Estimating the Risk of Paediatric Multisystem Inflammatory Syndrome (PIMS-TS) Following SARS-CoV-2 Infection in Children

Abstract

Background: Paediatric Multisystem Inflammatory Syndrome (PIMS-TS) is a rare life-threatening complication that occurs in some children two to four weeks after SARS-CoV-2 infection. Although the precise causal mechanisms underpinning the relationship between SARS-CoV-2 and PIMS-TS are unclear, several recent studies have confirmed a strong temporal association. This study provides further evidence in support of a causal and temporal link. A novel methodology is presented whereby PIMS-TS incidence parameters estimated from data published on SARS-CoV-2 in the first wave of the COVID-19 pandemic in England were used to make accurate projections of PIMS-TS cases in the second wave. Methods: Case classifications and data on PIMS-TS cases were obtained from the British Paediatric Surveillance Unit (BPSU) in an endeavour initiated by Public Heath England (PHE). The dataset contained all PIMS-TS cases presenting as symptomatic in England in the first wave of the pandemic. PIMS-TS incidence rates in children aged years were estimated for the first wave and expressed as a fraction of SARS-CoV-2 cases. Data on SARS-CoV-2 cases were extracted from the PHE-Cambridge real-time model. Temporal analysis was performed to estimate the lag-time between peak SARS-CoV-2 incidence and peak PIMS-TS. The incidence and lag-time parameters estimated during the first wave were used to produce weekly projections of PIMS-TS cases in the second wave. These projections were then employed operationally in a clinical setting. Statistical analyses were performed to assess the accuracy of the forecasts once data on PIMS-TS cases were published by the BPSU approximately three months after the PIMS-TS forecasts were generated. Findings: Statistical analyses show that the PIMS-TS parameters estimated from the first wave produced accurate projections of PIMS-TS incidence in the second wave. Results at the aggregated national level showed there were no statistically significant differences observed between the PIMS-TS admission data and forecasts in England. Forecasts generated at the disaggregated regional level were also accurate, with no statistically significant differences observed between the PIMS-TS admissions data and forecasts in five of the nine Public Health England Centres (PHECs). However, a statistically significant divergence was observed between the PIMS-TS admissions data and the second wave forecasts in the regions of London and in the East, North West, and South West of England.Interpretation: This study provides further evidence in support of a causal and temporal association between SARS-CoV-2 and PIMS-TS, since data on SARS-CoV-2 incidence in the first wave of the COVID-19 pandemic in England have been shown to be a good baseline from which to generate forecasts of PIMS-TS incidence in the second wave, at both aggregated national and disaggregated regional levels.Funding Information: : Department of Health and Social Care (DHSC) Grant-in-aid funding to Public Health England (PHE).Declaration of Interests: None; this study did not receive any specific grant funding from external agencies in the public, commercial or not-for-profit sectors.Ethics Approval Statement: : PHE has legal permission under Regulation 3 of The Health Service (Control of Patient Information) Regulations 2002, to conduct national surveillance of communicable diseases in England and, as such, individual patient consent is not required. Public Health Wales, through the established order legislation, is required to conduct surveillance of communicable diseases in Wales and, as such, individual patient consent is not required. The surveillance protocol was approved by the Public Benefit and Privacy Panel for Health and Social Care in Scotland (Ref: 20210041, 19 May 2020).