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Superspreaders (individuals with a high propensity for disease spread) have played a pivotal role in recent emerging and re-emerging diseases. In disease outbreak studies, host heterogeneity based on demographic (e.g. age, sex, vaccination status) and environmental (e.g. climate, urban/rural residence, clinics) factors are critical for the spread of infectious diseases, such as Ebola and Middle East Respiratory Syndrome (MERS). Transmission rates can vary as demographic and environmental factors are altered naturally or due to modified behaviors in response to the implementation of public health strategies. In this work, we develop stochastic models to explore the effects of demographic and environmental variability on human-to-human disease transmission rates among superspreaders in the case of Ebola and MERS. We show that the addition of environmental variability results in reduced probability of outbreak occurrence, however the severity of outbreaks that do occur increases. These observations have implications for public health strategies that aim to control environmental variables.

The lessons learned from the 2009-2010 H1N1 influenza pandemic, as it moves out of the limelight, should not be under-estimated, particularly since the probability of novel influenza epidemics in the near future is not negligible and the potential consequences might be huge. Hence, as the world, particularly the industrialized world, responded to the potentially devastating effects of this novel A-H1N1 strain with substantial resources, reminders of the recurrent loss of life from a well established foe, seasonal influenza, could not be ignored. The uncertainties associated with the reported and expected levels of morbidity and mortality with this novel A-H1N1 live in a backdrop of deaths, over 200,000 hospitalizations, and millions of infections (20% of the population) attributed to seasonal influenza in the USA alone, each year. So, as the Northern Hemisphere braced for the possibility of a potentially "lethal" second wave of the novel A-H1N1 without a vaccine ready to mitigate its impact, questions of who should be vaccinated first if a vaccine became available, came to the forefront of the discussion. Uncertainty grew as we learned that the vaccine, once available, would be unevenly distributed around the world. Nations capable of acquiring large vaccine supplies soon became aware that those who could pay would have to compete for a limited vaccine stockpile. The challenges faced by nations dealing jointly with seasonal and novel A-H1N1 co-circulating strains under limited resources, that is, those with no access to novel A-H1N1 vaccine supplies, limited access to the seasonal influenza vaccine, and limited access to antivirals (like Tamiflu) are explored in this study. One- and two-strain models are introduced to mimic the influenza dynamics of a single and co-circulating strains, in the context of a single epidemic outbreak. Optimal control theory is used to identify and evaluate the "best" control policies. The controls account for the cost associated with social distancing and antiviral treatment policies. The optimal policies identified might have, if implemented, a substantial impact on the novel H1N1 and seasonal influenza co-circulating dynamics. Specifically, the implementation of antiviral treatment might reduce the number of influenza cases by up to 60% under a reasonable seasonal vaccination strategy, but only by up to 37% when the seasonal vaccine is not available. Optimal social distancing policies alone can be as effective as the combination of multiple policies, reducing the total number of influenza cases by more than 99% within a single outbreak, an unrealistic but theoretically possible outcome for isolated populations with limited resources.

Reproductive strategies comprise the timing and frequency of reproductive events and the number of offspring per reproductive event, depending on factors such as climate conditions. Therefore, species that exhibit plasticity in the allocation of reproductive effort can alter their behavior in response to climate change. Studying how the reproductive strategy of species varies along the latitudinal gradient can help us understand and predict how they will respond to climate change. We investigated the effects of the temporal allocation of reproductive effort on the population size of brown shrimp (Farfantepenaeus aztecus) along a latitudinal gradient. Multiple shrimp species exhibit variation in their reproductive strategies, and given the economic importance of brown shrimp to the commercial fishing sector of the Unites States, changes in the timing of their reproduction could have significant economic and social consequences. We used a stage-based, density-dependent matrix population model tailored to the life history of brown shrimp. Shrimp growth rates and environmental carrying capacity were varied based on the seasonal climate conditions at different latitudes, and we estimated the population size at equilibrium. The length of the growing season increased with decreasing latitude and the reproductive strategy leading to the highest population size changed from one annual birth pulse with high reproductive output to continuous low-output reproduction. Hence, our model confirms the classical paradigm of continuous reproduction at low latitudes, with increased seasonality of the breeding period towards the poles. Our results also demonstrate the potential for variation in climate to affect the optimal reproductive strategy for achieving maximum population sizes. Certainly, understanding these dynamics may inform more comprehensive management strategies for commercially important species like brown shrimp.

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