key: cord-1039632-fu5r3wsg
authors: Fefferman, Nina H.; Blacker, Katy-Ann; Price, Charles A.; LoBue, Vanessa
title: When do children avoid infection risks: Lessons for schools during the COVID-19 pandemic
date: 2022-02-26
journal: iScience
DOI: 10.1016/j.isci.2022.103989
sha: 8f9596cd51aa6046a87e6aa2810f1562af05a8da
doc_id: 1039632
cord_uid: fu5r3wsg

The physical closing of schools due to COVID-19 has disrupted both student learning and family logistics. There is significant pressure for in-person learning to remain open for all children. However, as is expected with outbreaks of novel infections, vaccines and other pharmaceutical therapeutics may not be instantly available. This raises serious public health questions about the risks to children and society at large. The best protective measures for keeping young children in school focus on behaviors that limit transmission. It is therefore critical to understand how we can engage children in age-appropriate ways that will best support their ability to adhere to protocols effectively. Here, we synthesize published studies with new results to investigate the earliest ages at which children form an understanding of infection risk and when they can translate that understanding effectively to protective action.

The ongoing COVID-19 pandemic has highlighted the differential vulnerability of 31 children to outbreaks of novel infectious diseases. While children are much less likely to suffer 32 severe acute outcomes from COVID-19 infection (Cruz and Zeichner, 2020) , that is not always 33 guaranteed to be true for each new disease threat. Although the risks are much lower than for 34 adults during the current pandemic, some children do become seriously ill and can die from 35 COVID-19 infection (Feldstein et al., 2021; Kamidani et al., 2021) . Further, already emergent 36 mutated strains of COVID-19 have demonstrated the ability to shift towards causing more severe 37 infection in younger people (de Souza et al., 2021) and until the pandemic is under global 38 control, the emergence of new strains with varied demographic impacts should not be 39 discounted. This is especially worrisome because as more adults and older children are 40 vaccinated, there will be increased evolutionary selective pressure on SARS-CoV-2 to shift to 41 better efficacy of transmission in younger populations (Kennedy and Read, 2020; Saad-Roy et 42 al., 2021) . Monitoring, and potentially interrupting transmission dynamics in school-age children 43 is further complicated by our current reliance on either symptoms or known symptomatic 44 contacts for disease surveillance (Lokuge et al., 2021) , including how to identify whom to test 45 for new asymptomatic infection. Since children are more likely to be asymptomatic but may still 46 be capable of transmitting infection (DeBiasi and Delaney, 2021) , outbreaks among children will 47 3 circulate widely, allowing more evolutionary opportunities for novel mutation that could make 50 the pathogen more successful in younger individuals or even overcoming immune protection 51 among those older individuals who have already been either infected or immunized. Lastly, 52 children continue to be likely to have delayed access to novel interventions such as vaccines or 53 pharmaceutical treatments (e.g., the later approvals during vaccine rollout; (Gumbrecht and Fox, 54 2021; Rodriguez, 2021)). 55 Of course, the greatest opportunity for transmission of infection among school-aged 56 children is in schools themselves. Since both society and children suffer when schools are closed 57 (Armitage and Nellums, 2020; Esposito and Principi, 2020) awaiting the roll-out of vaccines for younger school-aged children, our best tools have been 63 relying on children's behavioral interventions to limit potential transmission. Indoor social 64 distancing is difficult given the number of children in classrooms, and social distancing alone 65 may not be sufficient (Bazant and Bush, 2021) . This leaves us predominantly reliant on mask-66 wearing and hand-hygiene (Liu et al., 2021) . Both strategies can be cumbersome and difficult to 67 adhere to for adults (Crane et al., 2021) , much less for very young children, leaving us to ask if 68 there are any ways that we can increase adherence and/or efficacy in our youngest populations. 69 Training in intervention practices at any age can be challenging, but understanding the 70 rationale behind interventions can increase the probability of success beyond simply teaching 71 mechanical procedures (Whitby et al., 2007) . Teaching methods used with children should 72 J o u r n a l P r e -p r o o f consider children's ability to understand how illnesses spread, and when children can effectively 73 apply their understanding to act appropriately when faced with exposure risks. 74 Since children's understanding of the world increases with age, we need to answer two 75 critical questions: At what age can children learn to perform protective hygienic practices, and at 76 what age do children understand why engaging in hygienic practices (e.g., how they work, why 77 they are beneficial, etc.) can keep them healthy? Understanding disease transmission, and 78 therefore how some behaviors can protect against it, relies on two separate concepts: direct 79 contagion, in which a person is exposed by contact of some form with an infectious person, and 80 contamination, in which a person is exposed by encountering an area or object harboring 81 infectious agents. Both factors manifest in a variety of complicated and potentially dependent 82 epidemiological mechanisms, and while neither concept is natively apparent, contamination 83 requires the ability to consider intermediate, unobservable states as links in a chain leading to 84 infection risks. It is therefore probable that children develop an understanding of direct contagion 85 before they develop an understanding of contamination. 86 Recent studies have explored the effectiveness of educational interventions to increase 87 knowledge about hygiene and increased hygienic behaviors e.g. (Au et al., 2008; Bieri et al., 88 2013; Huis et al., 2012; Süß et al., 2011) "why" and instead focus on "how," training methods and mechanical skills. However, as soon as 97 children can begin to understand how illnesses are transmitted, education can be shifted to 98 include equal (if not greater) emphasis on the "why", explaining the "how" in terms of the 99 successful interruption of transmission and exploring how insufficient care with the "how" can 100 fail to achieve the goal of the practice. These guidelines could be enacted in group settings and 101 come in the form of advice to parents/caregivers to minimize frustration while increasing the 102 effectiveness of efforts to encourage personal hygienic practices in children. 103 Here, we review recent empirical studies that investigate the earliest ages at which Understanding illness transmission is difficult for young children, as it requires them to 113 reason about hidden or non-obvious properties and mechanisms (Au et al., 1993; Kalish, 1996; 114 Keil et al., 1999) . For example, when talking to even the youngest children about illness, we often 115 refer to "germs." But while talking about germs might make the concept of illness transmission 116 somewhat concrete for children, it still refers to a causal mechanism for illness that children cannot 117 J o u r n a l P r e -p r o o f see or touch. As a result, it takes some time for children to develop a full understanding of illness 118 transmission (see Figure 1 , Graphical Abstract). 119 Children's reasoning about illness transmission first begins to develop in the preschool 120 years and continues throughout middle childhood (Keil et al., 1999; Myant and Williams, 2005) . 121 By the age of 4, children have some understanding of illness transmission and can differentiate 122 between contagious and non-contagious interactions (Kalish, 1996) "germs" cause illness, and that germs are living or biological entities (Kalish, 1996) . At the same 127 age, children also prefer biological explanations for how someone might get sick to social ones 128 (Springer and Ruckel, 1992) , demonstrating that they have some basic intuitions about how illness 129 is transmitted. 130 However, studies examining a wider age-range suggest that a full understanding of illness 131 transmission develops slowly over time and that children's understanding of the complex 132 biological processes that underlie illness transmission do not appear until much later in 133 development (Fig 1) . For example, although preschool-aged children can pick out events that they 134 associate with illnesses, they cannot use that knowledge to make predictions about whether 135 someone will become sick after engaging in a risk behavior (Legare et al., 2009) . Further, while 136 3-to 6-year-old children understand that close physical interactions between two people can act as 137 a cue for illness transmission, older (5-and 6-year-old) children show superior performance when Three-and 4-year-old children were willing to eat the same amount of applesauce from both bowls, 154 but the 5-to 8-year-olds consumed more applesauce from the clean bowl than from the bowl that 155 had been "contaminated" by the sneeze, suggesting that between the ages of 5 and 8, children 156 begin to avoid contaminated foods. Importantly, however, even though the older children ate more 157 of the clean applesauce than the contaminated applesauce, many of them still ate some the 158 contaminated applesauce, suggesting that full avoidance may not develop until much later. 159 In another study, Blacker and LoBue (2016) probed children's behavior when faced with 160 contagion. In this study, 4-to 7-year-old children were prompted to interact with two 161 confederates-one that was "sick," and one that was not-and various toys that each of 162 confederates touched. Children were also given a vignette task to assess their verbal knowledge of 163 J o u r n a l P r e -p r o o f contagious illness. Only 6-and 7-year-olds avoided proximity to and contact with the sick 164 confederate and her toys; the 4-and 5-year-olds played equally long with each confederate's toys 165 and did not avoid physical proximity to either confederate. However, the best predictor of 166 children's avoidance behavior was not age, but instead, their ability to make predictions about 167 illness outcomes. In other words, even 4-and 5-year-olds avoided proximity to the sick confederate in this control condition did not show an increase in causal knowledge or hand washing behavior. 205 Thus, it appears that knowledge interventions that improve children's causal knowledge support 206 adaptive behavioral change. However, it is currently unclear whether such interventions would 207 lead to conceptual and behavioral change in children younger than age 8. 208 Only one recently published pilot study tested whether younger, preschool-aged children 

Children were seated on the floor in front of a laptop computer between two covered 22 boxes. One box was covered in green cardboard stars, while the other was covered in yellow 23 stars. The green box was always placed on the left, and the yellow box was always on the right. 24 Each box contained an identical set of four toys, chosen because they were appropriate for 25 preschool children, and they afford touching and, in some cases, breathing on the toys: bubbles, 26 Mr. Potato Head, pin art, and slinky. 27 The child was shown a video on the laptop depicting the same boxes in the same spatial 28 configuration placed in front of two confederates who were wearing t-shirts that matched the 29 boxes. The video was approximately two minutes long and depicted the confederates taking turns 30 removing the identical toys from their corresponding box and playing with them. For each set of 31 toys, the confederates either displayed a physical symptom of illness (sick confederate) or 32 performed a neutral action (neutral confederate) before removing each toy from the box and 33 performing an action with it. The symptoms were sneezing, coughing, and wiping her nose with 34 her hand. The neutral actions were sighing, yawning, and stretching her arms. Each symptom 35 was repeated twice over the course of the video. 36 The video began with the two confederates sitting directly behind the two closed boxes. The child was invited to sit on the floor directly in front of the laptop, which displayed 58 the paused video in full screen. The experimenter then informed the child about the video and the 59 toys in the boxes, "We're going to watch a video that my friends made for you right before I 60 came here this morning! They put toys in these boxes here for you to play with, and they made 61 the video to show you the toys in the boxes." Then, the experimenter pointed to each confederate 62 on the screen, then at the box on the screen, and then at the corresponding box next to the 63 computer, "See this girl here in the yellow/green shirt? This morning, she put toys in this box 64 right here with the yellow/green stars [points to box on screen] and then I brought it here [points 65 to real box next to computer]. This was repeated for the other confederate and box. Then, the 66 J o u r n a l P r e -p r o o f main experimenter described the symptomatic confederate as having "the flu, so they have a 67 fever, a headache, and a sore throat" and the asymptomatic confederate as having "a toothache, 68 so their tooth hurts a lot when they try to eat or drink anything." The introduction order was 69 counterbalanced, so that half of the children heard the sick experimenter described first, and the 70 other half heard her described second. 71 Next, the experimenter pressed play, and then took a seat next to, but slightly behind, the 72 child. When the video began to play, the experimenter drew the child's attention to the video, 

s faces from the Child Affective Face (CAFE) Set (LoBue and Thrasher, 90 2015) and asked questions about them. During the main portion of the interview

the children were read four vignettes-two about common 92 contagious illnesses (the cold and the flu) and two about non-contagious ailments (toothache and 93 broken arm). For example, in the cold vignette

Danny has a broken arm, so his arm is swollen and really hurts when he tries to move it

After each vignette, the child was asked to 98 provide an explanation for how the main character in the vignette became ill or injured. Then, 99 they were told that someone else played with main character and were asked to make a 100 prediction about whether that person would get the main character's ailment from playing with

Contact began when a child 105 touched a toy and ended when they put it down. Contact with the toys that came from the box the 106 symptomatic person interacted with were coded as "sick" and contact with toys from the other 107 box were coded as "healthy". Each child received an avoidance score that reflected the 108 percentage of the two-minute play session that they did not spend in contact with the 109 symptomatic person's toys. The child's

 113 Children's explanations were coded as follows: Risk Behaviors: Any mention of 114 engaging in a risk behavior (touching something dirty, falling down, etc.) was coded. Proximity: 115 Risk behaviors were further coded for whether they mentioned proximity to someone who was 116 sick or person-to-person contact. Preventative Measures: Explanations were also coded for 117 whether they mentioned failure to engage in a preventative measure (wearing a coat, washing 118 their hands, etc.). Biological: Explanations were coded for whether they explicitly mentioned 119 germs. Other: "I don't know" and all other responses were coded as "other". Contagion-120 relevant/irrelevant: Explanations were grouped as to whether they fell into two broad 121 categories-contagion-relevant or contagion-irrelevant. Explanations that were initially coded as 122 mentioning a risk behavior, as mentioning a failure to engage in a preventative measure, as 123 biological, or as including person-to-person contact or proximity (cold only) were categorized as 124 "contagion-relevant". Explanations that fell under "other" or "I don't know" were combined to 125 form the "contagion-irrelevant" category. 126 Children's responses to the prediction questions about person-to-person transmission 127 were coded as 1 for a correct response (e.g., yes for cold and no for broken arm) and as 0 for an 128 incorrect response (e.g., no for cold and yes for broken arm). A coder blind to condition coded 129 the responses on all measures for all children, and a second coder coded a random 25% of the 130 responses. Coder agreement was above 90% for all measures.