Household transmission of influenza A and B within a prospective cohort during the 2013‐2014 and 2014‐2015 seasons

Dahlgren, F. Scott; Foppa, Ivo M.; Stockwell, Melissa S.; Vargas, Celibell Y.; LaRussa, Philip; Reed, Carrie

doi:10.1002/sim.9181

Cited by 8 publications

(6 citation statements)

References 150 publications

(395 reference statements)

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“…The probability of transmission within households with smaller number of household members was higher, which was consistent with other studies [ 20 , 38 , 39 , 40 ]. These estimates of probabilities of household transmission demonstrated the significance of household transmission when there were infected household members, similar to the estimates based on data from household case-ascertain design [ 41 , 42 ].…”

Section: Discussionsupporting

confidence: 71%

Indirect Protection from Vaccinating Children against Influenza A Virus Infection in Households

Tsang

Wang

Fang

et al. 2022

Viruses

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Influenza vaccination is an important intervention to prevent influenza virus infection. Our previous analysis suggested that indirect protection is limited in an influenza B epidemic in Hong Kong. We further analyzed six influenza A epidemics to determine such potential. We applied a statistical model to estimate household transmission dynamics in the 3 influenza A(H3N2) and 3 pandemic influenza A(H1N1) epidemics. Then, we estimated the reduction in infection risk among unvaccinated household members when all children in households are vaccinated, with different assumptions on vaccine efficacy (VE). In the optimal scenario that VE was 70%, the reduction to the total probability of infection was only marginal, with relative probabilities ranged from 0.91–0.94 when all children in households were vaccinated because community was by far the main source of infection during the six epidemics in our study. The proportion of cases attributed to household transmission was 10% (95% CrI: 7%, 13%). Individual influenza vaccination is important even when other household members are vaccinated, given the degree of indirect protection is small.

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Section: Discussionsupporting

confidence: 71%

Indirect Protection from Vaccinating Children against Influenza A Virus Infection in Households

Tsang

Wang

Fang

et al. 2022

Viruses

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“…These biases differ substantially and systematically from biases in estimates of vaccine effects. Consistent with empirical studies, [1][2][3][4] the fraction of overall transmission accounted for by within-household transmission varies by parameters representing the setting-specific transmission of the pathogen of interest (i.e., b and t) as well as the size of households in the population; likewise, for a fixed set of parameters, this fraction varies over the course of the epidemic.…”

mentioning

confidence: 70%

“…Empirical evidence from a range of respiratory IDs suggests that withinhousehold transmission can be substantially more intense than community transmission. [1][2][3][4] While dynamic transmission microsimulation models with explicit contact networks avoid the need to make this simplification, they can be computationally intensive, especially when modeling large populations, and extensive data are required to parameterize their contact networks.…”

mentioning

confidence: 99%

Effects of Mitigation and Control Policies in Realistic Epidemic Models Accounting for Household Transmission Dynamics

Alarid-Escudero,

Andrews,

Goldhaber-Fiebert

2023

Med Decis Making

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Background Compartmental infectious disease (ID) models are often used to evaluate nonpharmaceutical interventions (NPIs) and vaccines. Such models rarely separate within-household and community transmission, potentially introducing biases in situations in which multiple transmission routes exist. We formulated an approach that incorporates household structure into ID models, extending the work of House and Keeling. Design We developed a multicompartment susceptible-exposed-infectious-recovered-susceptible-vaccinated (MC-SEIRSV) modeling framework, allowing nonexponentially distributed duration in exposed and infectious compartments, that tracks within-household and community transmission. We simulated epidemics that varied by community and household transmission rates, waning immunity rate, household size (3 or 5 members), and numbers of exposed and infectious compartments (1–3 each). We calibrated otherwise identical models without household structure to the early phase of each parameter combination’s epidemic curve. We compared each model pair in terms of epidemic forecasts and predicted NPI and vaccine impacts on the timing and magnitude of the epidemic peak and its total size. Meta-analytic regressions characterized the relationship between household structure inclusion and the size and direction of biases. Results Otherwise similar models with and without household structure produced equivalent early epidemic curves. However, forecasts from models without household structure were biased. Without intervention, they were upward biased on peak size and total epidemic size, with biases also depending on the number of exposed and infectious compartments. Model-estimated NPI effects of a 60% reduction in community contacts on peak time and size were systematically overestimated without household structure. Biases were smaller with a 20% reduction NPI. Because vaccination affected both community and household transmission, their biases were smaller. Conclusions ID models without household structure can produce biased outcomes in settings in which within-household and community transmission differ. Highlights Infectious disease models rarely separate household transmission from community transmission. The pace of household transmission may differ from community transmission, depends on household size, and can accelerate epidemic growth. Many infectious disease models assume exponential duration distributions for infected states. However, the duration of most infections is not exponentially distributed, and distributional choice alters modeled epidemic dynamics and intervention effectiveness. We propose a mathematical framework for household and community transmission that allows for nonexponential duration times and a suite of interventions and quantified the effect of accounting for household transmission by varying household size and duration distributions of infected states on modeled epidemic dynamics. Failure to include household structure induces biases in the modeled overall course of an epidemic and the effects of interventions delivered differentially in community settings. Epidemic dynamics are faster and more intense in populations with larger household sizes and for diseases with nonexponentially distributed infectious durations. Modelers should consider explicitly incorporating household structure to quantify the effects of non-pharmaceutical interventions (e.g., shelter-in-place).

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“…At-home specimen collection for respiratory pathogens enables community sampling and households have been highlighted as an important source of microbial spread within the community [29][30][31]. Thus, considerations of family members of different ages on comfort and ease with which samples can be obtained are critical for informing future large surveillance studies of microbial prevalence and transmission.…”

Section: Discussionmentioning

confidence: 99%

Family Research of Microbes Linked to Respiratory Infections (FAMILY Micro) observational study: Assessing the use of minimally invasive self-sampling methodologies at home for long-term monitoring of the oral, nasal and hand microbiota of adults and children within UK families

Nikolaou

German

Howard

et al. 2023

Preprint

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Background: Monitoring the presence of commensal and pathogenic microorganisms in the human oral, nasal and hand niches as determinants for respiratory tract infections is of critical global relevance as was evident during the COVID-19 pandemic. However, community-based surveillance is difficult because current sampling methods are not optimal for a wide age range of participants, particularly young children. We designed a platform of minimally invasive self-sampling at home and assessed its use for longitudinal monitoring of the oral, nasal and hand microbiota of adults and children within families. Methods: Healthy families with two adults and up to three children, living in and near Liverpool, United Kingdom, self-collected saliva, nasal lining fluid using synthetic absorptive matrices and hand swabs at home every two weeks for six months. Questionnaires were used to collect demographic and epidemiological data and assess feasibility and acceptability. At the end of the study, participants were invited to take part in an interview. Results: Thirty-three families completed the study. Sample collection using our approach was acceptable to 25/33 (76%) families, as sampling was fast (76%), easy (76%) and painless (60%). Saliva and hand sampling was acceptable to all participants of any age, whereas nasal sampling was accepted mostly by adults and children older than 5 years. Conclusion: Multi-niche self-sampling at home can be used by adults and children for longitudinal microbial surveillance, providing key data for monitoring respiratory infections.

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Household transmission of influenza A and B within a prospective cohort during the 2013‐2014 and 2014‐2015 seasons

Cited by 8 publications

References 150 publications

Indirect Protection from Vaccinating Children against Influenza A Virus Infection in Households

Indirect Protection from Vaccinating Children against Influenza A Virus Infection in Households

Effects of Mitigation and Control Policies in Realistic Epidemic Models Accounting for Household Transmission Dynamics

Family Research of Microbes Linked to Respiratory Infections (FAMILY Micro) observational study: Assessing the use of minimally invasive self-sampling methodologies at home for long-term monitoring of the oral, nasal and hand microbiota of adults and children within UK families

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