A Statistical Analysis of the Change in Age Distribution of Spawning Hatchery Salmon

Declines in salmon sizes have been reported primarily as a result of younger maturation rates. This change in age distribution poses serious threats to salmon-dependent peoples and ecological systems. We perform a statistical analysis to examine the change in age structure of spawning Alaskan chum salmon Oncorhynchus keta and Chinook salmon O. tshawytscha using 30 years of hatchery data. To highlight the impacts of this change, we investigate the average number of fry/smolt that each age of spawning chum/Chinook salmon produce. Our findings demonstrate an increase in younger hatchery salmon populations returning to spawn, and fewer amounts of fry produced by younger salmon compared to older salmon. These results suggest the potential risks associated with younger spawning salmon and aim to help better understand salmon behavior in order to sustain and protect healthy salmon populations

Stochastic models of influenza outbreaks on a college campus

Disease outbreaks on residential college campuses provide an ideal opportunity for mathematical modelling. Unfortunately, publicly available data are rare and many of these outbreaks are relatively small, confounding traditional data-fitting techniques such as least-squares. Using data from three outbreaks during the 2015 and 2017 flu seasons at Trinity College, we fit several SIR-type stochastic models by approximating the likelihood of each model. We find that stochasticity is a key driver in determining the size of the outbreak, and that it strongly depends on the amount of time between the start of the outbreak and the next school holiday. Our results indicate that in order to prevent or limit the size of an outbreak, school closure is likely to be more effective than increasing the vaccination rate. As influenza is a leading cause of negative academic outcomes, these results offer important guidance for school administrators