Hitting Hotspots: Spatial Targeting of Malaria for Control and Elimination
Publication Date
January 31, 2012
Journal
PLOS Medicine
Authors
Teun Bousema, Jamie T. Griffin, Robert W. Sauerwein, David L. Smith, et al
Volume
9
Issue
1
Pages
e1001165
DOI
https://dx.plos.org/10.1371/journal.pmed.1001165
Publisher URL
http://journals.plos.org/plosmedicine/article?id=10.1371%2Fjournal.pmed.1001165
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/22303287
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3269430
Europe PMC
http://europepmc.org/abstract/MED/22303287
Web of Science
000300419600013
Scopus
84856475855
Mendeley
http://www.mendeley.com/research/hitting-hotspots-spatial-targeting-malaria-control-elimination
Events
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Mendeley | Further Information

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CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/686803"], "description"=>"<p>Mosquito exposure and parasite carriage are highly focal in the dry season (A). People living in hotspots are exposed to higher mosquito densities and, because individuals in households belonging to hotspots are more likely to be infected and infectious, mosquitoes are more likely to acquire a malaria infection in these households. In the wet season, as mosquito density and geographic distribution increase, infectious mosquitoes drive infection out into the rest of the village (B).</p>", "links"=>[], "tags"=>["malaria"], "article_id"=>357289, "categories"=>["Biotechnology", "Infectious Diseases"], "users"=>["Teun Bousema", "Jamie T. Griffin", "Robert W. Sauerwein", "David L. Smith", "Thomas S. Churcher", "Willem Takken", "Azra Ghani", "Chris Drakeley", "Roly Gosling"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001165.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hotspots_of_malaria_transmission_in_the_dry_and_wet_season_/357289", "title"=>"Hotspots of malaria transmission in the dry and wet season.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 09:24:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/686877"], "description"=>"<p>The simulations for the low endemic setting with a baseline parasite prevalence of ∼15% in the general population (A) are based on parasite prevalence and mosquito exposure data from Korogwe, northern Tanzania (2008) <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001165#pmed.1001165-Bousema1\" target=\"_blank\">[14]</a>. Effective coverage with LLINs is scaled up over 6 years to 60% prior to the intervention, creating a starting point for interventions aiming towards malaria elimination <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001165#pmed.1001165-Flaxman1\" target=\"_blank\">[59]</a>. Subsequently, the impact of four intervention strategies is simulated using an individual-based simulation model <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001165#pmed.1001165-Griffin1\" target=\"_blank\">[24]</a>: (i) increasing LLIN coverage to 80% in a untargeted manner (blue solid line); (ii) increasing LLIN coverage with the same number of LLINs but preferentially targeting hotspots where 90% coverage is reached (dashed blue line); (iii) increasing LLIN coverage to 80% and yearly introducing IRS at 20% coverage in a untargeted manner (red solid line); (iv) a targeted approach using the same resources as the third scenario, reaching 90% effective coverage with LLINs and 90% effective coverage with yearly IRS in hotspots (dashed red line). LLINs were replaced every 4 years. Simulations were repeated for an area of high endemicity with a parasite prevalence of ∼40% in the general population (B).</p>", "links"=>[], "tags"=>["untargeted", "interventions", "long-lasting", "llins", "irs", "malaria", "elimination"], "article_id"=>357354, "categories"=>["Biotechnology", "Infectious Diseases"], "users"=>["Teun Bousema", "Jamie T. Griffin", "Robert W. Sauerwein", "David L. Smith", "Thomas S. Churcher", "Willem Takken", "Azra Ghani", "Chris Drakeley", "Roly Gosling"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001165.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Targeted_and_untargeted_interventions_with_long_lasting_LLINs_and_IRS_in_a_malaria_elimination_scenario_/357354", "title"=>"Targeted and untargeted interventions with long-lasting LLINs and IRS in a malaria elimination scenario.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 09:25:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/686954"], "description"=>"<p><i>R</i><sub>0</sub> was calculated by adjusting the mean mosquito exposure to match the equilibrium parasite prevalence for each village, with either homogeneous mosquito exposure or with variation in exposure with the same ratio of standard deviation to mean as observed in that village.</p>", "links"=>[], "tags"=>["reproductive", "parasite", "prevalence", "heterogeneous", "mosquito", "villages"], "article_id"=>357432, "categories"=>["Biotechnology", "Infectious Diseases"], "users"=>["Teun Bousema", "Jamie T. Griffin", "Robert W. Sauerwein", "David L. Smith", "Thomas S. Churcher", "Willem Takken", "Azra Ghani", "Chris Drakeley", "Roly Gosling"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001165.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimates_of_the_basic_reproductive_number_R_0_for_a_given_parasite_prevalence_and_heterogeneous_mosquito_exposure_in_four_villages_in_northern_Tanzania_/357432", "title"=>"Estimates of the basic reproductive number (<i>R</i><sub>0</sub>) for a given parasite prevalence and heterogeneous mosquito exposure in four villages in northern Tanzania.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 09:25:41"}

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Relative Metric

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