Global measles vaccine coverage has stagnated at approximately 85% for over a decade. By simplifying vaccine logistics and administration, the measles and rubella microarray patch (MR-MAP) may improve coverage. Clinical trials have demonstrated similar safety and immunogenicity in 9-month-old infants for MR-MAPs compared with syringe-and-needle vaccination. To aid commercialization, we present estimates of MR-MAP demand. We created a spreadsheet-based tool to estimate demand for MR-MAPs using data from 180 WHO countries during 2000-2016. Five immunization scenarios were analyzed: (1a) Supplementary Immunization Activities (SIAs) in Gavi, the Vaccine Alliance (Gavi)-eligible countries and (1b) WHO countries where preventive SIAs are routinely conducted; (2) SIAs and outbreak response immunization in all WHO countries; (3) routine immunization (RI) and SIAs in six high-burden measles countries (the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, and Pakistan); (4) RI and SIAs in six high-burden countries and Gavi-eligible countries; and (5) hard-to-reach populations. MR-MAP demand varied greatly across scenarios. Forecasts for 2025-2034 estimate from 137 million doses in hard-to-reach populations (scenario 5) to 2.587 billion doses for RI and SIAs in six high-burden countries and Gavi-eligible countries (scenario 4). When policymakers and manufacturers assess MR-MAP demand, they may consider multiple scenarios to allow for a complete consideration of potential markets and public health needs.

The 20142016 West African outbreak of Ebola Virus Disease (EVD) was the largest and most deadly to date. Contact tracing, following up those who may have been infected through contact with an infected individual to prevent secondary spread, plays a vital role in controlling such outbreaks. Our aim in this work was to mechanistically represent the contact tracing process to illustrate potential areas of improvement in managing contact tracing efforts. We also explored the role contact tracing played in eventually ending the outbreak. We present a system of ordinary differential equations to model contact tracing in Sierra Leonne during the outbreak. Using data on cumulative cases and deaths, we estimate most of the parameters in our model. We include the novel features of counting the total number of people being traced and tying this directly to the number of tracers doing this work. Our work highlights the importance of incorporating changing behavior into ones model as needed when indicated by the data and reported trends. Our results show that a larger contact tracing program would have reduced the death toll of the outbreak. Counting the total number of people being traced and including changes in behavior in our model led to better understanding of disease management.