Peer Group

The distribution of household sizes and the average numbers of children in households of different sizes were simulated to be consistent with Hong Kong [13 (link)]. We made all interventions active prior to the arrival of the infected individuals, and we challenged the system with a constant introduction of 1.5 infected individuals per day per 100,000 people for 365 d. Our results showed no significant sensitivity when the importation rate was proportional to an epidemic curve (see Figure S1). Susceptible individuals reported with influenza-like illness, caused by something other than the pandemic influenza strain, at a constant rate of 74 per day per 100,000 people. This provided a constant stream of false positives, which ensures that the number of households in quarantine in the early stages of the epidemic is not underestimated. However, it should be noted that the relative benefits derived from testing are higher for higher rates of false positives. The rate we used is approximately equal to the peak reporting rate of influenza-like illness in the Hong Kong primary care setting during 2004 (Hong Kong Centre for Health Protection; http://www.chp.gov.hk/sentinel.asp?lang=en&id=292&pid=44&ppid=26). These nonpandemic cases were symptomatic for 3 d on average.
The hazard of infection from an infectious person to a susceptible person in a household was set to be inversely proportional to household size, reflecting recent findings for endemic influenza household transmission dynamics [14 (link)]. Model-generated household attack rates were consistent with recent empirical studies [15 (link)], given uncertainties in the degree of community transmission present in those studies (see Figure S2). Workplaces and schools were represented as large, highly connected peer groups. A further substantial proportion of transmission, termed “community” transmission, was assumed to be outside of the peer group and the home. Large network neighborhood sizes and substantial community transmission are conservative assumptions with respect to the efficacy of contact tracing: they penalize contact tracing without significantly affecting other interventions. A formal definition of the transmission model is given in Protocol S1. As there was no spatial component in this model, our results will overestimate the speed of the epidemic in geographically dispersed populations. However, large countries will suffer importation of infectious individuals in all regions, and pandemic strains will spread rapidly between large cities. Therefore, it is unlikely that geographical heterogeneities will last longer than 1 or 2 wk in large countries such as the United States [16 (link)], which suggests that there will be little opportunity for the use of spatially heterogeneous intervention strategies.
An integrated process of voluntary household quarantine, voluntary individual isolation, anti-viral administration, and contact tracing was used to predict the impact of household-based intervention policies. If an individual complied with household quarantine, their infectiousness to other household members changed by a factor of ɛ_Q. Because quarantine increases the average time spent at home substantially for most people, the value of this parameter may be greater than unity (ɛ_Q = 2 at baseline; see Table 1). Also, the level of transmission in isolation may be higher than elsewhere. We assumed that the degree of transmission in isolation was a factor of ɛ_I greater (ɛ_I = 1 at baseline; see Table 1), i.e., the basic reproductive number inside transmission was equal to ɛ_IR₀ (see Protocol S1). Note that we assumed that for all policies, those individuals with symptoms severe enough to be hospitalized (see Figure 1) would be isolated. Hence, policies without explicit isolation elements used isolation resources. Also, we assumed that all those in isolation received anti-viral treatment. Hence, policies without explicit anti-viral elements used anti-viral doses. We modeled compliance at the individual level: a symptomatic individual in a household that was not quarantined decided for herself if she reported, but the other members of her household made independent decisions for themselves. We defined p_c to be the probability of compliance.
These interventions were implemented using the following algorithm.
Step 1: an individual from households not in voluntary quarantine had the opportunity to enter the program via one of the following three routes: she developed symptoms, she was contacted through contact tracing, or she was hospitalized. We assumed she volunteered and actually reported with probability p_c for symptoms and contact tracing, and with probability one for hospitalization. She complied with the program until released. After release, individuals were not bound by previous decisions to join or not join, i.e., they could choose again.
Step 2: each other member of her household complied with intervention instructions with probability p_c.
Step 3: after a delay of 1 d, all compliant nonsymptomatic household members took one dose of prophylactic anti-virals per day when anti-viral policies were in effect. Symptomatic household members took two doses of anti-virals per day.
Step 4: if contact tracing was in effect, each compliant adult member of the household named, on average, five members of their peer group, if she had not been asked to name contacts before.
Step 5: if isolation was in effect, newly found symptomatic individuals who were compliant voluntarily entered isolation with probability p_c after a delay of 1 d. If an isolated individual no longer showed symptoms after 3 d, she was released from isolation and joined her household, which might be quarantined. Otherwise, she was isolated for a further 3 d. This cycle repeated until she no longer showed symptoms or died (see Figure S4 for the distribution of durations of quarantine for different policies).
Step 6: isolated individuals were given two doses of anti-virals per day, without a delay, in all simulations, regardless of the policy for the use of anti-virals in households.
Step 7: if contact tracing was in effect, contacts (if known and not already in the program) of all newly found symptomatic or hospitalized household members were traced with a mean delay of 1 d.
Step 8: if there had been no new symptoms in compliant household members or hospitalizations of any household members for 7 d, the quarantined household was released from the program at the end of that period. Otherwise, we returned to Step 5 at the time new symptoms or hospitalizations occurred.

Our protocol was developed using the scoping review methodological framework proposed by Arksey and O’Malley (2005) [1 (link)] and further refined by the Joanna Briggs Institute [3 (link)]. The draft protocol was revised upon receiving feedback from the research team, including methodologists and healthcare providers, as well as the peer-review panel of the Canadian Institutes of Health Research. The final version of the protocol is available upon request from the corresponding author.

An initial broad based search was conducted using an exhaustive list of peer support concepts (based on a previous review [42 ]) combined with (Health Promotion OR Health Education OR Health Literacy). Searches were conducted across PubMed, Web of Science and Scopus for the period January 1997-December 2012. Results were limited to English Language. A total of 14,488 references were found, reduced to 6,864 after elimination of duplicates.
All references were sifted by the review team using an Excel spreadsheet and drop down categories for coding for explicit mentions of peer support, community engagement and health literacy. Inconclusive records were referred for retrieval of full text. This original set of 455 references constituted the original sampling frame for the review. A two-layered approach was then used for all relevant records – 39 UK records were marked for prioritization with a further 416 non-UK studies being kept in a holding file.
The 39 UK articles reflected community engagement and peer support across a wide range of client groups. What was immediately apparent was the arbitrariness of retrieval and subsequent inclusion of references based only on title, abstract and keywords. Keywords were revealed as a “blunt instrument” in seeking to identify conceptual development, particularly when such concepts are emergent. The team identified several instances where one or more reports of an initiative had been retrieved, or subsequently coded as relevant, when equally relevant reports from the same study had been omitted or subsequently excluded. For example, a journal article entitled “Does bar-based, peer-led sexual health promotion have a community-level effect amongst gay men in Scotland?” [43 (link)] contains both peer education and community engagement concepts. However a related article, “Good in parts: the Gay Men's Task Force in Glasgow--a response to Kelly” [43 (link)], only labels the peer education concept. In this same article the community engagement concept is neither clear from the title nor the abstract. In such a case a review team would wish to be able to judge the project as a whole as being eligible or not. It would be a cause for concern if one report of a study resulted in the project being considered relevant and yet another report of the same study led to that same project being excluded. Once the project, as described in one particular paper, passes the requirements for inclusion, on the basis of relevance, this should, in the interests of consistency, open the door for inclusion to earlier and subsequent reports associated with the same project.
The team decided to combat the perceived inconsistencies associated with project inclusion by using a cluster approach. Included references identified from the topic-based bibliographic search, retrieved using keywords, became gatekeepers for additional references by association or referral. A previously missed or wrongly excluded reference might receive a further chance for inclusion by being “vouched for”, bibliographically speaking, by a sibling study that had already been included (Figure 1).
Eight UK-based projects were identified as candidates for a study cluster approach. One project, the Glasgow Gay Men’s Task Force (GMTF), was nominated as an initial case study for developing a methodology for cluster searching. This was the project for which the information specialist, a member of the review team, was simultaneously involved in extracting subsequent data. The cluster methodology, once developed appropriately, would then be extended to the other projects to identify study clusters. Reasons for selecting the GMTF study were not methodological. The GMTF study was typical of the other projects in comprising an index citation that could be linked through berrypicking approaches to sibling (directly related) and kinship (theoretically linked) literature.

The care group started with quarterly reports in 2016 that enabled practices to compare individual practice performance with care group performance. The care group established indicators for the prevalence, registration and outcomes of cardiovascular risk factors for participating practices. Standards were set for mean value, minimal norm and best practice, an often used method to compare individual performance with peer group performance [18 (link)]. Practices asking for support, having problems with organizing adequate CVRM care or performing below a minimal norm based on the care groups’ standards were prioritized for visitation. In 2015 the care group started with visiting 52 practices and in 2016, 2017 and 2018 respectively, 98, 102 and 117 practices were visited at least once.

The study was conducted through an online questionnaire, self-completed through a computer or mobile phone with Internet access. The questionnaire was prepared using the Google Forms app. The “snowball” chain sampling procedure adapted to virtual social networks was used¹³. At the beginning of the study, invitations were sent with the link to access the questionnaire through the Facebook and Instagram virtual social networks, WhatsApp or e-mail to an initial group of people who are part of the target population (called “seeds”), which indicate peers from the same population group and so on.

As of 2019, foster parents in Denmark receive intensive support during the first six months of a placement consisting of both coursework and supervision from foster care consultants After the first year of placement, training consists of two one-day training courses annually [47 ]. As part of the follow-up casework, Danish foster parents receive face-to-face counseling from the local authorities at least once every six months [47 ]. Given their professional and personal skills, counselors can choose whatever counseling methods or techniques they deem best [48 (link)]. According to a large survey of services for foster parents and foster children in 50% of Danish municipalities, 35% of foster parents had not received any counseling within the previous year beyond the basic national requirements [49 ]. Nineteen percent of foster parents had received group supervision, 23% had received supervision by a trained psychologist or psychiatrist, 13% had participated in a peer group for foster parents, and 15% had received other types of supervision or counseling. Many foster children are, at some point during placement, offered an additional intervention besides the placement, such as treatment for mental health issues [49 ]. One out of three foster parents in the survey [49 ] reported feeling partially or entirely unequipped to raise children with mental health issues [48 (link), 49 ]. During the trial, families who receive the MBT intervention will not receive any other therapeutic interventions (including individual psychotherapy for the child). However, they may still receive the regular and mandatory support services available to all foster families in Denmark, consisting of coursework and the twice-yearly supervision. Foster care consultants will record the additional services and interventions received by the foster families in the control group during the trial. Researchers from VIVE will contact the families to motivate them to participate in the data collection.