Assessment of Anopheles salivary antigens as individual exposure biomarkers to species-specific malaria vector bites

The development of parasitological immunity against malaria affects the ability to detect infection, the efficiency of the local human parasite reservoir at infecting mosquitoes, and the response to reintroduction of parasites to previously cleared areas. Observations of similar age-trends in detected prevalence and mean parasitaemia across more than an order-of-magnitude of variation in baseline transmission complicate simple exposure-driven explanations. Mathematical models often employ age-dependent immune factors to match the observed trends, while the present model uses a new detailed mechanistic model of parasite transmission dynamics to explain age-trends through the mechanism of parasite diversity. Illustrative simulations are performed for multiple field sites in Tanzania and Nigeria, and observed age-trends and seasonality in parasite prevalence are recreated in silico, proffering possible mechanistic explanations of the observational data. Observed temporal dynamics in measured parasitaemia are recreated for each location and age-prevalence outputs are studied. Increasing population-level diversity in malaria surface antigens delays development of broad parasitological immunity. A local parasite population with high diversity can recreate the observed trends in age-prevalence across more than an order of magnitude of variation in transmission intensities. Mechanistic models of human immunity and parasite antigen diversity can recreate the observed temporal patterns for the development of parasitological immunity across a wide range of transmission intensities. This has implications for the distribution of disease burden across the population, the human transmission reservoir, design of elimination campaigns, and development and roll-out of potential vaccines.     

Estimating the numbers of malaria infections in blood samples using high-resolution genotyping data

People living in endemic areas often habour several malaria infections at once. High-resolution genotyping can distinguish between infections by detecting the presence of different alleles at a polymorphic locus. However the number of infections may not be accurately counted since parasites from multiple infections may carry the same allele. We use simulation to determine the circumstances under which the number of observed genotypes are likely to be substantially less than the number of infections present and investigate the performance of two methods for estimating the numbers of infections from high-resolution genotyping data.THE SIMULATIONS SUGGEST THAT THE PROBLEM IS NOT SUBSTANTIAL IN MOST DATASETS: the disparity between the mean numbers of infections and of observed genotypes was small when there was 20 or more alleles, 20 or more blood samples, a mean number of infections of 6 or less and where the frequency of the most common allele was no greater than 20%. The issue of multiple infections carrying the same allele is unlikely to be a major component of the errors in PCR-based genotyping.Simulations also showed that, with heterogeneity in allele frequencies, the observed frequencies are not a good approximation of the true allele frequencies. The first method that we proposed to estimate the numbers of infections assumes that they are a good approximation and hence did poorly in the presence of heterogeneity. In contrast, the second method by Li et al estimates both the numbers of infections and the true allele frequencies simultaneously and produced accurate estimates of the mean number of infections.     

No relationship between individual genetic diversity and prevalence of avian malaria in a migratory kestrel

Insight into the genetic basis of malaria resistance is crucial for understanding the consequences of this parasite group on animal populations. Here, we analyse the relationship between genotypic variation at 11 highly variable microsatellite loci and prevalence of three different lineages of avian malaria, two Plasmodium (RTSR1, LK6) and one Haemoproteus (LK2), in a wild population of the endangered lesser kestrel (Falco naumanni). Although we used a large sample size (584 typed individuals), we did not find any significant association between the prevalence of the studied parasite lineages and individual genetic diversity. Although our data set is large, the 11 neutral markers typed may have had low power to detect such association, in part because of the low parasite prevalence observed (less than 5% of infected birds). However, the fact that we have detected previous correlations between genetic diversity and other traits (ectoparasitism risk, fecundity) in the study population using the same panel of neutral markers and lower sample sizes suggests that other factors could underlie the absence of such a similar correlation with avian malaria. Differences in the genetics of the studied traits and in their particular basis of inbreeding depression (dominance vs. overdominance) may have led to malaria prevalence, but not other traits, being uncoupled with individual genetic diversity. Also, we cannot discard the possibility that the absence of association was a consequence of a low pathogenic effect of these particular malaria lineages on our lesser kestrel population, and thus we should not expect the evolution of genetic resistance against these parasites.     

True versus apparent malaria infection prevalence: the contribution of a Bayesian approach

Aims

To present a new approach for estimating the “true prevalence” of malaria and apply it to datasets from Peru, Vietnam, and Cambodia.

Methods

Bayesian models were developed for estimating both the malaria prevalence using different diagnostic tests (microscopy, PCR & ELISA), without the need of a gold standard, and the tests'' characteristics. Several sources of information, i.e. data, expert opinions and other sources of knowledge can be integrated into the model. This approach resulting in an optimal and harmonized estimate of malaria infection prevalence, with no conflict between the different sources of information, was tested on data from Peru, Vietnam and Cambodia.

Results

Malaria sero-prevalence was relatively low in all sites, with ELISA showing the highest estimates. The sensitivity of microscopy and ELISA were statistically lower in Vietnam than in the other sites. Similarly, the specificities of microscopy, ELISA and PCR were significantly lower in Vietnam than in the other sites. In Vietnam and Peru, microscopy was closer to the “true” estimate than the other 2 tests while as expected ELISA, with its lower specificity, usually overestimated the prevalence.

Conclusions

Bayesian methods are useful for analyzing prevalence results when no gold standard diagnostic test is available. Though some results are expected, e.g. PCR more sensitive than microscopy, a standardized and context-independent quantification of the diagnostic tests'' characteristics (sensitivity and specificity) and the underlying malaria prevalence may be useful for comparing different sites. Indeed, the use of a single diagnostic technique could strongly bias the prevalence estimation. This limitation can be circumvented by using a Bayesian framework taking into account the imperfect characteristics of the currently available diagnostic tests. As discussed in the paper, this approach may further support global malaria burden estimation initiatives.     

Estimating disease prevalence in two-phase studies

Disease prevalence is ideally estimated using a 'gold standard' to ascertain true disease status on all subjects in a population of interest. In practice, however, the gold standard may be too costly or invasive to be applied to all subjects, in which case a two-phase design is often employed. Phase 1 data consisting of inexpensive and non-invasive screening tests on all study subjects are used to determine the subjects that receive the gold standard in the second phase. Naive estimates of prevalence in two-phase studies can be biased (verification bias). Imputation and re-weighting estimators are often used to avoid this bias. We contrast the forms and attributes of the various prevalence estimators. Distribution theory and simulation studies are used to investigate their bias and efficiency. We conclude that the semiparametric efficient approach is the preferred method for prevalence estimation in two-phase studies. It is more robust and comparable in its efficiency to imputation and other re-weighting estimators. It is also easy to implement. We use this approach to examine the prevalence of depression in adolescents with data from the Great Smoky Mountain Study.     

Estimating field metabolic rates for Australian marsupials using phylogeny

Field metabolic rate (FMR) is a useful measure for the energy expenditure in free-ranging animals. Field metabolic rates for species that have not been measured are usually predicted by allometric equations on the basis of their body mass (BM). Phylogenetically informed methods improve estimates of both allometric relationships and species-specific FMR values by considering the evolutionary history of species. Further improvement is possible by incorporating isolated measurements on BM and FMR, but most existing methods force the user to discard such incomplete data. In the present study the FMR of most Australian marsupial species was predicted for the first time using a phylogenetic method that was explicitly designed to handle incomplete data. This allows full use of the dataset containing 35 samples of FMR and 130 samples of BM. Cross-validation demonstrated that FMRs were estimated with high accuracy. The resulting prediction equation was FMR (kJ day^? 1) = 5.27 BM (g)^0.69. Field metabolic rate and BM were highly phylogenetically correlated (r = 0.96), i.e. FMR and BM co-evolved. Differences between species-specific and generic marsupial estimates of FMR revealed that herbivores have lower energy expenditure than carnivores. Specifically, herbivorous macropods have on average lower relative FMR (kJ/d) (3.75 ± 0.53 BM^0.69; mean ± SD) than carnivorous dasyurids (7.64 ± 0.84 BM^0.69). Phylogenetically informed estimates for most extant Australian marsupial species are now available.     

Molecular approaches to field studies of malaria

The third 'Molecular Approaches to Malaria' conference was held in Lorne, Australia, in February 2008 and provided extensive information on the application of molecular tools in field studies on malaria. In recent years, technological advances and capacity building in malaria-endemic countries have permitted molecular tools to be applied much more frequently and successfully with exciting new findings. In this review, Hans-Peter Beck and Kevin Tetteh report on the most recent findings using molecular tools in field studies.     

Modeling erythropoiesis subject to malaria infection

A mathematical model of erythropoiesis subject to malaria infection is developed by combining ideas from previous models that addressed only one of the two phenomena. The nature of the model allows one to account for suppression of erythropoiesis by the toxin hemozoin, which is a by-product of digested hemoglobin. Following the derivation of the model, numerical simulations are performed and show that the number of parasites produced per bursting erythrocyte has the most significant effect of erythropoiesis. It is also shown that removing hemozoin may be an effective method for aiding the recovery of the erythrocyte population, but is not effective in maintaining a healthy population in the early stages of infection. The second half of the paper introduces an implicit finite difference scheme that was used to perform the simulations previously mentioned. An existence-uniqueness result is then provided via the numerical method.     

Estimating photosynthetic radiation use efficiency using incident light and photosynthesis of individual leaves

It has been theorized that photosynthetic radiation use efficiency (PhRUE) over the course of a day is constant for leaves throughout a canopy if leaf nitrogen content and photosynthetic properties are adapted to local light so that canopy photosynthesis over a day is optimized. To test this hypothesis, 'daily' photosynthesis of individual leaves of Solanum melongena plants was calculated from instantaneous rates of photosynthesis integrated over the daylight hours. Instantaneous photosynthesis was estimated from the photosynthetic responses to photosynthetically active radiation (PAR) and from the incident PAR measured on individual leaves during clear and overcast days. Plants were grown with either abundant or scarce N fertilization. Both net and gross daily photosynthesis of leaves were linearly related to daily incident PAR exposure of individual leaves, which implies constant PhRUE over a day throughout the canopy. The slope of these relationships (i.e. PhRUE) increased with N fertilization. When the relationship was calculated for hourly instead of daily periods, the regressions were curvilinear, implying that PhRUE changed with time of the day and incident radiation. Thus, linearity (i.e. constant PhRUE) was achieved only when data were integrated over the entire day. Using average PAR in place of instantaneous incident PAR increased the slope of the relationship between daily photosynthesis and incident PAR of individual leaves, and the regression became curvilinear. The slope of the relationship between daily gross photosynthesis and incident PAR of individual leaves increased for an overcast compared with a clear day, but the slope remained constant for net photosynthesis. This suggests that net PhRUE of all leaves (and thus of the whole canopy) may be constant when integrated over a day, not only when the incident PAR changes with depth in the canopy, but also when it varies on the same leaf owing to changes in daily incident PAR above the canopy. The slope of the relationship between daily net photosynthesis and incident PAR was also estimated from the photosynthetic light response curve of a leaf at the top of the canopy and from the incident PAR above the canopy, in place of that measured on individual leaves. The slope (i.e. net PhRUE) calculated in this simple way did not differ statistically from that calculated using data from individual leaves.     

Estimating the prevalence of inbreeding from incomplete pedigrees

A previous review of inbreeding in natural populations suggested that close inbreeding (inbreeding coefficient f = 0.25) is generally rare in wild birds and mammals. However, the review did not assess rates of moderate inbreeding (f = 0.125), which may make a rather larger contribution to overall inbreeding in a population. Furthermore, previous studies may have underestimated the prevalence of inbreeding in wild populations with incomplete pedigrees. By categorizing inbreeding events by the relationship of the parental pair, we suggest a simple method for estimating rates of close and moderate inbreeding from incomplete pedigree data. We applied this method to three wild populations of ruminants: red deer on Rum, Scotland, Soay sheep on Hirta, Scotland and reintroduced Arabian oryx on the Jiddat-al-Harasis, Oman. Although paternal half-sib pairs were the most common category of inbreeding in all three populations, there was considerable variation among populations in the frequencies of the various categories of inbreeding. This variation may be largely explained by differences in population size and dynamics, in maternal and paternal sibship size and in the overlap of reproductive lifespan of consecutive generations. Close and moderate inbreeding appear to be a routine part of breeding behaviour in these ruminant populations.     

Estimating local ancestry in admixed populations

Large-scale genotyping of SNPs has shown a great promise in identifying markers that could be linked to diseases. One of the major obstacles involved in performing these studies is that the underlying population substructure could produce spurious associations. Population substructure can be caused by the presence of two distinct subpopulations or a single pool of admixed individuals. In this work, we focus on the latter, which is significantly harder to detect in practice. New advances in this research direction are expected to play a key role in identifying loci that are different among different populations and are still associated with a disease. We evaluated current methods for inference of population substructure in such cases and show that they might be quite inaccurate even in relatively simple scenarios. We therefore introduce a new method, LAMP (Local Ancestry in adMixed Populations), which infers the ancestry of each individual at every single-nucleotide polymorphism (SNP). LAMP computes the ancestry structure for overlapping windows of contiguous SNPs and combines the results with a majority vote. Our empirical results show that LAMP is significantly more accurate and more efficient than existing methods for inferring locus-specific ancestries, enabling it to handle large-scale datasets. We further show that LAMP can be used to estimate the individual admixture of each individual. Our experimental evaluation indicates that this extension yields a considerably more accurate estimate of individual admixture than state-of-the-art methods such as STRUCTURE or EIGENSTRAT, which are frequently used for the correction of population stratification in association studies.     

Determinants of avian malaria prevalence in mountainous Transcaucasia

Deforestation, urban development, and global climate change can lead to dramatic changes of ecological communities and increase prevalence of infectious diseases at higher latitudes and altitudes. Identification of factors responsible for the prevalence of parasites is of crucial importance to understand the dynamics of parasite distribution in a changing environment. Mountain areas are especially suitable for studies of factors governing parasite distribution and prevalence due to heterogeneity of landscapes, climatic regimes, and other biotic and abiotic conditions. We examined 903 avian blood smears collected in mountains of Transcaucasia for prevalence of Haemoproteus and Plasmodium. We found that the haemoparasites prevalence differed among bird species and localities, highlighting the environmental components affecting disease distribution. The prevalence of both Haemoproteus and Plasmodium was significantly higher in males, adults, and migratory species than in females, juveniles, and resident species. Geographic Information System (GIS) and linear regression analyses revealed that elevation and monthly average precipitation were strongly correlated with proportion of infected birds with Plasmodium, indicating that the prevalence increased with increase of monthly average temperature and elevation. Birds from forested and high grassed areas were also more infected with avian haemosporidia. Our study provides baseline data for modelling of parasites distribution under global climate change scenarios, which is of great importance for monitoring and management of communities and environment for conservation and human health.     

Estimating individual contributions to population growth: evolutionary fitness in ecological time

Ecological and evolutionary change is generated by variation in individual performance. Biologists have consequently long been interested in decomposing change measured at the population level into contributions from individuals, the traits they express and the alleles they carry. We present a novel method of estimating individual contributions to population growth and changes in distributions of quantitative traits and alleles. An individual's contribution to population growth is an individual's realized annual fitness. We demonstrate how the quantities we develop can be used to address a range of empirical questions, and provide an application to a detailed dataset of Soay sheep. The approach provides results that are consistent with those obtained using lifetime estimates of individual performance, yet is substantially more powerful as it allows lifetime performance to be decomposed into annual survival and fecundity contributions.     

Widespread distribution of insecticide-impregnated curtains reduces child mortality, prevalence and intensity of malaria infection, and malaria transmission in rural Burkina Faso

The results of the first two years of implementation of a large scale trial of insecticide-treated curtains in Burkina Faso are summarised in this presentation. The trial was conducted in a highly malarious area and involved a population of slightly less than 100,000, distributed in 158 villages over an area of almost 1000 km2. A remarkable impact on entomological parameters (Anopheles density, sporozoite rate, entomological inoculation rate) was accompanied by a relatively modest reduction of parasitological indices (prevalence and density of Plasmodium falciparum). All-cause mortality in children 0.5 to 5 year old showed over two years a 15% decline. The authors believe that the wide surface of the protected zone and the almost total coverage achieved in the intervention villages were the major determinants of the observed reduction of transmission. A conclusive interpretation of the mortality results requires a further follow-up of the study population.     

Estimating the prevalence and strength of non-independent predator effects

Understanding whether multiple predator species have independent effects on shared prey is critical for understanding community dynamics. We describe the prevalence and strength of non-independence between predators by quantifying the prey’s risk of predation and the degree to which it deviates from the risk predicted from a null model of independent predator effects. Specifically, we document how frequently non-independent effects occur among ten different multiple predator combinations with mayfly larvae as prey. These predator combinations vary both predator density and predator species richness. Overall, the predator effects were non-independent and translated to an average of 27% fewer prey being consumed compared to independent predator effects. Non-independence of this magnitude is likely to have population level consequences for the prey and influence the distribution or prey preference of predators. Closer inspection shows that much of the risk reduction in this system is weak, to the point of being indistinguishable from independent predator effects, while few effects are strong. This pattern of many weak interactions and few strong ones parallels the pattern of interaction strengths documented previously in intertidal communities. Consequently, understanding strong interactors in multiple predator systems may help us understand the importance of a species.     

Estimating the malaria transmission of Plasmodium vivax based on serodiagnosis

ABSTRACT: BACKGROUND: Plasmodium vivax re-emerged in 1993 and has now become a major public health problem during the summer season in South Korea. The aim of this study was to interpret and understand the meaning of seroepidemiological studies for developing the best malaria control programme in South Korea. METHODS: Blood samples were collected in Gimpo city, Paju city, Yeoncheon County, Cheorwon County and Goseong County of high risk area in South Korea. Microscopy was performed to identify patients infected with P. vivax. Antibody detection for P. vivax was performed using indirect fluorescent antibody test (IFAT). RESULTS: A total of 1,574 blood samples was collected from participants in the study areas and evaluated against three parameters: IFAT positive rate, annual antibody positive index (AAPI), and annual parasite index (API). The IFAT positive rate was 7.24% (n = 114). Of the five study areas, Gimpo had the highest IFAT positive rate (13.68%) and AAPI (4.63). Yeongcheon had the highest API in 2005 (2.06) while Gimpo had the highest API in 2006 (5.00). No correlation was observed between any of the three parameters and study sites' distance from the demilitarized zone (DMZ). CONCLUSIONS: These results showed that P. vivax antibody levels could provide useful information about the prevalence of malaria in endemic areas. Furthermore, AAPI results for each year showed a closer relationship to API the following year than the API of the same year and thus could be helpful in predicting malaria transmission risks.