Social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong

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.

Measuring voluntary and policy-induced social distancing behavior during the COVID-19 pandemic

Staying home and avoiding unnecessary contact is an important part of the effort to contain COVID-19 and limit deaths. Every state in the United States enacted policies to encourage distancing and some mandated staying home. Understanding how these policies interact with individuals' voluntary responses to the COVID-19 epidemic is a critical initial step in understanding the role of these nonpharmaceutical interventions in transmission dynamics and assessing policy impacts. We use variation in policy responses along with smart device data that measures the amount of time Americans stayed home to disentangle the extent that observed shifts in staying home behavior are induced by policy. We find evidence that stay-at-home orders and voluntary response to locally reported COVID-19 cases and deaths led to behavioral change. For the median county, which implemented a stay-at-home order with about two cases, we find that the response to stay-at-home orders increased time at home as if the county had experienced 29 additional local cases. However, the relative effect of stay-at-home orders was much greater in select counties. On the one hand, the mandate can be viewed as displacing a voluntary response to this rise in cases. On the other hand, policy accelerated the response, which likely helped reduce spread in the early phase of the pandemic. It is important to be able to attribute the relative role of self-interested behavior or policy mandates to understand the limits and opportunities for relying on voluntary behavior as opposed to imposing stay-at-home orders.

Kenya's response to the COVID-19 pandemic: a balance between minimising morbidity and adverse economic impact

Coronavirus disease 2019 (COVID-19) has ravaged the world's socioeconomic systems forcing many governments across the globe to implement unprecedented stringent mitigation measures to restrain its rapid spread and adverse effects. A disproportionate number of COVID-19 related morbidities and mortalities were predicted to occur in Africa. However, Africa still has a lower than predicted number of cases, 4% of the global pandemic burden. In this open letter, we highlight some of the early stringent countermeasures implemented in Kenya, a sub-Saharan African country, to avert the severe effects of the COVID-19 pandemic. These mitigation measures strike a balance between minimising COVID-19 associated morbidity and fatalities and its adverse economic impact, and taken together have significantly dampened the pandemic's impact on Kenya's populace.

Real-time tracking and prediction of COVID-19 infection using digital proxies of population mobility and mixing

Digital proxies of human mobility and physical mixing have been used to monitor viral transmissibility and effectiveness of social distancing interventions in the ongoing COVID-19 pandemic. We develop a new framework that parameterizes disease transmission models with age-specific digital mobility data. By fitting the model to case data in Hong Kong, we are able to accurately track the local effective reproduction number of COVID-19 in near real time (i.e., no longer constrained by the delay of around 9 days between infection and reporting of cases) which is essential for quick assessment of the effectiveness of interventions on reducing transmissibility. Our findings show that accurate nowcast and forecast of COVID-19 epidemics can be obtained by integrating valid digital proxies of physical mixing into conventional epidemic models.

Digital proxies of human mobility can be used to monitor social distancing, and therefore have potential to infer COVID-19 dynamics. Here, the authors integrate travel card data from Hong Kong into a transmission model and show that it can be used to track transmissibility in near real-time.

A pilot study investigating the social contact patterns of Korean elderly

OBJECTIVES

This pilot study describes the characteristics of social contact patterns of the elderly, a group at high-risk for contracting infections.

DESIGN

A cross-sectional design was used.

SAMPLE

Participants included 30 volunteers aged 65 years or older.

MEASUREMENTS

Records of a contact diary were maintained for a period of 24-hr.

RESULTS

Thirty participants recorded 340 contacts within the 24 hr 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).

CONCLUSIONS

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.

C, Galloway D, Schweizer ML, Guclu H, Cousins J, Lingle C, Yearwood GMH, Li K, Calderone P, Noble E, Gao H, Rainey J, Uzicanin A, Read JM. Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.

Hand-to-Environment Contact During Indoor Activities in Senior Welfare Centers Among Korean Older Adults: A Pilot Study

(1) Background: This study aimed to describe the characteristics of hand-to-environment contact (HEC) and identify the influencing factors of HEC behavior during the indoor daily life of Korean older adults in senior welfare centers. (2) Methods: A cross-sectional observational study was used with 30 participants over 65 years of age attending programs in senior welfare centers. Video recordings of the 30 participants were collected for two hours a day for participants selected from 20 November to 4 December 2018. Contact frequency, density, and duration were measured. (3) Results: Video recordings of 3,930 HEC cases were analyzed. Furniture surface (25.0%), tableware and cooking utensils (5.4%), phones (5.3%), and door handles (0.1%) were found to be the items with the most frequent contact, in this order. The average contact frequency and contact density (frequency-duration/min/person) of HEC for two hours were highest for the Category I equipment (personally used, accounting for 70.4%), and the average contact duration of HEC was highest in the Category III equipment (commonly used, 47.7 s/contact/person). Contact density was as high as 266.5 (frequency-duration/min/person). Participants above 75 years of age and the unemployed showed high HEC with Category III. (4) Conclusions: Older adults need to be educated to avoid unnecessary hand contact with items in Category III. In particular, hand hygiene and sanitization through the regular and thorough disinfection of furniture surfaces and shared equipment are very important to prevent the spread of pathogens.

Six-year incidence and systemic associations of retinopathy in a multi-ethnic Asian population without diabetes

PURPOSE

We described the 6-year incidence and changes of retinopathy, and their associated risk factors in a multi-ethnic Asian population without diabetes.

METHODS

We included 4374 participants with non-diabetes from a population-based cohort, the Singapore Epidemiology of Eye Disease Study, with gradable retinal photographs at baseline and 6-year follow-up visit. Retinopathy was assessed according to the modified Airlie House classification system.

RESULTS

Over the 6-year period, the cumulative rates were 2.5% (106/4279) for retinopathy incidence, 1.0% (1/95) for retinopathy progression and 68.4% (65/95) for retinopathy regression. In multivariable analysis, higher diastolic blood pressure (DBP) (risk ratio (RR)=1.02; 95% CI: 1.00 to 1.04; per 10 mm Hg increase in DBP) and wider retinal arteriolar calibre (RR=1.36; 95% CI: 1.13 to 1.63; per SD increase in central retinal artery equivalent) were associated with higher risk of incident retinopathy, while higher level of high-density lipoprotein (HDL) was associated with lower risk of incident retinopathy (RR=0.56; 95% CI: 0.32 to 0.99; per mmol/L increase in HDL). Compared with Chinese, Malays were more likely to have retinopathy regression (RR=1.63; 95% CI: 1.20 to 2.22), while overweight (RR=0.47; 95% CI: 0.26 to 0.84) and higher glycosylated haemoglobin (HbA1c) level (RR=0.58; 95% CI: 0.37 to 0.93; per per cent increase in HbA1c) were associated with lower likelihood of retinopathy regression.

CONCLUSION

Risk of developing retinopathy in Asians without diabetes is generally low. However, regression of retinopathy over time is common, suggesting that these retinopathy signs may reflect subclinical reversible microvascular dysfunction. Several metabolic risk factors are associated with incidence or regression of retinopathy, suggesting that good metabolic control may still be important in the management of non-diabetic retinopathy.

Kenya's response to the COVID-19 pandemic: a balance between minimising morbidity and adverse economic impact

Coronavirus disease 2019 (COVID-19) has ravaged the world's socioeconomic systems forcing many governments across the globe to implement unprecedented stringent mitigation measures to restrain its rapid spread and adverse effects. A disproportionate number of COVID-19 related morbidities and mortalities were predicted to occur in Africa. However, Africa still has a lower than predicted number of cases, 4% of the global pandemic burden. In this open letter, we highlight some of the early stringent countermeasures implemented in Kenya, a sub-Saharan African country, to avert the severe effects of the COVID-19 pandemic. These mitigation measures strike a balance between minimising COVID-19 associated morbidity and fatalities and its adverse economic impact, and taken together have significantly dampened the pandemic's impact on Kenya's populace.

Pandemic Equation for Describing and Predicting COVID19 Evolution

The purpose of this work is to describe the dynamics of the COVID-19 pandemics accounting for the mitigation measures, for the introduction or removal of the quarantine, and for the effect of vaccination when and if introduced. The methods used include the derivation of the Pandemic Equation describing the mitigation measures via the evolution of the growth time constant in the Pandemic Equation resulting in an asymmetric pandemic curve with a steeper rise than a decrease and mitigation measures. The Pandemic Equation predicts how the quarantine removal and business opening lead to a spike in the pandemic curve. The effective vaccination reduces the new daily infections predicted by the Pandemic Equation. The pandemic curves in many localities have similar time dependencies but shifted in time. The Pandemic Equation parameters extracted from the well advanced pandemic curves can be used for predicting the pandemic evolution in the localities, where the pandemics is still in the initial stages. Using the multiple pandemic locations for the parameter extraction allows for the uncertainty quantification in predicting the pandemic evolution using the introduced Pandemic Equation. Compared with other pandemic models our approach allows for easier parameter extraction amenable to using Artificial Intelligence models.

Response to the COVID-19: Understanding implications of government lockdown policies

The rising number of COVID-19 cases and economic implications of lockdown measures indicate the tricky balancing act policy makers face as they implement the subsequent phases of 'unlock'. We develop a model to examine how lockdown and social distancing measures have influenced the behavioral conduct of people. The current situation highlights that policy makers need to focus on bringing awareness and social restraint among people rather than going for stringent lockdown measures. We believe this work will help the policy makers gain insights into the troubled COVID-19 times ahead, and based on the estimates, they can frame policies to navigate these wild waves in the best possible way.

Demographic and socio-economic factors, and healthcare resource indicators associated with the rapid spread of COVID-19 in Northern Italy: An ecological study

BACKGROUND

COVID-19 rapidly escalated into a pandemic, threatening 213 countries, areas, and territories the world over. We aimed to identify potential province-level socioeconomic determinants of the virus's dissemination, and explain between-province differences in the speed of its spread, based on data from 36 provinces of Northern Italy.

METHODS

This is an ecological study. We included all confirmed cases of SARS-CoV-2 reported between February 24th and March 30th, 2020. For each province, we calculated the trend of contagion as the relative increase in the number of individuals infected between two time endpoints, assuming an exponential growth. Pearson's test was used to correlate the trend of contagion with a set of healthcare-associated, economic, and demographic parameters by province. The virus's spread was input as a dependent variable in a stepwise OLS regression model to test the association between rate of spread and province-level indicators.

RESULTS

Multivariate analysis showed that the spread of COVID-19 was correlated negatively with aging index (p-value = 0.003), and positively with public transportation per capita (p-value = 0.012), the % of private long-term care hospital beds and, to a lesser extent (p-value = 0.070), the % of private acute care hospital beds (p-value = 0.006).

CONCLUSION

Demographic and socioeconomic factors, and healthcare organization variables were found associated with a significant difference in the rate of COVID-19 spread in 36 provinces of Northern Italy. An aging population seemed to naturally contain social contacts. The availability of healthcare resources and their coordination could play an important part in spreading infection.

Lifestyle Acquired Immunity, Decentralized Intelligent Infrastructures, and Revised Healthcare Expenditures May Limit Pandemic Catastrophe: A Lesson From COVID-19

Throughout history, the human race has often faced pandemics with substantial numbers of fatalities. As the COVID-19 pandemic has now affected the whole planet, even countries with moderate to strong healthcare support and expenditure have struggled to contain disease transmission and casualties. Countries affected by COVID-19 have different demographics, socioeconomic, and lifestyle health indicators. In this context, it is important to find out to what extent these parametric variations are modulating disease outcomes. To answer this, this study selected demographic, socioeconomic, and health indicators e.g., population density, percentage of the urban population, median age, health expenditure per capita, obesity, diabetes prevalence, alcohol intake, tobacco use, case fatality of non-communicable diseases (NCDs) as independent variables. Countries were grouped according to these variables and influence on dependent variables e.g., COVID-19 positive tests, case fatality, and case recovery rates were statistically analyzed. The results suggested that countries with variable median age had a significantly different outcome on positive test rate (P < 0.01). Both the median age (P = 0.0397) and health expenditure per capita (P = 0.0041) showed a positive relation with case recovery. An increasing number of tests per 100 K of the population showed a positive and negative relationship with the number of positives per 100 K population (P = 0.0001) and the percentage of positive tests (P < 0.0001), respectively. Alcohol intake per capita in liter (P = 0.0046), diabetes prevalence (P = 0.0389), and NCDs mortalities (P = 0.0477) also showed a statistical relation to the case fatality rate. Further analysis revealed that countries with high healthcare expenditure along with high median age and increased urban population showed more case fatality but also had a better recovery rate. Investment in the health sector alone is insufficient in controlling the severity of the pandemic. Intelligent and sustainable healthcare both in urban and rural settings and healthy lifestyle acquired immunity may reduce disease transmission and comorbidity induced fatalities, respectively.

Work exposure and associated risk of hospitalisation with pneumonia and influenza: A nationwide study

Background:

Pneumonia and influenza are major health concerns and constitute a high economic burden. However, few data are available on the associated risk of pneumonia and influenza and work exposure on a large population scale.

Aim:

This study aimed to examine the associated risk of pneumonia and influenza by type of work exposure.

Methods:

By cross-linking administrative Danish registries, we classified people in 10 different profession types. The main outcome was hospitalisation with pneumonia or influenza. A multivariable Poisson regression analysis was used to assess the associated incidence rate ratio (IRR) of being hospitalised with pneumonia or influenza by type of profession.

Results:

A total of 1,327,606 people added risk time to the analyses. In a multivariable model, work in day care, public transportation, sewers and nursing home care was associated with an increased risk of hospitalisation with pneumonia compared to work within public administration: IRR=1.20 (95% confidence interval (CI) 1.12–1.28), IRR=1.21 (95% CI 1.09–1.34), IRR=1.61 (95% CI 1.19–2.19) and IRR=1.10 (95% CI 1.03–1.18), respectively. In a multivariable analysis, people working within public transportation were associated with an increased risk of hospitalisation with influenza compared to people working within public administration: IRR=2.54 (95% CI 1.79–3.58).

Conclusions:

Working in day care, public transportation, sewers and nursing home care increased the associated risk of hospitalisation with pneumonia, and working within public transportation increased the associated risk of being hospitalised with influenza compared to working within public administration.

Prospective diary survey of preschool children's social contact patterns: A pilot study

Purpose

This pilot study aimed to describe children's social contact patterns and to analyze factors related to their social contacts.

Methods

The participants were 30 children aged ≥13 months to <7 years, whose teachers at childcare centers and parents at home were asked to maintain diaries of their social contacts prospectively for 24 hours. Data were collected from November 30, 2018, to January 7, 2019.

Results

The 30 participating children were in contact with 363 persons in a 24-hours period (mean, 12.1±9.1). The number of contacts showed significant relationships with day of the week (p<.001), number of family members/cohabitants (p=.015), area of residence (p=.003), and type of housing (p=.002). A multiple regression model showed significantly higher numbers of contacts on weekdays (B=10.64, p=.010). Physical versus non-physical types of contact showed significant differences in terms of duration, location, and frequency (p<.001). The duration of contacts showed significant relationships with their location and frequency (p<.001), while the frequency of contacts was significantly related to their location (p<.001).

Conclusion

This is the first survey describing the characteristics of Korean preschool children's social contacts. Further large-scale social contact studies of children should be conducted.

Hospital and Population-Based Evidence for COVID-19 Early Circulation in the East of France

BACKGROUND

Understanding SARS-CoV-2 dynamics and transmission is a serious issue. Its propagation needs to be modeled and controlled. The Alsace region in the East of France has been among the first French COVID-19 clusters in 2020.

METHODS

We confront evidence from three independent and retrospective sources: a population-based survey through internet, an analysis of the medical records from hospital emergency care services, and a review of medical biology laboratory data. We also check the role played in virus propagation by a large religious meeting that gathered over 2000 participants from all over France mid-February in Mulhouse.

RESULTS

Our results suggest that SARS-CoV-2 was circulating several weeks before the first officially recognized case in Alsace on 26 February 2020 and the sanitary alert on 3 March 2020. The religious gathering seems to have played a role for secondary dissemination of the epidemic in France, but not in creating the local outbreak.

CONCLUSIONS

Our results illustrate how the integration of data coming from multiple sources could help trigger an early alarm in the context of an emerging disease. Good information data systems, able to produce earlier alerts, could have avoided a general lockdown in France.

A Systematic Review of Social Contact Surveys to Inform Transmission Models of Close-contact Infections

BACKGROUND

Researchers increasingly use social contact data to inform models for infectious disease spread with the aim of guiding effective policies about disease prevention and control. In this article, we undertake a systematic review of the study design, statistical analyses, and outcomes of the many social contact surveys that have been published.

METHODS

We systematically searched PubMed and Web of Science for articles regarding social contact surveys. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines as closely as possible.

RESULTS

In total, we identified 64 social contact surveys, with more than 80% of the surveys conducted in high-income countries. Study settings included general population (58%), schools or universities (37%), and health care/conference/research institutes (5%). The largest number of studies did not focus on a specific age group (38%), whereas others focused on adults (32%) or children (19%). Retrospective (45%) and prospective (41%) designs were used most often with 6% using both for comparison purposes. The definition of a contact varied among surveys, e.g., a nonphysical contact may require conversation, close proximity, or both. We identified age, time schedule (e.g., weekday/weekend), and household size as relevant determinants of contact patterns across a large number of studies.

CONCLUSIONS

We found that the overall features of the contact patterns were remarkably robust across several countries, and irrespective of the study details. By considering the most common approach in each aspect of design (e.g., sampling schemes, data collection, definition of contact), we could identify recommendations for future contact data surveys that may be used to facilitate comparison between studies.

Simulation of the COVID-19 epidemic on the social network of Slovenia: Estimating the intrinsic forecast uncertainty

In the article a virus transmission model is constructed on a simplified social network. The social network consists of more than 2 million nodes, each representing an inhabitant of Slovenia. The nodes are organised and interconnected according to the real household and elderly-care center distribution, while their connections outside these clusters are semi-randomly distributed and undirected. The virus spread model is coupled to the disease progression model. The ensemble approach with the perturbed transmission and disease parameters is used to quantify the ensemble spread, a proxy for the forecast uncertainty. The presented ongoing forecasts of COVID-19 epidemic in Slovenia are compared with the collected Slovenian data. Results show that at the end of the first epidemic wave, the infection was twice more likely to transmit within households/elderly care centers than outside them. We use an ensemble of simulations (N = 1000) and data assimilation approach to estimate the COVID-19 forecast uncertainty and to inversely obtain posterior distributions of model parameters. We found that in the uncontrolled epidemic, the intrinsic uncertainty mostly originates from the uncertainty of the virus biology, i.e. its reproduction number. In the controlled epidemic with low ratio of infected population, the randomness of the social network becomes the major source of forecast uncertainty, particularly for the short-range forecasts. Virus transmission models with accurate social network models are thus essential for improving epidemics forecasting.

The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries

The ongoing coronavirus disease 2019 (COVID-19) pandemic poses a severe threat to public health worldwide. We combine data on demography, contact patterns, disease severity, and health care capacity and quality to understand its impact and inform strategies for its control. Younger populations in lower-income countries may reduce overall risk, but limited health system capacity coupled with closer intergenerational contact largely negates this benefit. Mitigation strategies that slow but do not interrupt transmission will still lead to COVID-19 epidemics rapidly overwhelming health systems, with substantial excess deaths in lower-income countries resulting from the poorer health care available. Of countries that have undertaken suppression to date, lower-income countries have acted earlier. However, this will need to be maintained or triggered more frequently in these settings to keep below available health capacity, with associated detrimental consequences for the wider health, well-being, and economies of these countries.

The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries

The ongoing coronavirus disease 2019 (COVID-19) pandemic poses a severe threat to public health worldwide. We combine data on demography, contact patterns, disease severity, and health care capacity and quality to understand its impact and inform strategies for its control. Younger populations in lower-income countries may reduce overall risk, but limited health system capacity coupled with closer intergenerational contact largely negates this benefit. Mitigation strategies that slow but do not interrupt transmission will still lead to COVID-19 epidemics rapidly overwhelming health systems, with substantial excess deaths in lower-income countries resulting from the poorer health care available. Of countries that have undertaken suppression to date, lower-income countries have acted earlier. However, this will need to be maintained or triggered more frequently in these settings to keep below available health capacity, with associated detrimental consequences for the wider health, well-being, and economies of these countries.

Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.

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

Objective

Establishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19.

Results

We 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 R\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{0}$$\end{document}0. We incorporated location-specific physical distancing measures (e.g. school closure or at work) 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 physical 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).

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

OBJECTIVE

Establishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19.

RESULTS

We 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 R[Formula: see text]. We incorporated location-specific physical distancing measures (e.g. school closure or at work) 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 physical 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).

Defining adequate contact for transmission of Mycobacterium tuberculosis in an African urban environment

Background

The risk of infection from respiratory pathogens increases according to the contact rate between the infectious case and susceptible contact, but the definition of adequate contact for transmission is not standard. In this study we aimed to identify factors that can explain the level of contact between tuberculosis cases and their social networks in an African urban environment.

Methods

This was a cross-sectional study conducted in Kampala, Uganda from 2013 to 2017. We carried out an exploratory factor analysis (EFA) in social network data from tuberculosis cases and their contacts. We evaluated the factorability of the data to EFA using the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO). We used principal axis factoring with oblique rotation to extract and rotate the factors, then we calculated factor scores for each using the weighted sum scores method. We assessed construct validity of the factors by associating the factors with other variables related to social mixing.

Results

Tuberculosis cases (N = 120) listed their encounters with 1154 members of their social networks. Two factors were identified, the first named “Setting” captured 61% of the variance whereas the second, named ‘Relationship’ captured 21%. Median scores for the setting and relationship factors were 10.2 (IQR 7.0, 13.6) and 7.7 (IQR 6.4, 10.1) respectively. Setting and Relationship scores varied according to the age, gender, and nature of the relationship among tuberculosis cases and their contacts. Family members had a higher median setting score (13.8, IQR 11.6, 15.7) than non-family members (7.2, IQR 6.2, 9.4). The median relationship score in family members (9.9, IQR 7.6, 11.5) was also higher than in non-family members (6.9, IQR 5.6, 8.1). For both factors, household contacts had higher scores than extra-household contacts (p < .0001). Contacts of male cases had a lower setting score as opposed to contacts of female cases. In contrast, contacts of male and female cases had similar relationship scores.

Conclusions

In this large cross-sectional study from an urban African setting, we identified two factors that can assess adequate contact between tuberculosis cases and their social network members. These findings also confirm the complexity and heterogeneity of social mixing.

Spatiotemporal heterogeneity of social contact patterns related to infectious diseases in the Guangdong Province, China

The social contact patterns associated with the infectious disease transmitted by airborne droplets or close contact follow specific rules. Understanding these processes can improve the accuracy of disease transmission models, permitting their integration into model simulations. In this study, we performed a large-scale population-based survey to collect social contact patterns in three cities on the Pearl River Delta of China in winter and summer. A total of 5,818 participants were face-to-face interviewed and 35,542 contacts were recorded. The average number of contacts per person each day was 16.7 considering supplementary professional contacts (SPCs). Contacts that occurred on a daily basis, lasted more than 4 hours, and took place in households were more likely to involve physical contact. The seasonal characteristics of social contact were heterogeneous, such that contact in the winter was more likely to involve physical contact compared to summer months. The spatial characteristics of the contacts were similar. Social mixing patterns differed according to age, but all ages maintained regular contact with their peers. Taken together, these findings describe the spatiotemporal distribution of social contact patterns relevant to infections in the Guangdong Province of China. This information provides important parameters for mathematical models of infectious diseases.

Contact Mixing Patterns and Population Movement among Migrant Workers in an Urban Setting in Thailand

Data relating to contact mixing patterns among humans are essential for the accurate modeling of infectious disease transmission dynamics. Here, we describe contact mixing patterns among migrant workers in urban settings in Thailand, based on a survey of 369 migrant workers of three nationalities. Respondents recorded their demographic data, including age, sex, nationality, workplace, income, and education. Each respondent chose a single day to record their contacts; this resulted in a total of more than 8300 contacts. The characteristics of contacts were recorded, including their age, sex, nationality, location of contact, and occurrence of physical contact. More than 75% of all contacts occurred among migrants aged 15 to 39 years. The contacts were highly clustered in this age group among migrant workers of all three nationalities. There were far fewer contacts between migrant workers with younger and older age groups. The pattern varied slightly among different nationalities, which was mostly dependent upon the types of jobs taken. Half of migrant workers always returned to their home country at most once a year and on a seasonal basis. The present study has helped us gain a better understanding of contact mixing patterns among migrant workers in urban settings. This information is useful both when simulating disease epidemics and for guiding optimal disease control strategies among this vulnerable section of the population.

Development of a Social Contact Survey Instrument Relevant to the Spread of Infectious Disease and Its Application in a Pilot Study Among Korean Adults

OBJECTIVES

This study aimed to develop a valid social contact survey instrument and to verify its feasibility for use among Korean adults.

METHODS

The Delphi technique was used to develop an instrument to assess social contacts, which was then applied in a cross-sectional pilot study. A panel of 15 medical professionals reviewed the feasibility and validity of each item. The minimum content validity ratio was 0.49. Thirty participants used the developed measure to record contacts during a 24-hour period.

RESULTS

After a systematic review, the survey instrument (parts I and II) was developed. Part I assessed social contact patterns over a 24-hour period, and part II assessed perceptions of contacts in daily life and preventive behaviors (hand hygiene and coughing etiquette). High validity and feasibility were found. In the pilot study, the 30 participants had a combined total of 198 contacts (mean, 6.6 daily contacts per person). The participants' age (p=0.012), occupation (p&lt;0.001), household size (p&lt;0.001), education (p&lt;0.001), personal income (p=0.003), and household income (p&lt;0.001) were significantly associated with the number of contacts. Contacts at home, of long duration, and of daily frequency were relatively likely to be physical. Assortative mixing was observed between individuals in their 20s and 50s. Contact type differed by location, duration, and frequency (p&lt;0.001).

CONCLUSIONS

The developed social contact survey instrument demonstrated high validity and feasibility, suggesting that it is viable for implementation.

Droplet-Transmitted Infection Risk Ranking Based on Close Proximity Interaction

We propose an automatic method to identify people who are potentially-infected by droplet-transmitted diseases. This high-risk group of infection was previously identified by conducting large-scale visits/interviews, or manually screening among tons of recorded surveillance videos. Both are time-intensive and most likely to delay the control of communicable diseases like influenza. In this paper, we address this challenge by solving a multi-tasking problem from the captured surveillance videos. This multi-tasking framework aims to model the principle of Close Proximity Interaction and thus infer the infection risk of individuals. The complete workflow includes three essential sub-tasks: (1) person re-identification (REID), to identify the diagnosed patient and infected individuals across different cameras, (2) depth estimation, to provide a spatial knowledge of the captured environment, (3) pose estimation, to evaluate the distance between the diagnosed and potentially-infected subjects. Our method significantly reduces the time and labor costs. We demonstrate the advantages of high accuracy and efficiency of our method. Our method is expected to be effective in accelerating the process of identifying the potentially infected group and ultimately contribute to the well-being of public health.

Patterns of human social contact and contact with animals in Shanghai, China

East Asia is as a principal hotspot for emerging zoonotic infections. Understanding the likely pathways for their emergence and spread requires knowledge on human-human and human-animal contacts, but such studies are rare. We used self-completed and interviewer-completed contact diaries to quantify patterns of these contacts for 965 individuals in 2017/2018 in a high-income densely-populated area of China, Shanghai City. Interviewer-completed diaries recorded more social contacts (19.3 vs. 18.0) and longer social contact duration (35.0 vs. 29.1 hours) than self-reporting. Strong age-assortativity was observed in all age groups especially among young participants (aged 7-20) and middle aged participants (25-55 years). 17.7% of participants reported touching animals (15.3% (pets), 0.0% (poultry) and 0.1% (livestock)). Human-human contact was very frequent but contact with animals (especially poultry) was rare although associated with frequent human-human contact. Hence, this densely populated area is more likely to act as an accelerator for human-human spread but less likely to be at the source of a zoonosis outbreak. We also propose that telephone interview at the end of reporting day is a potential improvement of the design of future contact surveys.

Reactive school closure weakens the network of social interactions and reduces the spread of influenza

School-closure policies are considered one of the most promising nonpharmaceutical interventions for mitigating seasonal and pandemic influenza. However, their effectiveness is still debated, primarily due to the lack of empirical evidence about the behavior of the population during the implementation of the policy. Over the course of the 2015 to 2016 influenza season in Russia, we performed a diary-based contact survey to estimate the patterns of social interactions before and during the implementation of reactive school-closure strategies. We develop an innovative hybrid survey-modeling framework to estimate the time-varying network of human social interactions. By integrating this network with an infection transmission model, we reduce the uncertainty surrounding the impact of school-closure policies in mitigating the spread of influenza. When the school-closure policy is in place, we measure a significant reduction in the number of contacts made by students (14.2 vs. 6.5 contacts per day) and workers (11.2 vs. 8.7 contacts per day). This reduction is not offset by the measured increase in the number of contacts between students and nonhousehold relatives. Model simulations suggest that gradual reactive school-closure policies based on monitoring student absenteeism rates are capable of mitigating influenza spread. We estimate that without the implemented reactive strategies the attack rate of the 2015 to 2016 influenza season would have been 33% larger. Our study sheds light on the social mixing patterns of the population during the implementation of reactive school closures and provides key instruments for future cost-effectiveness analyses of school-closure policies.

Quantifying heterogeneous contact patterns in Japan: a social contact survey

BACKGROUND

Social contact surveys can greatly help in quantifying the heterogeneous patterns of infectious disease transmission. The present study aimed to conduct a contact survey in Japan, offering estimates of contact by age and location and validating a social contact matrix using a seroepidemiological dataset of influenza.

METHODS

An internet-based questionnaire survey was conducted, covering all 47 prefectures in Japan and including a total of 1476 households. The social contact matrix was quantified assuming reciprocity and using the maximum likelihood method. By imposing several parametric assumptions for the next-generation matrix, the empirical seroepidemiological data of influenza A (H1N1) 2009 was analysed and we estimated the basic reproduction number, R0.

RESULTS

In total, the reported number of contacts on weekdays was 10,682 whereas that on weekend days was 8867. Strong age-dependent assortativity was identified. Forty percent of weekday contacts took place at schools or workplaces, but that declined to 14% on weekends. Accounting for the age-dependent heterogeneity with the known social contact matrix, the minimum value of the Akaike information criterion was obtained and R0 was estimated at 1.45 (95% confidence interval: 1.42, 1.49).

CONCLUSIONS

Survey datasets will be useful for parameterizing the heterogeneous transmission model of various directly transmitted infectious diseases in Japan. Age-dependent assortativity, especially among children, along with numerous contacts in school settings on weekdays implies the potential effectiveness of school closure.

Projecting social contact matrices to different demographic structures

The modeling of large-scale communicable epidemics has greatly benefited in the last years from the increasing availability of highly detailed data. Particullarly, in order to achieve quantitative descriptions of the evolution of epidemics, contact networks and mixing patterns are key. These heterogeneous patterns depend on several factors such as location, socioeconomic conditions, time, and age. This last factor has been shown to encapsulate a large fraction of the observed inter-individual variation in contact patterns, an observation validated by different measurements of age-dependent contact matrices. Recently, several works have studied how to project those matrices to areas where empirical data are not available. However, the dependence of contact matrices on demographic structures and their time evolution has been largely neglected. In this work, we tackle the problem of how to transform an empirical contact matrix that has been obtained for a given demographic structure into a different contact matrix that is compatible with a different demography. The methodology discussed here allows to extrapolate a contact structure measured in a particular area to any other whose demographic structure is known, as well as to obtain the time evolution of contact matrices as a function of the demographic dynamics of the populations they refer to. To quantify the effect of considering time-dynamics of contact patterns on disease modeling, we implemented a Susceptible-Exposed-Infected-Recovered (SEIR) model on 16 different countries and regions and evaluated the impact of neglecting the temporal evolution of mixing patterns. Our results show that simulated disease incidence rates, both at the aggregated and age-specific levels, are significantly dependent on contact structures variation driven by demographic evolution. The present work opens the path to eliminate technical biases from model-based impact evaluations of future epidemic threats and warns against the use of contact matrices to model diseases without correcting for demographic evolution or geographic variations.

Large scale epidemic outbreaks represent an ever increasing threat to humankind. In order to anticipate eventual pandemics, mathematical modeling should not only have the capacity to model in real time an ongoing disease, but also to predict the evolution of potential outbreaks in different locations and times. To this end, computational frameworks need to incorporate, among other ingredients, realistic contact patterns into the models. This not only implies anticipating the demographic structure of the populations under study, but also understanding how demographic evolution reshapes social mixing patterns along time. Here we present a mathematical framework to solve this problem and test our modeling approach on 16 different empirical contact matrices. We also evaluate the impact of an eventual future outbreak by simulating a SEIR scenario in the countries and regions analyzed. Our results show that using outdated or imported contact matrices that do not take into account demographic structure or its evolution can lead to largely misleading conclusions.

Close encounters between infants and household members measured through wearable proximity sensors

Describing and understanding close proximity interactions between infant and family members can provide key information on transmission opportunities of respiratory infections within households. Among respiratory infections, pertussis represents a public health priority. Pertussis infection can be particularly harmful to young, unvaccinated infants and for these patients, family members represent the main sources of transmission. Here, we report on the use of wearable proximity sensors based on RFID technology to measure face-to-face proximity between family members within 16 households with infants younger than 6 months for 2-5 consecutive days of data collection. The sensors were deployed over the course of approximately 1 year, in the context of a national research project aimed at the improvement of infant pertussis prevention strategies. We investigated differences in close-range interactions between family members and we assessed whether demographic variables or feeding practices affect contact patterns between parents and infants. A total of 5,958 contact events were recorded between 55 individuals: 16 infants, 4 siblings, 31 parents and 4 grandparents. The aggregated contact networks, obtained for each household, showed a heterogeneous distribution of the cumulative time spent in proximity with the infant by family members. Contact matrices defined by age and by family role showed that most of the contacts occurred between the infant and other family members (70%), while 30% of contacts was among family members (infants excluded). Many contacts were observed between infants and adults, in particular between infant and mother, followed by father, siblings and grandparents. A larger number of contacts and longer contact durations between infant and other family members were observed in families adopting exclusive breastfeeding, compared to families in which the infant receives artificial or mixed feeding. Our results demonstrate how a high-resolution measurement of contact matrices within infants' households is feasible using wearable proximity sensing devices. Moreover, our findings suggest the mother is responsible for the large majority of the infant's contact pattern, thus being the main potential source of infection for a transmissible disease. As the contribution to the infants' contact pattern by other family members is very variable, vaccination against pertussis during pregnancy is probably the best strategy to protect young, unvaccinated infants.

Temporal variation of human encounters and the number of locations in which they occur: a longitudinal study of Hong Kong residents

Patterns of social contact between individuals are important for the transmission of many pathogens and shaping patterns of immunity at the population scale. To refine our understanding of how human social behaviour may change over time, we conducted a longitudinal study of Hong Kong residents. We recorded the social contact patterns for 1450 individuals, up to four times each between May 2012 and September 2013. We found individuals made contact with an average of 12.5 people within 2.9 geographical locations, and spent an average estimated total duration of 9.1 h in contact with others during a day. Distributions of the number of contacts and locations in which contacts were made were not significantly different between study waves. Encounters were assortative by age, and the age mixing pattern was broadly consistent across study waves. Fitting regression models, we examined the association of contact rates (number of contacts, total duration of contact, number of locations) with covariates and calculated the inter- and intra-participant variation in contact rates. Participant age was significantly associated with the number of contacts made, the total duration of contact and the number of locations in which contact occurred, with children and parental-age adults having the highest rates of contact. The number of contacts and contact duration increased with the number of contact locations. Intra-individual variation in contact rate was consistently greater than inter-individual variation. Despite substantial individual-level variation, remarkable consistency was observed in contact mixing at the population scale. This suggests that aggregate measures of mixing behaviour derived from cross-sectional information may be appropriate for population-scale modelling purposes, and that if more detailed models of social interactions are required for improved public health modelling, further studies are needed to understand the social processes driving intra-individual variation.