Dataset Information

Micro-epidemiological structuring of Plasmodium falciparum parasite populations in regions with varying transmission intensities in Africa.

ABSTRACT: Background: The first models of malaria transmission assumed a completely mixed and homogeneous population of parasites. Recent models include spatial heterogeneity and variably mixed populations. However, there are few empiric estimates of parasite mixing with which to parametize such models. Methods: Here we genotype 276 single nucleotide polymorphisms (SNPs) in 5199 P. falciparum isolates from two Kenyan sites (Kilifi county and Rachuonyo South district) and one Gambian site (Kombo coastal districts) to determine the spatio-temporal extent of parasite mixing, and use Principal Component Analysis (PCA) and linear regression to examine the relationship between genetic relatedness and distance in space and time for parasite pairs. Results: Using 107, 177 and 82 SNPs that were successfully genotyped in 133, 1602, and 1034 parasite isolates from The Gambia, Kilifi and Rachuonyo South district, respectively, we show that there are no discrete geographically restricted parasite sub-populations, but instead we see a diffuse spatio-temporal structure to parasite genotypes. Genetic relatedness of sample pairs is predicted by relatedness in space and time. Conclusions: Our findings suggest that targeted malaria control will benefit the surrounding community, but unfortunately also that emerging drug resistance will spread rapidly through the population.

SUBMITTER: Omedo I

PROVIDER: S-EPMC5445974 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Micro-epidemiological structuring of Plasmodium falciparum parasite populations in regions with varying transmission intensities in Africa.

Omedo Irene I Mogeni Polycarp P Bousema Teun T Rockett Kirk K Amambua-Ngwa Alfred A Oyier Isabella I C Stevenson Jennifer J Y Baidjoe Amrish A de Villiers Etienne P EP Fegan Greg G Ross Amanda A Hubbart Christina C Jeffreys Anne A N Williams Thomas T Kwiatkowski Dominic D Bejon Philip P

Wellcome open research 20170908

Background: The first models of malaria transmission assumed a completely mixed and homogeneous population of parasites. Recent models include spatial heterogeneity and variably mixed populations. However, there are few empiric estimates of parasite mixing with which to parametize such models. Methods: Here we genotype 276 single nucleotide polymorphisms (SNPs) in 5199 P. falciparum isolates from two Kenyan sites (Kilifi county and Rachuonyo South district) and one Gambian ...[more]

PMID: 28612053

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Project description:The High Burden High Impact (HBHI) strategy for malaria encourages countries to use multiple sources of available data to define the sub-national vulnerabilities to malaria risk, including parasite prevalence. Here, a modelled estimate of Plasmodium falciparum from an updated assembly of community parasite survey data in Kenya, mainland Tanzania, and Uganda is presented and used to provide a more contemporary understanding of the sub-national malaria prevalence stratification across the sub-region for 2019. Malaria prevalence data from surveys undertaken between January 2010 and June 2020 were assembled form each of the three countries. Bayesian spatiotemporal model-based approaches were used to interpolate space-time data at fine spatial resolution adjusting for population, environmental and ecological covariates across the three countries. A total of 18,940 time-space age-standardised and microscopy-converted surveys were assembled of which 14,170 (74.8%) were identified after 2017. The estimated national population-adjusted posterior mean parasite prevalence was 4.7% (95% Bayesian Credible Interval 2.6-36.9) in Kenya, 10.6% (3.4-39.2) in mainland Tanzania, and 9.5% (4.0-48.3) in Uganda. In 2019, more than 12.7 million people resided in communities where parasite prevalence was predicted ≥ 30%, including 6.4%, 12.1% and 6.3% of Kenya, mainland Tanzania and Uganda populations, respectively. Conversely, areas that supported very low parasite prevalence (<1%) were inhabited by approximately 46.2 million people across the sub-region, or 52.2%, 26.7% and 10.4% of Kenya, mainland Tanzania and Uganda populations, respectively. In conclusion, parasite prevalence represents one of several data metrics for disease stratification at national and sub-national levels. To increase the use of this metric for decision making, there is a need to integrate other data layers on mortality related to malaria, malaria vector composition, insecticide resistance and bionomic, malaria care-seeking behaviour and current levels of unmet need of malaria interventions.

Project description:BackgroundMalaria is a significant public health challenge in Uganda, with Plasmodium falciparum (P. falciparum) responsible for most of malaria infections. The high genetic diversity and multiplicity of infection (MOI) associated with P. falciparum complicate treatment and prevention efforts. This study investigated temporal changes in P. falciparum genetic diversity and MOI across three sites with varying malaria transmission intensities. Understanding these changes is essential for informing effective malaria control strategies for the different malaria transmission settings.MethodsA total of 220 P. falciparum-positive dried blood spot (DBS) filter paper samples from participants in a study conducted during 2011-2012 and 2015-2016 were analyzed. Genotyping utilized seven polymorphic markers: Poly-α, TA1, TA109, PfPK2, 2490, C2M34-313, and C3M69-383. Genetic diversity metrics, including the number of alleles and expected heterozygosity, were calculated using GENALEX and ARLEQUIN software. MOI was assessed by counting distinct genotypes. Multi-locus linkage disequilibrium (LD) and genetic differentiation were evaluated using the standardized index of association (IAS) and Wright's fixation index (FST), respectively. Statistical comparisons were made using the Kruskal-Wallis test, and temporal trends were analyzed using the Jonckheere-Terpstra test, with statistical significance set at p < 0.05.ResultsOf the 220 samples, 180 were successfully amplified. The majority of participants were males (50.6%) and children aged 5-11 years (46.7%). Genetic diversity remained high, with mean expected heterozygosity (He) showing a slight decrease over time (range: 0.73-0.82). Polyclonal infections exceeded 50% at all sites, and mean MOI ranged from 1.7 to 2.2, with a significant reduction in Tororo (from 2.2 to 2.0, p = 0.03). Linkage disequilibrium showed a slight increase, with Kanungu exhibiting the lowest IAS in 2011-2012 (0.0085) and Jinja the highest (0.0239) in 2015-2016. Overall genetic differentiation remained low, with slight increases in pairwise FST values over time, notably between Jinja and Tororo (from 0.0145 to 0.0353).ConclusionsThis study highlights the genetic diversity and MOI of P. falciparum in Uganda's malaria transmission settings, noting a slight decrease in both genetic diversity and MOI overtime. Continued surveillance and targeted control strategies are essential for monitoring the impact of malaria control efforts in Uganda.

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Micro-epidemiological structuring of Plasmodium falciparum parasite populations in regions with varying transmission intensities in Africa.

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Micro-epidemiological structuring of <i>Plasmodium falciparum</i> parasite populations in regions with varying transmission intensities in Africa.

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Micro-epidemiological structuring of Plasmodium falciparum parasite populations in regions with varying transmission intensities in Africa.

Publications

Micro-epidemiological structuring of &lt;i&gt;Plasmodium falciparum&lt;/i&gt; parasite populations in regions with varying transmission intensities in Africa.

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OmicsDI is part of the ELIXIR infrastructure

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Micro-epidemiological structuring of <i>Plasmodium falciparum</i> parasite populations in regions with varying transmission intensities in Africa.