Background: Since the roll-out of COVID-19 vaccines in late 2020 and throughout 2021, European governments have relied on mathematical modelling to inform policy decisions about COVID-19... Show moreBackground: Since the roll-out of COVID-19 vaccines in late 2020 and throughout 2021, European governments have relied on mathematical modelling to inform policy decisions about COVID-19 vaccination. Aim: We present a scenario-based modelling analysis in the Netherlands during summer 2021, to inform whether to extend vaccination to adolescents (12-17-year-olds) and children (5-11-year-olds).Methods: We developed a deterministic, age-structured susceptible-exposedinfectious-recovered (SEIR) model and compared modelled incidences of infections, hospital and intensive care admissions, and deaths per loo,000 people across vaccination scenarios, before the emergence of the Omicron variant. Results: Our model projections showed that, on average, upon the release of all nonpharmaceutical control measures on 1 November 2021, a large COVID-19 wave may occur in winter 2021/22, followed by a smaller, second wave in spring 2022, regardless of the vaccination scenario. The model projected reductions in infections/severe disease outcomes when vaccination was extended to adolescents and further reductions when vaccination was extended to all people over 5 years-old. When examining projected disease outcomes by age group, individuals benefitting most from extending vaccination were adolescents and children themselves. We also observed reductions in disease outcomes in older age groups, particularly of parent age (30-49 years), when children and adolescents were vaccinated, suggesting some prevention of onward transmission from younger to older age groups. Conclusions: While our scenarios could not anticipate the emergence/consequences of SARS-CoV-2 Omicron variant, we illustrate how our approach can assist decision making. This could be useful when considering to provide booster doses or intervening against future infection waves. Show less
McDonald, S.A.; Wijhe, M. van; Gier, B. de; Altes, H.K.; Vlaminckx, B.J.M.; Hahne, S.; Wallinga, J. 2022
Background. Scarlet fever, an infectious disease caused by Streptococcus pyogenes, largely disappeared in developed countries during the twentieth century. In recent years, scarlet fever is on the... Show moreBackground. Scarlet fever, an infectious disease caused by Streptococcus pyogenes, largely disappeared in developed countries during the twentieth century. In recent years, scarlet fever is on the rise again, and there is a need for a better understanding of possible factors driving transmission. Methods. Using historical case notification data from the three largest cities in The Netherlands (Amsterdam, Rotterdam and The Hague) from 1906 to 1920, we inferred the transmission rate for scarlet fever using time-series susceptible-infected-recovered (TSIR) methods. Through additive regression modelling, we investigated the contributions of meteorological variables and school term times to transmission rates. Results. Estimated transmission rates varied by city, and were highest overall for Rotterdam, the most densely populated city at that time. High temperature, seasonal precipitation levels and school term timing were associated with transmission rates, but the roles of these factors were limited and not consistent over all three cities. Conclusions. While weather factors alone can only explain a small portion of the variability in transmission rates, these results help understand the historical dynamics of scarlet fever infection in an era with less advanced sanitation and no antibiotic treatment and may offer insights into the driving factors associated with its recent resurgence. Show less
Wijhe, M. van; Tulen, A.D.; Altes, H.K.; McDonald, S.A.; Melker, H.E. de; Postma, M.J.; Wallinga, J. 2018
