ASU Scholarship Showcase

Background: Highly refined surveillance data on the 2009 A/H1N1 influenza pandemic are crucial to quantify the spatial and temporal characteristics of the pandemic. There is little information about the spatial-temporal dynamics of pandemic influenza in South America. Here we provide a quantitative description of the age-specific morbidity pandemic patterns across administrative areas of Peru.

Methods: We used daily cases of influenza-like-illness, tests for A/H1N1 influenza virus infections, and laboratory-confirmed A/H1N1 influenza cases reported to the epidemiological surveillance system of Peru's Ministry of Health from May 1 to December 31, 2009. We analyzed the geographic spread of the pandemic waves and their association with the winter school vacation period, demographic factors, and absolute humidity. We also estimated the reproduction number and quantified the association between the winter school vacation period and the age distribution of cases.

Results: The national pandemic curve revealed a bimodal winter pandemic wave, with the first peak limited to school age children in the Lima metropolitan area, and the second peak more geographically widespread. The reproduction number was estimated at 1.6–2.2 for the Lima metropolitan area and 1.3–1.5 in the rest of Peru. We found a significant association between the timing of the school vacation period and changes in the age distribution of cases, while earlier pandemic onset was correlated with large population size. By contrast there was no association between pandemic dynamics and absolute humidity.

Conclusions: Our results indicate substantial spatial variation in pandemic patterns across Peru, with two pandemic waves of varying timing and impact by age and region. Moreover, the Peru data suggest a hierarchical transmission pattern of pandemic influenza A/H1N1 driven by large population centers. The higher reproduction number of the first pandemic wave could be explained by high contact rates among school-age children, the age group most affected during this early wave.

Endolithic microbial communities are prominent features of intertidal marine habitats, where they colonize a variety of substrates, contributing to their erosion. Almost 2 centuries worth of naturalistic studies focused on a few true-boring (euendolithic) phototrophs, but substrate preference has received little attention. The Isla de Mona (Puerto Rico) intertidal zone offers a unique setting to investigate substrate specificity of endolithic communities since various phosphate rock, limestone and dolostone outcrops occur there. High-throughput 16S rDNA genetic sampling, enhanced by targeted cultivation, revealed that, while euendolithic cyanobacteria were dominant operational taxonomic units (OTUs), the communities were invariably of high diversity, well beyond that reported in traditional studies and implying an unexpected metabolic complexity potentially contributed by secondary colonizers. While the overall community composition did not show differences traceable to the nature of the mineral substrate, we detected specialization among particular euendolithic cyanobacterial clades towards the type of substrate they excavate but only at the OTU phylogenetic level, implying that close relatives have specialized recurrently into particular substrates. The cationic mineral component was determinant in this preference, suggesting the existence in nature of alternatives to the boring mechanism described in culture that is based exclusively on transcellular calcium transport.

The filamentous, non-heterocystous cyanobacterium Lyngbya aestuarii is an important contributor to marine intertidal microbial mats system worldwide. The recent isolate L. aestuarii BL J, is an unusually powerful hydrogen producer. Here we report a morphological, ultrastructural, and genomic characterization of this strain to set the basis for future systems studies and applications of this organism. The filaments contain circa 17 μm wide trichomes, composed of stacked disk-like short cells (2 μm long), encased in a prominent, laminated exopolysaccharide sheath. Cellular division occurs by transversal centripetal growth of cross-walls, where several rounds of division proceed simultaneously. Filament division occurs by cell self-immolation of one or groups of cells (necridial cells) at the breakage point. Short, sheath-less, motile filaments (hormogonia) are also formed. Morphologically and phylogenetically L. aestuarii belongs to a clade of important cyanobacteria that include members of the marine Trichodesmiun and Hydrocoleum genera, as well as terrestrial Microcoleus vaginatus strains, and alkalyphilic strains of Arthrospira. A draft genome of strain BL J was compared to those of other cyanobacteria in order to ascertain some of its ecological constraints and biotechnological potential.

The genome had an average GC content of 41.1%. Of the 6.87 Mb sequenced, 6.44 Mb was present as large contigs (>10,000 bp). It contained 6515 putative protein-encoding genes, of which, 43% encode proteins of known functional role, 26% corresponded to proteins with domain or family assignments, 19.6% encode conserved hypothetical proteins, and 11.3% encode apparently unique hypothetical proteins. The strain's genome reveals its adaptations to a life of exposure to intense solar radiation and desiccation. It likely employs the storage compounds, glycogen, and cyanophycin but no polyhydroxyalkanoates, and can produce the osmolytes, trehalose, and glycine betaine. According to its genome, BL J strain also has the potential to produce a plethora of products of biotechnological interest such as Curacin A, Barbamide, Hemolysin-type calcium-binding toxin, the suncreens scytonemin, and mycosporines, as well as heptadecane and pentadecane alkanes. With respect to hydrogen production, initial comparisons of the genetic architecture and sequence of relevant genes and loci, and a comparative model of protein structure of the NiFe bidirectional hydrogenase, did not reveal conspicuous differences that could explain its unusual hydrogen producing capacity.

We formulate an in silico model of pathogen avoidance mechanism and investigate its impact on defensive behavioural measures (e.g., spontaneous social exclusions and distancing, crowd avoidance and voluntary vaccination adaptation). In particular, we use SIR(B)S (e.g., susceptible-infected-recovered with additional behavioural component) model to investigate the impact of homo-psychologicus aspects of epidemics. We focus on reactionary behavioural changes, which apply to both social distancing and voluntary vaccination participations. Our analyses reveal complex relationships between spontaneous and uncoordinated behavioural changes, the emergence of its contagion properties, and mitigation of infectious diseases. We find that the presence of effective behavioural changes can impede the persistence of disease. Furthermore, it was found that under perfect effective behavioural change, there are three regions in the response factor (e.g., imitation and/or reactionary) and behavioural scale factor (e.g., global/local) factors ρ–α behavioural space. Mainly, (1) disease is always endemic even in the presence of behavioural change, (2) behavioural-prevalence plasticity is observed and disease can sometimes be eradication, and (3) elimination of endemic disease under permanence of permanent behavioural change is achieved. These results suggest that preventive behavioural changes (e.g., non-pharmaceutical prophylactic measures, social distancing and exclusion, crowd avoidance) are influenced by individual differences in perception of risks and are a salient feature of epidemics. Additionally, these findings indicates that care needs to be taken when considering the effect of adaptive behavioural change in predicting the course of epidemics, and as well as the interpretation and development of the public health measures that account for spontaneous behavioural changes.

The coastal environments of South Africa’s Cape Floristic Region (CFR) provide some of the earliest and most abundant evidence for the emergence of cognitively modern humans. In particular, the south coast of the CFR provided a uniquely diverse resource base for hunter-gatherers, which included marine shellfish, game, and carbohydrate-bearing plants, especially those with Underground Storage Organs (USOs). It has been hypothesized that these resources underpinned the continuity of human occupation in the region since the Middle Pleistocene. Very little research has been conducted on the foraging potential of carbohydrate resources in the CFR. This study focuses on the seasonal availability of plants with edible carbohydrates at six-weekly intervals over a two-year period in four vegetation types on South Africa’s Cape south coast. Different plant species were considered available to foragers if the edible carbohydrate was directly (i.e. above-ground edible portions) or indirectly (above-ground indications to below-ground edible portions) visible to an expert botanist familiar with this landscape. A total of 52 edible plant species were recorded across all vegetation types. Of these, 33 species were geophytes with edible USOs and 21 species had aboveground edible carbohydrates. Limestone Fynbos had the richest flora, followed by Strandveld, Renosterveld and lastly, Sand Fynbos. The availability of plant species differed across vegetation types and between survey years. The number of available USO species was highest for a six-month period from winter to early summer (Jul–Dec) across all vegetation types. Months of lowest species’ availability were in mid-summer to early autumn (Jan–Apr); the early winter (May–Jun) values were variable, being highest in Limestone Fynbos. However, even during the late summer carbohydrate “crunch,” 25 carbohydrate bearing species were visible across the four vegetation types. To establish a robust resource landscape will require additional spatial mapping of plant species abundances. Nonetheless, our results demonstrate that plant-based carbohydrate resources available to Stone Age foragers of the Cape south coast, especially USOs belonging to the Iridaceae family, are likely to have comprised a reliable and nutritious source of calories over most of the year.

We describe a multi-parameter family of the minimum-uncertainty squeezed states for the harmonic oscillator in nonrelativistic quantum mechanics. They are derived by the action of the corresponding maximal kinematical invariance group on the standard ground state solution. We show that the product of the variances attains the required minimum value 1/4 only at the instances that one variance is a minimum and the other is a maximum, when the squeezing of one of the variances occurs. The generalized coherent states are explicitly constructed and their Wigner function is studied. The overlap coefficients between the squeezed, or generalized harmonic, and the Fock states are explicitly evaluated in terms of hypergeometric functions and the corresponding photon statistics are discussed. Some applications to quantum optics, cavity quantum electrodynamics and superfocusing in channelling scattering are mentioned. Explicit solutions of the Heisenberg equations for radiation field operators with squeezing are found.

Neglected tropical diseases (NTD), account for a large proportion of the global disease burden, and their control faces several challenges including diminishing human and financial resources for those distressed from such diseases. Visceral leishmaniasis (VL), the second-largest parasitic killer (after malaria) and an NTD affects poor populations and causes considerable cost to the affected individuals. Mathematical models can serve as a critical and cost-effective tool for understanding VL dynamics, however, complex array of socio-economic factors affecting its dynamics need to be identified and appropriately incorporated within a dynamical modeling framework. This study reviews literature on vector-borne diseases and collects challenges and successes related to the modeling of transmission dynamics of VL. Possible ways of creating a comprehensive mathematical model is also discussed.

Photoautotrophs assimilate oxidized carbon obtained from one of two sources: dissolved or atmospheric. Despite its size, the pool of lithospheric carbonate is not known to be a direct source for autotrophy. Yet, the mechanism that euendolithic cyanobacteria use to excavate solid carbonates suggests that minerals could directly supply CO[subscript 2] for autotrophy. Here, we use stable isotopes and NanoSIMS to show that the cyanobacterium Mastigocoleus testarum derives most of its carbon from the mineral it excavates, growing preferentially as an endolith when lacking dissolved CO[subscript 2]. Furthermore, natural endolithic communities from intertidal marine carbonate outcrops present carbon isotopic signatures consistent with mineral-sourced autotrophy. These data demonstrate a direct geomicrobial link between mineral carbonate pools and reduced organic carbon, which, given the geographical extent of carbonate outcrops, is likely of global relevance. The ancient fossil record of euendolithic cyanobacteria suggests that biological fixation of solid carbonate could have been relevant since the mid-Proterozoic.

Variation in behaviour among group members often impacts collective outcomes. Individuals may vary both in the task that they perform and in the persistence with which they perform each task. Although both the distribution of individuals among tasks and differences among individuals in behavioural persistence can each impact collective behaviour, we do not know if and how they jointly affect collective outcomes. Here, we use a detailed computational model to examine the joint impact of colony-level distribution among tasks and behavioural persistence of individuals, specifically their fidelity to particular resource sites, on the collective trade-off between exploring for new resources and exploiting familiar ones. We developed an agent-based model of foraging honeybees, parametrized by data from five colonies, in which we simulated scouts, who search the environment for new resources, and individuals who are recruited by the scouts to the newly found resources, i.e. recruits. We varied the persistence of returning to a particular food source of both scouts and recruits and found that, for each value of persistence, there is a different optimal ratio of scouts to recruits that maximizes resource collection by the colony. Furthermore, changes to the persistence of scouts induced opposite effects from changes to the persistence of recruits on the collective foraging of the colony. The proportion of scouts that resulted in the most resources collected by the colony decreased as the persistence of recruits increased. However, this optimal proportion of scouts increased as the persistence of scouts increased. Thus, behavioural persistence and task participation can interact to impact a colony's collective behaviour in orthogonal directions. Our work provides new insights and generates new hypotheses into how variations in behaviour at both the individual and colony levels jointly impact the trade-off between exploring for new resources and exploiting familiar ones.

Antiviral resistance in influenza is rampant and has the possibility of causing major morbidity and mortality. Previous models have identified treatment regimes to minimize total infections and keep resistance low. However, the bulk of these studies have ignored stochasticity and heterogeneous contact structures. Here we develop a network model of influenza transmission with treatment and resistance, and present both standard mean-field approximations as well as simulated dynamics. We find differences in the final epidemic sizes for identical transmission parameters (bistability) leading to different optimal treatment timing depending on the number initially infected. We also find, contrary to previous results, that treatment targeted by number of contacts per individual (node degree) gives rise to more resistance at lower levels of treatment than non-targeted treatment. Finally we highlight important differences between the two methods of analysis (mean-field versus stochastic simulations), and show where traditional mean-field approximations fail. Our results have important implications not only for the timing and distribution of influenza chemotherapy, but also for mathematical epidemiological modeling in general. Antiviral resistance in influenza may carry large consequences for pandemic mitigation efforts, and models ignoring contact heterogeneity and stochasticity may provide misleading policy recommendations.