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{"title"=>"Ecological Drivers of Mansonella perstans Infection in Uganda and Patterns of Co-endemicity with Lymphatic Filariasis and Malaria", "type"=>"journal", "authors"=>[{"first_name"=>"Anna Sofie", "last_name"=>"Stensgaard", "scopus_author_id"=>"8924014600"}, {"first_name"=>"Penelope", "last_name"=>"Vounatsou", "scopus_author_id"=>"7003291122"}, {"first_name"=>"Ambrose W.", "last_name"=>"Onapa", "scopus_author_id"=>"6603011297"}, {"first_name"=>"Jürg", "last_name"=>"Utzinger", "scopus_author_id"=>"7003667858"}, {"first_name"=>"Erling M.", "last_name"=>"Pedersen", "scopus_author_id"=>"7201545753"}, {"first_name"=>"Thomas K.", "last_name"=>"Kristensen", "scopus_author_id"=>"26429598300"}, {"first_name"=>"Paul E.", "last_name"=>"Simonsen", "scopus_author_id"=>"7005031677"}], "year"=>2016, "source"=>"PLoS Neglected Tropical Diseases", "identifiers"=>{"sgr"=>"84969420627", "doi"=>"10.1371/journal.pntd.0004319", "isbn"=>"1935-2727", "pmid"=>"26793972", "issn"=>"19352735", "scopus"=>"2-s2.0-84969420627", "pui"=>"607985749"}, "id"=>"b97485b9-d5eb-3b1f-849e-246c938212d1", "abstract"=>"BACKGROUND: Mansonella perstans is a widespread, but relatively unknown human filarial parasite transmitted by Culicoides biting midges. Although it is found in many parts of sub-Saharan Africa, only few studies have been carried out to deepen the understanding of its ecology, epidemiology, and health consequences. Hence, knowledge about ecological drivers of the vector and parasite distribution, integral to develop spatially explicit models for disease prevention, control, and elimination strategies, is limited. METHODOLOGY: We analyzed data from a comprehensive nationwide survey of M. perstans infection conducted in 76 schools across Uganda in 2000-2003, to identify environmental drivers. A suite of Bayesian geostatistical regression models was fitted, and the best fitting model based on the deviance information criterion was utilized to predict M. perstans infection risk for all of Uganda. Additionally, we investigated co-infection rates and co-distribution with Wuchereria bancrofti and Plasmodium spp. infections observed at the same survey by mapping geographically overlapping areas. PRINCIPAL FINDINGS: Several bioclimatic factors were significantly associated with M. perstans infection levels. A spatial Bayesian regression model showed the best fit, with diurnal temperature range, normalized difference vegetation index, and cattle densities identified as significant covariates. This model was employed to predict M. perstans infection risk at non-sampled locations. The level of co-infection with W. bancrofti was low (0.3%), due to limited geographic overlap. However, where the two infections did overlap geographically, a positive association was found. CONCLUSIONS/SIGNIFICANCE: This study presents the first geostatistical risk map for M. perstans in Uganda. We confirmed a widespread distribution of M. perstans, and identified important potential drivers of risk. The results provide new insight about the ecologic preferences of this otherwise poorly known filarial parasite and its Culicoides vector species in Uganda, which might be relevant for other settings in sub-Saharan Africa.", "link"=>"http://www.mendeley.com/research/ecological-drivers-mansonella-perstans-infection-uganda-patterns-coendemicity-lymphatic-filariasis-m", "reader_count"=>30, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Researcher"=>8, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>4, "Student > Postgraduate"=>1, "Student > Master"=>9, "Other"=>1, "Student > Bachelor"=>2, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Researcher"=>8, "Student > Doctoral Student"=>2, "Student > Ph. D. 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• http://doi.org/10.4269/ajtmh.18-0491
• http://doi.org/10.1038/s41598-019-46550-9
• http://doi.org/10.1371/journal.pntd.0006184
• http://doi.org/10.1186/s12936-018-2235-3
• http://doi.org/10.1186/s12916-019-1303-z
• http://doi.org/10.3390/ijerph17093070
• http://doi.org/10.1186/s41182-017-0060-y
• http://doi.org/10.1186/s13071-017-2515-8
• http://doi.org/10.1016/j.exppara.2019.107769
• http://doi.org/10.4269/ajtmh.17-0902
• http://doi.org/10.1371/journal.pntd.0008916

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• {"files"=>["https://ndownloader.figshare.com/files/2631072"], "description"=>"<div><p>Background</p><p><i>Mansonella perstans</i> is a widespread, but relatively unknown human filarial parasite transmitted by <i>Culicoides</i> biting midges. Although it is found in many parts of sub-Saharan Africa, only few studies have been carried out to deepen the understanding of its ecology, epidemiology, and health consequences. Hence, knowledge about ecological drivers of the vector and parasite distribution, integral to develop spatially explicit models for disease prevention, control, and elimination strategies, is limited.</p><p>Methodology</p><p>We analyzed data from a comprehensive nationwide survey of <i>M</i>. <i>perstans</i> infection conducted in 76 schools across Uganda in 2000–2003, to identify environmental drivers. A suite of Bayesian geostatistical regression models was fitted, and the best fitting model based on the deviance information criterion was utilized to predict <i>M</i>. <i>perstans</i> infection risk for all of Uganda. Additionally, we investigated co-infection rates and co-distribution with <i>Wuchereria bancrofti</i> and <i>Plasmodium</i> spp. infections observed at the same survey by mapping geographically overlapping areas.</p><p>Principal Findings</p><p>Several bioclimatic factors were significantly associated with <i>M</i>. <i>perstans</i> infection levels. A spatial Bayesian regression model showed the best fit, with diurnal temperature range, normalized difference vegetation index, and cattle densities identified as significant covariates. This model was employed to predict <i>M</i>. <i>perstans</i> infection risk at non-sampled locations. The level of co-infection with <i>W</i>. <i>bancrofti</i> was low (0.3%), due to limited geographic overlap. However, where the two infections did overlap geographically, a positive association was found.</p><p>Conclusions/Significance</p><p>This study presents the first geostatistical risk map for <i>M</i>. <i>perstans</i> in Uganda. We confirmed a widespread distribution of <i>M</i>. <i>perstans</i>, and identified important potential drivers of risk. The results provide new insight about the ecologic preferences of this otherwise poorly known filarial parasite and its <i>Culicoides</i> vector species in Uganda, which might be relevant for other settings in sub-Saharan Africa.</p></div>", "links"=>[], "tags"=>["deviance information criterion", "Malaria BackgroundMansonella perstans", "Mansonella perstans Infection", "areas.Principal FindingsSeveral bioclimatic factors", "geostatistical risk map", "Culicoides vector species", "Bayesian geostatistical regression models", "filarial parasite", "perstans infection levels", "perstans infection risk", "difference vegetation index", "Bayesian regression model"], "article_id"=>1640045, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Anna-Sofie Stensgaard", "Penelope Vounatsou", "Ambrose W. Onapa", "Jürg Utzinger", "Erling M. Pedersen", "Thomas K. Kristensen", "Paul E. Simonsen"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0004319", "stats"=>{"downloads"=>1, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Ecological_Drivers_of_Mansonella_perstans_Infection_in_Uganda_and_Patterns_of_Co_endemicity_with_Lymphatic_Filariasis_and_Malaria/1640045", "title"=>"Ecological Drivers of <i>Mansonella perstans</i> Infection in Uganda and Patterns of Co-endemicity with Lymphatic Filariasis and Malaria", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2016-01-28 12:38:57"}
• {"files"=>["https://ndownloader.figshare.com/files/2631070"], "description"=>"<p>Smooth map of the predicted mean prevalence of <i>M</i>. <i>perstans</i> (a), and the corresponding map of the standard deviations of the predictions (b), highlighting areas of high/low uncertainty associated with the model predictions.</p>", "links"=>[], "tags"=>["deviance information criterion", "Malaria BackgroundMansonella perstans", "Mansonella perstans Infection", "areas.Principal FindingsSeveral bioclimatic factors", "geostatistical risk map", "Culicoides vector species", "Bayesian geostatistical regression models", "filarial parasite", "perstans infection levels", "perstans infection risk", "difference vegetation index", "Bayesian regression model"], "article_id"=>1640043, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Anna-Sofie Stensgaard", "Penelope Vounatsou", "Ambrose W. Onapa", "Jürg Utzinger", "Erling M. Pedersen", "Thomas K. Kristensen", "Paul E. Simonsen"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0004319.g003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Geostatistical_model_based_predicted_mean_prevalence_of_Mansonella_perstans_in_school_aged_children_in_Uganda_/1640043", "title"=>"Geostatistical model-based predicted mean prevalence of <i>Mansonella perstans</i> in school-aged children in Uganda.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:38:58"}
• {"files"=>["https://ndownloader.figshare.com/files/2631071"], "description"=>"<p>The predicted areas are based on surveys of Ugandan school-aged children in 2000–2003 and Bayesian geostatistical model predictions of each (single) parasite infection. Predicted areas of high risk malaria (<i>Plasmodium</i> spp. infection prevalence >50%) is shown in hatch as an overlay.</p>", "links"=>[], "tags"=>["deviance information criterion", "Malaria BackgroundMansonella perstans", "Mansonella perstans Infection", "areas.Principal FindingsSeveral bioclimatic factors", "geostatistical risk map", "Culicoides vector species", "Bayesian geostatistical regression models", "filarial parasite", "perstans infection levels", "perstans infection risk", "difference vegetation index", "Bayesian regression model"], "article_id"=>1640044, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Anna-Sofie Stensgaard", "Penelope Vounatsou", "Ambrose W. Onapa", "Jürg Utzinger", "Erling M. Pedersen", "Thomas K. Kristensen", "Paul E. Simonsen"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0004319.g004", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Maps_of_the_predicted_geographic_co_distribution_of_M_perstans_and_W_bancrofti_based_on_A_a_10_prevalence_threshold_and_B_a_5_prevalence_threshold_/1640044", "title"=>"Maps of the predicted geographic co-distribution of <i>M</i>. <i>perstans</i> and <i>W</i>. <i>bancrofti</i>based on A) a 10% prevalence threshold, and B) a 5% prevalence threshold.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:38:58"}
• {"files"=>["https://ndownloader.figshare.com/files/2631068"], "description"=>"<p>School survey locations and observed prevalence of <i>M</i>. <i>perstans</i> microfilaremia in Uganda.</p>", "links"=>[], "tags"=>["deviance information criterion", "Malaria BackgroundMansonella perstans", "Mansonella perstans Infection", "areas.Principal FindingsSeveral bioclimatic factors", "geostatistical risk map", "Culicoides vector species", "Bayesian geostatistical regression models", "filarial parasite", "perstans infection levels", "perstans infection risk", "difference vegetation index", "Bayesian regression model"], "article_id"=>1640041, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Anna-Sofie Stensgaard", "Penelope Vounatsou", "Ambrose W. Onapa", "Jürg Utzinger", "Erling M. Pedersen", "Thomas K. Kristensen", "Paul E. Simonsen"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0004319.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_School_survey_locations_and_observed_prevalence_of_M_perstans_microfilaremia_in_Uganda_/1640041", "title"=>"School survey locations and observed prevalence of <i>M</i>. <i>perstans</i> microfilaremia in Uganda.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:38:58"}
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PMC Usage Stats | Further Information

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Relative Metric

{"start_date"=>"2016-01-01T00:00:00Z", "end_date"=>"2016-12-31T00:00:00Z", "subject_areas"=>[]}

F1000Prime