KITE – EPIDEMIOLOGICAL MODELLING OF INFECTION SPREAD IN CHILD CARE FACILITIES

During the global COVID-19 pandemic, numerous measures were taken to mitigate the spread of infection. Among these was the closure of childcare centers since non-pharmaceutical interventions like social distancing or mask-wearing are not applicable to preschool children. However, this has led to extensive negative effects, such as reducing educational, psychosocial, and nutritional opportunities for children and increasing the risk of parenting-related exhaustion, which poses a risk factor for child abuse. The World Health Organization addressed violence against children as “a hidden crisis of the COVID-19 pandemic”. Therefore, it is essential to research testing and quarantine strategies that allow the reopening of childcare facilities, while simultaneously preventing infection spread.

KITE (KIndergarten Test scenario Evaluator) is a state-based model for simulating the spread of different airborne viruses in kindergartens. The current main focus lies on COVID-19.

Framework structure. (A) Structure of a virtual day care center for children (DCC): The DCC contains of several groups of children with their associared child care workers (CCW). The DCC consists of a head. Children and CCW/Head interact within their own groups but also among different groups. (B) State-based model of an extended SIR model that determines infection, quarantine and recovery processes for children and adults individually. (C) Viral load curve that represent the temporal course of viral load inside the respiratory tract of an individual. It starts at the exposure with a latent period, followed by an exponential viral growth phase resulting in a viral peak around the symptom onset. It ends in a slow viral decline period until the virus can no longer be detected. (D) Infection risk calculator. The probability of one infected individual infecting another individual over time is calculated using an infection risk calculator. Based on the individual viral load curve and the viral characteristice different variants lead to different infection risks.

We developed a state-based model for simulating the spread of airborne viruses e.g. COVID- 19 in child care facilities. This framework allows monitoring the viral spread for various scenarios, such as different quarantine policies, the percentage of children participating in regular testing, different testing modalities (PCR-Test, rapid antigen tests, pool tests), the test frequency, or even certain test days. Moreover, mask wearing or vaccination of individuals are used to reduce the infection spread further.

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