142 research outputs found

    Modeling and control of malaria dynamics in fish farming regions

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    In this work we propose a model that represents the relation between fish ponds, the mosquito population and the transmission of malaria. It has been observed that in the Amazonic region of Acre, in the North of Brazil, fish farming is correlated to the transmission of malaria when carried out in artificial ponds that become breeding sites. Evidence has been found indicating that cleaning the vegetation from the edges of the crop tanks helps to control the size of the mosquito population. We use our model to determine the effective contribution of the fish tanks to the epidemic. The model consists of a nonlinear system of ordinary differential equations with jumps at the cleaning time, which act as impulsive controls. We study the asymptotic behaviour of the system in function of the intensity and periodicity of the cleaning, and the value of the parameters. In particular, we state sufficient conditions under which the mosquito population is exterminated or prevails, and under which the malaria is eradicated or becomes endemic. We prove our conditions by applying results for cooperative systems with concave nonlinearities

    Unveiling time in dose-response models to infer host susceptibility to pathogens

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    The biological effects of interventions to control infectious diseases typically depend on the intensity of pathogen challenge. As much as the levels of natural pathogen circulation vary over time and geographical location, the development of invariant efficacy measures is of major importance, even if only indirectly inferrable. Here a method is introduced to assess host susceptibility to pathogens, and applied to a detailed dataset generated by challenging groups of insect hosts (Drosophila melanogaster) with a range of pathogen (Drosophila C Virus) doses and recording survival over time. The experiment was replicated for flies carrying the Wolbachia symbiont, which is known to reduce host susceptibility to viral infections. The entire dataset is fitted by a novel quantitative framework that significantly extends classical methods for microbial risk assessment and provides accurate distributions of symbiont-induced protection. More generally, our data-driven modeling procedure provides novel insights for study design and analyses to assess interventions

    Social and demographic factors associated with morbidities in young children in Egypt: A Bayesian geo-additive semi-parametric multinomial model.

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    Globally, the burden of mortality in children, especially in poor developing countries, is alarming and has precipitated concern and calls for concerted efforts in combating such health problems. Examples of diseases that contribute to this burden of mortality include diarrhoea, cough, fever, and the overlap between these illnesses, causing childhood morbidity and mortality. Methods: To gain insight into these health issues, we employed the 2008 Demographic and Health Survey Data of Egypt, which recorded details from 10,872 children under five. This data focused on the demographic and socio-economic characteristics of household members. We applied a Bayesian multinomial model to assess the area-specific spatial effects and risk factors of co-morbidity of fever, diarrhoea and cough for children under the age of five. Results: The results showed that children under 20 months of age were more likely to have the three diseases (OR: 6.8; 95% CI: 4.6-10.2) than children between 20 and 40 months (OR: 2.14; 95% CI: 1.38-3.3). In multivariate Bayesian geo-additive models, the children of mothers who were over 20 years of age were more likely to have only cough (OR: 1.2; 95% 2 CI: 0.9-1.5) and only fever (OR: 1.2; 95% CI: 0.91-1.51) compared with their counterparts. Spatial results showed that the North-eastern region of Egypt has a higher incidence than most of other regions. Conclusions: This study showed geographic patterns of Egyptian governorates in the combined prevalence of morbidity among Egyptian children. It is obvious that the Nile Delta, Upper Egypt, and south-eastern Egypt have high rates of diseases and are more affected. Therefore, more attention is needed in these areas. Funding: The authors have no support or funding to report. Competing Interests: The authors have declared that no competing interests exist

    Endemic and epidemic dynamics of cholera: the role of the aquatic reservoir

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    BACKGROUND: In the last decades, attention to cholera epidemiology increased, as cholera epidemics became a worldwide health problem. Detailed investigation of V. cholerae interactions with its host and with other organisms in the environment suggests that cholera dynamics is much more complex than previously thought. Here, I formulate a mathematical model of cholera epidemiology that incorporates an environmental reservoir of V. cholerae. The objective is to explore the role of the aquatic reservoir on the persistence of endemic cholera as well as to define minimum conditions for the development of epidemic and endemic cholera. RESULTS: The reproduction rate of cholera in a community is defined by the product of social and environmental factors. The importance of the aquatic reservoir depends on the sanitary conditions of the community. Seasonal variations of contact rates force a cyclical pattern of cholera outbreaks, as observed in some cholera-endemic communities. CONCLUSIONS: Further development on cholera modeling requires a better understanding of V. cholerae ecology and epidemiology. We need estimates of the prevalence of V. cholerae infection in endemic populations as well as a better description of the relationship between dose and virulence

    Widespread fear of dengue transmission but poor practices of dengue prevention : A study in the slums of Delhi, India

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    Background This study has been conducted to throw light on the knowledge and practices related to dengue fever among the poor population living in Delhi's slums. Materials A household survey was conducted in 2013 among 3,350 households. The households were stratified by a number of variables related to socio-economic status and health events such as hospitalisation. The data collection was completed through face-to-face interviews conducted with the help of 25 field investigators. Results About 8% of the households had at least one diagnosed dengue case. In comparison to the population surveyed, teenagers (15-19 years) and adults (30-34 years) were more affected whereas children under four years of age were underrepresented. Housewives are more affected by dengue (24%) compared to their share of the population surveyed (17%). Despite the fact that 77% of the respondents are worried about mosquitoes, only 43% of them monitor environment to avoid the presence of breeding sites. Conclusion One cannot exclude the possibility that though young children under the age of four years are exposed to the virus, either their cases were asymptomatic or family members infected during this period had potentially more serious symptoms leading to hospitalisation. This result could thus be explained by budget-related health choices made by this population which do not favour small children. Educational programs should target housewives to improve their impact, as they are the ones mostly responsible for water storage and cleanliness of the house and its neighbourhood. Even with a dengue experience and potentially an acute perception of the risk and its factors, a proper management of environmental conditions is lacking. This along with the fact that word-of-mouth is the main source of information quoted should be a message for municipality health workers to give door-to-door information on how to prevent breeding sites and dengue infection

    Development, environmental degradation, and disease spread in the Brazilian Amazon.

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    The Amazon is Brazil's greatest natural resource and invaluable to the rest of the world as a buffer against climate change. The recent election of Brazil's president brought disputes over development plans for the region back into the spotlight. Historically, the development model for the Amazon has focused on exploitation of natural resources, resulting in environmental degradation, particularly deforestation. Although considerable attention has focused on the long-term global cost of "losing the Amazon," too little attention has focused on the emergence and reemergence of vector-borne diseases that directly impact the local population, with spillover effects to other neighboring areas. We discuss the impact of Amazon development models on human health, with a focus on vector-borne disease risk. We outline policy actions that could mitigate these negative impacts while creating opportunities for environmentally sensitive economic activities

    Forcing Versus Feedback: Epidemic Malaria and Monsoon Rains in Northwest India

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    Malaria epidemics in regions with seasonal windows of transmission can vary greatly in size from year to year. A central question has been whether these interannual cycles are driven by climate, are instead generated by the intrinsic dynamics of the disease, or result from the resonance of these two mechanisms. This corresponds to the more general inverse problem of identifying the respective roles of external forcings vs. internal feedbacks from time series for nonlinear and noisy systems. We propose here a quantitative approach to formally compare rival hypotheses on climate vs. disease dynamics, or external forcings vs. internal feedbacks, that combines dynamical models with recently developed, computational inference methods. The interannual patterns of epidemic malaria are investigated here for desert regions of northwest India, with extensive epidemiological records for Plasmodium falciparum malaria for the past two decades. We formulate a dynamical model of malaria transmission that explicitly incorporates rainfall, and we rely on recent advances on parameter estimation for nonlinear and stochastic dynamical systems based on sequential Monte Carlo methods. Results show a significant effect of rainfall in the inter-annual variability of epidemic malaria that involves a threshold in the disease response. The model exhibits high prediction skill for yearly cases in the malaria transmission season following the monsoonal rains. Consideration of a more complex model with clinical immunity demonstrates the robustness of the findings and suggests a role of infected individuals that lack clinical symptoms as a reservoir for transmission. Our results indicate that the nonlinear dynamics of the disease itself play a role at the seasonal, but not the interannual, time scales. They illustrate the feasibility of forecasting malaria epidemics in desert and semi-arid regions of India based on climate variability. This approach should be applicable to malaria in other locations, to other infectious diseases, and to other nonlinear systems under forcing
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