Genesis of Antibiotic Resistance LXVIII: Effective Vaccination (Campaigns) Decrease Antibiotic Consumption Consequent Antibiotic‐Resistance (AR) Pandemic(ARP) – <i>The exception that proves the rule</i>
Bibliographic record
Abstract
Vaccines are endeavored to provide immunity from the specific form of the target infectious agent(s) (resistant or wild type @ genotype/phenotype traits such as membrane proteins, glycoproteins conjugates), leading to a foreseeable clinical intervention with antimicrobial therapy. Vaccines for antibiotic‐resistant bacterial pathogens (ARBP) confer immunity to the host by reducing the pathogenic load, a threshold pathogenic count ( vs total pathogen load) for the onset of the infectious disease(s) (PNAS. 2018 Dec.115(51): 12896). Our hypothesis is that “vaccination campaigns abate antibiotic resistance pandemic (ARP)” as a secondary outcome, and it also indirectly reduces antibiotics consumption at the point of care clinical intervention. Here we present the corroborating evidence to support the hypothesis. Pneumococcal conjugate vaccination has been shown to (PCV13) limit the incidence of invasive pneumococcal disease 91 cases per 100,000 people in 1998 to 2 cases per 100,000 people in 2015 ( https://www.cdc.gov/pneumococcal/surveillance.html ). Based on the vaccination success rate, a prediction showed that an estimated 20 % reduction in influenza likely to reduce antibiotic prescribing by 8%. Also, data from a vaccination program in Canada estimated that a reduction in influenza‐associated antibiotic prescribing for respiratory infections by 64 % (CID 2009; 49 (5): 750–56; ICHE 32 (7): 706–9. 2011). Influenza vaccination is known to mitigate bacterial infections, up to 40 % of which otherwise require hospitalization (JID.2013: 208 (3): 43241; PMID: 24590244). The introduction of the pneumococcal vaccine has shown a reduction in penicillin‐resistant and multidrug‐resistant strains of Streptococcus pneumoniae —incidence by more than 50 % (PMID: 16598044). The vaccination program in South Africa showed a reduced infection rate of penicillin‐resistant strains by 67 percent and infection with trimethoprim‐sulfamethoxazole‐resistant strains by 56 percent (PMID: 14523142). Annual mass vaccination campaigns caregivers, family members, health care workers, primary care physicians, intensive care and emergency physicians have been suggested to disseminate the vaccine‐preventable diseases and comorbidity associated antibiotic utilization in clinical intervention for infectious diseases. Maternal immunization has been suggested to minimize the incidence of tetanus, influenza, and pertussis in neonatal patient care (PMID: 31773179).Taken together, a three‐prong approach of a. surveillance of emerging antibiotic‐resistant bacterial pathogens(ARBP), b. robust identification of vaccine/therapeutic targets in the ARBP in a global repository with a periodic update, and c . focused effort on vaccine research and development for expedited vaccination programs across the diverse socioeconomic spectrum encompassing Low‐income countries (LICs), Middle‐income countries (MICs) (a. lower‐middle‐income b. upper‐middle‐income (UMICs) to reduce the antibiotic use thus mitigate the emergence of ARP (Primary source: The IBRD/ The World Bank; 2017 Nov 3; Chapt 18).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".