Comparison of Two Detailed Models of Aedes aegypti Population Dynamics

The success of control programs for mosquito-­borne diseases can be enhanced by crucial information provided by models of the mosquito populations. Models, however, can differ in their structure, complexity, and biological assumptions, and these differences impact their predictions. Unfortunately, it is typically difficult to determine why two complex models make different predictions because we lack structured side-­by-­side comparisons of models using comparable parameterization. Here, we present a detailed comparison of two complex, spatially explicit, stochastic models of the population dynamics of Aedes aegypti, the main vector of dengue, yellow fever, chikungunya, and Zika viruses. Both models describe the mosquito?s biological and ecological characteristics, but differ in complexity and specific assumptions. We compare the predictions of these models in two selected climatic settings: a tropical and weakly seasonal climate in Iquitos, Peru, and a temperate and strongly seasonal climate in Buenos Aires, Argentina. Both models were calibrated to operate at identical average densities in unperturbedconditions in both settings, by adjusting parameters regulating densities in each model (number of larval development sites and amount of nutritional resources). We show that the models differ in their sensitivityto environmental conditions (temperature and rainfall) and trace differences to specific model assumptions.Temporal dynamics of the Ae. aegypti populations predicted by the two models differ more markedly under strongly seasonal Buenos Aires conditions. We use both models to simulate killing of larvae and/or adults with insecticides in selected areas. We show that predictions of population recovery by the models differ substantially, an effect likely related to model assumptions regarding larval development and (director delayed) density dependence. Our methodical comparison provides important guidance for model improvement by identifying key areas of Ae. aegypti ecology that substantially affect model predictions, and revealing the impact of model assumptions on population dynamics predictions in unperturbed and perturbed conditions.Fil: Legros, Mathieu. University of North Carolina; Estados UnidosFil: Otero, Marcelo Javier. Universidad de Buenos Aires; ArgentinaFil: Romeo Aznar, Victoria Teresa. Universidad de Buenos Aires; ArgentinaFil: Solari, Hernan Gustavo. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Gould, Fred. National Institutes of Health; Estados UnidosFil: Lloyd, Alun L.. National Institutes of Health; Estados Unido

Dengue epidemics and human mobility

In this work we explore the effects of human mobility on the dispersion of a vector borne disease. We combine an already presented stochastic model for dengue with a simple representation of the daily motion of humans on a schematic city of 20x20 blocks with 100 inhabitants in each block. The pattern of motion of the individuals is described in terms of complex networks in which links connect different blocks and the link length distribution is in accordance with recent findings on human mobility. It is shown that human mobility can turn out to be the main driving force of the disease dispersal.Comment: 24 pages, 13 figure

Different land use intensities in grassland ecosystems drive ecology of microbial communities involved in nitrogen turnover in soil

Understanding factors driving the ecology of N cycling microbial communities is of central importance for sustainable land use. In this study we report changes of abundance of denitrifiers, nitrifiers and nitrogen-fixing microorganisms (based on qPCR data for selected functional genes) in response to different land use intensity levels and the consequences for potential turnover rates. We investigated selected grassland sites being comparable with respect to soil type and climatic conditions, which have been continuously treated for many years as intensely used meadows (IM), intensely used mown pastures (IP) and extensively used pastures (EP), respectively. The obtained data were linked to above ground biodiversity pattern as well as water extractable fractions of nitrogen and carbon in soil. Shifts in land use intensity changed plant community composition from systems dominated by s-strategists in extensive managed grasslands to c-strategist dominated communities in intensive managed grasslands. Along the different types of land use intensity, the availability of inorganic nitrogen regulated the abundance of bacterial and archaeal ammonia oxidizers. In contrast, the amount of dissolved organic nitrogen determined the abundance of denitrifiers (nirS and nirK). The high abundance of nifH carrying bacteria at intensive managed sites gave evidence that the amounts of substrates as energy source outcompete the high availability of inorganic nitrogen in these sites. Overall, we revealed that abundance and function of microorganisms involved in key processes of inorganic N cycling (nitrification, denitrification and N fixation) might be independently regulated by different abiotic and biotic factors in response to land use intensity

Dengue fever epidemic potential as projected by general circulation models of global climate change.

Climate factors influence the transmission of dengue fever, the world's most widespread vector-borne virus. We examined the potential added risk posed by global climate change on dengue transmission using computer-based simulation analysis to link temperature output from three climate general circulation models (GCMs) to a dengue vectorial capacity equation. Our outcome measure, epidemic potential, is the reciprocal of the critical mosquito density threshold of the vectorial capacity equation. An increase in epidemic potential indicates that a smaller number of mosquitoes can maintain a state of endemicity of disease where dengue virus is introduced. Baseline climate data for comparison are from 1931 to 1980. Among the three GCMs, the average projected temperature elevation was 1.16 degrees C, expected by the year 2050. All three GCMs projected a temperature-related increase in potential seasonal transmission in five selected cities, as well as an increase in global epidemic potential, with the largest area change occurring in temperate regions. For regions already at risk, the aggregate epidemic potential across the three scenarios rose on average between 31 and 47% (range, 24-74%). If climate change occurs, as many climatologists believe, this will increase the epidemic potential of dengue-carrying mosquitoes, given viral introduction and susceptible human populations. Our risk assessment suggests that increased incidence may first occur in regions bordering endemic zones in latitude or altitude. Endemic locations may be at higher risk from hemorrhagic dengue if transmission intensity increases

Safety for the environment of sorbitan monolaurate as a feed additive for all animal species

The additive sorbitan monolaurate consists of sorbitol (and its anhydrides) esterified with fatty acids derived from coconut oil. It is currently authorised in the European Union and it is intended to be used as a technological additive (functional group of emulsifiers), in feedingstuffs for all animal species, at a maximum concentration of 85 mg/kg complete feed. In 2019, the EFSA Panel on Additives and Products or Substances used in Animal Feed (FEEDAP) issued an opinion on the safety and efficacy of sorbitan monolaurate. Owing the lack of data, the FEEDAP Panel could not conclude on the safety of the additive for the environment. The applicant submitted new data (fate and degradation as well as ecotoxicity data) that were evaluated in the present opinion. The absorption, distribution, metabolism and excretion of structurally related compounds (sorbitan monostearate and sorbitan trioleate) indicate that the additive is expected to be partially metabolised. In addition, sorbitan monolaurate and some related compounds are readily biodegradable. The limited available data on the effects of sorbitan monolaurate in marine crustaceans and in marine sediment indicate that the ecotoxicity of the additive is low, in consistency with the very low acute toxicity of sorbitan esters. Overall, the FEEDAP Panel concludes that a risk of sorbitan monolaurate to terrestrial and aquatic environment is unlikely. Therefore, no safety concerns for the environment are expected from the use of the additive under assessment according to the established conditions of use

Climate-Based Models for Understanding and Forecasting Dengue Epidemics

Dengue fever is a major public health problem in the tropics and subtropics. Since no vaccine exists, understanding and predicting outbreaks remain of crucial interest. Climate influences the mosquito-vector biology and the viral transmission cycle. Its impact on dengue dynamics is of growing interest. We analyzed the epidemiology of dengue in Noumea (New Caledonia) from 1971 to 2010 and its relationships with local and remote climate conditions using an original approach combining a comparison of epidemic and non epidemic years, bivariate and multivariate analyses. We found that the occurrence of outbreaks in Noumea was strongly influenced by climate during the last forty years. Efficient models were developed to estimate the yearly risk of outbreak as a function of two meteorological variables that were contemporaneous (explicative model) or prior (predictive model) to the outbreak onset. Local threshold values of maximal temperature and relative humidity were identified. Our results provide new insights to understand the link between climate and dengue outbreaks, and have a substantial impact on dengue management in New Caledonia since the health authorities have integrated these models into their decision making process and vector control policies. This raises the possibility to provide similar early warning systems in other countries

Safety of Lancer® (lanthanide citrate) as a zootechnical additive for weaned piglets

Following a request from the European Commission, the Panel on Additives and Products or Substances used in Animal Feed (FEEDAP) was asked to deliver a scientific opinion on the additional data submitted on Lancer® when used as a feed additive for weaned piglets. The FEEDAP Panel considered that uncertainty still remains on possible developmental neurotoxicity of Lancer® since it was unable to identify a no observed adverse effect level (NOAEL) for this specific endpoint applying a read-across strategy from the studies provided by the applicant. However, the FEEDAP Panel considered that the exposure to La and Ce from products of animals treated with Lancer® at 250 mg/kg feed would not add a significant contribution to the background exposure of these elements. The FEEDAP Panel concluded that the use of Lancer® in feed for weaned piglets (up to 120 days) according to the proposed conditions of use, does not represent a safety concern for the consumer and for the environment

Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors

BACKGROUND: During the last decades, dengue viruses have spread throughout the Americas region, with an increase in the number of severe forms of dengue. The surveillance system in Guadeloupe (French West Indies) is currently operational for the detection of early outbreaks of dengue. The goal of the study was to improve this surveillance system by assessing a modelling tool to predict the occurrence of dengue epidemics few months ahead and thus to help an efficient dengue control. METHODS: The Box-Jenkins approach allowed us to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA) model of dengue incidence from 2000 to 2006 using clinical suspected cases. Then, this model was used for calculating dengue incidence for the year 2007 compared with observed data, using three different approaches: 1 year-ahead, 3 months-ahead and 1 month-ahead. Finally, we assessed the impact of meteorological variables (rainfall, temperature and relative humidity) on the prediction of dengue incidence and outbreaks, incorporating them in the model fitting the best. RESULTS: The 3 months-ahead approach was the most appropriate for an effective and operational public health response, and the most accurate (Root Mean Square Error, RMSE = 0.85). Relative humidity at lag-7 weeks, minimum temperature at lag-5 weeks and average temperature at lag-11 weeks were variables the most positively correlated to dengue incidence in Guadeloupe, meanwhile rainfall was not. The predictive power of SARIMA models was enhanced by the inclusion of climatic variables as external regressors to forecast the year 2007. Temperature significantly affected the model for better dengue incidence forecasting (p-value = 0.03 for minimum temperature lag-5, p-value = 0.02 for average temperature lag-11) but not humidity. Minimum temperature at lag-5 weeks was the best climatic variable for predicting dengue outbreaks (RMSE = 0.72). CONCLUSION: Temperature improves dengue outbreaks forecasts better than humidity and rainfall. SARIMA models using climatic data as independent variables could be easily incorporated into an early (3 months-ahead) and reliably monitoring system of dengue outbreaks. This approach which is practicable for a surveillance system has public health implications in helping the prediction of dengue epidemic and therefore the timely appropriate and efficient implementation of prevention activities