Effect of Pediatric Influenza Vaccination on Antibiotic Resistance, England and Wales

Evaluating the impact of Respiratory Syncytial Virus immunisation strategies on antibiotic use and drug resistant bacterial infections in England

Background: Vaccines against viruses have been proposed as a novel means to reduce antibiotic use, which would, in turn, decrease selection for antibiotic resistant bacteria. However, the impact of this intervention is poorly quantified, and likely depends on setting-specific epidemiology. Therefore, with increasing confidence in a new vaccine against respiratory syncytial virus (RSV), it is important to quantify the impact of these vaccines on antibiotic prescribing and any downstream reduction in drug resistant bacterial infections. Methods: Here we integrate results from a dynamic transmission model of RSV and a statistical attribution framework to capture the impact of RSV vaccines on the reduction in antibiotic prescribing due to averted primary care visits in England. Results: Under base case assumptions, we find that the most impactful RSV vaccine strategy targets children aged 5–14 years, resulting in an annual reduction of 10.9 (8.0–14.2) antibiotic courses per 10,000 person years across the entire population, equivalent to reducing annual all-cause primary care prescribing by 0.23%. Our results suggest that this reduction in antibiotic use would gain 130 disability-adjusted life years and avert £51,000 associated with drug resistant bacterial infections. Seasonally administering monoclonal antibodies (mAbs) to high-risk infants under 6 months is the most efficient strategy, reducing per person year antibiotic prescribing by 2.6 (1.9–3.3) antibiotic courses per 1,000 mAb courses. Conclusions: Under optimistic conditions, the cost-effectiveness of RSV vaccine strategies in England would likely not be altered by integrating the benefits of preventing drug resistant infections in addition to RSV disease prevention.

Antibiotic prescribing across age groups in the Kaiser Permanente Northern California population in association with different diagnoses, and with influenza incidence, 2010-2018

There is limited information on the volume of antibiotic prescribing that is influenza-associated, resulting from influenza infections and their complications (such as streptococcal pharyngitis and otitis media). Here, we estimated age/diagnosis-specific proportions of antibiotic prescriptions (fills) for the Kaiser Permanente Northern California population during 2010-2018 that were influenza-associated. The proportion of influenza-associated antibiotic prescribing among all antibiotic prescribing was higher in children aged 5-17 years compared to children aged under 5 years, ranging from 1.4% [95% CI (0.7-2.1)] in aged <1 year to 2.7% (1.9-3.4) in aged 15-17 years. For adults aged over 20 years, the proportion of influenza-associated antibiotic prescribing among all antibiotic prescribing was lower, ranging from 0.7% (0.5-1) for aged 25-29 years to 1.6% (1.2-1.9) for aged 60-64 years. Most of the influenza-associated antibiotic prescribing in children aged under 10 years was for ear infections, while for age groups over 25 years, 45-84% of influenza-associated antibiotic prescribing was for respiratory diagnoses without a bacterial indication. This suggests a modest benefit of increasing influenza vaccination coverage for reducing antibiotic prescribing, as well as the potential benefit of other measures to reduce unnecessary antibiotic prescribing for respiratory diagnoses with no bacterial indication in persons aged over 25 years, both of which may further contribute to the mitigation of antimicrobial resistance.

Impact of the childhood influenza vaccine programme on antibiotic prescribing rates in primary care in England

Vaccines are a key part of the global strategy to tackle antimicrobial resistance (AMR) since prevention of infection should reduce antibiotic use. England commenced national rollout of a live attenuated influenza vaccine (LAIV) programme for children aged 2-3 years together with a series of geographically discrete pilot areas for primary school age children in 2013 extending to older children in subsequent seasons. We investigated vaccine programme impact on community antibiotic prescribing rates. Antibiotic prescribing incidence rates for respiratory (RTI) and urinary tract infections (UTI; controls) were calculated at general practice (GP) level by age category (children<=10 years/adults) and season for LAIV pilot and non-pilot areas between 2013/14 and 2015/16. To estimate the LAIV (primary school age children only) intervention effect, a random effects model was fitted. A multivariable random-effects Poisson regression investigated the association of antibiotic prescribing rates in children with LAIV uptake (2-3-year-olds only) at GP practice level. RTI antibiotic prescribing rates for children <=10 years and adults showed clear seasonal trends and were lower in LAIV-pilot and non-pilot areas after the introduction of the LAIV programme in 2013. The reductions for RTI prescriptions (children) were similar (within 3%) in all areas, which coincided with the start the UK AMR strategy. Antibiotic prescribing was significantly (p < 0.0001) related to LAIV uptake in 2-3-year-olds with antibiotic prescribing reduced by 2.7% (95% CI: 2.1% to 3.4%) for every 10% increase in uptake. We found no evidence the LAIV programme for primary school age children resulted in reductions in RTI antibiotic prescribing, however we detected a significant inverse association between increased vaccine uptake in pre-school age children and antibiotic prescribing at GP level. The temporal association of reduced RTI and UTI antibiotic prescribing with the launch of the UK's AMR Strategy in 2013 highlights the importance of a multifaceted approach to tackle AMR.

Antimicrobial resistance at the human-animal interface in the Pastoralist Communities of Kasese District, South Western Uganda

Intensive usage of antimicrobials in the management of animal diseases leads to selection for resistance among microorganisms. This study aimed to assess antimicrobial use and to describe factors associated with the transmission of antimicrobial resistance between humans and animals in pastoralist communities of Kasese district. A mixed-methods approach was employed in this study. Rectal swabs were collected from the participants and cattle and transported in Carry-Blaire transport medium to the laboratory within 24 h of collection for culture and sensitivity to confirm carriage of multi-drug resistant bacteria. In-depth interviews were conducted among veterinary officers, veterinary drug vendors, human health facility in-charges in both public and private health facilities, and operators of human pharmacies and drug shops. Carriage of multi-drug resistant bacteria among humans was 88 (93%) and 76(80%) among cattle. Consumption of lakeshore water and carriage of multi-drug resistant bacteria in cattle were associated with carriage of multi-drug resistant bacteria in the human population. The prevalence of multi-drug resistance among organisms Isolated from both humans and animals was high. There is a high likelihood of transmission of multi-drug resistance between humans and animals.

Mathematical modelling for antibiotic resistance control policy: do we know enough?

BACKGROUND

Antibiotics remain the cornerstone of modern medicine. Yet there exists an inherent dilemma in their use: we are able to prevent harm by administering antibiotic treatment as necessary to both humans and animals, but we must be mindful of limiting the spread of resistance and safeguarding the efficacy of antibiotics for current and future generations. Policies that strike the right balance must be informed by a transparent rationale that relies on a robust evidence base.

MAIN TEXT

One way to generate the evidence base needed to inform policies for managing antibiotic resistance is by using mathematical models. These models can distil the key drivers of the dynamics of resistance transmission from complex infection and evolutionary processes, as well as predict likely responses to policy change in silico. Here, we ask whether we know enough about antibiotic resistance for mathematical modelling to robustly and effectively inform policy. We consider in turn the challenges associated with capturing antibiotic resistance evolution using mathematical models, and with translating mathematical modelling evidence into policy.

CONCLUSIONS

We suggest that in spite of promising advances, we lack a complete understanding of key principles. From this we advocate for priority areas of future empirical and theoretical research.