73 research outputs found
The spatial epidemiology of the Duffy blood group and G6PD deficiency
Over a third of the worldās population lives at risk of potentially severe Plasmodium vivax malaria. Unique aspects of this parasiteās biology and interactions with its human host make it harder to control and eliminate than the better studied Plasmodium falciparum parasite. Spatial mapping of two human genetic polymorphisms were developed to support evidence-based targeting of control interventions and therapies. First, to enumerate and map the population at risk of P. vivax infection (PvPAR), the prevalence of this parasiteās human blood cell receptor ā the Duffy antigen ā was mapped globally. Duffy negative individuals are resistant to infection, and this map provided the means to objectively model the low endemicity of P. vivax across Africa. The Duffy maps helped resolve that only 3% of the global PvPAR was from Africa. The second major research focus was to map the spatial distribution of glucose-6-phosphate dehydrogenase enzyme deficiency (G6PDd), the genetic condition which predisposes individuals to potentially life-threatening haemolysis from primaquine therapy. Despite this drugās vital role in being the only treatment of relapsing P. vivax parasites, risks of G6PDd-associated haemolysis result in significant under-use of primaquine. G6PDd was found to be widespread, with an estimated frequency of 8.0% (50% CI: 7.4-8.8%) across malarious regions. Third, it was important to represent more detailed descriptions of the genetic diversity underpinning this enzyme disorder, which ranges in phenotype from expressing mild to life-threatening primaquine-induced haemolysis. These variantsā spatial distributions were mapped globally and showed strikingly conspicuous distributions, with widespread A- dominance across Africa, predominance of the Mediterranean variant from the Middle East across to India, and east of India diversifying into a different and diverse array of variants, showing heterogeneity both at regional and community levels. Fourth, the G6PDd prevalence and severity maps were synthesised into a framework assessing the spatial variability of overall risk from G6PDd to primaquine therapy. This found that risks from G6PDd were too widespread and potentially severe to sanction primaquine treatment without prior G6PDd screening, particularly across Asia where the majority of the population are Duffy positive and G6PDd was common and severe. Finally, the conclusions from these studies were discussed and recommendations made for essential further research needed to support current efforts into P. vivax control
Spatial patterns of clinically significant G6PD deficiency: variants, prevalence and an overall national risk index
Geographical variation in \u3ci\u3ePlasmodium vivax\u3c/i\u3e relapse
Background: Plasmodium vivax has the widest geographic distribution of the human malaria parasites and nearly 2.5 billion people live at risk of infection. The control of P. vivax in individuals and populations is complicated by its ability to relapse weeks to months after initial infection. Strains of P. vivax from different geographical areas are thought to exhibit varied relapse timings. In tropical regions strains relapse quickly (three to six weeks), whereas those in temperate regions do so more slowly (six to twelve months), but no comprehensive assessment of evidence has been conducted. Here observed patterns of relapse periodicity are used to generate predictions of relapse incidence within geographic regions representative of varying parasite transmission.
Methods: A global review of reports of P. vivax relapse in patients not treated with a radical cure was conducted. Records of time to first P. vivax relapse were positioned by geographic origin relative to expert opinion regions of relapse behaviour and epidemiological zones. Mixed-effects meta-analysis was conducted to determine which geographic classification best described the data, such that a description of the pattern of relapse periodicity within each region could be described. Model outputs of incidence and mean time to relapse were mapped to illustrate the global variation in relapse.
Results: Differences in relapse periodicity were best described by a historical geographic classification system used to describe malaria transmission zones based on areas sharing zoological and ecological features. Maps of incidence and time to relapse showed high relapse frequency to be predominant in tropical regions and prolonged relapse in temperate areas.
Conclusions: The results indicate that relapse periodicity varies systematically by geographic region and are categorized by nine global regions characterized by similar malaria transmission dynamics. This indicates that relapse may be an adaptation evolved to exploit seasonal changes in vector survival and therefore optimize transmission. Geographic patterns in P. vivax relapse are important to clinicians treating individual infections, epidemiologists trying to infer P. vivax burden, and public health officials trying to control and eliminate the disease in human populations
Geographical variation in \u3ci\u3ePlasmodium vivax\u3c/i\u3e relapse
Background: Plasmodium vivax has the widest geographic distribution of the human malaria parasites and nearly 2.5 billion people live at risk of infection. The control of P. vivax in individuals and populations is complicated by its ability to relapse weeks to months after initial infection. Strains of P. vivax from different geographical areas are thought to exhibit varied relapse timings. In tropical regions strains relapse quickly (three to six weeks), whereas those in temperate regions do so more slowly (six to twelve months), but no comprehensive assessment of evidence has been conducted. Here observed patterns of relapse periodicity are used to generate predictions of relapse incidence within geographic regions representative of varying parasite transmission.
Methods: A global review of reports of P. vivax relapse in patients not treated with a radical cure was conducted. Records of time to first P. vivax relapse were positioned by geographic origin relative to expert opinion regions of relapse behaviour and epidemiological zones. Mixed-effects meta-analysis was conducted to determine which geographic classification best described the data, such that a description of the pattern of relapse periodicity within each region could be described. Model outputs of incidence and mean time to relapse were mapped to illustrate the global variation in relapse.
Results: Differences in relapse periodicity were best described by a historical geographic classification system used to describe malaria transmission zones based on areas sharing zoological and ecological features. Maps of incidence and time to relapse showed high relapse frequency to be predominant in tropical regions and prolonged relapse in temperate areas.
Conclusions: The results indicate that relapse periodicity varies systematically by geographic region and are categorized by nine global regions characterized by similar malaria transmission dynamics. This indicates that relapse may be an adaptation evolved to exploit seasonal changes in vector survival and therefore optimize transmission. Geographic patterns in P. vivax relapse are important to clinicians treating individual infections, epidemiologists trying to infer P. vivax burden, and public health officials trying to control and eliminate the disease in human populations
Plasmodium vivax transmission in Africa
Malaria in sub-Saharan Africa has historically been almost exclusively attributed to Plasmodium falciparum (Pf). Current diagnostic and surveillance systems in much of sub-Saharan Africa are not designed to identify or report non-Pf human malaria infections accurately, resulting in a dearth of routine epidemiological data about their significance. The high prevalence of Duffy negativity provided a rationale for excluding the possibility of Plasmodium vivax (Pv) transmission. However, review of varied evidence sources including traveller infections, community prevalence surveys, local clinical case reports, entomological and serological studies contradicts this viewpoint. Here, these data reports are weighted in a unified framework to reflect the strength of evidence of indigenous Pv transmission in terms of diagnostic specificity, size of individual reports and corroboration between evidence sources. Direct evidence was reported from 21 of the 47 malaria-endemic countries studied, while 42 countries were attributed with infections of visiting travellers. Overall, moderate to conclusive evidence of transmission was available from 18 countries, distributed across all parts of the continent. Approximately 86.6 million Duffy positive hosts were at risk of infection in Africa in 2015. Analysis of the mechanisms sustaining Pv transmission across this continent of low frequency of susceptible hosts found that reports of Pv prevalence were consistent with transmission being potentially limited to Duffy positive populations. Finally, reports of apparent Duffy-independent transmission are discussed. While Pv is evidently not a major malaria parasite across most of sub-Saharan Africa, the evidence presented here highlights its widespread low-level endemicity. An increased awareness of Pv as a potential malaria parasite, coupled with policy shifts towards species-specific diagnostics and reporting, will allow a robust assessment of the public health significance of Pv, as well as the other neglected non-Pf parasites, which are currently invisible to most public health authorities in Africa, but which can cause severe clinical illness and require specific control intervention
Prioritising Infectious Disease Mapping.
BACKGROUND: Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available. METHODOLOGY/PRINCIPAL FINDINGS: Automation of ID mapping requires bespoke methodological adjustments tailored to the epidemiological characteristics of different types of diseases. Diseases were therefore grouped into 33 clusters based upon taxonomic divisions and shared epidemiological characteristics. Disability-adjusted life years, derived from the Global Burden of Disease 2013 study, were used as a globally consistent metric of disease burden. A review of global health stakeholders, existing literature and national health priorities was undertaken to assess relative interest in the diseases. The clusters were ranked by combining both metrics, which identified 44 diseases of main concern within 15 principle clusters. Whilst malaria, HIV and tuberculosis were the highest priority due to their considerable burden, the high priority clusters were dominated by neglected tropical diseases and vector-borne parasites. CONCLUSIONS/SIGNIFICANCE: A quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited
Prioritising Infectious Disease Mapping.
BACKGROUND: Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available. METHODOLOGY/PRINCIPAL FINDINGS: Automation of ID mapping requires bespoke methodological adjustments tailored to the epidemiological characteristics of different types of diseases. Diseases were therefore grouped into 33 clusters based upon taxonomic divisions and shared epidemiological characteristics. Disability-adjusted life years, derived from the Global Burden of Disease 2013 study, were used as a globally consistent metric of disease burden. A review of global health stakeholders, existing literature and national health priorities was undertaken to assess relative interest in the diseases. The clusters were ranked by combining both metrics, which identified 44 diseases of main concern within 15 principle clusters. Whilst malaria, HIV and tuberculosis were the highest priority due to their considerable burden, the high priority clusters were dominated by neglected tropical diseases and vector-borne parasites. CONCLUSIONS/SIGNIFICANCE: A quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited
Protein restriction during pregnancy alters Cdkn1c silencing, dopamine circuitry and offspring behaviour without changing expression of key neuronal marker genes
We tracked the consequences of in utero protein restriction in mice throughout their development and life course using a luciferase-based allelic reporter of imprinted Cdkn1c. Exposure to gestational low-protein diet (LPD) results in the inappropriate expression of paternally inherited Cdkn1c in the brains of embryonic and juvenile mice. These animals were characterised by a developmental delay in motor skills, and by behavioural alterations indicative of reduced anxiety. Exposure to LPD in utero resulted in significantly more tyrosine hydroxylase positive (dopaminergic) neurons in the midbrain of adult offspring as compared to age-matched, control-diet equivalents. Positron emission tomography (PET) imaging revealed an increase in striatal dopamine synthesis capacity in LPD-exposed offspring, where elevated levels of dopamine correlated with an enhanced sensitivity to cocaine. These data highlight a profound sensitivity of the developing epigenome to gestational protein restriction. Our data also suggest that loss of Cdkn1c imprinting and p57KIP2 upregulation alters the cellular composition of the developing midbrain, compromises dopamine circuitry, and thereby provokes behavioural abnormalities in early postnatal life. Molecular analyses showed that despite this phenotype, exposure to LPD solely during pregnancy did not significantly change the expression of key neuronal- or dopamine-associated marker genes in adult offspring
Mapping malaria by sharing spatial information between incidence and prevalence data sets
As malaria incidence decreases and more countries move towards elimination, maps of malaria risk in low-prevalence areas are increasingly needed. For low-burden areas, disaggregation regression models have been developed to estimate risk at high spatial resolution from routine surveillance reports aggregated by administrative unit polygons. However, in areas with both routine surveillance data and prevalence surveys, models that make use of the spatial information from prevalence point-surveys might make more accurate predictions. Using case studies in Indonesia, Senegal and Madagascar, we compare the out-of-sample mean absolute error for two methods for incorporating point-level, spatial information into disaggregation regression models. The first simply fits a binomial-likelihood, logit-link, Gaussian random field to prevalence point-surveys to create a new covariate. The second is a multi-likelihood model that is fitted jointly to prevalence point-surveys and polygon incidence data. We find that in most cases there is no difference in mean absolute error between models. In only one case, did the new models perform the best. More generally, our results demonstrate that combining these types of data has the potential to reduce absolute error in estimates of malaria incidence but that simpler baseline models should always be fitted as a benchmark
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