54 research outputs found

    The interaction of seasonal forcing and immunity and the resonance dynamics of malaria

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    This is the final version of the article. Available from the Royal Society via the DOI in this recordTheory has emphasized the importance of both intrinsic factors such as host immunity and extrinsic drivers such as climate in determining disease dynamics. In particular, seasonality may lead to multi-annual cycles in prevalence, but the likelihood of this depends on the role of acquired immunity. Some diseases including malaria have immunity that falls between the classic susceptible-infectious-removed and susceptible-infectious-susceptible models. Here, we investigate the general conditions promoting the subharmonic resonance behaviour that may lead to multi-annual cycles in a general malaria dynamical model. Utilizing two complementary approaches to bifurcation analyses, we show that resonance is promoted by processes shortening the length of the infectious period and that subharmonic cycles are favoured in situations with strong seasonality in transmission but at intermediate levels of endemicity. We discuss the implications of our results for understanding prevalence patterns in long-term malaria datasets from Kenya that show multi-annual cycles and one from Thailand that does not and discuss the possible implications of treatment.This work was supported by the award of a Leverhulme Early Career Research Fellowship to D.Z.C. and a Welcome Trust VIP grant M.B

    Multigenerational pedigree analysis of wild individually marked black sparrowhawks suggests that dark plumage coloration is a dominant autosomal trait

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    The black sparrowhawk (Accipiter melanoleucus) is a color-polymorphic sub-Saharan raptor, with adults occurring in two discrete color morphs: dark and light. It has previously been suggested that plumage coloration is determined by a one-locus two-allele system, with the light allele being dominant over the dark allele. Here, we revisit that assumption with an extended dataset of 130 individuals and pedigree information from 75 individuals spanning five generations. We test the observed offspring phenotypic ratio against the expected ratio under the Hardy- Weinberg equilibrium and find significant deviations from the expected values. Contrary to the previous assumption, our data indicate that the dark allele is in fact dominant over the light allele. Similarly, the multigenerational pedigrees obtained are incompatible with a one-locus two-allele system, where the light allele is dominant but are consistent with a scenario where the dark allele is dominant instead. However, without knowledge of the underlying molecular basis of plumage polymorphism, uncertainty remains, and the intra-morph variation observed suggests that modifier genes or environmental factors may also be involved. Our study not only provides a foundation for future research on the adaptive function of color polymorphism in the species but also highlights the need for caution when drawing conclusions about the mode of inheritance in wild animal populations in the absence of genetic data, especially when one color variant is numerically much rarer than the other.</p

    Operational approach to open dynamics and quantifying initial correlations

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    A central aim of physics is to describe the dynamics of physical systems. Schrodinger's equation does this for isolated quantum systems. Describing the time evolution of a quantum system that interacts with its environment, in its most general form, has proved to be difficult because the dynamics is dependent on the state of the environment and the correlations with it. For discrete processes, such as quantum gates or chemical reactions, quantum process tomography provides the complete description of the dynamics, provided that the initial states of the system and the environment are independent of each other. However, many physical systems are correlated with the environment at the beginning of the experiment. Here, we give a prescription of quantum process tomography that yields the complete description of the dynamics of the system even when the initial correlations are present. Surprisingly, our method also gives quantitative expressions for the initial correlation.Comment: Completely re-written for clarity of presentation. 15 pages and 2 figure

    Modeling the clonal heterogeneity of stem cells

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    Recent experimental studies suggest that tissue stem cell pools are composed of functionally diverse clones. Metapopulation models in ecology concentrate on collections of populations and their role in stabilizing coexistence and maintaining selected genetic or epigenetic variation. Such models are characterized by expansion and extinction of spatially distributed populations. We develop a mathematical framework derived from the multispecies metapopulation model of Tilman et al (1994) to study the dynamics of heterogeneous stem cell metapopulations. In addition to normal stem cells, the model can be applied to cancer cell populations and their response to treatment. In our model disturbances may lead to expansion or contraction of cells with distinct properties, reflecting proliferation, apoptosis, and clonal competition. We first present closed-form expressions for the basic model which defines clonal dynamics in the presence of exogenous global disturbances. We then extend the model to include disturbances which are periodic and which may affect clones differently. Within the model framework, we propose a method to devise an optimal strategy of treatments to regulate expansion, contraction, or mutual maintenance of cells with specific properties

    Space-time variation of malaria incidence in Yunnan province, China

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    Abstract Background Understanding spatio-temporal variation in malaria incidence provides a basis for effective disease control planning and monitoring. Methods Monthly surveillance data between 1991 and 2006 for Plasmodium vivax and Plasmodium falciparum malaria across 128 counties were assembled for Yunnan, a province of China with one of the highest burdens of malaria. County-level Bayesian Poisson regression models of incidence were constructed, with effects for rainfall, maximum temperature and temporal trend. The model also allowed for spatial variation in county-level incidence and temporal trend, and dependence between incidence in June–September and the preceding January–February. Results Models revealed strong associations between malaria incidence and both rainfall and maximum temperature. There was a significant association between incidence in June–September and the preceding January–February. Raw standardised morbidity ratios showed a high incidence in some counties bordering Myanmar, Laos and Vietnam, and counties in the Red River valley. Clusters of counties in south-western and northern Yunnan were identified that had high incidence not explained by climate. The overall trend in incidence decreased, but there was significant variation between counties. Conclusion Dependence between incidence in summer and the preceding January–February suggests a role of intrinsic host-pathogen dynamics. Incidence during the summer peak might be predictable based on incidence in January–February, facilitating malaria control planning, scaled months in advance to the magnitude of the summer malaria burden. Heterogeneities in county-level temporal trends suggest that reductions in the burden of malaria have been unevenly distributed throughout the province

    Malaria risk and access to prevention and treatment in the paddies of the Kilombero Valley, Tanzania

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    Background: The Kilombero Valley is a highly malaria-endemic agricultural area in south-eastern Tanzania. Seasonal flooding of the valley is favourable to malaria transmission. During the farming season, many households move to distant field sites (shamba in Swahili) in the fertile river floodplain for the cultivation of rice. In the shamba, people live for several months in temporary shelters, far from the nearest health services. This study assessed the impact of seasonal movements to remote fields on malaria risk and treatment-seeking behaviour. Methods: A longitudinal study followed approximately 100 randomly selected farming households over six months. Every household was visited monthly and whereabouts of household members, activities in the fields, fever cases and treatment seeking for recent fever episodes were recorded. Results: Fever incidence rates were lower in the shamba compared to the villages and moving to the shamba did not increase the risk of having a fever episode. Children aged 1-4 years, who usually spend a considerable amount of time in the shamba with their caretakers, were more likely to have a fever than adults (odds ratio = 4.47, 95 confidence interval 2.35-8.51). Protection with mosquito nets in the fields was extremely good (98 antimalarials was uncommon. Despite the long distances to health services, 55.8 health facility, while home-management was less common (37 17.4-50.5). Conclusion: Living in the shamba does not appear to result in a higher fever-risk. Mosquito nets usage and treatment of fever in health facilities reflect awareness of malaria. Inability to obtain drugs in the fields may contribute to less irrational use of drugs but may pose an additional burden on poor farming households. A comprehensive approach is needed to improve access to treatment while at the same time assuring rational use of medicines and protecting fragile livelihoods

    Using serological measures to monitor changes in malaria transmission in Vanuatu

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    BACKGROUND: With renewed interest in malaria elimination, island environments present unique opportunities to achieve this goal. However, as transmission decreases, monitoring and evaluation programmes need increasingly sensitive tools to assess Plasmodium falciparum and Plasmodium vivax exposure. In 2009, to assess the role of serological markers in evaluating malaria transmission, a cross-sectional seroprevalence study was carried out in Tanna and Aneityum, two of the southernmost islands of the Vanuatu archipelago, areas where malaria transmission has been variably reduced over the past few decades. METHODS: Malaria transmission was assessed using serological markers for exposure to P. falciparum and P. vivax. Filter blood spot papers were collected from 1,249 people from Tanna, and 517 people from Aneityum to assess the prevalence of antibodies to two P. falciparum antigens (MSP-119 and AMA-1) and two P. vivax antigens (MSP-119 and AMA-1). Age-specific prevalence was modelled using a simple catalytic conversion model based on maximum likelihood to generate a community seroconversion rate (SCR). RESULTS: Overall seropositivity in Tanna was 9.4%, 12.4% and 16.6% to P. falciparum MSP-119, AMA-1 and Schizont Extract respectively and 12.6% and 15.0% to P. vivax MSP-119 and AMA-1 respectively. Serological results distinguished between areas of differential dominance of either P. vivax or P. falciparum and analysis of age-stratified results showed a step in seroprevalence occurring approximately 30 years ago on both islands, indicative of a change in transmission intensity at this time. Results from Aneityum suggest that several children may have been exposed to malaria since the 2002 P. vivax epidemic. CONCLUSION: Seroepidemiology can provide key information on malaria transmission for control programmes, when parasite rates are low. As Vanuatu moves closer to malaria elimination, monitoring changes in transmission intensity and identification of residual malaria foci is paramount in order to concentrate intervention efforts

    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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