Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0024530 (malaria)
 44,886 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Significant progress in our understanding of disease transmission in the wild can be made by examining variation in host-parasite-vector interactions after founder events of the host. This study is the first to document patterns in avian malaria, Plasmodium spp., infecting an endemic New Zealand passerine, Anthornis melanura, at multiple-host subpopulations simultaneously. We assess the Beaudoin hypothesis of bimodal seasonality and use AIC model selection to determine host factors associated with disease prevalence. We had the rare opportunity to test the enemy release hypothesis (ERH) after a recent colonisation event of the bellbird host. Four Plasmodium species were found to infect bellbirds. Temporal patterns of three exotic parasite lineages, including GRW06 Plasmodium (Huffia) elongatum, SYAT05 Plasmodium (Novyella) vaughani and a Plasmodium (Haemamoeba) relictum, were sporadic with low prevalence year round. The fourth species was an endemic parasite, an unresolved Plasmodium (Novyella) sp. here called ANME01, which exhibited a strong winter peak at the source subpopulations possibly indicating greater immune stressors at the densely populated source site. At the colonies, we observed bimodal seasonality in the prevalence of ANME01 with autumn and spring peaks. These infection peaks were male-biased, and the amplitude of sex bias was more pronounced at the newer colony perhaps due to increased seasonal competition resulting from territory instability. We observed a decrease in parasite species diversity and increase in body condition from source to founder sites, but statistical differences in the direct relationship between body condition and malaria prevalence between source and colony were weak and significant only during winter. Though our data did not strongly support the ERH, we highlight the benefits of 'conspecific release' associated with decreased population density and food competition. Our findings contribute to the identification of ecological and environmental drivers of variability in malaria transmission, which is valuable for predicting the consequences of both natural range expansions, as well as host re-introductions resulting from intensive conservation practices.
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PMID:Patterns in avian malaria at founder and source populations of an endemic New Zealand passerine. 2287 94

The disease burden of malaria has decreased as malaria elimination efforts progress. The mapping approach that uses spatial risk distribution modeling needs some adjustment and reinvestigation in accordance with situational changes. Here we applied a mathematical modeling approach for standardized morbidity ratio (SMR) calculated by annual parasite incidence using routinely aggregated surveillance reports, environmental data such as remote sensing data, and non-environmental anthropogenic data to create fine-scale spatial risk distribution maps of western Cambodia. Furthermore, we incorporated a combination of containment status indicators into the model to demonstrate spatial heterogeneities of the relationship between containment status and risks. The explanatory model was fitted to estimate the SMR of each area (adjusted Pearson correlation coefficient R2 = 0.774; Akaike information criterion AIC = 149.423). A Bayesian modeling framework was applied to estimate the uncertainty of the model and cross-scale predictions. Fine-scale maps were created by the spatial interpolation of estimated SMRs at each village. Compared with geocoded case data, corresponding predicted values showed conformity [Spearman's rank correlation r = 0.662 in the inverse distance weighed interpolation and 0.645 in ordinal kriging (95% confidence intervals of 0.414-0.827 and 0.368-0.813, respectively), Welch's t-test; Not significant]. The proposed approach successfully explained regional malaria risks and fine-scale risk maps were created under low-to-moderate malaria transmission settings where reinvestigations of existing risk modeling approaches were needed. Moreover, different representations of simulated outcomes of containment status indicators for respective areas provided useful insights for tailored interventional planning, considering regional malaria endemicity.
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PMID:Fine-Scale Mapping by Spatial Risk Distribution Modeling for Regional Malaria Endemicity and Its Implications under the Low-to-Moderate Transmission Setting in Western Cambodia. 2741 23