Spatio-temporal dynamics of Plasmodium falciparum transmission within a spatial unit on the Colombian Pacific Coast.
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SUBMITTER: Knudson A
PROVIDER: S-EPMC7048816 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Characterising connectivity between geographically separated biological populations is a common goal in many fields. Recent approaches to understanding connectivity between malaria parasite populations, with implications for disease control efforts, have used estimates of relatedness based on identity-by-descent (IBD). However, uncertainty around estimated relatedness has not been accounted for. IBD-based relatedness estimates with uncertainty were computed for pairs of monoclonal Plasmodium falciparum samples collected from five cities on the Colombian-Pacific coast where long-term clonal propagation of P. falciparum is frequent. The cities include two official ports, Buenaventura and Tumaco, that are separated geographically but connected by frequent marine traffic. Fractions of highly-related sample pairs (whose classification using a threshold accounts for uncertainty) were greater within cities versus between. However, based on both highly-related fractions and on a threshold-free approach (Wasserstein distances between parasite populations) connectivity between Buenaventura and Tumaco was disproportionally high. Buenaventura-Tumaco connectivity was consistent with transmission events involving parasites from five clonal components (groups of statistically indistinguishable parasites identified under a graph theoretic framework). To conclude, P. falciparum population connectivity on the Colombian-Pacific coast abides by accessibility not isolation-by-distance, potentially implicating marine traffic in malaria transmission with opportunities for targeted intervention. Further investigations are required to test this hypothesis. For the first time in malaria epidemiology (and to our knowledge in ecological and epidemiological studies more generally), we account for uncertainty around estimated relatedness (an important consideration for studies that plan to use genotype versus whole genome sequence data to estimate IBD-based relatedness); we also use threshold-free methods to compare parasite populations and identify clonal components. Threshold-free methods are especially important in analyses of malaria parasites and other recombining organisms with mixed mating systems where thresholds do not have clear interpretation (e.g. due to clonal propagation) and thus undermine the cross-comparison of studies.
| S-EPMC7704048 | biostudies-literature
Project description:BackgroundThe global decline of malaria burden and goals for elimination has led to an increased interest in the fine-scale epidemiology of malaria. Micro-geographic heterogeneity of malaria infection could have implications for designing targeted small-area interventions.MethodsTwo-year longitudinal cohort study data were used to explore the spatial and spatio-temporal distribution of malaria episodes in 2040 children aged < 10 years in 16 villages near the Gilgel-Gibe hydropower dam in Southwest Ethiopia. All selected households (HHs) were geo-referenced, and children were followed up through weekly house-to-house visits for two consecutive years to identify febrile episodes of P. falciparum and P. vivax infections. After confirming the spatial dependence of malaria episodes with Ripley's K function, SatScanTM was used to identify purely spatial and space-time clusters (hotspots) of annual malaria incidence for 2 years follow-up: year 1 (July 2008-June 2009) and year 2 (July 2009-June 2010).ResultsIn total, 685 P. falciparum episodes (in 492 HHs) and 385 P. vivax episodes (in 290 HHs) were identified, representing respectively incidence rates of 14.6 (95% CI: 13.4-15.6) and 8.2 (95% CI: 7.3-9.1) per 1000 child-months at risk. In year 1, the most likely (128 HHs with 63 episodes, RR = 2.1) and secondary (15 HHs with 12 episodes, RR = 5.31) clusters of P. vivax incidence were found respectively in southern and north-western villages; while in year 2, the most likely cluster was located only in north-western villages (85 HHs with 16 episodes, RR = 4.4). Instead, most likely spatial clusters of P. falciparum incidence were consistently located in villages south of the dam in both years: year 1 (167 HHs with 81 episodes, RR = 1.8) and year 2 (133 HHs with 67 episodes, RR = 2.2). Space-time clusters in southern villages for P. vivax were found in August-November 2008 in year 1 and between November 2009 and February 2010 in year 2; while for P. falciparum, they were found in September-November 2008 in year 1 and October-November 2009 in year 2.ConclusionHotspots of P. falciparum incidence in children were more stable at the geographical level and over time compared to those of P. vivax incidence during the study period.
| S-EPMC5397782 | biostudies-literature
Project description:BackgroundResistance to chloroquine and antifolate drugs has evolved independently in South America, suggesting that genotype - phenotype studies aimed at understanding the genetic basis of resistance to these and other drugs should be conducted in this continent. This research was conducted to better understand the population structure of Colombian Plasmodium falciparum in preparation for such studies.ResultsA set of 384 SNPs were genotyped in blood spot DNA samples from 447 P. falciparum infected subjects collected over a ten year period from four provinces of the Colombian Pacific coast to evaluate clonality, population structure and linkage disequilibrium (LD). Most infections (81%) contained a single predominant clone. These clustered into 136 multilocus genotypes (MLGs), with 32% of MLGs recovered from multiple (2 - 28) independent subjects. We observed extremely low genotypic richness (R?=?0.42) and long persistence of MLGs through time (median?=?537 days, range?=?1 - 2,997 days). There was a high probability (>5%) of sampling parasites from the same MLG in different subjects within 28 days, suggesting caution is needed when using genotyping methods to assess treatment success in clinical drug trials. Panmixia was rejected as four well differentiated subpopulations (FST?=?0.084 - 0.279) were identified. These occurred sympatrically but varied in frequency within the four provinces. Linkage disequilibrium (LD) decayed more rapidly (r2?=?0.17 for markers <10 kb apart) than observed previously in South American samples.ConclusionsWe conclude that Colombian populations have several advantages for association studies, because multiple clone infections are uncommon and LD decays over the scale of one or a few genes. However, the extensive population structure and low genotype richness will need to be accounted for when designing and analyzing association studies.
| S-EPMC3563461 | biostudies-literature
Project description:The mangrove bivalves, Anadara tuberculosa and Anadara similis, are pivotal for the Colombian Pacific coast mangrove ecosystems and economies. In this study, the current and future potential distribution of these bivalves is modeled considering climate change. The future models (2030 and 2050) were projected considering the new climate scenarios (SSP1, SSP2, and SSP5) proposed by the IPCC in its sixth report. Our findings reveal areas in the Colombian Pacific coast, notably Nariño, Cauca, southern Valle del Cauca, and Chocó, with high environmental suitability for these bivalves. However, the 2050 projections, especially under the pessimistic SSP5 scenario, indicate potential adverse impacts from climate change. By 2030 and 2050, the species might lean more toward a southwesterly distribution in the Colombian Pacific coast. Climate-induced spatiotemporal mismatches could occur between the bivalves and the mangroves in some areas. These insights are crucial for effective conservation and management strategies for these species.
| S-EPMC11321327 | biostudies-literature
Project description:Aims: This study examines the dynamics of malaria as influenced by meteorological factors in French Guiana from 2005 to 2019. It explores spatial hotspots of malaria transmission and aims to determine the factors associated with variation of hotspots with time. Methods: Data for individual malaria cases came from the surveillance system of the Delocalized Centers for Prevention and Care (CDPS) (n = 17) from 2005-2019. Meteorological data was acquired from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) database. The Box-Jenkins autoregressive integrated moving average (ARIMA) model tested stationarity of the time series, and the impact of meteorological indices (issued from principal component analysis-PCA) on malaria incidence was determined with a general additive model. Hotspot characterization was performed using spatial scan statistics. Results: The current sample includes 7050 eligible Plasmodium vivax (n = 4111) and Plasmodium falciparum (n = 2939) cases from health centers across French Guiana. The first and second PCA-derived meteorological components (maximum/minimum temperature/minimum humidity and maximum humidity, respectively) were significantly negatively correlated with total malaria incidence with a lag of one week and 10 days, respectively. Overall malaria incidence decreased across the time series until 2017 when incidence began to trend upwards. Hotspot characterization revealed a few health centers that exhibited spatial stability across the entire time series: Saint Georges de l'Oyapock and Antecume Pata for P. falciparum, and Saint Georges de l'Oyapock, Antecume Pata, Régina and Camopi for P. vivax. Conclusions: This study highlighted changing malaria incidence in French Guiana and the influences of meteorological factors on transmission. Many health centers showed spatial stability in transmission, albeit not temporal. Knowledge of the areas of high transmission as well as how and why transmission has changed over time can inform strategies to reduce the transmission of malaria in French Guiana. Hotspots should be further investigated to understand other influences on local transmission, which will help to facilitate elimination.
| S-EPMC7908074 | biostudies-literature
Project description:BackgroundOver a decade ago, the Roll Back Malaria Partnership was launched, and since then there has been unprecedented investment in malaria control. We examined the change in malaria transmission intensity during the period 2000-10 in Africa.MethodsWe assembled a geocoded and community Plasmodium falciparum parasite rate standardised to the age group 2-10 years (PfPR2-10) database from across 49 endemic countries and territories in Africa from surveys undertaken since 1980. The data were used within a Bayesian space-time geostatistical framework to predict PfPR2-10 in 2000 and 2010 at a 1 × 1 km spatial resolution. Population distribution maps at the same spatial resolution were used to compute populations at risk by endemicity class and estimate population-adjusted PfPR2-10 (PAPfPR2-10) for each of the 44 countries for which predictions were possible for each year.FindingsBetween 2000 and 2010, the population in hyperendemic (>50% to 75% PfPR2-10) or holoendemic (>75% PfPR2-10) areas decreased from 218·6 million (34·4%) of 635·7 million to 183·5 million (22·5%) of 815·7 million across 44 malaria-endemic countries. 280·1 million (34·3%) people lived in areas of mesoendemic transmission (>10% to 50% PfPR2-10) in 2010 compared with 178·6 million (28·1%) in 2000. Population in areas of unstable or very low transmission (<5% PfPR2-10) increased from 131·7 million people (20·7%) in 2000 to 219·0 million (26·8%) in 2010. An estimated 217·6 million people, or 26·7% of the 2010 population, lived in areas where transmission had reduced by at least one PfPR2-10 endemicity class. 40 countries showed a reduction in national mean PAPfPR2-10. Only ten countries contributed 87·1% of the population living in areas of hyperendemic or holoendemic transmission in 2010.InterpretationSubstantial reductions in malaria transmission have been achieved in endemic countries in Africa over the period 2000-10. However, 57% of the population in 2010 continued to live in areas where transmission remains moderate to intense and global support to sustain and accelerate the reduction of transmission must remain a priority.FundingWellcome Trust.
| S-EPMC4030588 | biostudies-literature
Project description:The human malaria parasite, Plasmodium falciparum, modifies the red blood cells (RBCs) that it infects by exporting proteins to the host cell. One key virulence protein, P. falciparum Erythrocyte Membrane Protein-1 (PfEMP1), is trafficked to the surface of the infected RBC, where it mediates adhesion to the vascular endothelium. We have investigated the organization and development of the exomembrane system that is used for PfEMP1 trafficking. Maurer's cleft cisternae are formed early after invasion and proteins are delivered to these (initially mobile) structures in a temporally staggered and spatially segregated manner. Membrane-Associated Histidine-Rich Protein-2 (MAHRP2)-containing tether-like structures are generated as early as 4 h post invasion and become attached to Maurer's clefts. The tether/Maurer's cleft complex docks onto the RBC membrane at ~20 h post invasion via a process that is not affected by cytochalasin D treatment. We have examined the trafficking of a GFP chimera of PfEMP1 expressed in transfected parasites. PfEMP1B-GFP accumulates near the parasite surface, within membranous structures exhibiting a defined ultrastructure, before being transferred to pre-formed mobile Maurer's clefts. Endogenous PfEMP1 and PfEMP1B-GFP are associated with Electron-Dense Vesicles that may be responsible for trafficking PfEMP1 from the Maurer's clefts to the RBC membrane.
| S-EPMC3711974 | biostudies-literature
Project description:BACKGROUND:Reliable measures of disease burden over time are necessary to evaluate the impact of interventions and assess sub-national trends in the distribution of infection. Three Malaria Indicator Surveys (MISs) have been conducted in Madagascar since 2011. They provide a valuable resource to assess changes in burden that is complementary to the country's routine case reporting system. METHODS:A Bayesian geostatistical spatio-temporal model was developed in an integrated nested Laplace approximation framework to map the prevalence of Plasmodium falciparum malaria infection among children from 6 to 59 months in age across Madagascar for 2011, 2013 and 2016 based on the MIS datasets. The model was informed by a suite of environmental and socio-demographic covariates known to influence infection prevalence. Spatio-temporal trends were quantified across the country. RESULTS:Despite a relatively small decrease between 2013 and 2016, the prevalence of malaria infection has increased substantially in all areas of Madagascar since 2011. In 2011, almost half (42.3%) of the country's population lived in areas of very low malaria risk (<1% parasite prevalence), but by 2016, this had dropped to only 26.7% of the population. Meanwhile, the population in high transmission areas (prevalence >20%) increased from only 2.2% in 2011 to 9.2% in 2016. A comparison of the model-based estimates with the raw MIS results indicates there was an underestimation of the situation in 2016, since the raw figures likely associated with survey timings were delayed until after the peak transmission season. CONCLUSIONS:Malaria remains an important health problem in Madagascar. The monthly and annual prevalence maps developed here provide a way to evaluate the magnitude of change over time, taking into account variability in survey input data. These methods can contribute to monitoring sub-national trends of malaria prevalence in Madagascar as the country aims for geographically progressive elimination.
| S-EPMC5964908 | biostudies-other
Project description:Knowledge of how malaria infections spread locally is important both for the design of targeted interventions aiming to interrupt malaria transmission and the design of trials to assess the interventions. A previous analysis of 1602 genotyped Plasmodium falciparum parasites in Kilifi, Kenya collected over 12 years found an interaction between time and geographic distance: the mean number of single nucleotide polymorphism (SNP) differences was lower for pairs of infections which were both a shorter time interval and shorter geographic distance apart. We determine whether the empiric pattern could be reproduced by a simple model, and what mean geographic distances between parent and offspring infections and hypotheses about genotype-specific immunity or a limit on the number of infections would be consistent with the data. We developed an individual-based stochastic simulation model of households, people and infections. We parameterized the model for the total number of infections, and population and household density observed in Kilifi. The acquisition of new infections, mutation, recombination, geographic location and clearance were included. We fit the model to the observed numbers of SNP differences between pairs of parasite genotypes. The patterns observed in the empiric data could be reproduced. Although we cannot rule out genotype-specific immunity or a limit on the number of infections per individual, they are not necessary to account for the observed patterns. The mean geographic distance between parent and offspring malaria infections for the base model was 0.5?km (95% CI 0.3-1.5), for a distribution with 68% of distances shorter than the mean. Very short mean distances did not fit well, but mixtures of distributions were also consistent with the data. For a pathogen which undergoes meiosis in a setting with moderate transmission and a low coverage of infections, analytic methods are limited but an individual-based model can be used with genotyping data to estimate parameter values and investigate hypotheses about underlying processes.
| S-EPMC6911066 | biostudies-literature
Project description:BackgroundSpatial and temporal malaria risk maps are essential tools to monitor the impact of control, evaluate priority areas to reorient intervention approaches and investments in malaria endemic countries. Here, the analysis of 36 years data on Plasmodium falciparum prevalence is used to understand the past and chart a future for malaria control in Kenya by confidently highlighting areas within important policy relevant thresholds to allow either the revision of malaria strategies to those that support pre-elimination or those that require additional control efforts.MethodsPlasmodium falciparum parasite prevalence (PfPR) surveys undertaken in Kenya between 1980 and 2015 were assembled. A spatio-temporal geostatistical model was fitted to predict annual malaria risk for children aged 2-10 years (PfPR2-10) at 1 × 1 km spatial resolution from 1990 to 2015. Changing PfPR2-10 was compared against plausible explanatory variables. The fitted model was used to categorize areas with varying degrees of prediction probability for two important policy thresholds PfPR2-10 < 1% (non-exceedance probability) or ≥ 30% (exceedance probability).Results5020 surveys at 3701 communities were assembled. Nationally, there was an 88% reduction in the mean modelled PfPR2-10 from 21.2% (ICR: 13.8-32.1%) in 1990 to 2.6% (ICR: 1.8-3.9%) in 2015. The most significant decline began in 2003. Declining prevalence was not equal across the country and did not directly coincide with scaled vector control coverage or changing therapeutics. Over the period 2013-2015, of Kenya's 47 counties, 23 had an average PfPR2-10 of < 1%; four counties remained ≥ 30%. Using a metric of 80% probability, 8.5% of Kenya's 2015 population live in areas with PfPR2-10 ≥ 30%; while 61% live in areas where PfPR2-10 is < 1%.ConclusionsKenya has made substantial progress in reducing the prevalence of malaria over the last 26 years. Areas today confidently and consistently with < 1% prevalence require a revised approach to control and a possible consideration of strategies that support pre-elimination. Conversely, there remains several intractable areas where current levels and approaches to control might be inadequate. The modelling approaches presented here allow the Ministry of Health opportunities to consider data-driven model certainty in defining their future spatial targeting of resources.
| S-EPMC6158896 | biostudies-literature