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Bardoe D, Bio RB, Yar DD, Hayford D. Assessing the prevalence, risk factors, and socio-demographic predictors of malaria among pregnant women in the Bono East Region of Ghana: a multicentre hospital-based mixed-method cross-sectional study. Malar J 2024; 23:302. [PMID: 39385188 PMCID: PMC11466029 DOI: 10.1186/s12936-024-05120-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2024] [Accepted: 09/28/2024] [Indexed: 10/12/2024] Open
Abstract
BACKGROUND Malaria is one of the world's most lethal vector-borne diseases, causing significant health burdens in endemic countries. Several studies on the prevalence of malaria among pregnant women in Ghana have been conducted in various parts of the country, yielding evidence pointing to intra- and inter-regional variations. The current study assessed the prevalence, risk factors, and sociodemographic predictors of malaria among pregnant women in the Bono East Region of Ghana. METHODS This multicentre hospital-based study employed a mixed-method cross-sectional design. A multistage sampling technique was used to select seven health facilities and recruited 1452 pregnant women who attended ANC at seven selected health facilities. Haematological examination, a structured closed-ended questionnaire, in-depth interviews (IDIs), and focus group discussions (FGDs) were used to obtain relevant data. Quantitative data were analysed with STATA 14 (StataCorp, College Station, USA). Likewise, the four-step thematic analysis was used to analyse qualitative data. A significant level was set at (p < 0.05) at a 95% confidence interval (CI). RESULTS The ages of the pregnant women at enrolment ranged between 17 and 40 years, with a mean (SD) of 28.8 ± 3.73 (95% C.I: 28.63-29.02). The overall prevalence of malaria infection among pregnant women was 10.8% (95% CI: 9.32-12.56). Presence of farm or domestic animals, living close to drainage tunnels, living near overgrown vegetation, not married, not having formal education, living in extended-type households, living in compound-type households, mud and thatch households, mud and iron sheet households, primigravidae, multiparity, first-time pregnant women, second-time, third-time, fourth-time, and fifth-time ANC visits, blood groups A, B, and AB were independent factors or predictors significantly associated with increased risk of malaria. CONCLUSION The current study revealed an approximately 10.8% prevalence of malaria among pregnant women. The prevalence revealed, was, however, higher than the national prevalence of 8.6%. The high prevalence of malaria, associated risk factors, and sociodemographic and maternal predictors highlight the need to strengthen screening for malaria, administer treatments, monitor maternal and foetal health, and provide education and counselling.
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Affiliation(s)
- Dennis Bardoe
- Department of Public Health Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Mampong, Ghana.
| | - Robert Bagngmen Bio
- Department of Public Health Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Mampong, Ghana
| | - Denis Dekugmen Yar
- Department of Public Health Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Mampong, Ghana
| | - Daniel Hayford
- Department of Integrated Science Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Mampong, Ghana
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Zhan Q, He Q, Tiedje KE, Day KP, Pascual M. Hyper-diverse antigenic variation and resilience to transmission-reducing intervention in falciparum malaria. Nat Commun 2024; 15:7343. [PMID: 39187488 PMCID: PMC11347654 DOI: 10.1038/s41467-024-51468-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 08/07/2024] [Indexed: 08/28/2024] Open
Abstract
Intervention efforts against falciparum malaria in high-transmission regions remain challenging, with rapid resurgence typically following their relaxation. Such resilience co-occurs with incomplete immunity and a large transmission reservoir from high asymptomatic prevalence. Incomplete immunity relates to the large antigenic variation of the parasite, with the major surface antigen of the blood stage of infection encoded by the multigene and recombinant family known as var. With a stochastic agent-based model, we investigate the existence of a sharp transition in resurgence ability with intervention intensity and identify molecular indicators informative of its proximity. Their application to survey data with deep sampling of var sequences from individual isolates in northern Ghana suggests that the transmission system was brought close to transition by intervention with indoor residual spraying. These results indicate that sustaining and intensifying intervention would have pushed malaria dynamics to a slow-rebound regime with an increased probability of local parasite extinction.
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Affiliation(s)
- Qi Zhan
- Committee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA
| | - Qixin He
- Department of Biological Sciences, Purdue University, West Lafayette, IN, 47907, USA
| | - Kathryn E Tiedje
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne, Melbourne, Australia
| | - Karen P Day
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne, Melbourne, Australia
| | - Mercedes Pascual
- Department of Biology, New York University, New York, NY, 10003, USA.
- Department of Environmental Studies, New York University, New York, NY, 10003, USA.
- Santa Fe Institute, Santa Fe, NM, 87501, USA.
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Tiedje KE, Zhan Q, Ruybal-Pesantez S, Tonkin-Hill G, He Q, Tan MH, Argyropoulos DC, Deed SL, Ghansah A, Bangre O, Oduro AR, Koram KA, Pascual M, Day KP. Measuring changes in Plasmodium falciparum census population size in response to sequential malaria control interventions. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.05.18.23290210. [PMID: 37292908 PMCID: PMC10246142 DOI: 10.1101/2023.05.18.23290210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Here we introduce a new endpoint ″census population size″ to evaluate the epidemiology and control of Plasmodium falciparum infections, where the parasite, rather than the infected human host, is the unit of measurement. To calculate census population size, we rely on a definition of parasite variation known as multiplicity of infection (MOI var ), based on the hyper-diversity of the var multigene family. We present a Bayesian approach to estimate MOI var from sequencing and counting the number of unique DBLα tags (or DBLα types) of var genes, and derive from it census population size by summation of MOI var in the human population. We track changes in this parasite population size and structure through sequential malaria interventions by indoor residual spraying (IRS) and seasonal malaria chemoprevention (SMC) from 2012 to 2017 in an area of high-seasonal malaria transmission in northern Ghana. Following IRS, which reduced transmission intensity by > 90% and decreased parasite prevalence by ~40-50%, significant reductions in var diversity, MOI var , and population size were observed in ~2,000 humans across all ages. These changes, consistent with the loss of diverse parasite genomes, were short lived and 32-months after IRS was discontinued and SMC was introduced, var diversity and population size rebounded in all age groups except for the younger children (1-5 years) targeted by SMC. Despite major perturbations from IRS and SMC interventions, the parasite population remained very large and retained the var population genetic characteristics of a high-transmission system (high var diversity; low var repertoire similarity) demonstrating the resilience of P. falciparum to short-term interventions in high-burden countries of sub-Saharan Africa.
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Zhan Q, Tiedje KE, Day KP, Pascual M. From multiplicity of infection to force of infection for sparsely sampled Plasmodium falciparum populations at high transmission. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.12.24302148. [PMID: 38853963 PMCID: PMC11160831 DOI: 10.1101/2024.02.12.24302148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
High multiplicity of infection or MOI, the number of genetically distinct parasite strains co-infecting a single human host, characterizes infectious diseases including falciparum malaria at high transmission. It accompanies high asymptomatic Plasmodium falciparum prevalence despite high exposure, creating a large transmission reservoir challenging intervention. High MOI and asymptomatic prevalence are enabled by immune evasion of the parasite achieved via vast antigenic diversity. Force of infection or FOI, the number of new infections acquired by an individual host over a given time interval, is the dynamic sister quantity of MOI, and a key epidemiological parameter for monitoring the impact of antimalarial interventions and assessing vaccine or drug efficacy in clinical trials. FOI remains difficult, expensive, and labor-intensive to accurately measure, especially in high-transmission regions, whether directly via cohort studies or indirectly via the fitting of epidemiological models to repeated cross-sectional surveys. We propose here the application of queuing theory to obtain FOI on the basis of MOI, in the form of either a two-moment approximation method or Little's law. We illustrate these methods with MOI estimates obtained under sparse sampling schemes with the recently proposed " v a r coding" method, based on sequences of the v a r multigene family encoding for the major variant surface antigen of the blood stage of malaria infection. The methods are evaluated with simulation output from a stochastic agent-based model, and are applied to an interrupted time-series study from Bongo District in northern Ghana before and immediately after a three-round transient indoor residual spraying (IRS) intervention. We incorporate into the sampling of the simulation output, limitations representative of those encountered in the collection of field data, including under-sampling of v a r genes, missing data, and usage of antimalarial drug treatment. We address these limitations in MOI estimates with a Bayesian framework and an imputation bootstrap approach. We demonstrate that both proposed methods give good and consistent FOI estimates across various simulated scenarios. Their application to the field surveys shows a pronounced reduction in annual FOI during intervention, of more than 70%. The proposed approach should be applicable to the many geographical locations where cohort or cross-sectional studies with regular and frequent sampling are lacking but single-time-point surveys under sparse sampling schemes are available, and for MOI estimates obtained in different ways. They should also be relevant to other pathogens of humans, wildlife and livestock whose immune evasion strategies are based on large antigenic variation resulting in high multiplicity of infection.
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Affiliation(s)
- Qi Zhan
- Committee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
| | - Kathryn E. Tiedje
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne, Melbourne, Australia
| | - Karen P. Day
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne, Melbourne, Australia
| | - Mercedes Pascual
- Department of Biology, New York University, New York, NY, USA
- Department of Environmental Studies, New York University, New York, NY, USA
- Santa Fe Institute, Santa Fe, NM, USA
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5
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Zhan Q, He Q, Tiedje KE, Day KP, Pascual M. Hyper-diverse antigenic variation and resilience to transmission-reducing intervention in falciparum malaria. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.01.24301818. [PMID: 38370729 PMCID: PMC10871444 DOI: 10.1101/2024.02.01.24301818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Intervention against falciparum malaria in high transmission regions remains challenging, with relaxation of control efforts typically followed by rapid resurgence. Resilience to intervention co-occurs with incomplete immunity, whereby children eventually become protected from severe disease but not infection and a large transmission reservoir results from high asymptomatic prevalence across all ages. Incomplete immunity relates to the vast antigenic variation of the parasite, with the major surface antigen of the blood stage of infection encoded by the multigene family known as var. Recent deep sampling of var sequences from individual isolates in northern Ghana showed that parasite population structure exhibited persistent features of high-transmission regions despite the considerable decrease in prevalence during transient intervention with indoor residual spraying (IRS). We ask whether despite such apparent limited impact, the transmission system had been brought close to a transition in both prevalence and resurgence ability. With a stochastic agent-based model, we investigate the existence of such a transition to pre-elimination with intervention intensity, and of molecular indicators informative of its approach. We show that resurgence ability decreases sharply and nonlinearly across a narrow region of intervention intensities in model simulations, and identify informative molecular indicators based on var gene sequences. Their application to the survey data indicates that the transmission system in northern Ghana was brought close to transition by IRS. These results suggest that sustaining and intensifying intervention would have pushed malaria dynamics to a slow-rebound regime with an increased probability of local parasite extinction.
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Affiliation(s)
- Qi Zhan
- Committee on Genetics, Genomics and Systems Biology, The University of Chicago; Chicago, IL, 60637, USA
| | - Qixin He
- Department of Biological Sciences, Purdue University; West Lafayette, IN, 47907, USA
| | - Kathryn E Tiedje
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne; Melbourne, Australia
| | - Karen P Day
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne; Melbourne, Australia
| | - Mercedes Pascual
- Department of Biology, New York University; New York, NY, 10012, USA
- Department of Environmental Studies, New York University; New York, NY, 10012, USA
- Santa Fe Institute; Santa Fe, NM, 87501, USA
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Tan MH, Tiedje KE, Feng Q, Zhan Q, Pascual M, Shim H, Chan YB, Day KP. A paradoxical population structure of var DBLα types in Africa. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.05.565723. [PMID: 37986738 PMCID: PMC10659346 DOI: 10.1101/2023.11.05.565723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The var multigene family encodes the P. falciparum erythrocyte membrane protein 1 (PfEMP1), which is important in host-parasite interaction as a virulence factor and major surface antigen of the blood stages of the parasite, responsible for maintaining chronic infection. Whilst important in the biology of P. falciparum, these genes (50 to 60 genes per parasite genome) are routinely excluded from whole genome analyses due to their hyper-diversity, achieved primarily through recombination. The PfEMP1 head structure almost always consists of a DBLα-CIDR tandem. Categorised into different groups (upsA, upsB, upsC), different head structures have been associated with different ligand-binding affinities and disease severities. We study how conserved individual DBLα types are at the country, regional, and local scales in Sub-Saharan Africa. Using publicly-available sequence datasets and a novel ups classification algorithm, cUps, we performed an in silico exploration of DBLα conservation through time and space in Africa. In all three ups groups, the population structure of DBLα types in Africa consists of variants occurring at rare, low, moderate, and high frequencies. Non-rare variants were found to be temporally stable in a local area in endemic Ghana. When inspected across different geographical scales, we report different levels of conservation; while some DBLα types were consistently found in high frequencies in multiple African countries, others were conserved only locally, signifying local preservation of specific types. Underlying this population pattern is the composition of DBLα types within each isolate DBLα repertoire, revealed to also consist of a mix of types found at rare, low, moderate, and high frequencies in the population. We further discuss the adaptive forces and balancing selection, including host genetic factors, potentially shaping the evolution and diversity of DBLα types in Africa.
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Affiliation(s)
- Mun Hua Tan
- Department of Microbiology and Immunology, The University of Melbourne, Bio21 Institute and Peter Doherty Institute, Melbourne, AU
| | - Kathryn E Tiedje
- Department of Microbiology and Immunology, The University of Melbourne, Bio21 Institute and Peter Doherty Institute, Melbourne, AU
| | - Qian Feng
- School of Mathematics and Statistics / Melbourne Integrative Genomics, The University of Melbourne, Melbourne, Australia
| | - Qi Zhan
- Department of Ecology and Evolution, University of Chicago; Chicago, Illinois, USA
| | - Mercedes Pascual
- Department of Ecology and Evolution, University of Chicago; Chicago, Illinois, USA
| | - Heejung Shim
- School of Mathematics and Statistics / Melbourne Integrative Genomics, The University of Melbourne, Melbourne, Australia
| | - Yao-Ban Chan
- School of Mathematics and Statistics / Melbourne Integrative Genomics, The University of Melbourne, Melbourne, Australia
| | - Karen P Day
- Department of Microbiology and Immunology, The University of Melbourne, Bio21 Institute and Peter Doherty Institute, Melbourne, AU
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Argyropoulos DC, Tan MH, Adobor C, Mensah B, Labbé F, Tiedje KE, Koram KA, Ghansah A, Day KP. Performance of SNP barcodes to determine genetic diversity and population structure of Plasmodium falciparum in Africa. Front Genet 2023; 14:1071896. [PMID: 37323661 PMCID: PMC10267394 DOI: 10.3389/fgene.2023.1071896] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 05/17/2023] [Indexed: 06/17/2023] Open
Abstract
Panels of informative biallelic single nucleotide polymorphisms (SNPs) have been proposed to be an economical method to fast-track the population genetic analysis of Plasmodium falciparum in malaria-endemic areas. Whilst used successfully in low-transmission areas where infections are monoclonal and highly related, we present the first study to evaluate the performance of these 24- and 96-SNP molecular barcodes in African countries, characterised by moderate-to-high transmission, where multiclonal infections are prevalent. For SNP barcodes it is generally recommended that the SNPs chosen i) are biallelic, ii) have a minor allele frequency greater than 0.10, and iii) are independently segregating, to minimise bias in the analysis of genetic diversity and population structure. Further, to be standardised and used in many population genetic studies, these barcodes should maintain characteristics i) to iii) across various iv) geographies and v) time points. Using haplotypes generated from the MalariaGEN P. falciparum Community Project version six database, we investigated the ability of these two barcodes to fulfil these criteria in moderate-to-high transmission African populations in 25 sites across 10 countries. Predominantly clinical infections were analysed, with 52.3% found to be multiclonal, generating high proportions of mixed-allele calls (MACs) per isolate thereby impeding haplotype construction. Of the 24- and 96-SNPs, loci were removed if they were not biallelic and had low minor allele frequencies in all study populations, resulting in 20- and 75-SNP barcodes respectively for downstream population genetics analysis. Both SNP barcodes had low expected heterozygosity estimates in these African settings and consequently biased analyses of similarity. Both minor and major allele frequencies were temporally unstable. These SNP barcodes were also shown to identify weak genetic differentiation across large geographic distances based on Mantel Test and DAPC. These results demonstrate that these SNP barcodes are vulnerable to ascertainment bias and as such cannot be used as a standardised approach for malaria surveillance in moderate-to-high transmission areas in Africa, where the greatest genomic diversity of P. falciparum exists at local, regional and country levels.
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Affiliation(s)
- Dionne C. Argyropoulos
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne, Melbourne, VIC, Australia
| | - Mun Hua Tan
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne, Melbourne, VIC, Australia
| | - Courage Adobor
- Department of Parasitology, Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana, Accra, Ghana
| | - Benedicta Mensah
- Department of Parasitology, Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana, Accra, Ghana
| | - Frédéric Labbé
- Department of Ecology and Evolution, The University of Chicago, Chicago, IL, United States
| | - Kathryn E. Tiedje
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne, Melbourne, VIC, Australia
| | - Kwadwo A. Koram
- Epidemiology Department, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
| | - Anita Ghansah
- Department of Parasitology, Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana, Accra, Ghana
| | - Karen P. Day
- Department of Microbiology and Immunology, Bio21 Institute and Peter Doherty Institute, The University of Melbourne, Melbourne, VIC, Australia
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Ghansah A, Tiedje KE, Argyropoulos DC, Onwona CO, Deed SL, Labbé F, Oduro AR, Koram KA, Pascual M, Day KP. Comparison of molecular surveillance methods to assess changes in the population genetics of Plasmodium falciparum in high transmission. FRONTIERS IN PARASITOLOGY 2023; 2:1067966. [PMID: 38031549 PMCID: PMC10686283 DOI: 10.3389/fpara.2023.1067966] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
A major motivation for developing molecular methods for malaria surveillance is to measure the impact of control interventions on the population genetics of Plasmodium falciparum as a potential marker of progress towards elimination. Here we assess three established methods (i) single nucleotide polymorphism (SNP) barcoding (panel of 24-biallelic loci), (ii) microsatellite genotyping (panel of 12-multiallelic loci), and (iii) varcoding (fingerprinting var gene diversity, akin to microhaplotyping) to identify changes in parasite population genetics in response to a short-term indoor residual spraying (IRS) intervention. Typical of high seasonal transmission in Africa, multiclonal infections were found in 82.3% (median 3; range 1-18) and 57.8% (median 2; range 1-12) of asymptomatic individuals pre- and post-IRS, respectively, in Bongo District, Ghana. Since directly phasing multilocus haplotypes for population genetic analysis is not possible for biallelic SNPs and microsatellites, we chose ~200 low-complexity infections biased to single and double clone infections for analysis. Each genotyping method presented a different pattern of change in diversity and population structure as a consequence of variability in usable data and the relative polymorphism of the molecular markers (i.e., SNPs < microsatellites < var). Varcoding and microsatellite genotyping showed the overall failure of the IRS intervention to significantly change the population structure from pre-IRS characteristics (i.e., many diverse genomes of low genetic similarity). The 24-SNP barcode provided limited information for analysis, largely due to the biallelic nature of SNPs leading to a high proportion of double-allele calls and a view of more isolate relatedness compared to microsatellites and varcoding. Relative performance, suitability, and cost-effectiveness of the methods relevant to sample size and local malaria elimination in high-transmission endemic areas are discussed.
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Affiliation(s)
- Anita Ghansah
- Department of Parasitology, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Ghana
| | - Kathryn E. Tiedje
- Department of Microbiology and Immunology, The University of Melbourne, Bio21 Institute and Peter Doherty Institute, Melbourne, VIC, Australia
| | - Dionne C. Argyropoulos
- Department of Microbiology and Immunology, The University of Melbourne, Bio21 Institute and Peter Doherty Institute, Melbourne, VIC, Australia
| | - Christiana O. Onwona
- Department of Parasitology, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Ghana
| | - Samantha L. Deed
- Department of Microbiology and Immunology, The University of Melbourne, Bio21 Institute and Peter Doherty Institute, Melbourne, VIC, Australia
| | - Frédéric Labbé
- Department Ecology and Evolution, The University of Chicago, Chicago, IL, United States
| | - Abraham R. Oduro
- Navrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana
| | - Kwadwo A. Koram
- Epidemiology Department, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Ghana
| | - Mercedes Pascual
- Department Ecology and Evolution, The University of Chicago, Chicago, IL, United States
- Santa Fe Institute, Santa Fe, NM, United States
| | - Karen P. Day
- Department of Microbiology and Immunology, The University of Melbourne, Bio21 Institute and Peter Doherty Institute, Melbourne, VIC, Australia
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Arambepola R, Bérubé S, Freedman B, Taylor SM, Prudhomme O’Meara W, Obala AA, Wesolowski A. Exploring how space, time, and sampling impact our ability to measure genetic structure across Plasmodium falciparum populations. FRONTIERS IN EPIDEMIOLOGY 2023; 3:1058871. [PMID: 38516334 PMCID: PMC10956351 DOI: 10.3389/fepid.2023.1058871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 01/18/2023] [Indexed: 03/23/2024]
Abstract
A primary use of malaria parasite genomics is identifying highly related infections to quantify epidemiological, spatial, or temporal factors associated with patterns of transmission. For example, spatial clustering of highly related parasites can indicate foci of transmission and temporal differences in relatedness can serve as evidence for changes in transmission over time. However, for infections in settings of moderate to high endemicity, understanding patterns of relatedness is compromised by complex infections, overall high forces of infection, and a highly diverse parasite population. It is not clear how much these factors limit the utility of using genomic data to better understand transmission in these settings. In particular, further investigation is required to determine which patterns of relatedness we expect to see with high quality, densely sampled genomic data in a high transmission setting and how these observations change under different study designs, missingness, and biases in sample collection. Here we investigate two identity-by-state measures of relatedness and apply them to amplicon deep sequencing data collected as part of a longitudinal cohort in Western Kenya that has previously been analysed to identify individual-factors associated with sharing parasites with infected mosquitoes. With these data we use permutation tests, to evaluate several hypotheses about spatiotemporal patterns of relatedness compared to a null distribution. We observe evidence of temporal structure, but not of fine-scale spatial structure in the cohort data. To explore factors associated with the lack of spatial structure in these data, we construct a series of simplified simulation scenarios using an agent based model calibrated to entomological, epidemiological and genomic data from this cohort study to investigate whether the lack of spatial structure observed in the cohort could be due to inherent power limitations of this analytical method. We further investigate how our hypothesis testing behaves under different sampling schemes, levels of completely random and systematic missingness, and different transmission intensities.
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Affiliation(s)
- Rohan Arambepola
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Batlimore, MD, United States
| | - Sophie Bérubé
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Batlimore, MD, United States
| | - Betsy Freedman
- Division of Infectious Diseases, Duke University Medical Center, Durham, NC, United States
| | - Steve M. Taylor
- Division of Infectious Diseases, Duke University Medical Center, Durham, NC, United States
- Duke Global Health Institute, Durham, NC, United States
| | - Wendy Prudhomme O’Meara
- Division of Infectious Diseases, Duke University Medical Center, Durham, NC, United States
- Duke Global Health Institute, Durham, NC, United States
| | | | - Amy Wesolowski
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Batlimore, MD, United States
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Tan MH, Shim H, Chan YB, Day KP. Unravelling var complexity: Relationship between DBLα types and var genes in Plasmodium falciparum. FRONTIERS IN PARASITOLOGY 2023; 1. [PMID: 36998722 PMCID: PMC10060044 DOI: 10.3389/fpara.2022.1006341] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
The enormous diversity and complexity of var genes that diversify rapidly by recombination has led to the exclusion of assembly of these genes from major genome initiatives (e.g., Pf6). A scalable solution in epidemiological surveillance of var genes is to use a small ‘tag’ region encoding the immunogenic DBLα domain as a marker to estimate var diversity. As var genes diversify by recombination, it is not clear the extent to which the same tag can appear in multiple var genes. This relationship between marker and gene has not been investigated in natural populations. Analyses of in vitro recombination within and between var genes have suggested that this relationship would not be exclusive. Using a dataset of publicly-available assembled var sequences, we test this hypothesis by studying DBLα-var relationships for four study sites in four countries: Pursat (Cambodia) and Mae Sot (Thailand), representing low malaria transmission, and Navrongo (Ghana) and Chikwawa (Malawi), representing high malaria transmission. In all study sites, DBLα-var relationships were shown to be predominantly 1-to-1, followed by a second largest proportion of 1-to-2 DBLα-var relationships. This finding indicates that DBLα tags can be used to estimate not just DBLα diversity but var gene diversity when applied in a local endemic area. Epidemiological applications of this result are discussed.
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Affiliation(s)
- Mun Hua Tan
- Department of Microbiology and Immunology, The University of Melbourne, Bio21 Institute, Melbourne, VIC, Australia
| | - Heejung Shim
- School of Mathematics and Statistics/Melbourne Integrative Genomics, The University of Melbourne, Melbourne, VIC, Australia
| | - Yao-ban Chan
- School of Mathematics and Statistics/Melbourne Integrative Genomics, The University of Melbourne, Melbourne, VIC, Australia
| | - Karen P. Day
- Department of Microbiology and Immunology, The University of Melbourne, Bio21 Institute, Melbourne, VIC, Australia
- CORRESPONDENCE Karen P. Day,
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