Targeting Imperfect Vaccines against Drug-Resistance Determinants: A Strategy for Countering the Rise of Drug Resistance
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{"title"=>"Targeting Imperfect Vaccines against Drug-Resistance Determinants: A Strategy for Countering the Rise of Drug Resistance", "type"=>"journal", "authors"=>[{"first_name"=>"Regina", "last_name"=>"Joice", "scopus_author_id"=>"55805892100"}, {"first_name"=>"Marc", "last_name"=>"Lipsitch", "scopus_author_id"=>"7006236353"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pui"=>"369439204", "doi"=>"10.1371/journal.pone.0068940", "sgr"=>"84880763256", "scopus"=>"2-s2.0-84880763256", "isbn"=>"1932-6203", "pmid"=>"23935910"}, "id"=>"3a71d25a-3d06-3260-8d9e-3708a532a547", "abstract"=>"The growing prevalence of antimicrobial resistance in major pathogens is outpacing discovery of new antimicrobial classes. Vaccines mitigate the effect of antimicrobial resistance by reducing the need for treatment, but vaccines for many drug-resistant pathogens remain undiscovered or have limited efficacy, in part because some vaccines selectively favor pathogen strains that escape vaccine-induced immunity. A strain with even a modest advantage in vaccinated hosts can have high fitness in a population with high vaccine coverage, which can offset a strong selection pressure such as antimicrobial use that occurs in a small fraction of hosts. We propose a strategy to target vaccines against drug-resistant pathogens, by using resistance-conferring proteins as antigens in multicomponent vaccines. Resistance determinants may be weakly immunogenic, offering only modest specific protection against resistant strains. Therefore, we assess here how varying the specific efficacy of the vaccine against resistant strains would affect the proportion of drug-resistant vs. -sensitive strains population-wide for three pathogens--Streptococcus pneumoniae, Staphylococcus aureus, and influenza virus--in which drug resistance is a problem. Notably, if such vaccines confer even slightly higher protection (additional efficacy between 1% and 8%) against resistant variants than sensitive ones, they may be an effective tool in controlling the rise of resistant strains, given current levels of use for many antimicrobial agents. We show that the population-wide impact of such vaccines depends on the additional effect on resistant strains and on the overall effect (against all strains). Resistance-conferring accessory gene products or resistant alleles of essential genes could be valuable as components of vaccines even if their specific protective effect is weak.", "link"=>"http://www.mendeley.com/research/targeting-imperfect-vaccines-against-drugresistance-determinants-strategy-countering-rise-drug-resis", "reader_count"=>44, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>15, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>4, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>5, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>15, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>4, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>5, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Agricultural and Biological Sciences"=>7, "Veterinary Science and Veterinary Medicine"=>1, "Computer Science"=>2, "Biochemistry, Genetics and Molecular Biology"=>3, "Materials Science"=>1, "Mathematics"=>2, "Medicine and Dentistry"=>14, "Pharmacology, Toxicology and Pharmaceutical Science"=>2, "Physics and Astronomy"=>1, "Psychology"=>1, "Social Sciences"=>1, "Immunology and Microbiology"=>4}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>14}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>1}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>5}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>7}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Vietnam"=>1, "Taiwan"=>1, "United Kingdom"=>1, "Kenya"=>1}, "group_count"=>4}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1131485"], "description"=>"<p><b>a</b>, SIR model with a proportion of the population as vaccinated susceptibles ( subscript) and as unvaccinated susceptibles ( subscript), who can get infected with either the drug-sensitive ( superscript) or –resistant ( superscript) strains, get treated ( superscript) or not ( superscript) and are removed due to recovery or death (). This is the model of Ref. <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068940#pone.0068940-Lipsitch2\" target=\"_blank\">[2]</a>, modified to include vaccination. <b>b</b>, Model evaluations for final cumulative proportion resistant among all infections over the course of one season, as a function of the additional vaccine efficacy against resistant, compared to sensitive strains (x-axis) and the fraction of influenza infections treated (y-axis). Here, vaccine coverage is 40% and  = 59%.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "microbiology", "Bacterial pathogens", "staphylococci", "streptococci", "Virology", "Mechanisms of resistance and susceptibility", "Viral vaccines", "microbial ecology", "Population biology", "epidemiology", "Infectious disease epidemiology", "Population Dynamics", "Disease dynamics", "Clinical immunology", "immunity", "vaccination", "Vaccine development", "Infectious diseases", "Bacterial diseases", "Staphylococcus aureus", "Streptococcal infections", "Viral diseases", "influenza", "Infectious disease modeling", "Public health", "immunizations", "efficacy", "drug-resistance", "determinants", "pathogen"], "article_id"=>755435, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Regina Joice", "Marc Lipsitch"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0068940.g003", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Modeling_a_vaccine_with_increased_efficacy_against_drug_resistance_determinants_for_an_epidemic_pathogen_seasonal_influenza_/755435", "title"=>"Modeling a vaccine with increased efficacy against drug-resistance determinants for an epidemic pathogen (seasonal influenza).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-25 02:51:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/1131486"], "description"=>"<p>Parameter Values.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "microbiology", "Bacterial pathogens", "staphylococci", "streptococci", "Virology", "Mechanisms of resistance and susceptibility", "Viral vaccines", "microbial ecology", "Population biology", "epidemiology", "Infectious disease epidemiology", "Population Dynamics", "Disease dynamics", "Clinical immunology", "immunity", "vaccination", "Vaccine development", "Infectious diseases", "Bacterial diseases", "Staphylococcus aureus", "Streptococcal infections", "Viral diseases", "influenza", "Infectious disease modeling", "Public health", "immunizations"], "article_id"=>755436, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Regina Joice", "Marc Lipsitch"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0068940.t001", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Parameter_Values_/755436", "title"=>"Parameter Values.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-25 02:51:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/1131483"], "description"=>"<p><b>a</b>, SIS model with a proportion of the population vaccinated and initially susceptible () and unvaccinated and initially susceptible (), who can get infected with either the drug-sensitive strain ( subscript), –resistant strain ( subscript), or both ( subscript) strains. Plots depict model state at equilibrium (all drug-resistant, all drug-sensitive, stable co-existence of both strains, or elimination of all strains) across a range of overall vaccine efficacy () and additional vaccine efficacy against resistant strain (), where vaccine coverage is 80%. Plots show situation with no fitness cost (<b>b</b>) and with 8% fitness cost (<b>c</b>). Color scheme throughout the paper is as follows: uninfected (gray), sensitive (blue), resistant (red), co-infected with both strains/coexistence of both strains (purple). This model corresponds to Model E of Ref <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068940#pone.0068940-Colijn1\" target=\"_blank\">[11]</a>.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "microbiology", "Bacterial pathogens", "staphylococci", "streptococci", "Virology", "Mechanisms of resistance and susceptibility", "Viral vaccines", "microbial ecology", "Population biology", "epidemiology", "Infectious disease epidemiology", "Population Dynamics", "Disease dynamics", "Clinical immunology", "immunity", "vaccination", "Vaccine development", "Infectious diseases", "Bacterial diseases", "Staphylococcus aureus", "Streptococcal infections", "Viral diseases", "influenza", "Infectious disease modeling", "Public health", "immunizations", "efficacy", "drug-resistance", "determinants", "endemic", "colonizing", "pathogen"], "article_id"=>755433, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Regina Joice", "Marc Lipsitch"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0068940.g001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Modeling_a_vaccine_with_increased_efficacy_against_drug_resistance_determinants_for_an_endemic_colonizing_pathogen_S_pneumoniae_/755433", "title"=>"Modeling a vaccine with increased efficacy against drug-resistance determinants for an endemic colonizing pathogen (<i>S.</i><i>pneumoniae</i>).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-25 02:51:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/1131484"], "description"=>"<p><b>a</b>, SIS model with a proportion of the population as vaccinated susceptibles () and as unvaccinated susceptibles (), who can get colonized with either the drug-sensitive ( subscript), or –resistant ( subscript) strain. <b>b</b>, Contour plot of equilibrium stability conditions as a function of vaccine coverage () and specific vaccine efficacy against resistant strain (), for 3 fitness costs. Stability conditions for the resistant-only and sensitive-only equilibrium were obtained analytically and were mutually exclusive. The stable equilibrium state is plotted by color as a function of fitness cost (different panels), vaccine efficacy against the resistant strain (x-axis) and vaccine coverage (y-axis).</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "microbiology", "Bacterial pathogens", "staphylococci", "streptococci", "Virology", "Mechanisms of resistance and susceptibility", "Viral vaccines", "microbial ecology", "Population biology", "epidemiology", "Infectious disease epidemiology", "Population Dynamics", "Disease dynamics", "Clinical immunology", "immunity", "vaccination", "Vaccine development", "Infectious diseases", "Bacterial diseases", "Staphylococcus aureus", "Streptococcal infections", "Viral diseases", "influenza", "Infectious disease modeling", "Public health", "immunizations", "drug-resistance", "determinants", "endemic", "colonizing", "pathogen", "exists"], "article_id"=>755434, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Regina Joice", "Marc Lipsitch"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0068940.g002", "stats"=>{"downloads"=>0, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Modeling_a_vaccine_against_drug_resistance_determinants_for_an_endemic_colonizing_pathogen_for_which_no_vaccine_currently_exists_S_aureus_/755434", "title"=>"Modeling a vaccine against drug-resistance determinants for an endemic colonizing pathogen for which no vaccine currently exists (<i>S.</i><i>aureus</i>).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-25 02:51:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/1131489", "https://ndownloader.figshare.com/files/1131490", "https://ndownloader.figshare.com/files/1131491", "https://ndownloader.figshare.com/files/1131492"], "description"=>"<div><p>The growing prevalence of antimicrobial resistance in major pathogens is outpacing discovery of new antimicrobial classes. Vaccines mitigate the effect of antimicrobial resistance by reducing the need for treatment, but vaccines for many drug-resistant pathogens remain undiscovered or have limited efficacy, in part because some vaccines selectively favor pathogen strains that escape vaccine-induced immunity. A strain with even a modest advantage in vaccinated hosts can have high fitness in a population with high vaccine coverage, which can offset a strong selection pressure such as antimicrobial use that occurs in a small fraction of hosts. We propose a strategy to target vaccines against drug-resistant pathogens, by using resistance-conferring proteins as antigens in multicomponent vaccines. Resistance determinants may be weakly immunogenic, offering only modest specific protection against resistant strains. Therefore, we assess here how varying the specific efficacy of the vaccine against resistant strains would affect the proportion of drug-resistant vs. –sensitive strains population-wide for three pathogens – <i>Streptococcus pneumoniae</i>, <i>Staphylococcus aureus</i>, and influenza virus – in which drug resistance is a problem. Notably, if such vaccines confer even slightly higher protection (additional efficacy between 1% and 8%) against resistant variants than sensitive ones, they may be an effective tool in controlling the rise of resistant strains, given current levels of use for many antimicrobial agents. We show that the population-wide impact of such vaccines depends on the additional effect on resistant strains and on the overall effect (against all strains). Resistance-conferring accessory gene products or resistant alleles of essential genes could be valuable as components of vaccines even if their specific protective effect is weak.</p></div>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "microbiology", "Bacterial pathogens", "staphylococci", "streptococci", "Virology", "Mechanisms of resistance and susceptibility", "Viral vaccines", "microbial ecology", "Population biology", "epidemiology", "Infectious disease epidemiology", "Population Dynamics", "Disease dynamics", "Clinical immunology", "immunity", "vaccination", "Vaccine development", "Infectious diseases", "Bacterial diseases", "Staphylococcus aureus", "Streptococcal infections", "Viral diseases", "influenza", "Infectious disease modeling", "Public health", "immunizations", "imperfect", "vaccines", "drug-resistance", "countering"], "article_id"=>755439, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Regina Joice", "Marc Lipsitch"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0068940.s001", "https://dx.doi.org/10.1371/journal.pone.0068940.s002", "https://dx.doi.org/10.1371/journal.pone.0068940.s003", "https://dx.doi.org/10.1371/journal.pone.0068940.s004"], "stats"=>{"downloads"=>3, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Targeting_Imperfect_Vaccines_against_Drug_Resistance_Determinants_A_Strategy_for_Countering_the_Rise_of_Drug_Resistance_/755439", "title"=>"Targeting Imperfect Vaccines against Drug-Resistance Determinants: A Strategy for Countering the Rise of Drug Resistance", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-07-25 02:51:07"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"8", "full-text"=>"5", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"10", "full-text"=>"8", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"10", "full-text"=>"7", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"6", "full-text"=>"8", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"3", "full-text"=>"1", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"9", "full-text"=>"10", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"12"}
  • {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"2"}
  • {"unique-ip"=>"6", "full-text"=>"9", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2020", "month"=>"3"}
  • {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"4"}
  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"5"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
  • {"unique-ip"=>"2", "full-text"=>"4", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2020", "month"=>"8"}

Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Immunology", "average_usage"=>[266, 466, 591, 701, 799, 887, 982, 1067, 1155, 1237, 1317, 1395, 1458]}, {"subject_area"=>"/Medicine and health sciences/Immunology", "average_usage"=>[262, 463, 587, 693, 790, 882, 965, 1051, 1135, 1218, 1300, 1376, 1438]}, {"subject_area"=>"/Medicine and health sciences/Pharmacology", "average_usage"=>[265, 471, 604, 723, 827, 926, 1022, 1113, 1210, 1290, 1377, 1454, 1532]}, {"subject_area"=>"/Medicine and health sciences/Public and occupational health", "average_usage"=>[291, 491, 610, 723, 817, 906, 991, 1071, 1153, 1238, 1324, 1411, 1478]}]}
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