Optimal Population-Level Infection Detection Strategies for Malaria Control and Elimination in a Spatial Model of Malaria Transmission
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{"title"=>"Optimal Population-Level Infection Detection Strategies for Malaria Control and Elimination in a Spatial Model of Malaria Transmission", "type"=>"journal", "authors"=>[{"first_name"=>"Jaline", "last_name"=>"Gerardin", "scopus_author_id"=>"56613213400"}, {"first_name"=>"Caitlin A.", "last_name"=>"Bever", "scopus_author_id"=>"56613081800"}, {"first_name"=>"Busiku", "last_name"=>"Hamainza", "scopus_author_id"=>"26429327000"}, {"first_name"=>"John M.", "last_name"=>"Miller", "scopus_author_id"=>"55547139383"}, {"first_name"=>"Philip A.", "last_name"=>"Eckhoff", "scopus_author_id"=>"24398642700"}, {"first_name"=>"Edward A.", "last_name"=>"Wenger", "scopus_author_id"=>"55325307500"}], "year"=>2016, "source"=>"PLoS Computational Biology", "identifiers"=>{"issn"=>"15537358", "scopus"=>"2-s2.0-84956844000", "pmid"=>"26764905", "doi"=>"10.1371/journal.pcbi.1004707", "pui"=>"608034694", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)", "sgr"=>"84956844000"}, "id"=>"789e7c8b-f1e9-3c5c-bb55-cfdd725b34ab", "abstract"=>"Mass campaigns with antimalarial drugs are potentially a powerful tool for local elimination of malaria, yet current diagnostic technologies are insufficiently sensitive to identify all individuals who harbor infections. At the same time, overtreatment of uninfected individuals increases the risk of accelerating emergence of drug resistance and losing community acceptance. Local heterogeneity in transmission intensity may allow campaign strategies that respond to index cases to successfully target subpatent infections while simultaneously limiting overtreatment. While selective targeting of hotspots of transmission has been proposed as a strategy for malaria control, such targeting has not been tested in the context of malaria elimination. Using household locations, demographics, and prevalence data from a survey of four health facility catchment areas in southern Zambia and an agent-based model of malaria transmission and immunity acquisition, a transmission intensity was fit to each household based on neighborhood age-dependent malaria prevalence. A set of individual infection trajectories was constructed for every household in each catchment area, accounting for heterogeneous exposure and immunity. Various campaign strategies-mass drug administration, mass screen and treat, focal mass drug administration, snowball reactive case detection, pooled sampling, and a hypothetical serological diagnostic-were simulated and evaluated for performance at finding infections, minimizing overtreatment, reducing clinical case counts, and interrupting transmission. For malaria control, presumptive treatment leads to substantial overtreatment without additional morbidity reduction under all but the highest transmission conditions. Compared with untargeted approaches, selective targeting of hotspots with drug campaigns is an ineffective tool for elimination due to limited sensitivity of available field diagnostics. 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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2627643"], "description"=>"<p>(A) Distribution of fitted household transmission intensities by HFCA. EIR: entomological inoculation rate, the number of infectious bites per person per year. Shaded areas indicate 95% confidence intervals from 100 stochastic realizations. (B) Household transmission intensity varied spatially within an HFCA. Geometric mean transmission intensity observed over 100 stochastic realizations. (C) Asexual parasite prevalence and infectious potential of constructed populations by HFCA, age, and detectability of asexual parasites by current RDTs, improved RDTs, and PCR, normalized to population 1000, on June 15. Here the infectious potential was defined as the number of mosquitoes that would be infected if 1000 mosquitoes were to feed on a village of 1000 people. Results shown are means of 100 stochastic realizations.</p>", "links"=>[], "tags"=>["transmission intensity", "Malaria Transmission Mass campaigns", "snowball reactive case detection", "overtreatment", "presumptive treatment", "malaria elimination", "strategy", "tool", "Mass Drug Administration", "household", "health facility catchment areas", "Malaria Control", "target subpatent infections"], "article_id"=>1637665, "categories"=>["Biological Sciences"], "users"=>["Jaline Gerardin", "Caitlin A. Bever", "Busiku Hamainza", "John M. Miller", "Philip A. Eckhoff", "Edward A. Wenger"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004707.g002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Fitting_of_transmission_intensities_to_individual_households_in_four_HFCAs_shows_a_prominent_role_for_transmission_by_subpatent_individuals_/1637665", "title"=>"Fitting of transmission intensities to individual households in four HFCAs shows a prominent role for transmission by subpatent individuals.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:36:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/2627647"], "description"=>"<p>(A) Success of infection detection strategies at depleting the infectious reservoir. Fraction of infectious reservoir eliminated was defined as the decrease in infectious potential integrated over 30 days post-campaign. Results shown are means of 100 stochastic realizations per coverage level. (B) Success of infection detection strategies at averting new infections. Results shown are means of 100 stochastic realizations per coverage level. HFCA populations were normalized to 1000.</p>", "links"=>[], "tags"=>["transmission intensity", "Malaria Transmission Mass campaigns", "snowball reactive case detection", "overtreatment", "presumptive treatment", "malaria elimination", "strategy", "tool", "Mass Drug Administration", "household", "health facility catchment areas", "Malaria Control", "target subpatent infections"], "article_id"=>1637669, "categories"=>["Uncategorised"], "users"=>["Jaline Gerardin", "Caitlin A. Bever", "Busiku Hamainza", "John M. Miller", "Philip A. Eckhoff", "Edward A. Wenger"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004707.g003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Infection_detection_strategies_differ_in_ability_to_reduce_transmission_/1637669", "title"=>"Infection detection strategies differ in ability to reduce transmission.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:36:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/2627649"], "description"=>"<p>(A) Success of infection detection strategies at finding infected individuals while avoiding overtreatment of uninfected individuals. Results shown are means of 100 stochastic realizations per coverage level. Ticks indicate 20% steps in coverage. (B) Success of infection detection strategies at averting clinical cases while minimizing overtreatment at 80% coverage. Results shown are means and 95% confidence intervals of 100 stochastic realizations per coverage level. HFCA populations were normalized to 1000.</p>", "links"=>[], "tags"=>["transmission intensity", "Malaria Transmission Mass campaigns", "snowball reactive case detection", "overtreatment", "presumptive treatment", "malaria elimination", "strategy", "tool", "Mass Drug Administration", "household", "health facility catchment areas", "Malaria Control", "target subpatent infections"], "article_id"=>1637671, "categories"=>["Biological Sciences"], "users"=>["Jaline Gerardin", "Caitlin A. Bever", "Busiku Hamainza", "John M. Miller", "Philip A. Eckhoff", "Edward A. Wenger"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004707.g004", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Infection_detection_strategies_differ_in_ability_to_minimize_overtreatment_/1637671", "title"=>"Infection detection strategies differ in ability to minimize overtreatment.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:36:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/2627652"], "description"=>"<p>(A) Probability that less than one new infection is seeded from vectors infected in the 30 days post-campaign. Results shown are means of 1000 stochastic realizations per coverage level. (B) Success of infection detection strategies at finding infected individuals while minimizing overtreatment. Results shown are means of 1000 stochastic realizations per coverage level. Ticks indicate 20% steps in coverage.</p>", "links"=>[], "tags"=>["transmission intensity", "Malaria Transmission Mass campaigns", "snowball reactive case detection", "overtreatment", "presumptive treatment", "malaria elimination", "strategy", "tool", "Mass Drug Administration", "household", "health facility catchment areas", "Malaria Control", "target subpatent infections"], "article_id"=>1637674, "categories"=>["Biological Sciences"], "users"=>["Jaline Gerardin", "Caitlin A. Bever", "Busiku Hamainza", "John M. Miller", "Philip A. Eckhoff", "Edward A. Wenger"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004707.g005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MDA_and_sensitive_serological_diagnostics_are_the_most_effective_detection_strategies_for_malaria_elimination_/1637674", "title"=>"MDA and sensitive serological diagnostics are the most effective detection strategies for malaria elimination.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:36:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/2627654", "https://ndownloader.figshare.com/files/2627659", "https://ndownloader.figshare.com/files/2627663", "https://ndownloader.figshare.com/files/2627664", "https://ndownloader.figshare.com/files/2627665", "https://ndownloader.figshare.com/files/2627666", "https://ndownloader.figshare.com/files/2627667", "https://ndownloader.figshare.com/files/2627668"], "description"=>"<div><p>Mass campaigns with antimalarial drugs are potentially a powerful tool for local elimination of malaria, yet current diagnostic technologies are insufficiently sensitive to identify all individuals who harbor infections. At the same time, overtreatment of uninfected individuals increases the risk of accelerating emergence of drug resistance and losing community acceptance. Local heterogeneity in transmission intensity may allow campaign strategies that respond to index cases to successfully target subpatent infections while simultaneously limiting overtreatment. While selective targeting of hotspots of transmission has been proposed as a strategy for malaria control, such targeting has not been tested in the context of malaria elimination. Using household locations, demographics, and prevalence data from a survey of four health facility catchment areas in southern Zambia and an agent-based model of malaria transmission and immunity acquisition, a transmission intensity was fit to each household based on neighborhood age-dependent malaria prevalence. A set of individual infection trajectories was constructed for every household in each catchment area, accounting for heterogeneous exposure and immunity. Various campaign strategies—mass drug administration, mass screen and treat, focal mass drug administration, snowball reactive case detection, pooled sampling, and a hypothetical serological diagnostic—were simulated and evaluated for performance at finding infections, minimizing overtreatment, reducing clinical case counts, and interrupting transmission. For malaria control, presumptive treatment leads to substantial overtreatment without additional morbidity reduction under all but the highest transmission conditions. Compared with untargeted approaches, selective targeting of hotspots with drug campaigns is an ineffective tool for elimination due to limited sensitivity of available field diagnostics. Serological diagnosis is potentially an effective tool for malaria elimination but requires higher coverage to achieve similar results to mass distribution of presumptive treatment.</p></div>", "links"=>[], "tags"=>["transmission intensity", "Malaria Transmission Mass campaigns", "snowball reactive case detection", "overtreatment", "presumptive treatment", "malaria elimination", "strategy", "tool", "Mass Drug Administration", "household", "health facility catchment areas", "Malaria Control", "target subpatent infections"], "article_id"=>1637676, "categories"=>["Biological Sciences"], "users"=>["Jaline Gerardin", "Caitlin A. Bever", "Busiku Hamainza", "John M. Miller", "Philip A. Eckhoff", "Edward A. Wenger"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1004707.s001", "https://dx.doi.org/10.1371/journal.pcbi.1004707.s002", "https://dx.doi.org/10.1371/journal.pcbi.1004707.s003", "https://dx.doi.org/10.1371/journal.pcbi.1004707.s004", "https://dx.doi.org/10.1371/journal.pcbi.1004707.s005", "https://dx.doi.org/10.1371/journal.pcbi.1004707.s006", "https://dx.doi.org/10.1371/journal.pcbi.1004707.s007", "https://dx.doi.org/10.1371/journal.pcbi.1004707.s008"], "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Optimal_Population_Level_Infection_Detection_Strategies_for_Malaria_Control_and_Elimination_in_a_Spatial_Model_of_Malaria_Transmission_/1637676", "title"=>"Optimal Population-Level Infection Detection Strategies for Malaria Control and Elimination in a Spatial Model of Malaria Transmission", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2016-01-28 12:36:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/2627634"], "description"=>"<p>(A) Study area with June-July 2012 RDT prevalence. (B) Household RDT positive rate varied spatially within a HFCA. (C) RDT positive individuals within a HFCA were clustered within households and within 50m. Conditional probabilities of being RDT+ were calculated as the fraction of an RDT+ individual’s family members who were also RDT+, the fraction of people who were RDT+ within a 50m radius but not within the household of an RDT+ individual, and the fraction of people who were RDT+ between 50m and 200m of an RDT+ individual. Bars indicate 95% confidence intervals. (D) RDT positive rate varied with age within each HFCA. Shaded areas indicate 95% confidence intervals.</p>", "links"=>[], "tags"=>["transmission intensity", "Malaria Transmission Mass campaigns", "snowball reactive case detection", "overtreatment", "presumptive treatment", "malaria elimination", "strategy", "tool", "Mass Drug Administration", "household", "health facility catchment areas", "Malaria Control", "target subpatent infections"], "article_id"=>1637662, "categories"=>["Biological Sciences"], "users"=>["Jaline Gerardin", "Caitlin A. Bever", "Busiku Hamainza", "John M. Miller", "Philip A. Eckhoff", "Edward A. Wenger"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004707.g001", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_RDT_positive_infections_are_clustered_within_four_HFCAs_in_Southern_Province_Zambia_/1637662", "title"=>"RDT-positive infections are clustered within four HFCAs in Southern Province, Zambia.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:36:24"}

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"=>[]}
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