Publications by authors named "Gwenan M Knight"

52 Publications

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.

BMC Health Serv Res 2021 Jun 9;21(1):566. Epub 2021 Jun 9.

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, UK.

Background: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient's "bed pathway" - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy.

Methods: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020.

Results: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: "Ward, CC, Ward", "Ward, CC", "CC" and "CC, Ward". Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities.

Conclusions: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19.

Trial Registration: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.
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http://dx.doi.org/10.1186/s12913-021-06509-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8188158PMC
June 2021

Antimicrobial resistance at the G7.

BMJ 2021 06 3;373:n1417. Epub 2021 Jun 3.

Antimicrobial Resistance Centre, London School of Hygiene and Tropical Medicine, London, UK.

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http://dx.doi.org/10.1136/bmj.n1417DOI Listing
June 2021

Implication of backward contact tracing in the presence of overdispersed transmission in COVID-19 outbreaks.

Wellcome Open Res 2020 31;5:239. Epub 2021 Mar 31.

Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.

Contact tracing has the potential to control outbreaks without the need for stringent physical distancing policies, e.g. civil lockdowns. Unlike forward contact tracing, backward contact tracing identifies the source of newly detected cases. This approach is particularly valuable when there is high individual-level variation in the number of secondary transmissions (overdispersion). By using a simple branching process model, we explored the potential of combining backward contact tracing with more conventional forward contact tracing for control of COVID-19. We estimated the typical size of clusters that can be reached by backward tracing and simulated the incremental effectiveness of combining backward tracing with conventional forward tracing. Across ranges of parameter values consistent with dynamics of SARS-CoV-2, backward tracing is expected to identify a primary case generating 3-10 times more infections than a randomly chosen case, typically increasing the proportion of subsequent cases averted by a factor of 2-3. The estimated number of cases averted by backward tracing became greater with a higher degree of overdispersion. Backward contact tracing can be an effective tool for outbreak control, especially in the presence of overdispersion as is observed with SARS-CoV-2.
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http://dx.doi.org/10.12688/wellcomeopenres.16344.3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610176.3PMC
March 2021

Community transmission of multidrug-resistant tuberculosis is associated with activity space overlap in Lima, Peru.

BMC Infect Dis 2021 Mar 18;21(1):275. Epub 2021 Mar 18.

Universidad Peruana Cayetano Heredia, Lima, Peru.

Background: Transmission of multidrug-resistant tuberculosis (MDRTB) requires spatial proximity between infectious cases and susceptible persons. We assess activity space overlap among MDRTB cases and community controls to identify potential areas of transmission.

Methods: We enrolled 35 MDRTB cases and 64 TB-free community controls in Lima, Peru. Cases were whole genome sequenced and strain clustering was used as a proxy for transmission. GPS data were gathered from participants over seven days. Kernel density estimation methods were used to construct activity spaces from GPS locations and the utilization distribution overlap index (UDOI) was used to quantify activity space overlap.

Results: Activity spaces of controls (median = 35.6 km, IQR = 25.1-54) were larger than cases (median = 21.3 km, IQR = 17.9-48.6) (P = 0.02). Activity space overlap was greatest among genetically clustered cases (mean UDOI = 0.63, sd = 0.67) and lowest between cases and controls (mean UDOI = 0.13, sd = 0.28). UDOI was positively associated with genetic similarity of MDRTB strains between case pairs (P < 0.001). The odds of two cases being genetically clustered increased by 22% per 0.10 increase in UDOI (OR = 1.22, CI = 1.09-1.36, P < 0.001).

Conclusions: Activity space overlap is associated with MDRTB clustering. MDRTB transmission may be occurring in small, overlapping activity spaces in community settings. GPS studies may be useful in identifying new areas of MDRTB transmission.
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http://dx.doi.org/10.1186/s12879-021-05953-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7977184PMC
March 2021

Antimicrobial resistance and COVID-19: Intersections and implications.

Elife 2021 02 16;10. Epub 2021 Feb 16.

AMR Centre, London School of Hygiene and Tropical Medicine (LSHTM), London, United Kingdom.

Before the coronavirus 2019 (COVID-19) pandemic began, antimicrobial resistance (AMR) was among the top priorities for global public health. Already a complex challenge, AMR now needs to be addressed in a changing healthcare landscape. Here, we analyse how changes due to COVID-19 in terms of antimicrobial usage, infection prevention, and health systems affect the emergence, transmission, and burden of AMR. Increased hand hygiene, decreased international travel, and decreased elective hospital procedures may reduce AMR pathogen selection and spread in the short term. However, the opposite effects may be seen if antibiotics are more widely used as standard healthcare pathways break down. Over 6 months into the COVID-19 pandemic, the dynamics of AMR remain uncertain. We call for the AMR community to keep a global perspective while designing finely tuned surveillance and research to continue to improve our preparedness and response to these intersecting public health challenges.
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http://dx.doi.org/10.7554/eLife.64139DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886324PMC
February 2021

The effectiveness of biosecurity interventions in reducing the transmission of bacteria from livestock to humans at the farm level: A systematic literature review.

Zoonoses Public Health 2021 09 4;68(6):549-562. Epub 2021 Feb 4.

London School of Hygiene & Tropical Medicine (LSHTM), London, UK.

Zoonotic bacterial infections are a health hazard for people who are in regular contact with livestock at the farm level. Improved biosecurity can limit zoonotic pathogen transmission within farms. The aim of this review was to summarize the effectiveness of farm-level biosecurity interventions in reducing bacterial transmission from animals to people who lived, worked in or visited farms. A systematic literature review was conducted using Embase, Ovid Medline and Agris databases, which were searched on 7 of July 2019, limited to English language papers but with no time exclusion criteria. A narrative synthesis was undertaken utilizing the Centre for Reviews and Dissemination approach, reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias within and across the included studies was performed using established checklists. Out of 869 studies retrieved through database searches, 11 studies were selected. In addition, three studies were found through study reference lists. Fourteen studies were therefore included in this review. Biosecurity interventions were grouped into five categories: hand washing, sanitization and hygienic measures (six studies); personal protective equipment (five studies); vaccination (two studies); other interventions (e.g. air ventilation flap) (four studies); and routine farm activities (two studies). Across studies that investigated odds of human colonization or infection (three studies), odds were seen to both be increased and decreased through use of tested biosecurity measures. Large confidence intervals that often crossed the threshold of an odds ratio equal to 1 were found. Most of the studies' overall risk of bias was 'medium risk' (11 studies), with selection bias domains generally being scored 'medium risk.' Biosecurity interventions are potentially beneficial in reducing bacterial transmission from animals to humans. However, more high-quality evidence is needed to increase certainty in which interventions, in which contexts, are most effective from the human health perspective.
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http://dx.doi.org/10.1111/zph.12807DOI Listing
September 2021

Definition of a genetic relatedness cutoff to exclude recent transmission of meticillin-resistant : a genomic epidemiology analysis.

Lancet Microbe 2020 Dec;1(8):e328-e335

Department of Medicine, University of Cambridge, Cambridge, UK.

Background: Whole-genome sequencing (WGS) can be used in genomic epidemiology investigations to confirm or refute outbreaks of bacterial pathogens, and to support targeted and efficient infection control interventions. We aimed to define a genetic relatedness cutoff, quantified as a number of single-nucleotide polymorphisms (SNP), for meticillin-resistant (MRSA), above which recent (ie, within 6 months) patient-to-patient transmission could be ruled out.

Methods: We did a retrospective genomic and epidemiological analysis of MRSA data from two prospective observational cohort studies in the UK to establish SNP cutoffs for genetic relatedness, above which recent transmission was unlikely. We used three separate approaches to calculate these thresholds. First, we applied a linear mixed model to estimate the substitution rate and 95th percentile within-host diversity in a cohort in which multiple isolates were sequenced per individual. Second, we applied a simulated transmission model to this same genomic dataset. Finally, in a second cohort, we determined the genetic distance (ie, the number of SNPs) that would capture 95% of epidemiologically linked cases. We applied the three approaches to both whole-genome and core-genome sequences.

Findings: In the linear mixed model, the estimated substitution rate was roughly 5 whole-genome SNPs (wgSNPs) or 3 core-genome SNPs (cgSNPs) per genome per year, and the 95th percentile within-host diversity was 19 wgSNPs or 10 cgSNPs. The combined SNP cutoffs for detection of MRSA transmission within 6 months per this model were thus 24 wgSNPs or 13 cgSNPs. The simulated transmission model suggested that cutoffs of 17 wgSNPs or 12 cgSNPs would detect 95% of MRSA transmission events within the same timeframe. Finally, in the second cohort, cutoffs of 22 wgSNPs or 11 cgSNPs captured 95% of epidemiologically linked cases within 6 months.

Interpretation: On the basis of our results, we propose conservative cutoffs of 25 wgSNPs or 15 cgSNPS above which transmission of MRSA within the previous 6 months can be ruled out. These cutoffs could potentially be used as part of a genomic sequencing approach to the management of outbreaks of MRSA in conjunction with traditional epidemiological techniques.

Funding: UK Department of Health, Wellcome Trust, UK National Institute for Health Research.
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http://dx.doi.org/10.1016/S2666-5247(20)30149-XDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721685PMC
December 2020

Quantitatively evaluating the cross-sectoral and One Health impact of interventions: A scoping review and case study of antimicrobial resistance.

One Health 2021 Jun 14;11:100194. Epub 2020 Nov 14.

London School of Hygiene & Tropical Medicine, London, United Kingdom.

Background: Current frameworks evaluating One Health (OH) interventions focus on intervention-design and -implementation. Cross-sectoral impact evaluations are needed to more effectively tackle OH-issues, such as antimicrobial resistance (AMR). We aimed to describe quantitative evaluation methods for interventions related to OH and cross-sectoral issues, to propose an explicit approach for evaluating such interventions, and to apply this approach to AMR.

Methods: A scoping review was performed using WebofScience, EconLit, PubMed and gray literature. Quantitative evaluations of interventions that had an impact across two or more of the human, animal and environment sectors were included. Information on the interventions, methods and outcome measures found was narratively summarised. The information from this review informed the construction of a new approach to OH-related intervention evaluation, which then was applied to the field of AMR.

Results: The review included 90 studies: 73 individual evaluations (from 72 papers) and 18 reviews, with a range of statistical modelling ( = 13 studies), mathematical modelling ( = 53) and index-creation/preference-ranking ( = 14) methods discussed. The literature highlighted the need to (I) establish stakeholder objectives, (II) establish quantifiable outcomes that feed into those objectives, (III) establish agents and compartments that affect these outcomes and (IV) select appropriate methods (described in this review) accordingly. Based on this, an evaluation model for AMR was conceptualised; a decision-tree of intervention options, a compartmental-microeconomic model across sectors and a general-equilibrium (macroeconomic) model are linked. The outcomes of this multi-level model (including cost-utility and Gross Domestic Product impact) can then feed into multi-criteria-decision analyses that weigh respective impact estimates alongside other chosen outcome estimates (for example equity or uncertainty).

Conclusion: In conclusion, stakeholder objectives are key in establishing which evaluation methods (and associated outcome measures) should be used for OH-related interventions. The stated multi-level approach also allows for sub-systems to be modelled in succession, where resources are constrained.
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http://dx.doi.org/10.1016/j.onehlt.2020.100194DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718152PMC
June 2021

Potential impact of tuberculosis vaccines in China, South Africa, and India.

Sci Transl Med 2020 10;12(564)

TB Modelling Group, TB Centre and Centre for the Mathematical Modelling of Infectious Diseases, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, UK.

More effective tuberculosis vaccines are needed to help reach World Health Organization tuberculosis elimination goals. Insufficient evidence exists on the potential impact of future tuberculosis vaccines with varying characteristics and in different epidemiological settings. To inform vaccine development decision making, we modeled the impact of hypothetical tuberculosis vaccines in three high-burden countries. We calibrated () transmission models to age-stratified demographic and epidemiological data from China, South Africa, and India. We varied vaccine efficacy to prevent infection or disease, effective in persons uninfected or infected, and duration of protection. We modeled routine early-adolescent vaccination and 10-yearly mass campaigns from 2025. We estimated median percentage population-level tuberculosis incidence rate reduction (IRR) in 2050 compared to a no new vaccine scenario. In all settings, results suggested vaccines preventing disease in -infected populations would have greatest impact by 2050 (10-year, 70% efficacy against disease, IRR 51%, 52%, and 54% in China, South Africa, and India, respectively). Vaccines preventing reinfection delivered lower potential impact (IRR 1, 12, and 17%). Intermediate impact was predicted for vaccines effective only in uninfected populations, if preventing infection (IRR 21, 37, and 50%) or disease (IRR 19, 36, and 51%), with greater impact in higher-transmission settings. Tuberculosis vaccines have the potential to deliver substantial population-level impact. For prioritizing impact by 2050, vaccine development should focus on preventing disease in -infected populations. Preventing infection or disease in uninfected populations may be useful in higher transmission settings. As vaccine impact depended on epidemiology, different development strategies may be required.
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http://dx.doi.org/10.1126/scitranslmed.aax4607DOI Listing
October 2020

COVID-19 length of hospital stay: a systematic review and data synthesis.

BMC Med 2020 09 3;18(1):270. Epub 2020 Sep 3.

Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.

Background: The COVID-19 pandemic has placed an unprecedented strain on health systems, with rapidly increasing demand for healthcare in hospitals and intensive care units (ICUs) worldwide. As the pandemic escalates, determining the resulting needs for healthcare resources (beds, staff, equipment) has become a key priority for many countries. Projecting future demand requires estimates of how long patients with COVID-19 need different levels of hospital care.

Methods: We performed a systematic review of early evidence on length of stay (LoS) of patients with COVID-19 in hospital and in ICU. We subsequently developed a method to generate LoS distributions which combines summary statistics reported in multiple studies, accounting for differences in sample sizes. Applying this approach, we provide distributions for total hospital and ICU LoS from studies in China and elsewhere, for use by the community.

Results: We identified 52 studies, the majority from China (46/52). Median hospital LoS ranged from 4 to 53 days within China, and 4 to 21 days outside of China, across 45 studies. ICU LoS was reported by eight studies-four each within and outside China-with median values ranging from 6 to 12 and 4 to 19 days, respectively. Our summary distributions have a median hospital LoS of 14 (IQR 10-19) days for China, compared with 5 (IQR 3-9) days outside of China. For ICU, the summary distributions are more similar (median (IQR) of 8 (5-13) days for China and 7 (4-11) days outside of China). There was a visible difference by discharge status, with patients who were discharged alive having longer LoS than those who died during their admission, but no trend associated with study date.

Conclusion: Patients with COVID-19 in China appeared to remain in hospital for longer than elsewhere. This may be explained by differences in criteria for admission and discharge between countries, and different timing within the pandemic. In the absence of local data, the combined summary LoS distributions provided here can be used to model bed demands for contingency planning and then updated, with the novel method presented here, as more studies with aggregated statistics emerge outside China.
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http://dx.doi.org/10.1186/s12916-020-01726-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467845PMC
September 2020

Ongoing challenges to understanding multidrug- and rifampicin-resistant tuberculosis in children adults.

Eur Respir J 2021 02 4;57(2). Epub 2021 Feb 4.

TB Modelling Group, TB Centre and Centre for Mathematical Modelling of Infectious Diseases, Dept of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.

Previous analyses suggest that children with tuberculosis (TB) are no more or no less likely to have multidrug (MDR)- or rifampicin-resistant (RR)-TB than adults. However, the availability of new data, particularly for high MDR/RR-TB burden countries, suggest updates of country-specific estimates are warranted.We used data from population-representative surveys and surveillance collected between 2000 and 2018 to compare the odds ratio of MDR/RR-TB among children (aged <15 years) with TB, compared to the odds of MDR/RR-TB among adults (aged ≥15 years) with TB.In most settings (45 out of 55 countries), and globally as a whole, there is no evidence that age is associated with odds of MDR/RR-TB. However, in some settings, such as former Soviet Union countries in general, and Georgia, Kazakhstan, Lithuania, Tajikistan and Uzbekistan in particular, as well as Peru, MDR/RR-TB is positively associated with age ≥15 years. Meanwhile, in Western Europe in general, and the United Kingdom, Poland, Finland and Luxembourg in particular, MDR/RR-TB is positively associated with age <15 years. 16 countries had sufficient data to compare over time between 2000-2011 and 2012-2018, with evidence for decreases in the odds ratio in children compared to adults in Germany, Kazakhstan and the United States of America.Our results support findings that in most settings a child with TB is as likely as an adult with TB to have MDR/RR-TB. However, setting-specific heterogeneity requires further investigation. Furthermore, the odds ratio for MDR/RR-TB in children compared to adults is generally either stable or decreasing. There are important gaps in detection, recording and reporting of drug resistance among paediatric TB cases, limiting our understanding of transmission risks and measures needed to combat the global TB epidemic.
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http://dx.doi.org/10.1183/13993003.02504-2020DOI Listing
February 2021

The contribution of asymptomatic SARS-CoV-2 infections to transmission on the Diamond Princess cruise ship.

Elife 2020 08 24;9. Epub 2020 Aug 24.

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.

A key unknown for SARS-CoV-2 is how asymptomatic infections contribute to transmission. We used a transmission model with asymptomatic and presymptomatic states, calibrated to data on disease onset and test frequency from the Diamond Princess cruise ship outbreak, to quantify the contribution of asymptomatic infections to transmission. The model estimated that 74% (70-78%, 95% posterior interval) of infections proceeded asymptomatically. Despite intense testing, 53% (51-56%) of infections remained undetected, most of them asymptomatic. Asymptomatic individuals were the source for 69% (20-85%) of all infections. The data did not allow identification of the infectiousness of asymptomatic infections, however low ranges (0-25%) required a net reproduction number for individuals progressing through presymptomatic and symptomatic stages of at least 15. Asymptomatic SARS-CoV-2 infections may contribute substantially to transmission. Control measures, and models projecting their potential impact, need to look beyond the symptomatic cases if they are to understand and address ongoing transmission.
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http://dx.doi.org/10.7554/eLife.58699DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527238PMC
August 2020

No antimicrobial resistance research agenda without tuberculosis.

Lancet Glob Health 2020 08;8(8):e987-e988

TB Modelling Group, TB Centre, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK. Electronic address:

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http://dx.doi.org/10.1016/S2214-109X(20)30309-0DOI Listing
August 2020

What settings have been linked to SARS-CoV-2 transmission clusters?

Wellcome Open Res 2020 5;5:83. Epub 2020 Jun 5.

Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.

: Concern about the health impact of novel coronavirus SARS-CoV-2 has resulted in widespread enforced reductions in people's movement ("lockdowns"). However, there are increasing concerns about the severe economic and wider societal consequences of these measures. Some countries have begun to lift some of the rules on physical distancing in a stepwise manner, with differences in what these "exit strategies" entail and their timeframes. The aim of this work was to inform such exit strategies by exploring the types of indoor and outdoor settings where transmission of SARS-CoV-2 has been reported to occur and result in clusters of cases. Identifying potential settings that result in transmission clusters allows these to be kept under close surveillance and/or to remain closed as part of strategies that aim to avoid a resurgence in transmission following the lifting of lockdown measures. : We performed a systematic review of available literature and media reports to find settings reported in peer reviewed articles and media with these characteristics. These sources are curated and made available in an editable online database. : We found many examples of SARS-CoV-2 clusters linked to a wide range of mostly indoor settings. Few reports came from schools, many from households, and an increasing number were reported in hospitals and elderly care settings across Europe. We identified possible places that are linked to clusters of COVID-19 cases and could be closely monitored and/or remain closed in the first instance following the progressive removal of lockdown restrictions. However, in part due to the limits in surveillance capacities in many settings, the gathering of information such as cluster sizes and attack rates is limited in several ways: inherent recall bias, biased media reporting and missing data.
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http://dx.doi.org/10.12688/wellcomeopenres.15889.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327724PMC
June 2020

Feasibility of informing syndrome-level empiric antibiotic recommendations using publicly available antibiotic resistance datasets.

Wellcome Open Res 2019 24;4:140. Epub 2020 Jun 24.

Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.

Antibiotics are often prescribed empirically to treat infection syndromes before causative bacteria and their susceptibility to antibiotics are identified. Guidelines on empiric antibiotic prescribing are key to effective treatment of infection syndromes, and need to be informed by likely bacterial aetiology and antibiotic resistance patterns. We aimed to create a clinically-relevant composite index of antibiotic resistance for common infection syndromes to inform recommendations at the national level. To create our index, we used open-access antimicrobial resistance (AMR) surveillance datasets, including the ECDC Surveillance Atlas, CDDEP ResistanceMap, WHO GLASS and the newly-available Pfizer ATLAS dataset. We integrated these with data on aetiology of common infection syndromes, existing empiric prescribing guidelines, and pricing and availability of antibiotics.  The ATLAS dataset covered many more bacterial species (287) and antibiotics (52) than other datasets (ranges = 8-11 and 16-32 respectively), but had a similar number of samples per country per year. Using these data, we were able to make empiric prescribing recommendations for bloodstream infection, pneumonia and cellulitis/skin abscess in up to 44 countries. There was insufficient data to make national-level recommendations for the other six syndromes investigated. Results are presented in an interactive web app, where users can visualise underlying resistance proportions to first-line empiric antibiotics for infection syndromes and countries of interest. We found that whilst the creation of a composite resistance index for empiric antibiotic therapy was technically feasible, the ATLAS dataset in its current form can only inform on a limited number of infection syndromes. Other open-access AMR surveillance datasets are largely limited to bloodstream infection specimens and cannot directly inform treatment of other syndromes. With improving availability of international AMR data and better understanding of infection aetiology, this approach may prove useful for informing empiric prescribing decisions in settings with limited local AMR surveillance data.
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http://dx.doi.org/10.12688/wellcomeopenres.15477.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327722PMC
June 2020

The risk of multidrug- or rifampicin-resistance in males females with tuberculosis.

Eur Respir J 2020 09 17;56(3). Epub 2020 Sep 17.

TB Modelling Group, TB Centre and Centre for Mathematical Modelling of Infectious Diseases, Dept of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.

Males are at an increased risk of tuberculosis (TB) disease compared to females. Additionally, several risk factors for multidrug-resistant (MDR) or rifampicin-resistant (RR) TB disease are more common in males, hence male TB patients may have a higher relative risk of MDR/RR-TB than female TB patients.We used sex-disaggregated data of TB patients reported to the World Health Organization for 106 countries to calculate male-to-female (M:F) risk ratios of having MDR/RR-TB.There was no evidence of either sex being more at risk of MDR/RR-TB in 81% (86 out of 106) of countries, with an overall random-effects weighted M:F risk ratio of 1.04 (95% CI 0.97-1.11). In 12% (13 out of 106) of countries there was evidence that males were more at risk, while in 7% (seven out of 106), females were more at risk. The risk of having TB that was MDR/RR increased for males compared to females as MDR/RR-TB incidence increased, and was higher for males than females in the former Soviet Union, where the risk ratio was 1.16 (1.06-1.28). Conversely, the risk increased for females compared to males as gross domestic product purchase power parity increased, and was higher for females than males in countries where the majority of TB burden was found in the foreign-born population, where the risk ratio was 0.84 (0.75-0.94).In general, the risk of MDR/RR-TB, among those with TB, is the same for males as for females. However, males in higher MDR/RR-TB burden countries, particularly the former Soviet Union, face an increased risk that their infection is MDR/RR-TB, highlighting the need for a sex-differentiated approach to TB case-finding and care.
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http://dx.doi.org/10.1183/13993003.00626-2020DOI Listing
September 2020

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

BMC Infect Dis 2019 Nov 29;19(1):1011. Epub 2019 Nov 29.

Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine (LSHTM), London, UK.

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.
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http://dx.doi.org/10.1186/s12879-019-4630-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6884858PMC
November 2019

The health and cost burden of antibiotic resistant and susceptible Escherichia coli bacteraemia in the English hospital setting: A national retrospective cohort study.

PLoS One 2019 10;14(9):e0221944. Epub 2019 Sep 10.

The Health Foundation, London, England.

Introduction: Antibiotic resistance poses a threat to public health and healthcare systems. Escherichia coli causes more bacteraemia episodes in England than any other bacterial species. This study aimed to estimate the burden of E. coli bacteraemia and associated antibiotic resistance in the secondary care setting.

Materials And Methods: This was a retrospective cohort study, with E. coli bacteraemia as the main exposure of interest. Adult hospital in-patients, admitted to acute NHS hospitals between July 2011 and June 2012 were included. English national surveillance and administrative datasets were utilised. Cox proportional hazard, subdistribution hazard and multistate models were constructed to estimate rate of discharge, rate of in-hospital death and excess length of stay, with a unit bed day cost applied to the latter to estimate cost burden from the healthcare system perspective.

Results: 14,042 E. coli bacteraemia and 8,919,284 non-infected inpatient observations were included. E. coli bacteraemia was associated with an increased rate of in-hospital death across all models, with an adjusted subdistribution hazard ratio of 5.88 (95% CI: 5.62-6.15). Resistance was not found to be associated with in-hospital mortality once adjusting for patient and hospital covariates. However, resistance was found to be associated with an increased excess length of stay. This was especially true for third generation cephalosporin (1.58 days excess length of stay, 95% CI: 0.84-2.31) and piperacillin/tazobactam resistance (1.23 days (95% CI: 0.50-1.95)). The annual cost of E. coli bacteraemia was estimated to be £14,346,400 (2012 £), with third-generation cephalosporin resistance associated with excess costs per infection of £420 (95% CI: 220-630).

Conclusions: E. coli bacteraemia places a statistically significant burden on patient health and the hospital sector in England. Resistance to front-line antibiotics increases length of stay; increasing the cost burden of such infections in the secondary care setting.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221944PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736296PMC
March 2020

Mathematical modelling to study the horizontal transfer of antimicrobial resistance genes in bacteria: current state of the field and recommendations.

J R Soc Interface 2019 08 14;16(157):20190260. Epub 2019 Aug 14.

Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.

Antimicrobial resistance (AMR) is one of the greatest public health challenges we are currently facing. To develop effective interventions against this, it is essential to understand the processes behind the spread of AMR. These are partly dependent on the dynamics of horizontal transfer of resistance genes between bacteria, which can occur by conjugation (direct contact), transformation (uptake from the environment) or transduction (mediated by bacteriophages). Mathematical modelling is a powerful tool to investigate the dynamics of AMR; however, the extent of its use to study the horizontal transfer of AMR genes is currently unclear. In this systematic review, we searched for mathematical modelling studies that focused on horizontal transfer of AMR genes. We compared their aims and methods using a list of predetermined criteria and used our results to assess the current state of this research field. Of the 43 studies we identified, most focused on the transfer of single genes by conjugation in Escherichia coli in culture and its impact on the bacterial evolutionary dynamics. Our findings highlight the existence of an important research gap in the dynamics of transformation and transduction and the overall public health implications of horizontal transfer of AMR genes. To further develop this field and improve our ability to control AMR, it is essential that we clarify the structural complexity required to study the dynamics of horizontal gene transfer, which will require cooperation between microbiologists and modellers.
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http://dx.doi.org/10.1098/rsif.2019.0260DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6731517PMC
August 2019

Global burden of latent multidrug-resistant tuberculosis: trends and estimates based on mathematical modelling.

Lancet Infect Dis 2019 08 4;19(8):903-912. Epub 2019 Jul 4.

Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK.

Background: To end the global tuberculosis epidemic, latent tuberculosis infection needs to be addressed. All standard treatments for latent tuberculosis contain drugs to which multidrug-resistant (MDR) Mycobacterium tuberculosis is resistant. We aimed to estimate the global burden of multidrug-resistant latent tuberculosis infection to inform tuberculosis elimination policy.

Methods: By fitting a flexible statistical model to tuberculosis drug resistance surveillance and survey data collated by WHO, we estimated national trends in the proportion of new tuberculosis cases that were caused by MDR strains. We used these data as a proxy for the proportion of new infections caused by MDR M tuberculosis and multiplied trends in annual risk of infection from previous estimates of the burden of latent tuberculosis to generate trends in the annual risk of infection with MDR M tuberculosis. These estimates were used in a cohort model to estimate changes in the global and national prevalence of latent infection with MDR M tuberculosis. We also estimated recent infection levels (ie, in 2013 and 2014) and made predictions for the future burden of MDR tuberculosis in 2035 and 2050.

Findings: 19·1 million (95% uncertainty interval [UI] 16·4 million-21·7 million) people were latently infected with MDR tuberculosis in 2014-a global prevalence of 0·3% (95% UI 0·2-0·3). MDR strains accounted for 1·2% (95% UI 1·0-1·4) of the total latent tuberculosis burden overall, but for 2·9% (95% UI 2·6-3·1) of the burden among children younger than 15 years (risk ratio for those younger than 15 years vs those aged 15 years or older 2·65 [95% UI 2·11-3·25]). Recent latent infection with MDR M tuberculosis meant that 1·9 million (95% UI 1·7 million-2·3 million) people globally were at high risk of active MDR tuberculosis in 2015.

Interpretation: We estimate that three in every 1000 people globally carry latent MDR tuberculosis infection, and prevalence is around ten times higher among those younger than 15 years. If current trends continue, the proportion of latent tuberculosis caused by MDR strains will increase, which will pose serious challenges for management of latent tuberculosis-a cornerstone of tuberculosis elimination strategies.

Funding: UK Medical Research Council, Bill & Melinda Gates Foundation, and European Research Council.
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http://dx.doi.org/10.1016/S1473-3099(19)30307-XDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6656782PMC
August 2019

Dose finding for new vaccines: The role for immunostimulation/immunodynamic modelling.

J Theor Biol 2019 03 10;465:51-55. Epub 2019 Jan 10.

Vaccitech, Oxford, UK.

Current methods to optimize vaccine dose are purely empirically based, whereas in the drug development field, dosing determinations use far more advanced quantitative methodology to accelerate decision-making. Applying these established methods in the field of vaccine development may reduce the currently large clinical trial sample sizes, long time frames, high costs, and ultimately have a better potential to save lives. We propose the field of immunostimulation/immunodynamic (IS/ID) modelling, which aims to translate mathematical frameworks used for drug dosing towards optimizing vaccine dose decision-making. Analogous to Pharmacokinetic/Pharmacodynamic (PK/PD) modelling, the mathematical description of drug distribution (PK) and effect (PD) in host, IS/ID modelling approaches apply mathematical models to describe the underlying mechanisms by which the immune response is stimulated by vaccination (IS) and the resulting measured immune response dynamics (ID). To move IS/ID modelling forward, existing datasets and further data on vaccine allometry and dose-dependent dynamics need to be generated and collate, requiring a collaborative environment with input from academia, industry, regulators, governmental and non-governmental agencies to share modelling expertise, and connect modellers to vaccine data.
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http://dx.doi.org/10.1016/j.jtbi.2019.01.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6860008PMC
March 2019

Age-targeted tuberculosis vaccination in China and implications for vaccine development: a modelling study.

Lancet Glob Health 2019 02 7;7(2):e209-e218. Epub 2019 Jan 7.

TB Modelling Group, TB Centre and Centre for the Mathematical Modelling of Infectious Diseases, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.

Background: Tuberculosis is the leading single-pathogen cause of death worldwide, and China has the third largest number of cases worldwide. New tools, such as new vaccines, are needed to meet WHO tuberculosis goals. Tuberculosis vaccine development strategies mostly target infants or adolescents, but given China's ageing epidemic, vaccinating older people might be important. We modelled the potential impact of new tuberculosis vaccines in China targeting adolescents (15-19 years) or older adults (60-64 years) with varying vaccine characteristics to inform strategic vaccine development.

Methods: A Mycobacterium tuberculosis transmission model was calibrated to age-stratified demographic and epidemiological data from China. Varying scenarios of vaccine implementation (age targeting [adolescents or older adults] and coverage [30% or 70%]) and characteristics (efficacy [40%, 60%, or 80%], duration of protection [10 years or 20 years], and host infection status required for efficacy [pre-infection, post-infection in latency, post-infection in latency or recovered, or pre-infection and post-infection]) were assessed. Primary outcomes were tuberculosis incidence and mortality rate reduction in 2050 in each vaccine scenario compared with the baseline (no new vaccine) scenario and cumulative number needed to vaccinate (NNV) per case or death averted, 2025-50.

Findings: By 2050, results suggest that 74·5% (uncertainty interval [UI] 70·2-78·6) of incident tuberculosis cases in China would occur in people aged 65 years or older, and 75·1% (66·8-80·7) of all cases would be due to reactivation, rather than new infection. All vaccine profiles delivered to older adults had higher population-level impact (reduction of incidence and mortality rates) and lower NNV per case and per death averted than if delivered to adolescents. For an intermediate vaccine scenario of 60% efficacy, 10-year protection, and 70% coverage, the reduction of tuberculosis incidence rates with older adult vaccination was 1·9 times (UI 1·5-2·6) to 157·5 times (119·3-225·6) greater than with adolescent vaccination, and the NNV was 0·011 times (0·008-0·014) to 0·796 times (0·632-0·970) lower. Furthermore, with older adult vaccination, post-infection vaccines provided substantially greater mortality and incidence rate reductions than pre-infection vaccines.

Interpretation: Adolescent-targeted tuberculosis vaccines, the focus of many development plans, would have only a small impact in ageing, reactivation-driven epidemics such as those in China. Instead, an efficacious post-infection vaccine delivered to older adults will be crucial to maximise population-level impact in this setting and would provide an important contribution towards achieving WHO goals. Older adults should be included in tuberculosis vaccine clinical development and implementation planning.

Funding: Aeras and UK MRC.
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http://dx.doi.org/10.1016/S2214-109X(18)30452-2DOI Listing
February 2019

Using vaccine Immunostimulation/Immunodynamic modelling methods to inform vaccine dose decision-making.

NPJ Vaccines 2018 17;3:36. Epub 2018 Sep 17.

1TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, London, UK.

Unlike drug dose optimisation, mathematical modelling has not been applied to vaccine dose finding. We applied a novel Immunostimulation/Immunodynamic mathematical modelling framework to translate multi-dose TB vaccine immune responses from mice, to predict most immunogenic dose in humans. Data were previously collected on IFN-γ secreting CD4+ T cells over time for novel TB vaccines H56 and H1 adjuvanted with IC31 in mice (1 dose groups (0.1-1.5 and 15 μg H56 + IC31), 45 mice) and humans (1 dose (50 μg H56/H1 + IC31), 18 humans). A two-compartment mathematical model, describing the dynamics of the post-vaccination IFN-γ T cell response, was fitted to mouse and human data, separately, using nonlinear mixed effects methods. We used these fitted models and a vaccine dose allometric scaling assumption, to predict the most immunogenic human dose. Based on the changes in model parameters by mouse H56 + IC31 dose and by varying the H56 dose allometric scaling factor between mouse and humans, we established that, at a late time point (224 days) doses of 0.8-8 μg H56 + IC31 in humans may be the most immunogenic. A 0.8-8 μg of H-series TB vaccines in humans, may be as, or more, immunogenic, as larger doses. The Immunostimulation/Immunodynamic mathematical modelling framework is a novel, and potentially revolutionary tool, to predict most immunogenic vaccine doses, and accelerate vaccine development.
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http://dx.doi.org/10.1038/s41541-018-0075-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141590PMC
September 2018

A Case-Control Study to Identify Community Venues Associated with Genetically-clustered, Multidrug-resistant Tuberculosis Disease in Lima, Peru.

Clin Infect Dis 2019 04;68(9):1547-1555

London School of Hygiene and Tropical Medicine, United Kingdom.

Background: The majority of tuberculosis transmission occurs in community settings. Our primary aim in this study was to assess the association between exposure to community venues and multidrug-resistant (MDR) tuberculosis. Our secondary aim was to describe the social networks of MDR tuberculosis cases and controls.

Methods: We recruited laboratory-confirmed MDR tuberculosis cases and community controls that were matched on age and sex. Whole-genome sequencing was used to identify genetically clustered cases. Venue tracing interviews (nonblinded) were conducted to enumerate community venues frequented by participants. Logistic regression was used to assess the association between MDR tuberculosis and person-time spent in community venues. A location-based social network was constructed, with respondents connected if they reported frequenting the same venue, and an exponential random graph model (ERGM) was fitted to model the network.

Results: We enrolled 59 cases and 65 controls. Participants reported 729 unique venues. The mean number of venues reported was similar in both groups (P = .92). Person-time in healthcare venues (adjusted odds ratio [aOR] = 1.67, P = .01), schools (aOR = 1.53, P < .01), and transportation venues (aOR = 1.25, P = .03) was associated with MDR tuberculosis. Healthcare venues, markets, cinemas, and transportation venues were commonly shared among clustered cases. The ERGM indicated significant community segregation between cases and controls. Case networks were more densely connected.

Conclusions: Exposure to healthcare venues, schools, and transportation venues was associated with MDR tuberculosis. Intervention across the segregated network of case venues may be necessary to effectively stem transmission.
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http://dx.doi.org/10.1093/cid/ciy746DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7181380PMC
April 2019

Quantifying where human acquisition of antibiotic resistance occurs: a mathematical modelling study.

BMC Med 2018 08 23;16(1):137. Epub 2018 Aug 23.

National Institute of Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Diseases, Imperial College London, London, W12 0NN, UK.

Background: Antibiotic-resistant bacteria (ARB) are selected by the use of antibiotics. The rational design of interventions to reduce levels of antibiotic resistance requires a greater understanding of how and where ARB are acquired. Our aim was to determine whether acquisition of ARB occurs more often in the community or hospital setting.

Methods: We used a mathematical model of the natural history of ARB to estimate how many ARB were acquired in each of these two environments, as well as to determine key parameters for further investigation. To do this, we explored a range of realistic parameter combinations and considered a case study of parameters for an important subset of resistant strains in England.

Results: If we consider all people with ARB in the total population (community and hospital), the majority, under most clinically derived parameter combinations, acquired their resistance in the community, despite higher levels of antibiotic use and transmission of ARB in the hospital. However, if we focus on just the hospital population, under most parameter combinations a greater proportion of this population acquired ARB in the hospital.

Conclusions: It is likely that the majority of ARB are being acquired in the community, suggesting that efforts to reduce overall ARB carriage should focus on reducing antibiotic usage and transmission in the community setting. However, our framework highlights the need for better pathogen-specific data on antibiotic exposure, ARB clearance and transmission parameters, as well as the link between carriage of ARB and health impact. This is important to determine whether interventions should target total ARB carriage or hospital-acquired ARB carriage, as the latter often dominated in hospital populations.
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http://dx.doi.org/10.1186/s12916-018-1121-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6106940PMC
August 2018

Fast and expensive (PCR) or cheap and slow (culture)? A mathematical modelling study to explore screening for carbapenem resistance in UK hospitals.

BMC Med 2018 08 16;16(1):141. Epub 2018 Aug 16.

National Institute of Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, Commonwealth Building, Hammersmith Campus, Imperial College London, Du Cane Road, London, W12 0NN, UK.

Background: Enterobacteriaceae are a common cause of hospital infections. Carbapenems are a clinically effective treatment of such infections. However, resistance is on the rise. In particular, carbapenemase-producing carbapenem-resistant Enterobacteriaceae (CP-CRE) are increasingly common. In order to limit spread in clinical settings, screening and isolation is being recommended, but many different screening methods are available. We aimed to compare the impact and costs of three algorithms for detecting CP-CRE carriage.

Methods: We developed an individual-based simulation model to compare three screening algorithms using data from a UK National Health Service (NHS) trust. The first algorithm, "Direct PCR", was highly sensitive/specific and quick (half a day), but expensive. The second, "Culture + PCR", was relatively sensitive/specific but slower, requiring 2.5 days. A third algorithm, "PHE", repeated the "Culture + PCR" three times with an additional PCR. Scenario analysis was used to compare several levels of CP-CRE prevalence and coverage of screening, different specialities as well as isolation strategies. Our outcomes were (1) days that a patient with CP-CRE was not detected and hence not isolated ("days at risk"), (2) isolation bed days, (3) total costs and (4) mean cost per CP-CRE risk day averted per year. We also explored limited isolation bed day capacity.

Results: We found that although a Direct PCR algorithm would reduce the number of CP-CRE days at risk, the mean cost per CP-CRE risk day averted per year was substantially higher than for a Culture + PCR algorithm. For example, in our model of an intensive care unit, during a year with a 1.6% CP-CRE prevalence and 63% screening coverage, there were 508 (standard deviation 15), 642 (14) and 655 (14) days at risk under screening algorithms Direct PCR, Culture + PCR and PHE respectively, with mean costs per risk day averted of £192, £61 and £79. These results were robust to sensitivity analyses.

Conclusions: Our results indicate that a Culture + PCR algorithm provides the optimal balance of cost and risk days averted, at varying isolation, prevalence and screening coverage scenarios. Findings from this study will help clinical organisations determine the optimal screening approach for CP-CRE, balancing risk and resources.
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http://dx.doi.org/10.1186/s12916-018-1117-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6094916PMC
August 2018

The relative fitness of drug-resistant : a modelling study of household transmission in Peru.

J R Soc Interface 2018 06;15(143)

TB Centre, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.

The relative fitness of drug-resistant versus susceptible bacteria in an environment dictates resistance prevalence. Estimates for the relative fitness of resistant () strains are highly heterogeneous and mostly derived from experiments. Measuring fitness in the field allows us to determine how the environment influences the spread of resistance. We designed a household structured, stochastic mathematical model to estimate the fitness costs associated with multidrug resistance (MDR) carriage in in Lima, Peru during 2010-2013. By fitting the model to data from a large prospective cohort study of TB disease in household contacts, we estimated the fitness, relative to susceptible strains with a fitness of 1, of MDR- to be 0.32 (95% credible interval: 0.15-0.62) or 0.38 (0.24-0.61), if only transmission or progression to disease, respectively, was affected. The relative fitness of MDR- increased to 0.56 (0.42-0.72) when the fitness cost influenced both transmission and progression to disease equally. We found the average relative fitness of MDR- circulating within households in Lima, Peru during 2010-2013 to be significantly lower than concurrent susceptible If these fitness levels do not change, then existing TB control programmes are likely to keep MDR-TB prevalence at current levels in Lima, Peru.
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http://dx.doi.org/10.1098/rsif.2018.0025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030636PMC
June 2018

Potential impact of influenza vaccine roll-out on antibiotic use in Africa.

J Antimicrob Chemother 2018 08;73(8):2197-2200

Vaccines and Immunity Theme, Medical Research Council Unit, The Gambia at the London School of Hygiene and Tropical Medicine, Banjul, The Gambia.

Background: Influenza infections result in both inappropriate and appropriate antibiotic prescribing. There is a huge burden of both influenza and infections caused by antimicrobial-resistant pathogens in Africa. Influenza vaccines have the potential to reduce appropriate antibiotic use, through reduction of secondary bacterial infections, as well as to reduce levels of influenza misdiagnosed and treated as a bacterial infection (inappropriate).

Objectives: To estimate potential reductions in antibiotic use that are achievable by introducing an influenza vaccine into various African settings.

Methods: Influenza incidence was combined with population size, vaccine and health system characteristics.

Results: We estimated that the direct impact of vaccination could avert more than 390 prescriptions per 100 000 population per year if a 50% efficacious influenza vaccine at 30% coverage was introduced to adults >65 years old in South Africa or children 2-5 years old in Senegal. Across Africa, purely through reducing the number of severe acute respiratory infections, the same vaccine characteristics could avert at least 24 000 antibiotic prescriptions per year if given to children <5 years old.

Conclusions: The introduction of an influenza vaccine into multiple African settings could have a dramatic indirect impact on antibiotic usage. Our values are limited underestimates, capturing only the direct impact of vaccination in a few settings and risk groups. This is owing to the huge lack of epidemiological information on antibiotic use and influenza in Africa. However, it is likely that influenza vaccination in Africa could substantially impact antibiotic usage in addition to influenza-related mortality and morbidity.
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http://dx.doi.org/10.1093/jac/dky172DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6054263PMC
August 2018

Estimating the burden of antimicrobial resistance: a systematic literature review.

Antimicrob Resist Infect Control 2018 25;7:58. Epub 2018 Apr 25.

4Modelling and Economics Unit, National Infection Service, Public Health England, 61 Colindale Avenue, London, NW9 5EQ UK.

Background: Accurate estimates of the burden of antimicrobial resistance (AMR) are needed to establish the magnitude of this global threat in terms of both health and cost, and to paramaterise cost-effectiveness evaluations of interventions aiming to tackle the problem. This review aimed to establish the alternative methodologies used in estimating AMR burden in order to appraise the current evidence base.

Methods: MEDLINE, EMBASE, Scopus, EconLit, PubMed and grey literature were searched. English language studies evaluating the impact of AMR (from any microbe) on patient, payer/provider and economic burden published between January 2013 and December 2015 were included. Independent screening of title/abstracts followed by full texts was performed using pre-specified criteria. A study quality score (from zero to one) was derived using Newcastle-Ottawa and Philips checklists. Extracted study data were used to compare study method and resulting burden estimate, according to perspective. Monetary costs were converted into 2013 USD.

Results: Out of 5187 unique retrievals, 214 studies were included. One hundred eighty-seven studies estimated patient health, 75 studies estimated payer/provider and 11 studies estimated economic burden. 64% of included studies were single centre. The majority of studies estimating patient or provider/payer burden used regression techniques. 48% of studies estimating mortality burden found a significant impact from resistance, excess healthcare system costs ranged from non-significance to $1 billion per year, whilst economic burden ranged from $21,832 per case to over $3 trillion in GDP loss. Median quality scores (interquartile range) for patient, payer/provider and economic burden studies were 0.67 (0.56-0.67), 0.56 (0.46-0.67) and 0.53 (0.44-0.60) respectively.

Conclusions: This study highlights what methodological assumptions and biases can occur dependent on chosen outcome and perspective. Currently, there is considerable variability in burden estimates, which can lead in-turn to inaccurate intervention evaluations and poor policy/investment decisions. Future research should utilise the recommendations presented in this review.

Trial Registration: This systematic review is registered with PROSPERO (PROSPERO CRD42016037510).
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http://dx.doi.org/10.1186/s13756-018-0336-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918775PMC
July 2019

Addressing the Unknowns of Antimicrobial Resistance: Quantifying and Mapping the Drivers of Burden.

Clin Infect Dis 2018 02;66(4):612-616

Health Protection Research Unit in Healthcare Associated Infection and Antimicrobial Resistance, National Institute of Health Research, and Department of Infectious Diseases.

The global threat of antimicrobial resistance (AMR) has arisen through a network of complex interacting factors. Many different sources and transmission pathways contribute to the ever-growing burden of AMR in our clinical settings. The lack of data on these mechanisms and the relative importance of different factors causing the emergence and spread of AMR hampers our global efforts to effectively manage the risks. Importantly, we have little quantitative knowledge on the relative contributions of these sources and are likely to be targeting our interventions suboptimally as a result. Here we propose a systems mapping approach to address the urgent need for reliable and timely data to strengthen the response to AMR.
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http://dx.doi.org/10.1093/cid/cix765DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850617PMC
February 2018
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