Anticipating the risk and spatial spread of measles in populations with high MMR uptake: using school-household networks to understand the 2013 - 2014 outbreak in the Netherlands

Measles outbreaks are still routine, even in countries where vaccination coverage exceeds the guideline of 95%. Therefore, achieving ambitions for measles eradication will require understanding how unvaccinated children interact with others who are unvaccinated. Here we propose a novel framework for modelling measles transmission to better understand outbreaks in high uptake situations. The high importance of school- and home-based transmission to overall outbreak dynamics is well established. Making use of this, we created a network of all primary and secondary schools in the Netherlands based on the total number of household pairs between each school. A household pair are siblings from the same household who attend a different school. We parameterised the network with individual level administrative household data provided by the Dutch Ministry for Education and estimates of school level uptake of the Mumps, Measles and Rubella (MMR) vaccine. We analyse the network to establish the relative strength of contact between schools. We simulated measles outbreaks on the network and evaluated the model against empirical measles data per postcode-area from a large outbreak in 2013 (2766 cases), comparing the model to alternative models that do not account for specific network structure or school-level vaccine uptake. Our network analysis shows that schools associated with low vaccine uptake are highly connected, particularly Orthodox-Protestant schools (Coleman Homophily Index = 0.63). Simulations on the Network were able to reproduce the observed size and spatial distribution of the historic outbreak much more clearly than the alternative models, with a case weighted Receiver Operating Condition sensitivity of 0.94 for the data-driven network model and 0.38 and 0.23 for the alternative models. Further, we establish that variation in local network properties result in clear differences in final size of outbreaks seeded in orthodox-protestant-affiliated and other schools with low MMR coverage. Our framework indicates that clustering of unvaccinated children in primary schools connected by unvaccinated children in related secondary schools lead to large, connected clusters of unvaccinated children. Using our approach, we could explain historical outbreaks on a spatial level. Our framework could be further developed to aid future outbreak response. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement JM, AJvH and KEA received funding from the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in immunisation at the London School of Hygiene & Tropical Medicine in partnership with Public Health England. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the UK NIHR, the UK Medical Research Council, the UK Department of Health or the UK Health Security Agency. The remaining authors received no specific funding for this research. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Research Ethics Committee of London School of Hygiene and Tropical Medicine gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as [ClinicalTrials.gov][1]. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The code and school network data is available at [github.com/jdmunday/SchoolsMealesNL][2]. School population statistics are publically available from: . The Measles case data is available on request from RIVM: osiris.aiz{at}rivm.nl * ### List of abbreviations DUO : the Education Executive Agency in the netherlands HI / CHI : Homophily index / Coleman Homophily Index IQR : Interquartile Range MMR : The Measles, Mumps and Rubella Vaccine MPP : Mean Pairwise Probability OSIRIS : The Netherlands National registry of reportable infectious disease PC4 : Four digit postcode RIVM : National Institute for Public Health and the Environment ROC / wROC : Receiver Operating Characteristic / Weighted Receiver Operating Characteristic [1]: http://ClinicalTrials.gov [2]: http://github.com/jdmunday/SchoolsMealesNL