, but the highest incidence of critical disease is expected in remote subsistence farming settlements. School closure contributed to reduce the reproduction number by 49% and the attack rate of infections by 28–34%.ConclusionsOur results suggest that the relatively low burden of COVID-19 in Ethiopia observed so far may depend on social mixing patterns, underlying demography, and the enacted school closures. Our findings highlight that socio-demographic factors can also determine marked heterogeneities across different geographical contexts within the same region, and they contribute to understand why sub-Saharan Africa is experiencing a relatively lower attack rate of severe cases compared to high-income countries.

A pilot study investigating the social contact patterns of Korean elderly.

This pilot study describes the characteristics of social contact patterns of the elderly, a group at high-risk for contracting infections. A cross-sectional design was used. Participants included 30 volunteers aged 65years or older. Records of a contact diary were maintained for a period of 24-hr. Thirty participants recorded 340 contacts within the 24hr period, with a mean of 11.3 people daily. Physical encounters accounted for 50.9% of contacts. Participants with an occupation had significantly higher contacts than those without (p=.013). Contact type differed by location and duration (p<.001). Contact locations included: home (11.5%), work (2.4%), elderly welfare facilities (32.9%), transport (1.2%), and other places (52.1%). Contact duration (p<.001) and frequency (p<.001) differed by location. Contact duration differed by frequency (p<.001). The elderly participate in frequent physical contact that increases their risk of infection, especially among those with an occupation in comparison to those without an occupation. Infection control nursing should focus on providing education to reduce the risk of infections during contact events. Social distancing should be applied to limited periods of infection transmission risk.

Combining Wearable Devices and Mobile Surveys to Study Child and Youth Development in Malawi: Implementation Study of a Multimodal Approach.

BackgroundMultimodal approaches have been shown to be a promising way to collect data on child development at high frequency, combining different data inputs (from phone surveys to signals from noninvasive biomarkers) to understand children’s health and development outcomes more integrally from multiple perspectives.ObjectiveThe aim of this work was to describe an implementation study using a multimodal approach combining noninvasive biomarkers, social contact patterns, mobile surveying, and face-to-face interviews in order to validate technologies that help us better understand child development in poor countries at a high frequency.MethodsWe carried out a mixed study based on a transversal descriptive analysis and a longitudinal prospective analysis in Malawi. In each village, children were sampled to participate in weekly sessions in which data signals were collected through wearable devices (electrocardiography [ECG] hand pads and electroencephalography [EEG] headbands). Additionally, wearable proximity sensors to elicit the social network were deployed among children and their caregivers. Mobile surveys using interactive voice response calls were also used as an additional layer of data collection. An end-line face-to-face survey was conducted at the end of the study.ResultsDuring the implementation, 82 EEG/ECG data entry points were collected across four villages. The sampled children for EEG/ECG were 0 to 5 years old. EEG/ECG data were collected once a week. In every session, children wore the EEG headband for 5 minutes and the ECG hand pad for 3 minutes. In total, 3531 calls were sent over 5 weeks, with 2291 participants picking up the calls and 984 of those answering the consent question. In total, 585 people completed the surveys over the course of 5 weeks.ConclusionsThis study achieved its objective of demonstrating the feasibility of generating data through the unprecedented use of a multimodal approach for tracking child development in Malawi, which is one of the poorest countries in the world. Above and beyond its multiple dimensions, the dynamics of child development are complex. It is the case not only that no data stream in isolation can accurately characterize it, but also that even if combined, infrequent data might miss critical inflection points and interactions between different conditions and behaviors. In turn, combining different modes at a sufficiently high frequency allows researchers to make progress by considering contact patterns, reported symptoms and behaviors, and critical biomarkers all at once. This application showcases that even in developing countries facing multiple constraints, complementary technologies can leverage and accelerate the digitalization of health, bringing benefits to populations that lack new tools for understanding child well-being and development.

Workplace influenza vaccination to reduce employee absenteeism: An economic analysis from the employers’ perspective

BackgroundEach year, up to 10% of unvaccinated adults contracts seasonal influenza, with half of this proportion developing symptoms. As a result, employers experience significant economic losses in terms of employee absenteeism. Influenza vaccines can be instrumental in reducing this burden. Workplace vaccination is expected to reduce employee absenteeism more than linearly as a result of positive externalities. It remains unclear whether workplace influenza vaccination yields a positive return on investment. MethodsWe simulated the spread of influenza in the seasons 2011–12 up to 2017–18 in Belgium by means of a compartmental transmission model. We accounted for age-specific social contact patterns and included reduced contact behavior when symptomatically infected. We simulated the impact of employer-funded influenza vaccination at the workplace and performed a cost-benefit analysis to assess the employers’ return on workplace vaccination. Furthermore, we look into the cost-benefit of rewarding vaccinated employees by offering an additional day off. ResultsWorkplace vaccination reduced the burden of influenza both on the workplace and in the population at large. Compared to the current vaccine coverage – 21% in the population at large – an employee vaccine coverage of 90% could avert an additional 355 000 cases, of which about 150 000 in the employed population and 205 000 in the unemployed population. While seasonal influenza vaccination has been cost-saving on average at about €10 per vaccinated employee, the cost-benefit analysis was prone to between-season variability. ConclusionsVaccinated employees can serve as a barrier to limit the spread of influenza in the population, reducing the attack rate by 78% at an employee coverage of 90%. While workplace vaccination is relatively inexpensive (due to economies of scale) and convenient, the return on investment is volatile. Government subsidies can be pivotal to encourage employers to provide vaccination at the workplace with positive externalities to society as a whole.

Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities.

The coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges to the formulation of preventive interventions, particularly since the effects of physical distancing measures and upcoming vaccines on reducing susceptible social contacts and eventually halting transmission remain unclear. Here, using anonymized mobile geolocation data in China, we devise a mobility-associated social contact index to quantify the impact of both physical distancing and vaccination measures in a unified way. Building on this index, our epidemiological model reveals that vaccination combined with physical distancing can contain resurgences without relying on stay-at-home restrictions, whereas a gradual vaccination process alone cannot achieve this. Further, for cities with medium population density, vaccination can reduce the duration of physical distancing by 36% to 78%, whereas for cities with high population density, infection numbers can be well-controlled through moderate physical distancing. These findings improve our understanding of the joint effects of vaccination and physical distancing with respect to a city's population density and social contact patterns.

Effects of Social Distancing Measures during the First Epidemic Wave of Severe Acute Respiratory Syndrome Infection, Greece.

Greece imposed a nationwide lockdown in March 2020 to mitigate transmission of severe acute respiratory syndrome coronavirus 2 during the first epidemic wave. We conducted a survey on age-specific social contact patterns to assess effects of physical distancing measures and used a susceptible-exposed-infectious-recovered model to simulate the epidemic. Because multiple distancing measures were implemented simultaneously, we assessed their overall effects and the contribution of each measure. Before measures were implemented, the estimated basic reproduction number (R0) was 2.38 (95% CI 2.01–2.80). During lockdown, daily contacts decreased by 86.9% and R0 decreased by 81.0% (95% credible interval [CrI] 71.8%–86.0%); each distancing measure decreased R0 by 10%–24%. By April 26, the attack rate in Greece was 0.12% (95% CrI 0.06%–0.26%), one of the lowest in Europe, and the infection fatality ratio was 1.12% (95% CrI 0.55%–2.31%). Multiple social distancing measures contained the first epidemic wave in Greece.