3 . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/19008417 doi: medRxiv preprint that occurs in other settings [28] . Figure 1 : Schematic representation of disease states in a model of a measles outbreak in Cox's Bazar. Individuals are either susceptible to measles (S), infectious with measles (I), or recovered from and immune to measles infection (R), either due natural immunity from infection or prior vaccination. β represents the transmission coefficient, γ is the recovery rate, and µ is the birth and death rate. The model starts with one infected (and infectious) measles case (i.e., I(0) = 1). The number of recovered individuals at time = 0 was calculated as R(0) = N − S(0) − I(0). The model tracks the number of individuals that move between the compartments each day and is run for one year using the ordinary differential equations 1-3.
The transmission coefficient, β, was estimated according to the relationship β = R0/N D, where N is the total 93 population (i.e., S + I + R) and D is the average duration of infectiousness ( The model uses one infected case as the initial value for the number of individuals in the infected compartment, I(0).
The initial value for the recovered compartment was calculated as (Table 1) . The model runs for 365 days to reflect one year following the start of the outbreak.
LHS was used to take into account uncertainty in parameter estimates; 1,000 values for each parameter were sampled 105 from the assumed parameter probability distributions (Table 1) 
where VC is ≥ 1 dose coverage of the Measles, Mumps, and Rubella (MMR) vaccine, VE is the median effectiveness . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/19008417 doi: medRxiv preprint now. Table 1 reports all parameters and calculations used as inputs in the mathematical model. LHS was again used 113 to take into account uncertainty in parameter estimates. 114 For this analysis, the SIR model was run for two years to estimate the impact of vaccination on the next outbreak.
The cumulative number of cases over two years was calculated for vaccination coverage rates of 10%, 50%, and 90% of 116 the at-risk population. Cumulative cases were estimated as the cumulative proportion of the population that moves 117 into the infectious compartment in the SIR framework. Distributions of our estimates for the cumulative number of 118 cases at two years under the different vaccination rate scenarios are presented. To contrast these results with the 119 scenario of the next measles outbreak in the absence of vaccination, the same model used to estimate the size of the 120 2017 outbreak in the absence of vaccination was used with two changes: 1) the total population size was increased to 121 870,534 [1] , and 2) the proportion of the population that was assumed to be susceptible at the start of the outbreak 122 was estimated as su instead of s0 (Table 1) Figure 3 ). Vaccination therefore has the potential to avert between approximately 4,000 and 19,000 cases over two 160 years depending on the coverage rate. Figure 4B shows estimates in terms of boxplots to reflect the uncertainty in 161 our model's results due to parameter uncertainty. . 167 We find that nearly 77,000 cases were averted over the course of one year due to vaccination in the 2017 outbreak.
The daily effective reproductive number declined from its maximum value of 4.3 at the end of week 5 to below 1 by 169 the middle of week 11. When we apply our model to estimate the impact of vaccination on subsequent outbreaks, 170 6 . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/19008417 doi: medRxiv preprint CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/19008417 doi: medRxiv preprint isolation of infectious cases were implemented during the outbreak, which would have the effect of shortening the it may be reasonable to assume that these interventions were not widely used given their infeasibility in this setting. 179 Secondly, the contraction of the serial interval described by Kenah, Lipsitch, and Robins [35] in high transmission 180 settings is not considered in this analysis. Instead, a constant serial interval distribution is assumed. For these reasons, Second, reporting rates and how these rates changed over time are also not considered in this analysis. One 187 possible scenario is that identification of measles was worse at the start of the epidemic relative to later in the 188 epidemic, and that fewer measles cases were therefore reported in the early phase of the epidemic. If this were the 189 case, the initial case counts may underestimate the true extent of measles transmission at the start of the epidemic, CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/19008417 doi: medRxiv preprint Figure 1 : Histogram of estimated R 0 values using LHS with 1,000 parameter combinations, where the maximum has been restricted to 20. Summary statistics: 13.67 (mean), 13.69 (median), 7.76 (2.5%) and 19.49 (97.5%) 13 . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/19008417 doi: medRxiv preprint CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/19008417 doi: medRxiv preprint