A Temperature Conditioned Markov Chain Model for Predicting the Dynamics of Mosquito Vectors of Disease.

Understanding and predicting mosquito population dynamics is crucial for gaining insight into the abundance of arthropod disease vectors and for the design of effective vector control strategies. In this work, a climate-conditioned Markov chain (CMC) model was developed and applied for the first time to predict the dynamics of vectors of important medical diseases. Temporal changes in mosquito population profiles were generated to simulate the probabilities of a high population impact. The simulated transition probabilities of the mosquito populations achieved from the trained model are very near to the observed data transitions that have been used to parameterize and validate the model. Thus, the CMC model satisfactorily describes the temporal evolution of the mosquito population process. In general, our numerical results, when temperature is considered as the driver of change, indicate that it is more likely for the population system to move into a state of high population level when the former is a state of a lower population level than the opposite. Field data on frequencies of successive mosquito population levels, which were not used for the data inferred MC modeling, were assembled to obtain an empirical intensity transition matrix and the frequencies observed. Our findings match to a certain degree the empirical results in which the probabilities follow analogous patterns while no significant differences were observed between the transition matrices of the CMC model and the validation data (ChiSq = 14.58013, df = 24, p = 0.9324451). The proposed modeling approach is a valuable eco-epidemiological study. Moreover, compared to traditional Markov chains, the benefit of the current CMC model is that it takes into account the stochastic conditional properties of ecological-related climate variables. The current modeling approach could save costs and time in establishing vector eradication programs and mosquito surveillance programs.

An in vitro ULV olfactory bioassay method for testing the repellent activity of essential oils against moths.

A prototype olfactory device was developed and used for first time to study the bioactivity of Ultra Low Volumes (ULV) of three essential oilsagainst the moth pest Anarsia lineatella (Lepidoptera: Gelechiidae). Particle sizes calibration and standard ULV time-doses range tests were performed prior the olfactory bioassays. Three essential oils were tested Cymbopogon citratus (Lemon Grass), Gaultheria procumbens (Winter Grass) and Rosmarinus officinalis (Rosmarin) according to the proposed method. The most active oil was that of R. officinalis and moths expressed approximately 3-5 fold faster moving behavior (50% repellence response times to ULV, RT50: 20-30 min) compared to G. procumbens (RT50:74-79 min) and C. citratus (RT50:82-96 min). Apart from direct observed repellence, moths sprayed with ULV show clearly signs of knock down symptoms and high fatality in a period 15-60 min after their treatment especial in the case of R. officinalis. Longevity of female moths was significantly affected by the initial ULV application. Furthermore, choice test showed that essential oils significantly deterred oviposition in most cases. Considering the urgent need for alternative to conventional pesticides the current work may provide a framework of testing the bioactivity of bio rational compounds in the form of ULV and under Lab conditions.

Age Related Assessment of Sugar and Protein Intake of Ceratitis capitata in ad libitum Conditions and Modeling Its Relation to Reproduction.

In the inquiry on the age related dietary assessment of an organism, knowledge of the distributional patterns of food intake throughout the entire life span is very important, however, age related nutritional studies often lack robust feeding quantification methods due to their limitations in obtaining short-term food-intake measurements. In this study, we developed and standardized a capillary method allowing precise life-time measurements of food consumption by individual adult medflies, Ceratitis capitata (Diptera: Tephritidae), under laboratory conditions. Protein or sugar solutions were offered via capillaries to individual adults for a 5 h interval daily and their consumption was measured, while individuals had lifetime ad libitum access to sugar or protein, respectively, in solid form. Daily egg production was also measured. The multivariate data-set (i.e., the age-dependent variations in the amount of sugar and protein ingestion and their relation to egg production) was analyzed using event history charts and 3D interpolation models. Maximum sugar intake was recorded early in adult life; afterwards, ingestion progressively dropped. On the other hand, maximum levels of protein intake were observed at mid-ages; consumption during early and late adult ages was kept at constant levels. During the first 30 days of age, type of diet and sex significantly contributed to the observed difference in diet intake while number of laid eggs varied independently. Male and female adult longevity was differentially affected by diet: protein ingestion extended the lifespan, especially, of males. Smooth surface models revealed a significant relationship between the age dependent dietary intake and reproduction. Both sugar and protein related egg-production have a bell-shaped relationship, and the association between protein and egg-production is better described by a 3D Lorenzian function. Additionally, the proposed 3D interpolation models produced good estimates of egg production and diet intake as affected by age, providing us with a reliable multivariate analytical tool to model nutritional trends in insects, and other organisms, and their effect upon life history traits. The modeling also strengthened the knowledge that egg production is closely related to protein consumption, as suggested by the shape of the medfly reproduction-response function and its functional relationship to diet intake and age.

Energetic loads and informational entropy during insect metamorphosis: measuring structural variability and self-organization.

In this work an information theory approach is presented for measuring structural variability during insect metamorphosis. Following a self-organizational perspective, the underlying assumption is that an insect pupa is a cybernetic bio-system, which displays a homeostatic control during its metamorphosis. The description of structural variability was based on biochemical data (lipids, glycogen, carbohydrates and proteins) analysed at different time intervals during the metamorphosis of Anarsia lineatella Zeller (Lepidoptera: Gelechiidae). Probabilities of biochemical variables were further treated by considering a finite countable set of progressive metamorphosis states having Markov properties at isothermal conditions (25 °C, 16:8h L:D, 65 ± 5%RH). The probabilities of the biochemical variables, as well as the related informational entropies, are affected when the system moves one step forward for each successive state. In most cases, but protein, there is some observable evidence that histolysis could be related to a decrease in informational entropy H ('disorganization of the system'), followed by a 'stable balance period' during the middle stages of metamorphosis. An initial increase in H is measured at the last stages of metamorphosis, which theoretically correspond to histogenesis ('reorganization of the system'). In this context, the temporal evolution of pupal structural variability was probabilistically quantified according to the classical information theory. The principles of the proposed holistic system are independent of its detailed dynamics and the proposed model can potentially describe part of the observable experimental data during metamorphosis of a holometabolous insect.