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Sinha A, Kar S, Chauhan C, Yadav CP, Kori L. Meta-analysis on Plasmodium falciparum sulfadoxine-pyrimethamine resistance-conferring mutations in India identifies hot spots for genetic surveillance. Int J Antimicrob Agents 2024; 63:107071. [PMID: 38154659 DOI: 10.1016/j.ijantimicag.2023.107071] [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: 07/27/2023] [Revised: 12/05/2023] [Accepted: 12/19/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND India is on track to eliminate malaria by 2030 but emerging resistance to first-line antimalarials is a recognised threat. Two instances of rapid development, spread, and natural selection of drug-resistant mutant parasites in India (chloroquine across the country and artesunate + sulfadoxine-pyrimethamine [AS+SP] in the northeastern states) translated into drug policy changes for Plasmodium falciparum malaria in 2010 and 2013, respectively. Considering these rapid changes in the SP drug resistance-conferring mutation profile of P. falciparum, there is a need to systematically monitor the validated mutations in Pfdhfr and Pfdhps genes across India alongside AS+SP therapeutic efficacy studies. There has been no robust, systematic countrywide surveillance reported for these parameters in India, hence the current study was undertaken. METHODS Studies that reported data on WHO-validated SP resistance markers in P. falciparum across India from 2008 to January 2023 were included. Five major databases, PubMedⓇ, Web of ScienceTM, ScopusⓇ, EmbaseⓇ, and Google Scholar, were exhaustively searched. Individual and pooled prevalence estimates of mutations were obtained through random- and fixed-effect models. Data were depicted using forest plots created with a 95% confidence interval. The study is registered with PROSPERO (CRD42021236012). RESULTS A total of 37 publications, and 533 Pfdhfr and 134 Pfdhps National Centre of Biotechnology Information (NCBI) DNA sequences were included from >4000 samples. The study included information from 80 districts, 21 states and 3 union territories (UTs) from India. The two PfDHFR mutations, C59R (62%) and S108N (74%), were the most prevalent mutations (pooled estimates 61% and 71%, respectively) and appeared to be stabilised/fixed. Although rarest overall, the prevalence of I164L was observed to be as high as 32%. The PfDHFR double mutants were the most prevalent overall (51%; pooled 42%). The prevalence of triple and quadruple mutations was 6% and 5%, respectively, and is an immediate concern for some states. The most prevalent PfDHPS mutation was A437G (39%), followed by K540E (25%) and A581G (12%). There was a low overall prevalence of PfDHFR/PfDHPS quintuple and sextuple mutations but surveillance for these mutations is critical for some areas. CONCLUSION The analyses span the two critical policy changes, highlight the areas of concern, and guide policymakers in strategising and refining the anti-malaria drug policy for malaria elimination. The results of the analyses also highlight the SP-resistance hot spots, critical gaps and challenges, and indicate that focal and local malaria genetic surveillance (including drug-resistance markers) is needed until malaria is successfully eliminated.
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Affiliation(s)
- Abhinav Sinha
- ICMR-National Institute of Malaria Research, New Delhi, India.
| | - Sonalika Kar
- ICMR-National Institute of Malaria Research, New Delhi, India
| | - Charu Chauhan
- ICMR-National Institute of Malaria Research, New Delhi, India
| | | | - Lokesh Kori
- ICMR-National Institute of Malaria Research, New Delhi, India
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2
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Lestarisa T, Arwati H, Dachlan YP, Keman S, Safruddin D. THE USE OF ARCHIVED GIEMSA-STAINED BLOOD SMEARS AND RDT FOR PCR-BASED GENOTYPING OF Plasmodium v ivax MEROZOITE SURFACE PROTEIN-1 IN CENTRAL KALIMANTAN PROVINCE, INDONESIA. Afr J Infect Dis 2022; 16:13-20. [PMID: 35047726 PMCID: PMC8751392 DOI: 10.21010/ajid.v16i1.3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 11/11/2021] [Accepted: 11/17/2021] [Indexed: 11/23/2022] Open
Abstract
Background: Plasmodium vivax is transmitted most across the country of Indonesia. The country has set out a malaria elimination program by 2030. The information on genetic diversity of malarial parasites relates to malaria transmission in an endemic area may provide the information that can help the malaria control program to achieve the target. Therefore, the purpose of this study was to determine the genetic diversity of the Pvmsp-1 gene in Central Kalimantan Province. Materials and Methods: Samples were 140 of archived Giemsa-stained blood smear and rapid detection test. Samples were divided into the indigenous and migrant populations. After confirmation by single-step PCR, only P. vivax and mixed infection samples were amplified to nested PCR for genotyping of Pvmsp-1 allelic variation in segments F1, F2, and F3. Results: Genotyping of 23 PCR positive samples resulted in 13 genotypes. In segment F1, three allelic variants type A containing subtype A1 (1,050 bp), A2 (350 bp), A3 (150 bp), and type B (100 bp). In segment F2, mono genotypes were detected as variant type A (1,050 bp) and type B3 (150 bp), multiple genotypes were detected as type B containing subtype B1 (250 bp), B2 (200 bp), and B3 (150bp). In segment F3, three allelic variants generated from four mono genotypes were type A (350 bp), type B (300 bp), and two type C (250 bp). Conclusion: The low allelic variation of Pvmsp-1 gene may reflect the actual situation of the low malaria endemic status of the study sites.
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Affiliation(s)
- Trilianty Lestarisa
- Doctoral Program on Public Health, Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia.,Department of Public Health, Faculty of Medicine, Universitas Palangka Raya, Palangka Raya City, Indonesia
| | - Heny Arwati
- Department of Medical Parasitology, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia
| | - Yoes Prijatna Dachlan
- Department of Medical Parasitology, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia
| | - Soedjajadi Keman
- Department of Environmental Health, Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia
| | - Din Safruddin
- Eijkman Institute for Molecular Biology, Jakarta, Indonesia.,Department of Parasitology, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia
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3
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Hendry JA, Kwiatkowski D, McVean G. Elucidating relationships between P.falciparum prevalence and measures of genetic diversity with a combined genetic-epidemiological model of malaria. PLoS Comput Biol 2021; 17:e1009287. [PMID: 34411093 PMCID: PMC8407561 DOI: 10.1371/journal.pcbi.1009287] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 08/31/2021] [Accepted: 07/19/2021] [Indexed: 12/05/2022] Open
Abstract
There is an abundance of malaria genetic data being collected from the field, yet using these data to understand the drivers of regional epidemiology remains a challenge. A key issue is the lack of models that relate parasite genetic diversity to epidemiological parameters. Classical models in population genetics characterize changes in genetic diversity in relation to demographic parameters, but fail to account for the unique features of the malaria life cycle. In contrast, epidemiological models, such as the Ross-Macdonald model, capture malaria transmission dynamics but do not consider genetics. Here, we have developed an integrated model encompassing both parasite evolution and regional epidemiology. We achieve this by combining the Ross-Macdonald model with an intra-host continuous-time Moran model, thus explicitly representing the evolution of individual parasite genomes in a traditional epidemiological framework. Implemented as a stochastic simulation, we use the model to explore relationships between measures of parasite genetic diversity and parasite prevalence, a widely-used metric of transmission intensity. First, we explore how varying parasite prevalence influences genetic diversity at equilibrium. We find that multiple genetic diversity statistics are correlated with prevalence, but the strength of the relationships depends on whether variation in prevalence is driven by host- or vector-related factors. Next, we assess the responsiveness of a variety of statistics to malaria control interventions, finding that those related to mixed infections respond quickly (∼months) whereas other statistics, such as nucleotide diversity, may take decades to respond. These findings provide insights into the opportunities and challenges associated with using genetic data to monitor malaria epidemiology.
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Affiliation(s)
- Jason A. Hendry
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Dominic Kwiatkowski
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Medical Research Council Centre for Genomics and Global Health, University of Oxford, Oxford, United Kingdom
- Wellcome Sanger Institute, Cambridge, United Kingdom
| | - Gil McVean
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Medical Research Council Centre for Genomics and Global Health, University of Oxford, Oxford, United Kingdom
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4
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Watson OJ, Okell LC, Hellewell J, Slater HC, Unwin HJT, Omedo I, Bejon P, Snow RW, Noor AM, Rockett K, Hubbart C, Nankabirwa JI, Greenhouse B, Chang HH, Ghani AC, Verity R. Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling. Mol Biol Evol 2021; 38:274-289. [PMID: 32898225 PMCID: PMC7783189 DOI: 10.1093/molbev/msaa225] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.
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Affiliation(s)
- Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Joel Hellewell
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Hannah C Slater
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - H Juliette T Unwin
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Irene Omedo
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-Coast, Kilifi, Kenya
| | - Philip Bejon
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-Coast, Kilifi, Kenya
| | - Robert W Snow
- Population Health Unit, Kenya Medical Research Institute—Wellcome Trust Research Programme, Nairobi, Kenya
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | | | - Kirk Rockett
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Christina Hubbart
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Joaniter I Nankabirwa
- Infectious Diseases Research Collaboration, Kampala, Uganda
- Makerere University College of Health Sciences, Kampala, Uganda
| | - Bryan Greenhouse
- Department of Medicine, University of California, San Francisco, San Francisco, CA
| | - Hsiao-Han Chang
- Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, MA
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
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5
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Daniels RF, Schaffner SF, Dieye Y, Dieng G, Hainsworth M, Fall FB, Diouf CN, Ndiop M, Cisse M, Gueye AB, Sarr O, Guinot P, Deme AB, Bei AK, Sy M, Thwing J, MacInnis B, Earle D, Guinovart C, Sene D, Hartl DL, Ndiaye D, Steketee RW, Wirth DF, Volkman SK. Genetic evidence for imported malaria and local transmission in Richard Toll, Senegal. Malar J 2020; 19:276. [PMID: 32746830 PMCID: PMC7397603 DOI: 10.1186/s12936-020-03346-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 07/25/2020] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Malaria elimination efforts can be undermined by imported malaria infections. Imported infections are classified based on travel history. METHODS A genetic strategy was applied to better understand the contribution of imported infections and to test for local transmission in the very low prevalence region of Richard Toll, Senegal. RESULTS Genetic relatedness analysis, based upon molecular barcode genotyping data derived from diagnostic material, provided evidence for both imported infections and ongoing local transmission in Richard Toll. Evidence for imported malaria included finding that a large proportion of Richard Toll parasites were genetically related to parasites from Thiès, Senegal, a region of moderate transmission with extensive available genotyping data. Evidence for ongoing local transmission included finding parasites of identical genotype that persisted across multiple transmission seasons as well as enrichment of highly related infections within the households of non-travellers compared to travellers. CONCLUSIONS These data indicate that, while a large number of infections may have been imported, there remains ongoing local malaria transmission in Richard Toll. These proof-of-concept findings underscore the value of genetic data to identify parasite relatedness and patterns of transmission to inform optimal intervention selection and placement.
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Affiliation(s)
- Rachel F. Daniels
- grid.38142.3c000000041936754XHarvard T.H. Chan School of Public Health, Boston, MA USA ,grid.66859.34Broad Institute, Cambridge, MA USA
| | | | | | | | | | - Fatou B. Fall
- Senegal National Malaria Control Programme, Dakar, Senegal
| | | | - Medoune Ndiop
- Senegal National Malaria Control Programme, Dakar, Senegal
| | | | | | - Oumar Sarr
- Senegal National Malaria Control Programme, Dakar, Senegal
| | | | - Awa B. Deme
- Dantec Teaching and Research Hospital, Dakar, Senegal
| | - Amy K. Bei
- grid.38142.3c000000041936754XHarvard T.H. Chan School of Public Health, Boston, MA USA
| | - Mouhamad Sy
- Dantec Teaching and Research Hospital, Dakar, Senegal
| | - Julie Thwing
- grid.416738.f0000 0001 2163 0069Centers for Disease Control and Prevention, Atlanta, GA USA
| | | | | | | | - Doudou Sene
- Senegal National Malaria Control Programme, Dakar, Senegal
| | - Daniel L. Hartl
- grid.38142.3c000000041936754XHarvard University, Cambridge, MA USA
| | - Daouda Ndiaye
- grid.8191.10000 0001 2186 9619Cheikh Anta Diop University, Dakar, Senegal
| | | | - Dyann F. Wirth
- grid.38142.3c000000041936754XHarvard T.H. Chan School of Public Health, Boston, MA USA ,grid.66859.34Broad Institute, Cambridge, MA USA
| | - Sarah K. Volkman
- grid.38142.3c000000041936754XHarvard T.H. Chan School of Public Health, Boston, MA USA ,grid.66859.34Broad Institute, Cambridge, MA USA ,grid.28203.3b0000 0004 0378 6053Simmons University, Boston, MA USA
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6
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Tessema SK, Raman J, Duffy CW, Ishengoma DS, Amambua-Ngwa A, Greenhouse B. Applying next-generation sequencing to track falciparum malaria in sub-Saharan Africa. Malar J 2019; 18:268. [PMID: 31477139 PMCID: PMC6720407 DOI: 10.1186/s12936-019-2880-1] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2019] [Accepted: 07/11/2019] [Indexed: 01/13/2023] Open
Abstract
Next-generation sequencing (NGS) technologies are increasingly being used to address a diverse range of biological and epidemiological questions. The current understanding of malaria transmission dynamics and parasite movement mainly relies on the analyses of epidemiologic data, e.g. case counts and self-reported travel history data. However, travel history data are often not routinely collected or are incomplete, lacking the necessary level of accuracy. Although genetic data from routinely collected field samples provides an unprecedented opportunity to track the spread of malaria parasites, it remains an underutilized resource for surveillance due to lack of local awareness and capacity, limited access to sensitive laboratory methods and associated computational tools and difficulty in interpreting genetic epidemiology data. In this review, the potential roles of NGS in better understanding of transmission patterns, accurately tracking parasite movement and addressing the emerging challenges of imported malaria in low transmission settings of sub-Saharan Africa are discussed. Furthermore, this review highlights the insights gained from malaria genomic research and challenges associated with integrating malaria genomics into existing surveillance tools to inform control and elimination strategies.
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Affiliation(s)
- Sofonias K Tessema
- EPPIcenter Program, Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
| | - Jaishree Raman
- Centre for Emerging Zoonotic and Parasitic Diseases, National Institute for Communicable Disease, Sandringham, Gauteng, South Africa
| | - Craig W Duffy
- Department of Infection Biology, University of Liverpool, Liverpool, UK
| | - Deus S Ishengoma
- National Institute for Medical Research, Tanga Research Centre, Tanga, Tanzania
| | | | - Bryan Greenhouse
- EPPIcenter Program, Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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7
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Dalmat R, Naughton B, Kwan-Gett TS, Slyker J, Stuckey EM. Use cases for genetic epidemiology in malaria elimination. Malar J 2019; 18:163. [PMID: 31064369 PMCID: PMC6503548 DOI: 10.1186/s12936-019-2784-0] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 04/22/2019] [Indexed: 12/22/2022] Open
Abstract
Background While traditional epidemiological approaches have supported significant reductions in malaria incidence across many countries, higher resolution information about local and regional malaria epidemiology will be needed to efficiently target interventions for elimination. The application of genetic epidemiological methods for the analysis of parasite genetics has, thus far, primarily been confined to research settings. To illustrate how these technical methods can be used to advance programmatic and operational needs of National Malaria Control Programmes (NMCPs), and accelerate global progress to eradication, this manuscript presents seven use cases for which genetic epidemiology approaches to parasite genetic data are informative to the decision-making of NMCPs. Methods The use cases were developed through a highly iterative process that included an extensive review of the literature and global guidance documents, including the 2017 World Health Organization’s Framework for Malaria Elimination, and collection of stakeholder input. Semi-structured interviews were conducted with programmatic and technical experts about the needs and opportunities for genetic epidemiology methods in malaria elimination. Results Seven use cases were developed: Detect resistance, Assess drug resistance gene flow, Assess transmission intensity, Identify foci, Determine connectivity of parasite populations, Identify imported cases, and Characterize local transmission chains. The method currently used to provide the information sought, population unit for implementation, the pre-conditions for using these approaches, and post-conditions intended as a product of the use case were identified for each use case. Discussion This framework of use cases will prioritize research and development of genetic epidemiology methods that best achieve the goals of NMCPs, and ultimately, inform the establishment of normative policy guidance for their uses. With significant engagement of stakeholders from malaria endemic countries and collaboration with local programme experts to ensure strategic implementation, genetic epidemiological approaches have tremendous potential to accelerate global malaria elimination efforts. Electronic supplementary material The online version of this article (10.1186/s12936-019-2784-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ronit Dalmat
- Department of Epidemiology, University of Washington, Seattle, WA, USA.,Strategic Analysis Research and Training Center, University of Washington, Seattle, WA, USA
| | - Brienna Naughton
- Department of Global Health, University of Washington, Seattle, WA, USA.,Strategic Analysis Research and Training Center, University of Washington, Seattle, WA, USA
| | - Tao Sheng Kwan-Gett
- Department of Health Services, University of Washington, Seattle, WA, USA.,Strategic Analysis Research and Training Center, University of Washington, Seattle, WA, USA
| | - Jennifer Slyker
- Department of Epidemiology, University of Washington, Seattle, WA, USA.,Department of Global Health, University of Washington, Seattle, WA, USA.,Strategic Analysis Research and Training Center, University of Washington, Seattle, WA, USA
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8
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Ayanful-Torgby R, Quashie NB, Boampong JN, Williamson KC, Amoah LE. Seasonal variations in Plasmodium falciparum parasite prevalence assessed by varying diagnostic tests in asymptomatic children in southern Ghana. PLoS One 2018; 13:e0199172. [PMID: 29906275 PMCID: PMC6003688 DOI: 10.1371/journal.pone.0199172] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 06/01/2018] [Indexed: 12/24/2022] Open
Abstract
Plasmodium falciparum infections presenting either as symptomatic or asymptomatic may contain sexual stage parasites (gametocytes) that are crucial to malaria transmission. In this study, the prevalence of microscopic and submicroscopic asexual and gametocyte parasite stages were assessed in asymptomatic children from two communities in southern Ghana. Eighty children aged twelve years and below, none of whom exhibited signs of clinical malaria living in Obom and Cape Coast were sampled twice, one during the rainy (July 2015) and subsequently during the dry (January 2016) season. Venous blood was used to prepare thick and thin blood smears, spot a rapid malaria diagnostic test (PfHRP2 RDT) as well as prepare filter paper blood spots. Blood cell pellets were preserved in Trizol for RNA extraction. Polymerase chain reaction (PCR) and semi-quantitative real time reverse transcriptase PCR (qRT-PCR) were used to determine submicroscopic parasite prevalence. In both sites 87% (95% CI: 78-96) of the asymptomatic individuals surveyed were parasites positive during the 6 month study period. The prevalence of asexual and gametocyte stage parasites in the rainy season were both significantly higher in Obom than in Cape Coast (P < 0.001). Submicroscopic gametocyte prevalence was highest in the rainy season in Obom but in the dry season in Cape Coast. Parasite prevalence determined by PCR was similar to that determined by qRT-PCR in Obom but significantly lower than that determined by qRT-PCR in Cape Coast. Communities with varying parasite prevalence exhibit seasonal variations in the prevalence of gametocyte carriers. Submicroscopic asymptomatic parasite and gametocyte carriage is very high in southern Ghana, even during the dry season in communities with low microscopic parasite prevalence and likely to be missed during national surveillance exercises.
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Affiliation(s)
- Ruth Ayanful-Torgby
- Department of Immunology, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
- School of Biomedical Sciences, University of Cape Coast, Cape Coast, Ghana
| | - Neils B. Quashie
- Centre for Tropical Clinical Pharmacology and Therapeutics, University of Ghana, Accra, Ghana
| | | | - Kim C. Williamson
- Department of Microbiology, Uniform Services University of the Health Sciences, Bethesda, Maryland, United States of America
| | - Linda E. Amoah
- Department of Immunology, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
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9
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Taylor AR, Schaffner SF, Cerqueira GC, Nkhoma SC, Anderson TJC, Sriprawat K, Pyae Phyo A, Nosten F, Neafsey DE, Buckee CO. Quantifying connectivity between local Plasmodium falciparum malaria parasite populations using identity by descent. PLoS Genet 2017; 13:e1007065. [PMID: 29077712 PMCID: PMC5678785 DOI: 10.1371/journal.pgen.1007065] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Revised: 11/08/2017] [Accepted: 10/10/2017] [Indexed: 01/18/2023] Open
Abstract
With the rapidly increasing abundance and accessibility of genomic data, there is a growing interest in using population genetic approaches to characterize fine-scale dispersal of organisms, providing insight into biological processes across a broad range of fields including ecology, evolution and epidemiology. For sexually recombining haploid organisms such as the human malaria parasite P. falciparum, however, there have been no systematic assessments of the type of data and methods required to resolve fine scale connectivity. This analytical gap hinders the use of genomics for understanding local transmission patterns, a crucial goal for policy makers charged with eliminating this important human pathogen. Here we use data collected from four clinics with a catchment area spanning approximately 120 km of the Thai-Myanmar border to compare the ability of divergence (FST) and relatedness based on identity by descent (IBD) to resolve spatial connectivity between malaria parasites collected from proximal clinics. We found no relationship between inter-clinic distance and FST, likely due to sampling of highly related parasites within clinics, but a significant decline in IBD-based relatedness with increasing inter-clinic distance. This association was contingent upon the data set type and size. We estimated that approximately 147 single-infection whole genome sequenced parasite samples or 222 single-infection parasite samples genotyped at 93 single nucleotide polymorphisms (SNPs) were sufficient to recover a robust spatial trend estimate at this scale. In summary, surveillance efforts cannot rely on classical measures of genetic divergence to measure P. falciparum transmission on a local scale. Given adequate sampling, IBD-based relatedness provides a useful alternative, and robust trends can be obtained from parasite samples genotyped at approximately 100 SNPs.
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Affiliation(s)
- Aimee R. Taylor
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Infectious Disease and Microbiome Program, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Stephen F. Schaffner
- Infectious Disease and Microbiome Program, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Gustavo C. Cerqueira
- Infectious Disease and Microbiome Program, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Standwell C. Nkhoma
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Timothy J. C. Anderson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Kanlaya Sriprawat
- Shoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand
| | - Aung Pyae Phyo
- Shoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand
| | - François Nosten
- Shoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine Research building, University of Oxford, Old Road campus, Oxford, United Kingdom
| | - Daniel E. Neafsey
- Infectious Disease and Microbiome Program, Broad Institute, Cambridge, Massachusetts, United States of America
- Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Caroline O. Buckee
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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10
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Wang D, Cotter C, Sun X, Bennett A, Gosling RD, Xiao N. Adapting the local response for malaria elimination through evaluation of the 1-3-7 system performance in the China-Myanmar border region. Malar J 2017; 16:54. [PMID: 28137293 PMCID: PMC5282924 DOI: 10.1186/s12936-017-1707-1] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Accepted: 01/20/2017] [Indexed: 11/10/2022] Open
Abstract
Background Assessing the essential components of ‘1-3-7’ strategy along the China–Myanmar border is critical to identify gaps and challenges to support evidence-based decision making. Methods A mixed-method retrospective study including quantitative and qualitative analysis of the 1-3-7 system components was conducted. Sampled counties were chosen based on malaria incidence from 1 January 2012 to 31 December 2014. Results All 260 confirmed malaria cases from sampled counties were reported within 1 day and had completed case investigations. 70.0% of all Reactive Case Detection (RACD) events were conducted and 90.1% of those were within 7 days. Only ten additional individuals were found malaria positive out of 3662 individuals tested (0.3%) by rapid diagnostic test during RACD events. Conclusions Key gaps were identified in case investigation and RACD activities in Yunnan Province border counties. This evidence supports improving the RACD (or “7”) response strategy in this setting. Given the challenges in this border region, it will be critical to adapt the RACD response to promote the malaria elimination along the China border. Electronic supplementary material The online version of this article (doi:10.1186/s12936-017-1707-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Duoquan Wang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory of Parasite and Vector Pathology, World Health Organization Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai, 200025, People's Republic of China
| | - Chris Cotter
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Xiaodong Sun
- Yunnan Institute of Parasitic Diseases, Puer, 665000, People's Republic of China
| | - Adam Bennett
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Roly D Gosling
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Ning Xiao
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory of Parasite and Vector Pathology, World Health Organization Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai, 200025, People's Republic of China.
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11
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Chang HH, Worby CJ, Yeka A, Nankabirwa J, Kamya MR, Staedke SG, Dorsey G, Murphy M, Neafsey DE, Jeffreys AE, Hubbart C, Rockett KA, Amato R, Kwiatkowski DP, Buckee CO, Greenhouse B. THE REAL McCOIL: A method for the concurrent estimation of the complexity of infection and SNP allele frequency for malaria parasites. PLoS Comput Biol 2017; 13:e1005348. [PMID: 28125584 PMCID: PMC5300274 DOI: 10.1371/journal.pcbi.1005348] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Revised: 02/09/2017] [Accepted: 01/05/2017] [Indexed: 12/24/2022] Open
Abstract
As many malaria-endemic countries move towards elimination of Plasmodium falciparum, the most virulent human malaria parasite, effective tools for monitoring malaria epidemiology are urgent priorities. P. falciparum population genetic approaches offer promising tools for understanding transmission and spread of the disease, but a high prevalence of multi-clone or polygenomic infections can render estimation of even the most basic parameters, such as allele frequencies, challenging. A previous method, COIL, was developed to estimate complexity of infection (COI) from single nucleotide polymorphism (SNP) data, but relies on monogenomic infections to estimate allele frequencies or requires external allele frequency data which may not available. Estimates limited to monogenomic infections may not be representative, however, and when the average COI is high, they can be difficult or impossible to obtain. Therefore, we developed THE REAL McCOIL, Turning HEterozygous SNP data into Robust Estimates of ALelle frequency, via Markov chain Monte Carlo, and Complexity Of Infection using Likelihood, to incorporate polygenomic samples and simultaneously estimate allele frequency and COI. This approach was tested via simulations then applied to SNP data from cross-sectional surveys performed in three Ugandan sites with varying malaria transmission. We show that THE REAL McCOIL consistently outperforms COIL on simulated data, particularly when most infections are polygenomic. Using field data we show that, unlike with COIL, we can distinguish epidemiologically relevant differences in COI between and within these sites. Surprisingly, for example, we estimated high average COI in a peri-urban subregion with lower transmission intensity, suggesting that many of these cases were imported from surrounding regions with higher transmission intensity. THE REAL McCOIL therefore provides a robust tool for understanding the molecular epidemiology of malaria across transmission settings.
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Affiliation(s)
- Hsiao-Han Chang
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Colin J. Worby
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Adoke Yeka
- Makerere University School of Public Health, College of Health Sciences, Kampala, Uganda
- Infectious Disease Research Collaboration, Kampala, Uganda
| | - Joaniter Nankabirwa
- Infectious Disease Research Collaboration, Kampala, Uganda
- Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Moses R. Kamya
- Infectious Disease Research Collaboration, Kampala, Uganda
- Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Sarah G. Staedke
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Grant Dorsey
- Department of Medicine, University of California, San Francisco, San Francisco, California, United States
| | - Maxwell Murphy
- Department of Medicine, University of California, San Francisco, San Francisco, California, United States
| | - Daniel E. Neafsey
- Genome Sequencing and Analysis Program, Broad Institute, Cambridge, Massachusetts, United States
| | - Anna E. Jeffreys
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Christina Hubbart
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Kirk A. Rockett
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Sanger Institute, Cambridge, United Kingdom
| | - Roberto Amato
- Wellcome Trust Sanger Institute, Cambridge, United Kingdom
| | - Dominic P. Kwiatkowski
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Sanger Institute, Cambridge, United Kingdom
| | - Caroline O. Buckee
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Bryan Greenhouse
- Department of Medicine, University of California, San Francisco, San Francisco, California, United States
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12
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Alshahrani AM, Abdelgader TM, Saeed I, Al-Akhshami A, Al-Ghamdi M, Al-Zahrani MH, El Hassan I, Kyalo D, Snow RW. The changing malaria landscape in Aseer region, Kingdom of Saudi Arabia: 2000-2015. Malar J 2016; 15:538. [PMID: 27821186 PMCID: PMC5100269 DOI: 10.1186/s12936-016-1581-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2016] [Accepted: 10/28/2016] [Indexed: 12/02/2022] Open
Abstract
Background In 2004, a revised action plan was developed, supported by the World Health Organization, to eliminate malaria from Saudi Arabia by preventing re-introduction of malaria into regions since declared malaria free, eliminating foci of transmission in the Mecca and Medina areas
and a concerted effort of foci surveillance and control, to eliminate malaria from the regions of Jazan and Aseer. This paper provides the context, activities, progress, and possible contributions toward malaria elimination in the Aseer region since 2000, with a more detailed analysis of the spatial location of locally acquired case incidence since 2012. Methods This is a descriptive study of all available Ministry of Health surveillance data and process reports since 2000, with higher spatial resolution analysis of data between 2012 and 2015. Results In 2000, there were 511 cases of Plasmodium falciparum locally acquired infection. The following 4 years witnessed a dramatic decline in cases to only 18 locally acquired infections reported in 2005. A resurgence in local infections was reported in 2006 (93) and 2007 (165), thereafter (2008–2014) local cases continued to decline to fewer than 40 per year across the region. However, in 2015, a small rise was noted (51). All locally acquired infections were P. falciparum. There has been a constant flow of imported infections into Aseer since 2000, mostly among immigrant labour from Pakistan, India, Sudan, and Yemen. Imported infections have included both Plasmodium vivax and P. falciparum. The spatial extent of malaria appears to be changing, but there remain two intractable areas Sarat Abeda and Dhran Aljanub, where risks per reporting centre have changed little since 2001, remaining above 0.5 per 10,000 population. Only seven villages contributed 55% of all locally acquired infection since 2012. Discussion Aseer has reached a state of very low incidence of locally acquired infections, despite a constant source of imported infections from outside the country. How many of the local infections are F2 generations from imported infections or how many are a result of residual active transmission between asymptomatic carriers of infections transmitted by pockets of existing Anopheles arabiensis populations remains unknown. A more detailed investigation of the spatial and temporal patterns of infected hosts, parasites and vectors would help define whether this region has managed to effectively prevent local transmission of new infections.
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Affiliation(s)
- Ali Mohamed Alshahrani
- Vector Control Administration, Aseer Health Affairs Directorate, Abha, Kingdom of Saudi Arabia. .,Aseer General Directorate of Health Affairs, Abha, Kingdom of Saudi Arabia.
| | - Tarig M Abdelgader
- Vector Control Administration, Aseer Health Affairs Directorate, Abha, Kingdom of Saudi Arabia.,Aseer General Directorate of Health Affairs, Abha, Kingdom of Saudi Arabia
| | - Ibrahim Saeed
- Vector Control Administration, Aseer Health Affairs Directorate, Abha, Kingdom of Saudi Arabia.,Aseer General Directorate of Health Affairs, Abha, Kingdom of Saudi Arabia
| | - AbdulRhman Al-Akhshami
- Vector Control Administration, Aseer Health Affairs Directorate, Abha, Kingdom of Saudi Arabia.,Aseer General Directorate of Health Affairs, Abha, Kingdom of Saudi Arabia
| | - Mohamed Al-Ghamdi
- Aseer General Directorate of Health Affairs, Abha, Kingdom of Saudi Arabia
| | | | - Ibrahim El Hassan
- Public Health and Tropical Medicine, University of Jazan, Jazan, Kingdom of Saudi Arabia
| | - David Kyalo
- Spatial Health Metrics Group, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Robert W Snow
- Spatial Health Metrics Group, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.,Nuffield Department of Clinical Medicine, Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, UK
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13
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The Hitchhiking Parasite: Why Human Movement Matters to Malaria Transmission and What We Can Do About It. Trends Parasitol 2016; 32:752-755. [PMID: 27496331 DOI: 10.1016/j.pt.2016.07.004] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Revised: 07/19/2016] [Accepted: 07/19/2016] [Indexed: 11/23/2022]
Abstract
The failure of the Global Malaria Eradication Program (GMEP) during the 1960s highlighted the relevance of human movement to both re-introducing parasites in elimination settings and spreading drug-resistant parasites widely. Today, given the sophisticated surveillance of human movement patterns and key traveler groups, it is hoped that interventions can be implemented to protect and treat travelers, prevent onward transmission in low transmission settings, and eliminate sources of transmission, including sources of drug-resistant parasites.
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14
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Mapping Malaria Risk in Low Transmission Settings: Challenges and Opportunities. Trends Parasitol 2016; 32:635-645. [PMID: 27238200 DOI: 10.1016/j.pt.2016.05.001] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2016] [Revised: 04/29/2016] [Accepted: 05/02/2016] [Indexed: 11/24/2022]
Abstract
As malaria transmission declines, it becomes increasingly focal and prone to outbreaks. Understanding and predicting patterns of transmission risk becomes an important component of an effective elimination campaign, allowing limited resources for control and elimination to be targeted cost-effectively. Malaria risk mapping in low transmission settings is associated with some unique challenges. This article reviews the main challenges and opportunities related to risk mapping in low transmission areas including recent advancements in risk mapping low transmission malaria, relevant metrics, and statistical approaches and risk mapping in post-elimination settings.
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15
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Reiner RC, Le Menach A, Kunene S, Ntshalintshali N, Hsiang MS, Perkins TA, Greenhouse B, Tatem AJ, Cohen JM, Smith DL. Mapping residual transmission for malaria elimination. eLife 2015; 4. [PMID: 26714110 PMCID: PMC4744184 DOI: 10.7554/elife.09520] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2015] [Accepted: 11/26/2015] [Indexed: 11/14/2022] Open
Abstract
Eliminating malaria from a defined region involves draining the endemic parasite reservoir and minimizing local malaria transmission around imported malaria infections. In the last phases of malaria elimination, as universal interventions reap diminishing marginal returns, national resources must become increasingly devoted to identifying where residual transmission is occurring. The needs for accurate measures of progress and practical advice about how to allocate scarce resources require new analytical methods to quantify fine-grained heterogeneity in malaria risk. Using routine national surveillance data from Swaziland (a sub-Saharan country on the verge of elimination), we estimated individual reproductive numbers. Fine-grained maps of reproductive numbers and local malaria importation rates were combined to show ‘malariogenic potential’, a first for malaria elimination. As countries approach elimination, these individual-based measures of transmission risk provide meaningful metrics for planning programmatic responses and prioritizing areas where interventions will contribute most to malaria elimination. DOI:http://dx.doi.org/10.7554/eLife.09520.001 Swaziland has set a national goal of eliminating malaria transmission in the very short term, which would make it the first country in sub-Saharan Africa to do so. More than half of the cases of malaria that are observed in Swaziland are caused by infections picked up by travelers while they were in other countries where the disease is much more prevalent. The other cases – people who became infected in Swaziland – are the cases that the government of Swaziland is trying to prevent. If Swaziland is going to eliminate malaria, it will need to identify any places where the malaria parasites are still spreading throughout the population so it can target those communities with effective prevention measures. It will also need to manage the risk that infections imported from abroad may re-start transmission in places where it has been stopped. To work out how likely it is that a malaria infection will be transmitted by mosquitoes in a particular place, researchers can look at past malaria data and calculate how many new infections are caused by each case. Reiner et al. have now produced a computer model that estimates how this number varies across Swaziland, highlighting places where the government is going to need to focus efforts to eliminate malaria. The model shows that in some rural areas near Mozambique, each individual infected with malaria is causing more than one other person to become infected. This confirms that the disease has not yet been eliminated from these areas. However, in other regions of the country, malaria rarely spreads between individuals. The detailed regional information from the model may help public health authorities in Swaziland better target their anti-malaria resources. In large cities where most cases are imported, Reiner et al. suggest focusing resources on providing preventive treatment to travelers who plan on visiting places where malaria is spreading. However, in rural areas where malaria continues to spread, preventively treating the whole population or providing them with tools to protect them from mosquitoes might be more appropriate. Similar considerations of regional differences in the spread of malaria could also help other countries to more effectively combat the disease. DOI:http://dx.doi.org/10.7554/eLife.09520.002
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Affiliation(s)
- Robert C Reiner
- Fogarty International Center, National Institutes of Health, Bethesda, United States.,Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, United States
| | | | - Simon Kunene
- National Malaria Control Program, Manzini, Swaziland
| | | | - Michelle S Hsiang
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, United States.,Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, San Francisco, United States.,Department of Pediatrics, University of California, San Francisco Benioff Children's Hospital, , United States
| | - T Alex Perkins
- Fogarty International Center, National Institutes of Health, Bethesda, United States.,Eck Institute for Global Health, University of Notre Dame, Notre Dame, United States.,Department of Biological Sciences, University of Notre Dame, Notre Dame, United States
| | - Bryan Greenhouse
- Department of Medicine, University of California, San Francisco, San Francisco, United States
| | - Andrew J Tatem
- Fogarty International Center, National Institutes of Health, Bethesda, United States.,Department of Geography and Environment, University of Southampton, Southampton, United Kingdom
| | | | - David L Smith
- Fogarty International Center, National Institutes of Health, Bethesda, United States.,Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom.,Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States.,Sanaria Institute for Global Health and Tropical Medicine, Rockville, Maryland, United States
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