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{"title"=>"Temperature-Dependent Pre-Bloodmeal Period and Temperature-Driven Asynchrony between Parasite Development and Mosquito Biting Rate Reduce Malaria Transmission Intensity", "type"=>"journal", "authors"=>[{"first_name"=>"Krijn P.", "last_name"=>"Paaijmans", "scopus_author_id"=>"6507367907"}, {"first_name"=>"Lauren J.", "last_name"=>"Cator", "scopus_author_id"=>"26031246200"}, {"first_name"=>"Matthew B.", "last_name"=>"Thomas", "scopus_author_id"=>"35612365500"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84873188335", "sgr"=>"84873188335", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0055777", "pmid"=>"23383280", "isbn"=>"1932-6203", "pui"=>"368246894"}, "id"=>"70269706-34d0-38e9-918f-f0d3eb5a0f02", "abstract"=>"A mosquito needs to bite at least twice for malaria transmission to occur: once to acquire parasites and, after these parasites complete their development in their mosquito host, once to transmit the parasites to the next vertebrate host. Here we investigate the relationship between temperature, parasite development, and biting frequency in a mosquito-rodent malaria model system. We show that the pre-bloodmeal period (the time lag between mosquito emergence and first bloodmeal) increases at lower temperatures. In addition, parasite development time and feeding exhibit different thermal sensitivities such that mosquitoes might not be ready to feed at the point at which the parasite is ready to be transmitted. Exploring these effects using a simple theoretical model of human malaria shows that delays in infection and transmission can reduce the vectorial capacity of malaria mosquitoes by 20 to over 60%, depending on temperature. These delays have important implications for disease epidemiology and control, and should be considered in future transmission models.", "link"=>"http://www.mendeley.com/research/temperaturedependent-prebloodmeal-period-temperaturedriven-asynchrony-between-parasite-development-m", "reader_count"=>67, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>6, "Researcher"=>11, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>5, "Student > Master"=>14, "Other"=>3, "Student > Bachelor"=>10, "Lecturer"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>6, "Researcher"=>11, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>5, "Student > Master"=>14, "Other"=>3, "Student > Bachelor"=>10, "Lecturer"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Agricultural and Biological Sciences"=>37, "Veterinary Science and Veterinary Medicine"=>1, "Decision Sciences"=>1, "Earth and Planetary Sciences"=>1, "Engineering"=>2, "Environmental Science"=>4, "Nursing and Health Professions"=>3, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>7, "Design"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Social Sciences"=>2, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>7}, "Social Sciences"=>{"Social Sciences"=>2}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>4}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>37}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Czech Republic"=>1, "United States"=>1, "Mexico"=>1, "India"=>1}, "group_count"=>4}

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• http://doi.org/10.1111/1365-2435.12487
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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/497906"], "description"=>"<p>The mean time between mosquito emergence and first bloodmeal (infection delay or <i>δ_i</i>) at 18, 26 and 32°C. The black line represents a polynomial regression (see methods).</p>", "links"=>[], "tags"=>["pre-bloodmeal"], "article_id"=>168428, "categories"=>["Microbiology", "Mathematics", "Infectious Diseases", "Biotechnology"], "users"=>["Krijn P. Paaijmans", "Lauren J. Cator", "Matthew B. Thomas"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055777.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Temperature_dependency_of_the_pre_bloodmeal_period_/168428", "title"=>"Temperature-dependency of the pre-bloodmeal period.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:11:26"}
• {"files"=>["https://ndownloader.figshare.com/files/497989"], "description"=>"<p>A–C: Length of the first and second gonotrophic (or feeding) cycle of <i>Anopheles stephensi</i>, D–F: Proportion of blood fed <i>An. stephensi</i> responding to feeding stimulus (on days 1–6), G–I: proportion of infectious mosquitoes over time, overlaid with mean length of the first (black line) and subsequent cycles (grey lines), derived from A–C, at 22, 24 and 26°C.</p>", "links"=>[], "tags"=>["feeding", "propensity", "eip"], "article_id"=>168513, "categories"=>["Microbiology", "Mathematics", "Infectious Diseases", "Biotechnology"], "users"=>["Krijn P. Paaijmans", "Lauren J. Cator", "Matthew B. Thomas"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055777.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Gonotrophic_cycle_length_feeding_propensity_and_EIP_across_temperature_/168513", "title"=>"Gonotrophic cycle length, feeding propensity and EIP across temperature.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:11:55"}
• {"files"=>["https://ndownloader.figshare.com/files/498119"], "description"=>"<p>The time between mosquito emergence and first bloodmeal (infection delay or <i>δ_i</i>), the length of the extrinsic incubation period of the parasite (EIP), time interval between mosquito feeding events (F), the time between completion of EIP and the next mosquito bite (transmission delay or <i>δ_t</i>), time between mosquito emergence and parasite transmission occurring (<i>δ_i</i>+EIP+<i>δ_t</i>), and the maximum potential waiting time between mosquito emergence and parasite transmission (parasites have to wait for a full feeding cycle before being transmitted; <i>δ_i</i>+EIP+F).</p>", "links"=>[], "tags"=>["asynchrony", "malaria", "parasite", "mosquito", "biting"], "article_id"=>168634, "categories"=>["Microbiology", "Mathematics", "Infectious Diseases", "Biotechnology"], "users"=>["Krijn P. Paaijmans", "Lauren J. Cator", "Matthew B. Thomas"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055777.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Temperature_driven_asynchrony_between_malaria_parasite_development_and_mosquito_biting_rate_/168634", "title"=>"Temperature-driven asynchrony between malaria parasite development and mosquito biting rate.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:12:36"}
• {"files"=>["https://ndownloader.figshare.com/files/498182"], "description"=>"<p>(A) Relative vectorial capacity of malaria mosquitoes using (<i>i</i>) the conventional approach (EIP only; <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055777#pone.0055777.e005\" target=\"_blank\">equation 5</a>), (<i>ii</i>) including infection and transmission delays (<i>δ_i</i>+EIP+<i>δ_t</i>; <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055777#pone.0055777.e006\" target=\"_blank\">eq. 6</a>), and (<i>iii</i>) including a ‘maximal’ wait (<i>δ_i</i>+EIP+F; <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055777#pone.0055777.e007\" target=\"_blank\">eq. 7</a>). (B) Relative reductions in vectorial capacity compared to the conventional approach.</p>", "links"=>[], "tags"=>["delays", "malaria"], "article_id"=>168703, "categories"=>["Microbiology", "Mathematics", "Infectious Diseases", "Biotechnology"], "users"=>["Krijn P. Paaijmans", "Lauren J. Cator", "Matthew B. Thomas"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055777.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_infection_and_transmission_delays_on_malaria_transmission_intensity_/168703", "title"=>"Effect of infection and transmission delays on malaria transmission intensity.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:12:58"}

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Relative Metric

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F1000Prime