Social contact patterns and implications for infectious disease transmission: a systematic review and meta-analysis of contact surveys

Social contact patterns and their impact on the transmission of respiratory pathogens in rural China

Introduction

Social contact patterns significantly influence the transmission dynamics of respiratory pathogens. Previous surveys have quantified human social contact patterns, yielding heterogeneous results across different locations. However, significant gaps remain in understanding social contact patterns in rural areas of China.

Methods

We conducted a pioneering study to quantify social contact patterns in Anhua County, Hunan Province, China, from June to October 2021, when there were minimal coronavirus disease-related restrictions in the area. Additionally, we simulated the epidemics under different assumptions regarding the relative transmission risks of various contact types (e.g., indoor versus outdoor, and physical versus non-physical).

Results

Participants reported an average of 12.0 contacts per day (95% confidence interval: 11.3-12.6), with a significantly higher number of indoor contacts compared to outdoor contacts. The number of contacts was associated with various socio-demographic characteristics, including age, education level, income, household size, and travel patterns. Contact patterns were assortative by age and varied based on the type of contact (e.g., physical versus non-physical). The reproduction number, daily incidence, and infection attack rate of simulated epidemics were remarkably stable.

Discussion

We found many intergenerational households and contacts that pose challenges in preventing and controlling infections among the elderly in rural China. Our study also underscores the importance of integrating various types of contact pattern data into epidemiological models and provides guidance to public health authorities and other major stakeholders in preparing and responding to infectious disease threats in rural China.

Why gender and sex matter in infectious disease modelling: A conceptual framework

The COVID-19 pandemic underscored the differential impact of infectious diseases across population groups, with gender and sex identified as important dimensions influencing transmission and health outcomes. Sex-related biological factors, such as differences in immune response and comorbidities, contribute to men's heightened severity risks, while gender norms and roles influence exposure patterns, adherence to prevention measures, and healthcare access, influencing women's higher reported infection rates in certain contexts. Despite widely observed gender/sex disparities, infectious disease models frequently overlook gender and sex as key dimensions, leading to gaps in understanding and potential blind spots in public health interventions. This paper develops a conceptual framework based on the Susceptible-Exposed-Infectious-Recovered/Deceased (SEIR/D) compartmental model to map pathways through which gender and sex may influence susceptibility, exposure, transmission, recovery, and mortality. Using a narrative review of modelling, epidemiological, and clinical studies, this framework identifies and characterises the main social and biological mechanisms on this matter-including gendered occupational exposure, differential adherence to preventive measures, and disparities in healthcare-seeking behaviour-alongside sex-based differences in immune response and disease severity. The framework also examines potential gender-related variations in epidemiological surveillance data, highlighting disparities in testing uptake and hospitalisation referrals that could influence model outputs. By synthesising these insights, this paper provides a theoretical foundation for integrating gender and sex into infectious disease models. It advocates for interdisciplinary collaboration between modellers, social scientists, and clinicians to advance gender- and sex-sensitive modelling approaches. Accounting for gender and sex can enhance predictive accuracy, inform intervention strategies, and promote health equity in pandemic response.

"Everything had stopped, no meeting, no gathering": Social interactions during the COVID-19 pandemic in the Central African Republic, the Democratic Republic of Congo, and Bangladesh

Understanding the spread of COVID-19 in humanitarian and fragile settings is challenging for many reasons, including the lack of data on social dynamics and preventive behaviors during an epidemic. We investigate social interactions in three such settings - Democratic Republic of the Congo (DRC), Central African Republic (CAR), Cox's Bazar (CXB), Bangladesh - and how they changed during the first year of the pandemic. This comparative mixed-methods study uses a representative household survey and focus group discussions or key informant interviews in each site. Descriptive weighted analysis of survey responses was conducted; multivariate logistic regression identified factors associated with changes in social interactions. Thematic analysis was conducted on qualitative data. Nearly all participants had social interactions the day before the survey, although the average number of daily interactions was low. Interactions primarily occurred indoors, at home and without masks. We saw a discrepancy between knowledge about and practice of preventive behaviors. Most respondents reported interacting less often (77.3% CXB, 86.7% CAR, 58.8% DRC) and having shorter meetings (80% CXB, 77.8% CAR, and 47.8% DRC). Reluctance towards the COVID-19 vaccine was a risk factor for non-compliant behaviors in CAR (OR increased frequency = 3.51, 95%CI = 1.41-8.75; OR increased duration = 2.47, 95%CI = 1.15-5.29) and DRC (OR increased duration = 3.06, 95%CI = 1.71-5.49), likely pointing to distrust towards institutional policies. Respondents from IDP communities in DRC were less likely to reduce the frequency of interaction, likely because living conditions did not facilitate physical distancing. Increased knowledge in CXB was associated with compliant behavior (for 1pt-increase: OR increased frequency = 0.47, 95%CI = 0.32-0.68; OR increased duration = 0.46, 95%CI = 0.31-0.69). Understanding social dynamics is fundamental to predict infectious disease spread, particularly in humanitarian settings. More evidence is needed to understand behaviors influencing disease dynamics and drivers of behaviors, including trust in authorities, social, and economic factors. Peace, community engagement, and reduction of misinformation remain critical for epidemic responses in humanitarian settings.

Rhinosinusitis: Evidence and experience - 2024

It has been 10-years since the publication of Rhinosinusitis: evidence and experience, and since then a lot has changed in our understanding of the disease. Advances in pathophysiology, endotyping and new treatments such as biologics brought a new era in the management of our patients. This new guideline, developed jointly by ABR and ABORL-CCF, with the help of ASBAI presents an updated, evidence-based approach to the different forms of rhinosinusitis that aims to improve the diagnosis and treatment of this complex disease. The document covers a wide range of topics, including clear definitions of the different stages of acute sinusitis. It also introduces a new term called Prolonged Acute Viral Rhinosinusitis. Reviews phenotypes and endotypes of chronic rhinosinusitis, recommending methods for clinical and laboratory investigation, clinical and surgical treatment. We also discuss in detail fungal sinusitis and pediatric sinusitis. The objective of this updated Consensus is to clarify some already established and recent concepts, highlighting the importance of an accurate diagnosis to promote treatment approaches that reflect the best practices based on solid evidence. Therefore, we seek not only to improve the results of patients care, but also to guide thealth professionals through a clinical panorama that is in constant transformation.

Immunity Debt for Seasonal Influenza After the COVID-19 Pandemic and as a Result of Nonpharmaceutical Interventions: An Ecological Analysis and Cohort Study

Non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic significantly reduced influenza transmission. This study explores the hypothesis of "immunity debt" which suggests increased vulnerability to influenza following reduced exposure during the pandemic. World Health Organization aggregated data on influenza from 116 countries and its association with NPI intensity as measured by the COVID-19 Stringency Index is analyzed. Where individual-level data available (France, the United Kingdom, Spain, Italy, Belgium, and Romania), the analyses of influenza monthly rates in six European countries (France, the United Kingdom, Spain, Italy, Belgium, and Romania) are replicated. The results indicate globally a 46.3% (95% CI: 15.79-70.78%) reduction in influenza cases during COVID-19 restrictions in the winter season, followed by a 131.7% (95% CI: 34.95-255.78%) increase in the first postrelaxation winter and a 161.2% (95% CI: 31.88-382.16%) increase in the summer as compared to the predicted level based on historical influenza epidemic trends. In addition, a positive association between the Stringency Index and post-relaxation influenza surge is observed globally (R2 = 0.14-0.17) and replicated regionally. The findings support the population immunity debt hypothesis for influenza and call for proactive preparations against its consequences in future pandemics.

Changes in social contact patterns in Germany during the SARS-CoV-2 pandemic - an analysis based on the COVIMOD study

BACKGROUND

During the SARS-CoV-2 pandemic, Germany employed several nonpharmaceutical interventions (NPIs) to reduce social contacts and decelerate the virus's spread. Associations between demographics and other factors, e.g. perceived pandemic threat level, might help explain variations in social contact behaviours. We aimed to estimate contact numbers during the pandemic in Germany and assess factors associated with changes therein.

METHODS

Between 04/2020 and 12/2021, we conducted an online contact survey (COVIMOD) with 33 waves in Germany. We calculated the mean and 95% confidence interval of daily reported contacts ("people who you met in person and with whom you exchanged at least a few words, or with whom you had physical contact") using bootstrapping. The effects of different factors on the number of contacts were determined by fitting generalized additive models (GAMs).

RESULTS

The COVIMOD survey recorded 59,585 responses from 7,851 participants across Germany. The overall mean number of daily social contacts during the study period was 3.30 (95%CI: 3.23-3.38), with the number of non-household contacts being twice as high as the number of contacts with household members. The lowest overall number of contacts (2.11, 95%CI: 2.01-2.22) was reported during Germany's strongest contact reduction campaigns (end of 04/2020), when the number of household contacts was three times higher than non-household contacts. The highest number of contacts (6.38, 95%CI: 5.67-7.15) was observed during periods of relaxed measures (June 2020), when household contacts were four times fewer than non-household contacts. The work and school contacts shaped the overall variation of contact patterns in Germany during the pandemic. In participants under 18 years, partially/fully closing schools reduced school contacts by 83% (95%CI: 80-85%) and overall contacts by 39% (95%CI: 36-42%). Higher risk perceptions regarding COVID-19 were associated with 11% (95% CI: 2-17%) more social contacts among all participants and 66% (95%CI: 32-108%) more work contacts in the adult participants.

CONCLUSIONS

Our study revealed fluctuations in the number of social contacts during the SARS-CoV-2 pandemic in Germany, with substantial variations influenced by NPIs and individual factors. Understanding these factors affecting social contacts is vital for refining disease transmission models and informing future pandemic response strategies.

The effect of COVID-19 vaccination on change in contact and implications for transmission

BACKGROUND

Monitoring human behavior as epidemic intelligence can critically complement traditional surveillance systems during epidemics. Retrospective analysis of novel behavioral data streams initiated during the COVID-19 pandemic help illustrate their utility. During the pandemic, behavior changed rapidly and was increasingly influenced by individual choice in response to changes such as newly available vaccines. Vaccines provided substantial protection against severe disease and deaths; however, their effect on behavior is understudied and it is unclear if vaccine effects against infection fully offset relaxation of social distancing behaviors.

METHODS & RESULTS

We analyzed data from a longitudinal cohort sampled from U.S. households that measured contact rates, risk mitigation and COVID-19 vaccination status between August 2020-April 2022. Contact rates universally increased across survey rounds among all sociodemographic groups, but unvaccinated individuals had persistently higher contact rates. Using a multilevel generalized linear mixed effects model, we found that individuals who newly completed a primary vaccine series had an additional increase of 1.93 (95 % CI: 0.27-3.59) contacts compared to individuals who remained unvaccinated. Using observed contact rates to estimate transmission, we found that observed increases in contact rates were not fully offset by vaccine protection against infection, but transmission was still maintained below levels without distancing and vaccination despite clusters of individuals with high contact and no vaccination.

CONCLUSION

We estimated changes in contact rates following vaccination and inferred the joint effect of changes in vaccination and contacts on population-level transmission, finding that observed increases in contact rates were not fully offset by vaccine effects. Our work highlights the potential utility of ongoing longitudinal monitoring of contact patterns during epidemics.

Dissecting transmission to understand parasite evolution

Parasite transmission is a complex, multi-stage process that significantly impacts host-parasite dynamics. Transmission plays a key role in epidemiology and virulence evolution, where it is expected to trade off with virulence. However, the extent to which classical models on virulence-transmission relationships apply in the real world is unclear. This insight piece proposes a novel framework that breaks transmission into three distinct stages: within-host infectiousness, an intermediate between-host stage (biotic or abiotic), and new host infection. Each stage is influenced by intrinsic and extrinsic factors to the parasite, which together will determine its transmission success. Analyzing the transmission stages separately and how they affect each other might enhance our understanding of which host-, parasite- or environmental-driven factors might shape parasite evolution and inform us about new effectors to act on when designing disease control strategies.

Social contacts and mixing patterns in rural Gambia

BACKGROUND

Close contact between an infectious and susceptible person is an important factor in respiratory disease transmission. Information on social contacts and mixing patterns in a population is crucial to understanding transmission patterns and informing transmission models of respiratory infections. Although West Africa has one of the highest burdens of respiratory infections, there is a lack of data on interpersonal contact and mixing patterns in this region.

METHODS

Between January and November 2022, we conducted a cross-sectional, social contact survey within the population of the Central and Upper River Regions of The Gambia. Selected participants completed a questionnaire about their travel history and social contacts, detailing the number, intensity, location, frequency, duration, and age of contacts. We calculated age-standardized contact matrices to determine contact patterns in the population.

RESULTS

Overall, individuals made an average of 12.7 (95% CI: 12.4-13.0) contacts per day. Contact patterns were mostly age-assortative and 84.5% of all contacts were physical. School-aged children (5-14 years) had the highest mean number of physical contacts (11.3, 95% CI: 10.9-11.8) while the < 1-year age group had the fewest contacts (9.4, 95% CI: 9.1-9.8). A large proportion of contacts (78%) occurred at home. Daily number of contacts increased with household size. While we did not observe any effect of gender on contact patterns, there were seasonal variations in contact type. Non-physical contacts were higher during the dry season compared to the rainy season. In contrast, there were more physical contacts in the rainy season compared to the dry season.

CONCLUSIONS

In rural Gambia, social contact patterns were primarily driven by household mixing. Most contacts were physical and mostly age-assortative, particularly among school-aged children. Our data can improve infectious disease transmission models of respiratory pathogens in high-transmission settings, which are valuable for optimizing the delivery of different interventions.

Evolution of social contacts patterns in France over the SARS-CoV-2 pandemic: results from the SocialCov survey

BACKGROUND

Non-pharmaceutical measures such as lockdowns, curfews and place closures were implemented in France during 2020-2022 to reduce contacts in the population, to limit the spread of SARS-CoV-2 and reduce COVID-19 healthcare burden. Individuals also changed their behaviours as a response to the pandemic. Here, we present the results of the SocialCov survey that characterise the evolution of contacts in France between December 2020 and May 2022 to better understand the short and long term impact of these interventions on social mixing.

METHODS

A questionnaire was advertised over six independent communication campaigns through the governmental application TousAntiCovid between December 2020 and June 2022. Participants were asked to detail social contacts in the previous day, including contact age, location, duration and type (physical/conversational).

RESULTS

Over the six distinct campaigns, 44,396 individuals participated in the survey, declaring 300,735 contacts in total. The patterns of contacts strongly evolved over time, along with the progressive easing of national mitigation measures. The number of contacts in the French population increased from 5.3 contacts per day on average in December 2020 to 9.7 in May 2022. Mixing patterns were affected by age of participants, holidays and weekends. Healthcare workers declared 18.4 contacts on average during working days, roughly twice more than other workers. Reported risk perception changed throughout the two year period.

CONCLUSIONS

Results provide a detailed picture of contact evolution over the years 2020-2022 in France. In addition to a major evolution of contact density over time, this study highlights strong heterogeneities in contact patterns according to age, employment and weekend/vacation periods. The contact matrices provided here can be used to inform age-stratified transmission models of respiratory pathogens in the context of implementation of multiple non-pharmaceutical measures.

Within-country heterogeneity in patterns of social contact relevant for tuberculosis infection transmission, prevention, and care

Mycobacterium tuberculosis (Mtb) transmission is driven by variable social, environmental, and biological factors, including the number and duration of indoor contacts. Social contact data can provide information on potential transmission patterns, but is underutilised outside the field of mathematical modelling. We explore three contexts where contact data can provide valuable insights: 1) household contact tracing; 2) infection prevention and control measures (IPC) in congregate settings; and 3) contamination in cluster randomised trials (CRTs). A social contact survey was conducted in three communities with comparable population sizes in South Africa: an urban township and peri-urban and rural clinic catchment areas. Participants reported congregate settings visited over 24-hours, visit durations, and estimated numbers of people present. To correspond with the three contexts, we estimated the proportion of contact hours occurring 1) within the home; 2) in congregate settings outside the home; and 3) outside the participants' communities. Participants reported a mean of 27.0 (rural), 55.2 (peri-urban), and 73.0 (urban) contact hours. The proportion within the home was similar among rural and peri-urban participants (76.8% and 71.7%), compared to urban (48.6%). Congregate settings visited varied; urban participants spent the most contact hours in retail/office settings (19.9%), peri-urban participants in community-service buildings (20.4%), and rural participants in other peoples' homes (25.5%). Urban participants reported the highest proportion of contact outside the community (67.0%) compared to rural (38.8%) and peri-urban (21.5%) participants. The heterogeneity in contact patterns has implications for TB interventions. Household contact tracing may be most effective in the rural community where household contact was highest. The diverse range of congregate settings visited suggests that prioritising IPC measures in these locations may enhance their overall efficacy. Considering contact patterns when designing clusters may reduce contamination risk in CRTs. Tailored interventions, informed by local contexts, are essential to reduce TB burden.

Characterizing US contact patterns relevant to respiratory transmission from a pandemic to baseline: Analysis of a large cross-sectional survey

Background

Contact plays a critical role in infectious disease transmission. Characterizing heterogeneity in contact patterns across individuals, time, and space is necessary to inform accurate estimates of transmission risk, particularly to explain superspreading, predict age differences in vulnerability, and inform social distancing policies. Current respiratory disease models often rely on data from the 2008 POLYMOD study conducted in Europe, which is now outdated and potentially unrepresentative of behavior in the US. We seek to understand the variation in contact patterns across time, spatial scales, and demographic and social classifications, and what social behavior looks like at baseline in the absence of an ongoing pandemic.

Methods

We analyze spatiotemporal non-household contact patterns across 10.7 million survey responses from June 2020 - April 2021 post-stratified on age and gender to correct for sample representation. To characterize spatiotemporal heterogeneity in respiratory contact patterns at the county-week scale, we use generalized additive models. In the absence of non-pandemic US contact data, we employ a regression approach to estimate baseline contact and address this gap.

Findings

Although contact patterns varied over time during the pandemic, contact is relatively stable after controlling for disease. We find that the mean number of non-household contacts is spatially heterogeneous regardless of disease. There is additional heterogeneity across age, gender, race/ethnicity, and contact setting, with mean contact decreasing with age and lower in women. The contacts of White individuals and contacts at work or social events change the most under increased national incidence.

Interpretation

We develop the first county-level estimates of non-pandemic contact rates for the US that can fill critical gaps in parameterizing future disease models. Our results identify that spatiotemporal, demographic, and social heterogeneity in contact patterns is highly structured, informing the risk landscape of respiratory infectious disease transmission in the US.

Funding

Research reported in this publication was supported by the National Institutes of Health under award number R01GM123007 and R35GM153478 (SB).

Addressing current limitations of household transmission studies by collecting contact data

Modeling studies of household transmission data have helped characterize the role of children in influenza and coronavirus disease 2019 (COVID-19) epidemics. However, estimates from these studies may be biased since they do not account for the heterogeneous nature of household contacts. Here, we quantified the impact of contact heterogeneity between household members on the estimation of child relative susceptibility and infectivity. We simulated epidemics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like and influenza virus-like infections in a synthetic population of 1000 households, assuming heterogeneous contact levels. Relative contact frequencies were derived from a household contact study according to which contacts are more frequent in the father-mother pair, followed by the child-mother, child-child, and finally child-father pairs. Child susceptibility and infectivity were then estimated while accounting for heterogeneous contacts or not. When ignoring contact heterogeneity, child relative susceptibility was underestimated by approximately 20% in the two disease scenarios. Child relative infectivity was underestimated by 20% when children and adults had different infectivity levels. These results are sensitive to our assumptions of European-style household contact patterns; but they highlight that household studies collecting both disease and contact data are needed to assess the role of complex household contact behavior on disease transmission and improve estimation of key biological parameters.

Directly observed social contact patterns among school children in rural Gambia

INTRODUCTION

School-aged children play a major role in the transmission of many respiratory pathogens due to high rate of close contacts in schools. The validity and accuracy of proxy-reported contact data may be limited, particularly for children when attending school. We observed social contacts within schools and assessed the accuracy of proxy-reported versus observed physical contact data among students in rural Gambia.

METHODS

We enrolled school children who had also been recruited to a survey of Streptococcus pneumoniae carriage and social contacts. We visited participants at school and observed their contact patterns within and outside the classroom for two hours. We recorded the contact type, gender and approximate age of the contactee, and class size. We calculated age-stratified contact matrices to determine in-school contact patterns. We compared proxy-reported estimated physical contacts for the subset of participants (18 %) randomised to be observed on the same day for which the parent or caregiver reported the school contacts.

RESULTS

We recorded 3822 contacts for 219 participants from 114 schools. The median number of contacts was 15 (IQR: 11-20). Contact patterns were strongly age-assortative, and mainly involved physical touch (67.5 %). Those aged 5-9 years had the highest mean number of contacts [19.0 (95 %CI: 16.7-21.3)] while the ≥ 15-year age group had fewer contacts [12.8 (95 %CI: 10.9-14.7)]. Forty (18 %) participants had their school-observed contact data collected on the same day as their caregiver reported their estimated physical contacts at school; only 22.5 % had agreement within ±2 contacts between the observed and reported contacts. Fifty-eight percent of proxy-reported contacts were under-estimates.

CONCLUSIONS

Social contact rates observed among pupils at schools in rural Gambia were high, strongly age-assortative, and physical. Reporting of school contacts by proxies may underestimate the effect of school-age children in modelling studies of transmission of infections. New approaches are needed to quantify contacts within schools.

Modelling vaccination approaches for mpox containment and mitigation in the Democratic Republic of the Congo

BACKGROUND

Mpox was first identified in the Democratic Republic of the Congo (DRC) in 1970. In 2023, a historic outbreak of mpox occurred in the country, continuing into 2024. Over 14 000 cases and 600 deaths were reported in 2023 alone, representing a major increase from previous outbreaks. The modified vaccinia Ankara vaccine (brand names JYNNEOS, Imvamune, and Imvanex) was used in the 2022 mpox outbreak in the USA and Europe. However, at the time of the study, vaccination had not been made available in the DRC. We aimed to inform policy and decision makers on the potential benefits of, and resources needed, for mpox vaccination campaigns in the DRC by providing counterfactual scenarios evaluating the short-term effects of various vaccination strategies on mpox cases and deaths, if such a vaccination campaign had been undertaken before the 2023-24 outbreak.

METHODS

A dynamic transmission model was used to simulate mpox transmission in the DRC, stratified by age (<5, 5-15, and >15 years) and province. The model was used to simulate potential vaccination strategies, varying by age and region (endemic provinces, non-endemic provinces with historic cases, and all provinces) assessing the effect the strategies would have on deaths and cases in an epidemic year similar to 2023. In addition, we estimated the number of vaccine doses needed to implement each strategy.

FINDINGS

Without vaccination, our model predicted 14 700 cases and 700 deaths from mpox over 365 days. Vaccinating 80% of all children younger than 5 years in endemic regions led to a 27% overall reduction in cases and a 43% reduction in deaths, requiring 10·5 million vaccine doses. Vaccinating 80% of all children younger than 5 years in all regions led to a 29% reduction in cases and a 43% reduction in deaths, requiring 33·1 million doses. Vaccinating 80% of children aged 15 years or younger in endemic provinces led to a 54% reduction in cases and a 71% reduction in deaths, requiring 26·6 million doses.

INTERPRETATION

When resources are limited, vaccinating children aged 15 years or younger, or younger than 5 years, in endemic regions of the DRC would be the most efficient use of vaccines. Further research is needed to explore long-term effects of a one-time or recurrent vaccination campaign.

FUNDING

Canadian Institutes of Health Research, Canadian International Development Research Centre, US Department of Defense (Defense Threat Reduction Agency, Mpox Threat Reduction Network), Global Affairs Canada (Weapons Threat Reduction Program), US Department for Agriculture (Agriculture Research Service, Non-Assistance Cooperative Agreement).

Generalized contact matrices allow integrating socioeconomic variables into epidemic models

Variables related to socioeconomic status (SES), including income, ethnicity, and education, shape contact structures and affect the spread of infectious diseases. However, these factors are often overlooked in epidemic models, which typically stratify social contacts by age and interaction contexts. Here, we introduce and study generalized contact matrices that stratify contacts across multiple dimensions. We demonstrate a lower-bound theorem proving that disregarding additional dimensions, besides age and context, might lead to an underestimation of the basic reproductive number. By using SES variables in both synthetic and empirical data, we illustrate how generalized contact matrices enhance epidemic models, capturing variations in behaviors such as heterogeneous levels of adherence to nonpharmaceutical interventions among demographic groups. Moreover, we highlight the importance of integrating SES traits into epidemic models, as neglecting them might lead to substantial misrepresentation of epidemic outcomes and dynamics. Our research contributes to the efforts aiming at incorporating socioeconomic and other dimensions into epidemic modeling.

Who Transmits Tuberculosis to Whom: A Cross-Sectional Analysis of a Cohort Study in Lima, Peru

Rationale: The persistent burden of tuberculosis (TB) disease emphasizes the need to identify individuals with TB for treatment and those at a high risk of incident TB for prevention. Targeting interventions toward those at high risk of developing and transmitting TB is a public health priority. Objectives: We aimed to identify characteristics of individuals involved in TB transmission in a community setting, which may guide the prioritization of targeted interventions. Methods: We collected clinical and sociodemographic data from a cohort of patients with TB in Lima, Peru. We used whole-genome sequencing data to assess the genetic distance between all possible pairs of patients; we considered pairs to be the result of a direct transmission event if they differed by three or fewer SNPs, and we assumed that the first diagnosed patient in a pair was the transmitter and the second was the recipient. We used logistic regression to examine the association between host factors and the likelihood of direct TB transmission. Measurements and Main Results: Analyzing data from 2,518 index patients with TB, we identified 1,447 direct transmission pairs. Regardless of recipient attributes, individuals less than 34 years old, males, and those with a history of incarceration had a higher likelihood of being transmitters in direct transmission pairs. Direct transmission was more likely when both patients were drinkers or smokers. Conclusions: This study identifies men, young adults, former prisoners, alcohol consumers, and smokers as priority groups for targeted interventions. Innovative strategies are needed to extend TB screening to social groups such as young adults and prisoners with limited access to routine preventive care.

An algorithm to build synthetic temporal contact networks based on close-proximity interactions data

Small populations (e.g., hospitals, schools or workplaces) are characterised by high contact heterogeneity and stochasticity affecting pathogen transmission dynamics. Empirical individual contact data provide unprecedented information to characterize such heterogeneity and are increasingly available, but are usually collected over a limited period, and can suffer from observation bias. We propose an algorithm to stochastically reconstruct realistic temporal networks from individual contact data in healthcare settings (HCS) and test this approach using real data previously collected in a long-term care facility (LTCF). Our algorithm generates full networks from recorded close-proximity interactions, using hourly inter-individual contact rates and information on individuals' wards, the categories of staff involved in contacts, and the frequency of recurring contacts. It also provides data augmentation by reconstructing contacts for days when some individuals are present in the HCS without having contacts recorded in the empirical data. Recording bias is formalized through an observation model, to allow direct comparison between the augmented and observed networks. We validate our algorithm using data collected during the i-Bird study, and compare the empirical and reconstructed networks. The algorithm was substantially more accurate to reproduce network characteristics than random graphs. The reconstructed networks reproduced well the assortativity by ward (first-third quartiles observed: 0.54-0.64; synthetic: 0.52-0.64) and the hourly staff and patient contact patterns. Importantly, the observed temporal correlation was also well reproduced (0.39-0.50 vs 0.37-0.44), indicating that our algorithm could recreate a realistic temporal structure. The algorithm consistently recreated unobserved contacts to generate full reconstructed networks for the LTCF. To conclude, we propose an approach to generate realistic temporal contact networks and reconstruct unobserved contacts from summary statistics computed using individual-level interaction networks. This could be applied and extended to generate contact networks to other HCS using limited empirical data, to subsequently inform individual-based epidemic models.

Contact patterns between index patients and their close contacts and assessing risk for COVID-19 transmission during different exposure time windows: a large retrospective observational study of 450 770 close contacts in Shanghai

ABSTRACT

Introduction

To characterise age-mixing patterns among index cases and contacts of COVID-19, and explore when patients are most infectious during the disease process.

Methods

This study examined all initial 90 885 confirmed index cases in Shanghai and their 450 770 close contacts. A generalised additive mixed model was used to analyse the associations of the number of close contacts with different demographic and clinical characteristics. The effect of different exposure time windows on the infection of close contacts was evaluated using a modified mixed-effects Poisson regression.

Results

Analysis of contacts indicated that 82 467 (18.29%; 95% CI 18.17%, 18.42%) were second-generation cases. Our result indicated the q-index was 0.300 (95% CI 0.298, 0.302) for overall contact matrix, and that assortativity was greatest for students (q-index=0.377; 95% CI 0.357, 0.396) and weakest for people working age not in the labour force (q-index=0.246; 95% CI 0.240, 0.252). The number of contacts was 4.96 individuals per index case (95% CI 4.86, 5.06). Contacts had a higher risk if they were exposed from 1 day before to 3 days after the onset of symptoms in the index patient, with a maximum at day 0 (adjusted relative risk (aRR)=1.52; 95% CI 1.30, 1.76). Contacts exposed from 3 days before to 3 days after an asymptomatic index case had a positive reverse transcriptase-PCR (RT-PCR) result had a higher risk, with a maximum on day 0 (aRR=1.48; 95% CI 1.37, 1.59).

Conclusions

The greatest assortativity was for students and weakest for people working age not in the labour force. Contact in the household was a significant contributor to the infection of close contacts. Contact tracing should focus on individuals who had contact soon before or soon after the onset of symptoms (or positive RT-PCR test) in the index case.

Social contacts patterns relevant to the transmission of infectious diseases in Suzhou, China following the COVID-19 epidemic

BACKGROUND

The COVID-19 pandemic has profoundly affected human social contact patterns, but there is limited understanding regarding the post-pandemic social contact patterns. Our objective is to quantitatively assess social contact patterns in Suzhou post-COVID-19.

METHODS

We employed a diary design and conducted social contact surveys from June to October 2023, utilizing paper questionnaires. A generalized linear model was utilized to analyze the relationship between individual contacts and covariates. We examined the proportions of contact type, location, duration, and frequency. Additionally, age-related mixed matrices were established.

RESULTS

The participants reported an average of 11.51 (SD 5.96) contact numbers and a total of 19.78 (SD 20.94) contact numbers per day, respectively. The number of contacts was significantly associated with age, household size, and the type of week. Compared to the 0-9 age group, those in the 10-19 age group reported a higher number of contacts (IRR = 1.12, CI: 1.01-1.24), while participants aged 20 and older reported fewer (IRR range: 0.54-0.67). Larger households (5 or more) reported more contacts (IRR = 1.09, CI: 1.01-1.18) and fewer contacts were reported on weekends (IRR = 0.95, CI: 0.90-0.99). School had the highest proportion of contact durations exceeding 4 h (49.5%) and daily frequencies (90.4%), followed by home and workplace. The contact patterns exhibited clear age-assortative mixing, with Q indices of 0.27 and 0.28.

CONCLUSIONS

We assessed the characteristics of social contact patterns in Suzhou, which are essential for parameterizing models of infectious disease transmission. The high frequency and intensity of contacts among school-aged children should be given special attention, making school intervention policies a crucial component in controlling infectious disease transmission.

Transmission matrices used in epidemiologic modelling

Mixing matrices are included in infectious disease models to reflect transmission opportunities between population strata. These matrices were originally constructed on the basis of theoretical considerations and most of the early work in this area originates from research on sexually transferred diseases in the 80s, in response to AIDS. Later work in the 90s populated these matrices on the basis of survey data gathered to capture transmission risks for respiratory diseases. We provide an overview of developments in the construction of matrices for capturing transmission opportunities in populations. Such transmission matrices are useful for epidemiologic modelling to capture within and between stratum transmission and can be informed from theoretical mixing assumptions, informed by empirical evidence gathered through investigation as well as generated on the basis of data. Links to summary measures and threshold conditions are also provided.

Seasonal variations in social contact patterns in a rural population in north India: Implications for pandemic control

Social contact mixing patterns are critical to model the transmission of communicable diseases, and have been employed to model disease outbreaks including COVID-19. Nonetheless, there is a paucity of studies on contact mixing in low and middle-income countries such as India. Furthermore, mathematical models of disease outbreaks do not account for the temporal nature of social contacts. We conducted a longitudinal study of social contacts in rural north India across three seasons and analysed the temporal differences in contact patterns. A contact diary survey was performed across three seasons from October 2015-16, in which participants were queried on the number, duration, and characteristics of contacts that occurred on the previous day. A total of 8,421 responses from 3,052 respondents (49% females) recorded characteristics of 180,073 contacts. Respondents reported a significantly higher number and duration of contacts in the winter, followed by the summer and the monsoon season (Nemenyi post-hoc, p<0.001). Participants aged 0-9 years and 10-19 years of age reported the highest median number of contacts (16 (IQR 12-21), 17 (IQR 13-24) respectively) and were found to have the highest node centrality in the social network of the region (pageranks = 0.20, 0.17). A large proportion (>80%) of contacts that were reported in schools or on public transport involved physical contact. To the best of our knowledge, our study is the first from India to show that contact mixing patterns vary by the time of the year and provides useful implications for pandemic control. We compared the differences in the number, duration and location of contacts by age-group and gender, and studied the impact of the season, age-group, employment and day of the week on the number and duration of contacts using multivariate negative binomial regression. We created a social network to further understand the age and gender-specific contact patterns, and used the contact matrices in each season to parameterise a nine-compartment agent-based model for simulating a COVID-19 epidemic in each season. Our results can be used to parameterize more accurate mathematical models for prediction of epidemiological trends of infections in rural India.

The role of vaccine status homophily in the COVID-19 pandemic: a cross-sectional survey with modelling

BACKGROUND

Vaccine homophily describes non-heterogeneous vaccine uptake within contact networks. This study was performed to determine observable patterns of vaccine homophily, as well as the impact of vaccine homophily on disease transmission within and between vaccination groups under conditions of high and low vaccine efficacy.

METHODS

Residents of British Columbia, Canada, aged ≥ 16 years, were recruited via online advertisements between February and March 2022, and provided information about vaccination status, perceived vaccination status of household and non-household contacts, compliance with COVID-19 prevention guidelines, and history of COVID-19. A deterministic mathematical model was used to assess transmission dynamics between vaccine status groups under conditions of high and low vaccine efficacy.

RESULTS

Vaccine homophily was observed among those with 0, 2, or 3 doses of the vaccine. Greater homophily was observed among those who had more doses of the vaccine (p < 0.0001). Those with fewer vaccine doses had larger contact networks (p < 0.0001), were more likely to report prior COVID-19 (p < 0.0001), and reported lower compliance with COVID-19 prevention guidelines (p < 0.0001). Mathematical modelling showed that vaccine homophily plays a considerable role in epidemic growth under conditions of high and low vaccine efficacy. Furthermore, vaccine homophily contributes to a high force of infection among unvaccinated individuals under conditions of high vaccine efficacy, as well as to an elevated force of infection from unvaccinated to suboptimally vaccinated individuals under conditions of low vaccine efficacy.

INTERPRETATION

The uneven uptake of COVID-19 vaccines and the nature of the contact network in the population play important roles in shaping COVID-19 transmission dynamics.

The role of absolute humidity in influenza transmission in Beijing, China: risk assessment and attributable fraction identification

To assess the impact of absolute humidity on influenza transmission in Beijing from 2014 to 2019, we estimated the influenza transmissibility via the instantaneous reproduction number (Rt), and evaluated its nonlinear exposure-response association and delayed effects with absolute humidity by using the distributed lag nonlinear model (DLNM). Attributable fraction (AF) of Rt due to absolute humidity was calculated. The result showed a significant M-shaped relationship between Rt and absolute humidity. Compared with the effect of high absolute humidity, the low absolute humidity effect was more immediate with the most significant effect observed at lag 6 days. AFs were relatively high for the group aged 15-24 years, and was the lowest for the group aged 0-4 years with low absolute humidity. Therefore, we concluded that the component attributed to the low absolute humidity effect is greater. Young and middle-aged people are more sensitive to low absolute humidity than children and elderly.

Does COVID-19 Vaccination Protect Contact Persons? A Systematic Review

The protective effect of COVID-19 vaccination for contact persons is controversial. Therefore, the aim of this review was to determine whether COVID-19 vaccination provides significant protection for them. A PubMed search was carried out using the terms “unvaccinated vaccinated covid” in combination with “viral load” and “transmission”. Studies were included if they reported original comparative data on the SARS-CoV-2 viral load, duration of SARS-CoV-2 detection, or SARS-CoV-2 transmission rates. A total of 332 articles were identified, of which 68 were included and analyzed. The differences in the viral load were equivocal in 57% of the 35 studies, significantly lower in the vaccinated in 11 studies and in the unvaccinated in 3 studies. The infectious virus levels were significantly lower in the vaccinated in two out of six studies. Virus clearance was significantly faster in vaccinated subjects in two of eight studies (detection of viral RNA) and two of four studies (detection of infectious virus). The secondary attack rates were significantly lower in vaccinated index cases in 6 of 15 studies. The vaccination status of contacts was described in two of the six studies and was 31.8% and 39.9% lower in households with an unvaccinated index case. The inconsistent and variable differences in the viral load, viral clearance and secondary attack rates between vaccinated and unvaccinated individuals, especially during the omicron predominance, suggests that COVID-19 vaccination is unlikely to prevent a relevant proportion of transmissions to contact persons, taking into account the relevance of the immunological status of the contact population (vaccination rates and previous infection).

Estimates of the global burden of Congenital Rubella Syndrome, 1996-2019

OBJECTIVES

Many countries introduced rubella-containing vaccination (RCV) after 2011, following changes in recommended World Health Organization (WHO) vaccination strategies and external support. We evaluated the impact of these introductions.

METHODS

We estimated the country-specific, region-specific, and global Congenital Rubella Syndrome (CRS) incidence during 1996-2019 using mathematical modeling, including routine and campaign vaccination coverage and seroprevalence data.

RESULTS

In 2019, WHO African and Eastern Mediterranean regions had the highest estimated CRS incidence (64 [95% confidence intervals (CI): 24-123] and 27 [95% CI: 4-67] per 100,000 live births respectively), where nearly half of births occur in countries that have introduced RCV. Other regions, where >95% of births occurred in countries that had introduced RCV, had a low estimated CRS incidence (<1 [95% CI: <1 to 8] and <1 [95% CI: <1 to 12] per 100,000 live births in South-East Asia [SEAR] and the Western Pacific [WPR] respectively, and similarly in Europe and the Americas). The estimated number of CRS births globally declined by approximately two-thirds during 2010-2019, from 100,000 (95% CI: 54,000-166,000) to 32,000 (95% CI: 13,000-60,000), representing a 73% reduction since 1996, largely following RCV introductions in WPR and SEAR, where the greatest reductions occurred.

CONCLUSIONS

Further reductions can occur by introducing RCV in remaining countries and maintaining high RCV coverage.

Prevalence and risk factors of M tuberculosis infection in young people across 14 communities in Zambia and South Africa

BACKGROUND

From 2018-2021 the TB Reduction through Expanded Antiretroviral Treatment and TB Screening (TREATS) project took place in 21 Zambian and South African communities. The TREATS Incidence of TB Infection Cohort Study was conducted in adolescents and young people (AYP), aged 15-24 years in 14 communities. We describe the baseline prevalence and risk factors of Mycobacterium tuberculosis (M. tuberculosis) infection among this cohort and explore the quantitative QFT-Plus interferon gamma (IFN-γ) responses.

METHODS AND FINDINGS

A random sample of approximately 300 AYP per community were recruited and information on TB/HIV risk factors, TB symptoms and social mixing patterns collected. QuantiFERON TB Gold Plus assay (QFT-Plus) was used to detect M. tuberculosis infection, following manufacturer's instructions. Logistic regression was used to determine factors associated with infection. 5577 eligible AYP were invited to participate across both countries, with 4648 enrolled. QFT-Plus results were available for 4529: 2552(Zambia) and 1977(South Africa). Overall, 47.6% (2156/4529) AYP had positive QFT-Plus results, the prevalence of infection in South Africa being twice that in Zambia (64.7% (1280/1977) vs 34.3% (867/2552) p<0.001). Infection was associated with age, household contact with TB and alcohol in Zambia but showed no associations in South Africa. The antigen tube differential (TB2-TB1>0.6 IU/ml) of the assay at baseline showed no evidence of association with recent TB exposure.

CONCLUSION

The high prevalence of infection in AYP warrants urgent action to address TB control, especially in South Africa. Further research is required to delineate antigen tube responses of the QFT-Plus assay more precisely to fully realise the benefit of the additional TB2 tube in high TB/HIV burden settings.

Evaluating the impact of test-trace-isolate for COVID-19 management and alternative strategies

There are many contrasting results concerning the effectiveness of Test-Trace-Isolate (TTI) strategies in mitigating SARS-CoV-2 spread. To shed light on this debate, we developed a novel static-temporal multiplex network characterizing both the regular (static) and random (temporal) contact patterns of individuals and a SARS-CoV-2 transmission model calibrated with historical COVID-19 epidemiological data. We estimated that the TTI strategy alone could not control the disease spread: assuming R0 = 2.5, the infection attack rate would be reduced by 24.5%. Increased test capacity and improved contact trace efficiency only slightly improved the effectiveness of the TTI. We thus investigated the effectiveness of the TTI strategy when coupled with reactive social distancing policies. Limiting contacts on the temporal contact layer would be insufficient to control an epidemic and contacts on both layers would need to be limited simultaneously. For example, the infection attack rate would be reduced by 68.1% when the reactive distancing policy disconnects 30% and 50% of contacts on static and temporal layers, respectively. Our findings highlight that, to reduce the overall transmission, it is important to limit contacts regardless of their types in addition to identifying infected individuals through contact tracing, given the substantial proportion of asymptomatic and pre-symptomatic SARS-CoV-2 transmission.

Early impact of COVID-19 vaccination on older populations in four countries of the Americas, 2021

Objective

To estimate the early impact of coronavirus disease 2019 (COVID-19) vaccination on cases in older populations in four countries (Chile, Colombia, Guatemala, and the United States of America), and on deaths in Chile and Guatemala.

Methods

Data were obtained from national databases of confirmed COVID-19 cases and deaths and vaccinations between 1 July 2020 and 31 August 2021. In each country, pre- and post-vaccination incidence ratios were calculated for COVID-19 cases and deaths in prioritized groups (50-59, 60-69, and ≥70 years) compared with those in the reference group (<50 years). Vaccination effect was calculated as the percentage change in incidence ratios between pre- and post-vaccination periods.

Results

The ratio of COVID-19 cases in those aged ≥50 years to those aged <50 years decreased significantly after vaccine implementation by 9.8% (95% CI: 9.5 to 10.1%) in Chile, 22.5% (95% CI: 22.0 to 23.1%) in Colombia, 20.8% (95% CI: 20.6 to 21.1%) in Guatemala, and 7.8% (95% CI: 7.6 to 7.9%) in the USA. Reductions in the ratio were highest in adults aged ≥70 years. The effect of vaccination on deaths, with time lags incorporated, was highest in the age group ≥70 years in both Chile and Guatemala: 14.4% (95% CI: 11.4 to 17.4%) and 37.3% (95% CI: 30.9 to 43.7%), respectively.

Conclusions

COVID-19 vaccination significantly reduced morbidity in the early post-vaccination period in targeted groups. In the context of a global pandemic with limited vaccine availability, prioritization strategies are important to reduce the burden of disease in high-risk age groups.

Characterisation of infection-induced SARS-CoV-2 seroprevalence amongst children and adolescents in North Carolina

Few prospective studies have documented the seropositivity among those children infected with severe acute respiratory syndrome coronavirus 2. From 2 April 2021 to 24 June 2021, we prospectively enrolled children between the ages of 2 and 17 years at three North Carolina healthcare systems. Participants received at least four at-home serological tests detecting the presence of antibodies against, but not differentiating between, the nucleocapsid or spike antigen. A total of 1,058 participants were enrolled in the study, completing 2,709 tests between 1 May 2021 and 31 October 2021. Using multilevel regression with poststratification techniques and considering our assay sensitivity and sensitivity, we estimated that the seroprevalence of infection-induced antibodies among unvaccinated children and adolescents aged 2-17 years in North Carolina increased from 15.2% (95% credible interval, CrI 9.0-22.0) in May 2021 to 54.1% (95% CrI 46.7-61.1) by October 2021, indicating an average infection-to-reported-case ratio of 5. A rapid rise in seropositivity was most pronounced in those unvaccinated children aged 12-17 years, based on our estimates. This study underlines the utility of serial, serological testing to inform a broader understanding of the regional immune landscape and spread of infection.

The effect of variation of individual infectiousness on SARS-CoV-2 transmission in households

Quantifying variation of individual infectiousness is critical to inform disease control. Previous studies reported substantial heterogeneity in transmission of many infectious diseases including SARS-CoV-2. However, those results are difficult to interpret since the number of contacts is rarely considered in such approaches. Here, we analyze data from 17 SARS-CoV-2 household transmission studies conducted in periods dominated by ancestral strains, in which the number of contacts was known. By fitting individual-based household transmission models to these data, accounting for number of contacts and baseline transmission probabilities, the pooled estimate suggests that the 20% most infectious cases have 3.1-fold (95% confidence interval: 2.2- to 4.2-fold) higher infectiousness than average cases, which is consistent with the observed heterogeneity in viral shedding. Household data can inform the estimation of transmission heterogeneity, which is important for epidemic management.

Age-specific contribution of contacts to transmission of SARS-CoV-2 in Germany

Current estimates of pandemic SARS-CoV-2 spread in Germany using infectious disease models often do not use age-specific infection parameters and are not always based on age-specific contact matrices of the population. They also do usually not include setting- or pandemic phase-based information from epidemiological studies of reported cases and do not account for age-specific underdetection of reported cases. Here, we report likely pandemic spread using an age-structured model to understand the age- and setting-specific contribution of contacts to transmission during different phases of the COVID-19 pandemic in Germany. We developed a deterministic SEIRS model using a pre-pandemic contact matrix. The model was optimized to fit age-specific SARS-CoV-2 incidences reported by the German National Public Health Institute (Robert Koch Institute), includes information on setting-specific reported cases in schools and integrates age- and pandemic period-specific parameters for underdetection of reported cases deduced from a large population-based seroprevalence studies. Taking age-specific underreporting into account, younger adults and teenagers were identified in the modeling study as relevant contributors to infections during the first three pandemic waves in Germany. For the fifth wave, the Delta to Omicron transition, only age-specific parametrization reproduces the observed relative and absolute increase in pediatric hospitalizations in Germany. Taking into account age-specific underdetection did not change considerably how much contacts in schools contributed to the total burden of infection in the population (up to 12% with open schools under hygiene measures in the third wave). Accounting for the pandemic phase and age-specific underreporting is important to correctly identify those groups of the population in which quarantine, testing, vaccination, and contact-reduction measures are likely to be most effective and efficient. Age-specific parametrization is also highly relevant to generate informative age-specific output for decision makers and resource planers.

Combination of Cetylpyridinium Chloride and Chlorhexidine Acetate: A Promising Candidate for Rapid Killing of Gram-Positive/Gram-Negative Bacteria and Fungi

Combined use of the present antimicrobial drugs has been proved to be an alternative approach for antimicrobial agents' development since the co-existed of the drugs working in different mechanism have been demonstrated potentially enhance their antimicrobial activity. In this work, antibacterial and antifungal activity of the cetylpyridinium chloride (CPC)/chlorhexidine acetate (CHA) combination was evaluated for the first time, while a universal concentration for the rapid killing of gram-positive/gram-negative bacteria and fungi was also proposed. The minimum inhibitory concentrations (MIC) of CPC and CHA used alone or in combination were first measured, showing that the combined treatment decreased the MIC against tested gram-positive/gram-negative bacteria and fungi to 1/8-1/2. Growth curve assays demonstrated CPC and CHA had dynamic combined effects against the tested microorganisms at the concentration equal to MIC. Besides, combined use of these two drugs could also enhance their biocidal activity, which was illustrated by fluorescence microscopy and SEM images, as well as soluble protein measurement. More importantly, in vitro acute eye and skin irritation tests showed short-term contact with CPC/CHA combination would not cause any damage to mammalian mucosa and skin. In a word, CPC/CHA combination exhibited broad-spectrum antibacterial and antifungal activity against tested gram-positive/gram-negative bacteria and fungi while without any acute irritation to mammalian mucosa and skin, providing a new perspective on the selection of personal disinfectants.

Higher COVID-19 Vaccination Rates Are Associated with Lower COVID-19 Mortality: A Global Analysis

Mass vaccination initiatives are underway worldwide, and a considerable percentage of the world's population is now vaccinated. This study examined the association of COVID-19 deaths per 1000 cases with a fully vaccinated population. The global median deaths per 1000 cases were 15.68 (IQR 9.84, 25.87) after 6 months of vaccinations and 11.96 (IQR 6.08, 20.63) after 12 months. Across 164 countries, we found significant variations in vaccination levels of populations, booster doses, and mortality, with higher vaccine coverage and lower mortality in high-income countries. Several regression models were performed to test the association between vaccination and COVID-19 mortality. Control variables were used to account for confounding variables. A 10-percentage-point increase in vaccination was associated with an 18.1% decrease in mortality after 6 months (95%CI, 7.4-28.8%) and a 16.8% decrease after 12 months (95%CI, 6.9-26.7%). A 10-percentage-point increase in booster vaccination rates was associated with a 33.1% decrease in COVID-19 mortality (95%CI, 16.0-50.2%). This relationship is present in most analyses by country income groups with variations in the effect size. Efforts are needed to reduce vaccine hesitancy while ensuring suitable infrastructure and supply to enable all countries to increase their vaccination rates.

Novel estimates reveal subnational heterogeneities in disease-relevant contact patterns in the United States

Population contact patterns fundamentally determine the spread of directly transmitted airborne pathogens such as SARS-CoV-2 and influenza. Reliable quantitative estimates of contact patterns are therefore critical to modeling and reducing the spread of directly transmitted infectious diseases and to assessing the effectiveness of interventions intended to limit risky contacts. While many countries have used surveys and contact diaries to collect national-level contact data, local-level estimates of age-specific contact patterns remain rare. Yet, these local-level data are critical since disease dynamics and public health policy typically vary by geography. To overcome this challenge, we introduce a flexible model that can estimate age-specific contact patterns at the subnational level by combining national-level interpersonal contact data with other locality-specific data sources using multilevel regression with poststratification (MRP). We estimate daily contact matrices for all 50 US states and Washington DC from April 2020 to May 2021 using national contact data from the US. Our results reveal important state-level heterogeneities in levels and trends of contacts across the US over the course of the COVID-19 pandemic, with implications for the spread of respiratory diseases.

Predictors of SARS-CoV-2 Infection in University Students: A Case-Control Study

Closure of Higher Education Institutions in the early phase of the SARS-CoV-2 pandemic was largely diffused. With their reopening, numerous preventive measures have been enacted, but limited evidence exists on students' behavior that could influence their infection risk. We conducted a case-control study at the Sapienza University of Rome to identify protective and risk factors for SARS-CoV-2 infection. Students attending the campus within 48 h of SARS-CoV-2 infection were considered cases. Controls were students who come in contact with a confirmed case within the campus. Demographic features and activities carried out before positivity or contact were investigated. Multivariable logistic regression models were built to identify factors associated with SARS-CoV-2 infection, estimating adjusted odds ratios (aOR) and 95% confidence intervals (95% CI). The analysis showed an increased risk of SARS-CoV-2 infection for attending the second year or above of university (aOR 17.7, 95% CI 2.21-142.82) and participating in private parties or ceremonies (aOR 15.9, 95% CI 2.30-109.67) while living outside the family (aOR 0.08, 95% CI 0.01-0.54) and attending practical activities or libraries on campus (aOR 0.29, 95% CI 0.08-0.97) reduced the risk. Data strongly suggests that it may be safe to participate in activities organized under strict infection prevention guidelines. Tailored prevention measures might reduce the risk of infection in university students.

Assessing the effect of school closures on the spread of COVID-19 in Zurich

The effect of school closure on the spread of COVID-19 has been discussed intensively in the literature and the news. To capture the interdependencies between children and adults, we consider daily age-stratified incidence data and contact patterns between age groups which change over time to reflect social distancing policy indicators. We fit a multivariate time-series endemic-epidemic model to such data from the Canton of Zurich, Switzerland and use the model to predict the age-specific incidence in a counterfactual approach (with and without school closures). The results indicate a 17% median increase of incidence in the youngest age group (0-14 year olds), whereas the relative increase in the other age groups drops to values between 2% and 3%. We argue that our approach is more informative to policy makers than summarising the effect of school closures with time-dependent effective reproduction numbers, which are difficult to estimate due to the sparsity of incidence counts within the relevant age groups.

Substantial impact of mobility restrictions on reducing COVID-19 incidence in Italy in 2020

BACKGROUND

Italy was the first country after China to be severely affected by the COVID-19 pandemic, in early 2020. The country responded swiftly to the outbreak with a nationwide two-step lockdown, the first one light and the second one tight. By analyzing 2020 national mobile phone movements, we assessed how lockdown compliance influenced its efficacy.

METHODS

We measured individual mobility during the first epidemic wave with mobile phone movements tracked through carrier networks, and related this mobility to daily new SARS-CoV-2 infections, hospital admissions, intensive care admissions and deaths attributed to COVID-19, taking into account reason for travel (work-related or not) and the means of transport.

RESULTS

The tight lockdown resulted in an 82% reduction in mobility for the entire country and was effective in swiftly curbing the outbreak as indicated by a shorter time-to-peak of all health outcomes, particularly for provinces with the highest mobility reductions and the most intense COVID-19 spread. Reduction of work-related mobility was accompanied by a nearly linear benefit in outbreak containment; work-unrelated movements had a similar effect only for restrictions exceeding 50%. Reduction in mobility by car and by airplane was nearly linearly associated with a decrease in most COVID-19 health outcomes, while for train travel reductions exceeding 55% had no additional beneficial effects. The absence of viral variants and vaccine availability during the study period eliminated confounding from these two sources.

CONCLUSIONS

Adherence to the COVID-19 tight lockdown during the first wave in Italy was high and effective in curtailing the outbreak. Any work-related mobility reduction was effective, but only high reductions in work-unrelated mobility restrictions were effective. For train travel, there was a threshold above which no further benefit occurred. These findings could be particular to the spread of SARS-CoV-2, but might also apply to other communicable infections with comparable transmission dynamics.

Investigating the relationship between interventions, contact patterns, and SARS-CoV-2 transmissibility

BACKGROUND

After a rapid upsurge of COVID-19 cases in Italy during the fall of 2020, the government introduced a three-tiered restriction system aimed at increasing physical distancing. The Ministry of Health, after periodic epidemiological risk assessments, assigned a tier to each of the 21 Italian regions and autonomous provinces. It is still unclear to what extent these different sets of measures altered the number of daily interactions and the social mixing patterns.

METHODS AND FINDINGS

We conducted a survey between July 2020 and March 2021 to monitor changes in social contact patterns among individuals in the metropolitan city of Milan, Italy, which was hardly hit by the second wave of the COVID-19 pandemic. The number of daily contacts during periods characterized by different levels of restrictions was analyzed through negative binomial regression models and age-specific contact matrices were estimated under the different tiers of restrictions. By relying on the empirically estimated mixing patterns, we quantified relative changes in SARS-CoV-2 transmission potential associated with the different tiers. As tighter restrictions were implemented during the fall of 2020, a progressive reduction in the mean number of daily contacts recorded by study participants was observed: from 15.9 % under mild restrictions (yellow tier), to 41.8 % under strong restrictions (red tier). Higher restrictions levels were also found to increase the relative contribution of contacts occurring within the household. The SARS-CoV-2 reproduction number was estimated to decrease by 17.1 % (95 %CI: 1.5-30.1), 25.1 % (95 %CI: 13.0-36.0) and 44.7 % (95 %CI: 33.9-53.0) under the yellow, orange, and red tiers, respectively.

CONCLUSIONS

Our results give an important quantification of the expected contribution of different restriction levels in shaping social contacts and decreasing the transmission potential of SARS-CoV-2. These estimates can find an operational use in anticipating the effect that the implementation of these tiered restriction can have on SARS-CoV-2 reproduction number under an evolving epidemiological situation.

Social mixing patterns relevant to infectious diseases spread by close contact in urban Blantyre, Malawi

INTRODUCTION

Understanding human mixing patterns relevant to infectious diseases spread through close contact is vital for modelling transmission dynamics and optimisation of disease control strategies. Mixing patterns in low-income countries like Malawi are not well known.

METHODOLOGY

We conducted a social mixing survey in urban Blantyre, Malawi between April and July 2021 (between the 2nd and 3rd wave of COVID-19 infections). Participants living in densely-populated neighbourhoods were randomly sampled and, if they consented, reported their physical and non-physical contacts within and outside homes lasting at least 5 min during the previous day. Age-specific mixing rates were calculated, and a negative binomial mixed effects model was used to estimate determinants of contact behaviour.

RESULTS

Of 1201 individuals enroled, 702 (58.5%) were female, the median age was 15 years (interquartile range [IQR] 5-32) and 127 (10.6%) were HIV-positive. On average, participants reported 10.3 contacts per day (range: 1-25). Mixing patterns were highly age-assortative, particularly those within the community and with skin-to-skin contact. Adults aged 20-49 y reported the most contacts (median:11, IQR: 8-15) of all age groups; 38% (95%CI: 16-63) more than infants (median: 8, IQR: 5-10), who had the least contacts. Household contact frequency increased by 3% (95%CI: 2-5) per additional household member. Unemployed participants had 15% (95%CI: 9-21) fewer contacts than other adults. Among long range (>30 m away from home) contacts, secondary school children had the largest median contact distance from home (257 m, IQR 78-761). HIV-positive status in adults >=18 years-old was not associated with changed contact patterns (rate ratio: 1.01, 95%CI: (0.91-1.12)). During this period of relatively low COVID-19 incidence in Malawi, 301 (25.1%) individuals stated that they had limited their contact with others due to COVID-19 precautions; however, their reported contacts were 8% (95%CI: 1-13) higher.

CONCLUSION

In urban Malawi, contact rates, are high and age-assortative, with little reported behavioural change due to either HIV-status or COVID-19 circulation. This highlights the limits of contact-restriction-based mitigation strategies in such settings and the need for pandemic preparedness to better understand how contact reductions can be enabled and motivated.

Social Contacts and Transmission of COVID-19 in British Columbia, Canada

Background

Close-contact rates are thought to be a driving force behind the transmission of many infectious respiratory diseases. Yet, contact rates and their relation to transmission and the impact of control measures, are seldom quantified. We quantify the response of contact rates, reported cases and transmission of COVID-19, to public health contact-restriction orders, and examine the associations among these three variables in the province of British Columbia, Canada.

Methods

We derived time series data for contact rates, daily cases and transmission of COVID-19 from a social contacts survey, reported case counts and by fitting a transmission model to reported cases, respectively. We used segmented regression to investigate impacts of public health orders; Pearson correlation to determine associations between contact rates and transmission; and vector autoregressive modeling to quantify lagged associations between contacts rates, daily cases, and transmission.

Results

Declines in contact rates and transmission occurred concurrently with the announcement of public health orders, whereas declines in cases showed a reporting delay of about 2 weeks. Contact rates were a significant driver of COVID-19 and explained roughly 19 and 20% of the variation in new cases and transmission, respectively. Interestingly, increases in COVID-19 transmission and cases were followed by reduced contact rates: overall, daily cases explained about 10% of the variation in subsequent contact rates.

Conclusion

We showed that close-contact rates were a significant time-series driver of transmission and ultimately of reported cases of COVID-19 in British Columbia, Canada and that they varied in response to public health orders. Our results also suggest possible behavioral feedback, by which increased reported cases lead to reduced subsequent contact rates. Our findings help to explain and validate the commonly assumed, but rarely measured, response of close contact rates to public health guidelines and their impact on the dynamics of infectious diseases.

Updating age-specific contact structures to match evolving demography in a dynamic mathematical model of tuberculosis vaccination

We investigated the effects of updating age-specific social contact matrices to match evolving demography on vaccine impact estimates. We used a dynamic transmission model of tuberculosis in India as a case study. We modelled four incremental methods to update contact matrices over time, where each method incorporated its predecessor: fixed contact matrix (M0), preserved contact reciprocity (M1), preserved contact assortativity (M2), and preserved average contacts per individual (M3). We updated the contact matrices of a deterministic compartmental model of tuberculosis transmission, calibrated to epidemiologic data between 2000 and 2019 derived from India. We additionally calibrated the M0, M2, and M3 models to the 2050 TB incidence rate projected by the calibrated M1 model. We stratified age into three groups, children (<15y), adults (≥15y, <65y), and the elderly (≥65y), using World Population Prospects demographic data, between which we applied POLYMOD-derived social contact matrices. We simulated an M72-AS01_E-like tuberculosis vaccine delivered from 2027 and estimated the per cent TB incidence rate reduction (IRR) in 2050 under each update method. We found that vaccine impact estimates in all age groups remained relatively stable between the M0–M3 models, irrespective of vaccine-targeting by age group. The maximum difference in impact, observed following adult-targeted vaccination, was 7% in the elderly, in whom we observed IRRs of 19% (uncertainty range 13–32), 20% (UR 13–31), 22% (UR 14–37), and 26% (UR 18–38) following M0, M1, M2 and M3 updates, respectively. We found that model-based TB vaccine impact estimates were relatively insensitive to demography-matched contact matrix updates in an India-like demographic and epidemiologic scenario. Current model-based TB vaccine impact estimates may be reasonably robust to the lack of contact matrix updates, but further research is needed to confirm and generalise this finding.

Mathematical models are increasingly used to predict the impact of new and existing tools, e.g., vaccines, that aim to control the transmission of infectious diseases. Within these models, investigators often assume that individuals contact each other according to specific patterns, particularly between and within different age groups. These patterns are typically derived from surveys of social contact or other models and reflect the particular age composition of their source population. However, when models are set over long time scales, e.g., decades, population age composition is likely to change. Despite this reality, few models update their contact patterns to match changing age composition. Furthermore, none have assessed whether their final estimates of disease-control intervention impact are affected by updating contact patterns. We measured whether different techniques to update social contact patterns to match evolving demography produce different vaccine impact estimates, using a mathematical model of tuberculosis set in an India-like scenario between 2025–2050. We found that vaccine impact was stable across a range of different update methods. Thus, existing model-based vaccine impact estimates may be stable to a lack of these updates, but further work is required to confirm these findings.