Dataset Information

Estimating age-mixing patterns relevant for the transmission of airborne infections.

ABSTRACT:

Introduction

Age-mixing patterns can have substantial effects on infectious disease dynamics and intervention effects. Data on close contacts (people spoken to and/or touched) are often used to estimate age-mixing. These are not the only relevant contacts for airborne infections such as tuberculosis, where transmission can occur between anybody 'sharing air' indoors. Directly collecting data on age-mixing patterns between casual contacts (shared indoor space, but not 'close') is difficult however. We demonstrate a method for indirectly estimating age-mixing patterns between casual indoor contacts from social contact data.

Methods

We estimated age-mixing patterns between close, casual, and all contacts using data from a social contact survey in South Africa. The age distribution of casual contacts in different types of location was estimated from the reported time spent in the location type by respondents in each age group.

Results

Patterns of age-mixing calculated from contact numbers were similar between close and all contacts, however patterns of age-mixing calculated from contact time were more age-assortative in all contacts than in close contacts. There was also more variation by age group in total numbers of casual and all contacts, than in total numbers of close contacts. Estimates were robust to sensitivity analyses.

Conclusions

Patterns of age-mixing can be estimated for all contacts using data that can be easily collected as part of social contact surveys or time-use surveys, and may differ from patterns between close contacts.

SUBMITTER: McCreesh N

PROVIDER: S-EPMC6731521 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Publications

Estimating age-mixing patterns relevant for the transmission of airborne infections.

McCreesh Nicky N Morrow Carl C Middelkoop Keren K Wood Robin R White Richard G RG

Epidemics 20190320

<h4>Introduction</h4>Age-mixing patterns can have substantial effects on infectious disease dynamics and intervention effects. Data on close contacts (people spoken to and/or touched) are often used to estimate age-mixing. These are not the only relevant contacts for airborne infections such as tuberculosis, where transmission can occur between anybody 'sharing air' indoors. Directly collecting data on age-mixing patterns between casual contacts (shared indoor space, but not 'close') is difficul ...[more]

PMID: 30910644

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Project description:Debate and scientific inquiries regarding airborne transmission of respiratory infections such as COVID-19 and influenza continue. Health authorities including the WHO and the US CDC have recognized the airborne transmission of COVID-19 in specific settings, although the ventilation requirements remain to be determined. In this work we consider the long-range airborne transmission as an extended short-range airborne route, which reconciles the link between short- and long-range airborne routes. The effective short-range distance is defined as the distance in short range at which long-range route has the same volumetric exposure value as that due to short-range route. Our data show that a decrease in ventilation rate or room volume per person, or an increase in the ratio of the number of infected to susceptible people reduces the effective short-range distance. In a normal breathing scenario with one out of five people infected and a room volume of 12 m3 per person to ensure an effective short-range distance of 1.5 m, a ventilation rate of 10 L/s per person is needed for a duration of 2 h. Our results suggest that effective environmental prevention strategies for respiratory infections require appropriate increases in the ventilation rate while maintaining a sufficiently low occupancy. PRACTICAL IMPLICATIONS: Demonstration of the long-range airborne route as an extended short-range airborne route suggests the significant role played by building ventilation in respiratory infection exposure. The reconciliation of short- and long-range airborne transmission suggests that the commonly observed dominance of close-contact transmission is a probable evidence of short-range airborne transmission, following a separate earlier study that revealed the relative insignificance of large droplet transmission in comparison with the short-range airborne-route. Existing ventilation standards do not account for respiratory infection control, and this study presents a possible approach to account for infection under new ventilation standards.

Project description:IntroductionUnderstanding 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.MethodologyWe 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.ResultsOf 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.ConclusionIn 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.

Project description:BACKGROUND:Sexual mixing between heterogeneous population subgroups is an integral component of mathematical models of sexually transmitted infections (STIs). This study compares the fit of different mixing representations to survey data and the impact of different mixing assumptions on the predicted benefits of hypothetical human papillomavirus (HPV) vaccine strategies. METHODS:We compared novel empirical (data-driven) age mixing structures with the more commonly-used assortative-proportionate (A-P) mixing structure. The A-P mixing structure assumes that a proportion of sexual contacts - known as the assortativity constant, typically estimated from survey data or calibrated - occur exclusively within one's own age group and the remainder mixes proportionately among all age groups. The empirical age mixing structure was estimated from the National Survey on Sexual Attitudes and Lifestyles 3 (Natsal-3) using regression methods, and the assortativity constant was estimated from Natsal-3 as well. Using a simplified HPV transmission model under each mixing assumption, we calibrated the model to British HPV16 prevalence data, then estimated the reduction in steady-state prevalence and the number of infections averted due to expanding HPV vaccination from 12- through 26-year-old females alone to 12-year-old males or 27- to 39-year-old females. RESULTS:Empirical mixing provided a better fit to the Natsal-3 data than the best-fitting A-P structure. Using the model with empirical mixing as a reference, the model using the A-P structure often under- or over-estimated the benefits of vaccination, in one case overestimating by 2-fold the number of infections prevented due to extended female catch-up in a high vaccine uptake setting. CONCLUSIONS:An empirical mixing structure more accurately represents sexual mixing survey data, and using the less accurate, yet commonly-used A-P structure has a notable effect on estimates of HPV vaccination benefits. This underscores the need for mixing structures that are less dependent on unverified assumptions and are directly informed by sexual behavior data.

Dataset Information

Estimating age-mixing patterns relevant for the transmission of airborne infections.

Introduction

Methods

Results

Conclusions

Publications

Estimating age-mixing patterns relevant for the transmission of airborne infections.

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