Economic burden of antibiotic resistance: how much do we really know?

AbstractThe declining effectiveness of antibiotics imposes potentially large health and economic burdens on societies. Quantifying the economic outcomes of antibiotic resistance effectively can help policy-makers and healthcare professionals to set priorities, but determining the actual effect of antibiotic resistance on clinical outcomes is a necessary first step. In this article, we review and discuss the contributions and limitations of studies that estimate the disease burden attributable to antibiotic resistance and studies that estimate the economic burden of resistance. We also consider other factors that are important in a comprehensive approach to evaluating the economic burden of antibiotic resistance

Quantifying uncertainty in intervention effectiveness with structured expert judgement : an application to obstetric fistula

To demonstrate a new application of structured expert judgement to assess the effectiveness of surgery to correct obstetric fistula in a low-income setting. Intervention effectiveness is a major input of evidence-informed priority setting in healthcare, but information on intervention effectiveness is generally lacking. This is particularly problematic in the context of poorly resourced healthcare settings where even efficacious interventions fail to translate into improvements in health. The few intervention effectiveness studies related to obstetric fistula treatment focus on the experience of single facilities and do not consider the impact of multiple factors that may affect health outcomes. We use the classical model of structured expert judgement, a method that has been used to quantify uncertainty in the areas of engineering and environmental risk assessment when data are unavailable. Under this method, experts quantify their uncertainty about rates of long-term disability in patients with fistula following treatment in different contexts, but the information content drawn from their responses is statistically conditioned on the accuracy and informativeness of their responses to a set of calibration questions. Through this method, we develop best estimates and uncertainty bounds for the rate of disability associated with each treatment scenario and setting. Eight experts in obstetric fistula repair in low and middle income countries. Estimates developed using performance weights were statistically superior to those involving a simple averaging of expert responses. The performance-weight decision maker's assessments are narrower for 9 of the 10 calibration questions and 21 of 23 variables of interest. We find that structured expert judgement is a viable approach to investigating the effectiveness of medical interventions where randomised controlled trials are not possible. Understanding the effectiveness of surgery performed at different types of facilities can guide programme planning to increase access to fistula treatment

Anthropological and socioeconomic factors contributing to global antimicrobial resistance: a univariate and multivariable analysis

Background Understanding of the factors driving global antimicrobial resistance is limited. We analysed antimicrobial resistance and antibiotic consumption worldwide versus many potential contributing factors. Methods Using three sources of data (ResistanceMap, the WHO 2014 report on antimicrobial resistance, and contemporary publications), we created two global indices of antimicrobial resistance for 103 countries using data from 2008 to 2014: Escherichia coli resistance—the global average prevalence of E coli bacteria that were resistant to third-generation cephalosporins and fluoroquinolones, and aggregate resistance—the combined average prevalence of E coli and Klebsiella spp resistant to third-generation cephalosporins, fluoroquinolones, and carbapenems, and meticillin-resistant Staphylococcus aureus. Antibiotic consumption data were obtained from the IQVIA MIDAS database. The World Bank DataBank was used to obtain data for governance, education, gross domestic product (GDP) per capita, health-care spending, and community infrastructure (eg, sanitation). A corruption index was derived using data from Transparency International. We examined associations between antimicrobial resistance and potential contributing factors using simple correlation for a univariate analysis and a logistic regression model for a multivariable analysis. Findings In the univariate analysis, GDP per capita, education, infrastructure, public health-care spending, and antibiotic consumption were all inversely correlated with the two antimicrobial resistance indices, whereas higher temperatures, poorer governance, and the ratio of private to public health expenditure were positively correlated. In the multivariable regression analysis (confined to the 73 countries for which antibiotic consumption data were available) considering the effect of changes in indices on E coli resistance (R2 0·54) and aggregate resistance (R2 0·75), better infrastructure (p=0·014 and p=0·0052) and better governance (p=0·025 and p<0·0001) were associated with lower antimicrobial resistance indices. Antibiotic consumption was not significantly associated with either antimicrobial resistance index in the multivariable analysis (p=0·64 and p=0·070). Interpretation Reduction of antibiotic consumption will not be sufficient to control antimicrobial resistance because contagion—the spread of resistant strains and resistance genes—seems to be the dominant contributing factor. Improving sanitation, increasing access to clean water, and ensuring good governance, as well as increasing public health-care expenditure and better regulating the private health sector are all necessary to reduce global antimicrobial resistance

Seasonal and Temperature-Associated Increases in Gram-Negative Bacterial Bloodstream Infections among Hospitalized Patients

BACKGROUND: Knowledge of seasonal trends in hospital-associated infection incidence may improve surveillance and help guide the design and evaluation of infection prevention interventions. We estimated seasonal variation in the frequencies of inpatient bloodstream infections (BSIs) caused by common bacterial pathogens and examined associations of monthly BSI frequencies with ambient outdoor temperature, precipitation, and humidity levels. METHODS: A database containing blood cultures from 132 U.S. hospitals collected between January 1999 and September 2006 was assembled. The database included monthly counts of inpatient blood cultures positive for several clinically important Gram-negative bacteria (Acinetobacter spp, Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa) and Gram-positive bacteria (Enterococcus spp and Staphylococcus aureus). Monthly mean temperature, total precipitation, and mean relative humidity in the postal ZIP codes of participating hospitals were obtained from national meteorological databases. RESULTS: A total of 211,697 inpatient BSIs were reported during 9,423 hospital-months. Adjusting for long-term trends, BSIs caused by each gram-negative organism examined were more frequent in summer months compared with winter months, with increases ranging from 12.2% for E. coli (95% CI 9.2-15.4) to 51.8% for Acinetobacter (95% CI 41.1-63.2). Summer season was associated with 8.7% fewer Enterococcus BSIs (95% CI 11.0-5.8) and no significant change in S. aureus BSI frequency relative to winter. Independent of season, monthly humidity, monthly precipitation, and long-term trends, each 5.6°C (10°F) rise in mean monthly temperature corresponded to increases in gram-negative bacterial BSI frequencies ranging between 3.5% for E. coli (95% CI 2.1-4.9) to 10.8% for Acinetobacter (95% CI 6.9-14.7). The same rise in mean monthly temperature corresponded to an increase of 2.2% in S. aureus BSI frequency (95% CI 1.3-3.2) but no significant change in Enterococcus BSI frequency. CONCLUSIONS: Summer season and higher mean monthly outdoor temperature are associated with substantially increased frequency of BSIs, particularly among clinically important gram-negative bacteria

Gender Gaps in Cognitive and Noncognitive Skills: Roles of SES and Gender Attitudes

Gender gaps in skills exist around the world but differ remarkably among the high and low-and-middle income countries. This paper uses a unique data set with more than 20,000 adolescents in rural India to examine whether socioeconomic status and gender attitudes predict gender gaps in cognitive and noncognitive skills. We find steep socioeconomic and attitude gradients in both cognitive and noncognitive skills, with bigger effect sizes for the socioeconomic status (SES) gradients. Our results suggest that a sizable improvement in gender attitudes would yield important gains for females, but substantial gains would come only from large improvements in household socioeconomic status. Overall, the household socioeconomic and cultural environment is significantly associated with the gender gaps in both cognitive and noncognitive skills

Health and economic benefits of public financing of epilepsy treatment in India : an agent-based simulation model

OBJECTIVE: An estimated 6-10 million people in India live with active epilepsy, and less than half are treated. We analyze the health and economic benefits of three scenarios of publicly financed national epilepsy programs that provide: (1) first-line antiepilepsy drugs (AEDs), (2) first- and second-line AEDs, and (3) first- and second-line AEDs and surgery. METHODS: We model the prevalence and distribution of epilepsy in India using IndiaSim, an agent-based, simulation model of the Indian population. Agents in the model are disease-free or in one of three disease states: untreated with seizures, treated with seizures, and treated without seizures. Outcome measures include the proportion of the population that has epilepsy and is untreated, disability-adjusted life years (DALYs) averted, and cost per DALY averted. Economic benefit measures estimated include out-of-pocket (OOP) expenditure averted and money-metric value of insurance. RESULTS: All three scenarios represent a cost-effective use of resources and would avert 800,000-1 million DALYs per year in India relative to the current scenario. However, especially in poor regions and populations, scenario 1 (which publicly finances only first-line therapy) does not decrease the OOP expenditure or provide financial risk protection if we include care-seeking costs. The OOP expenditure averted increases from scenarios 1 through 3, and the money-metric value of insurance follows a similar trend between scenarios and typically decreases with wealth. In the first 10 years of scenarios 2 and 3, households avert on average over US$80 million per year in medical expenditure. SIGNIFICANCE: Expanding and publicly financing epilepsy treatment in India averts substantial disease burden. A universal public finance policy that covers only first-line AEDs may not provide significant financial risk protection. Covering costs for both first- and second-line therapy and other medical costs alleviates the financial burden from epilepsy and is cost-effective across wealth quintiles and in all Indian states

Analysis of the universal immunization programme and introduction of a rotavirus vaccine in India with IndiaSim

India has the highest under-five death toll globally, approximately 20% of which is attributed to vaccine-preventable diseases. India's Universal Immunization Programme (UIP) is working both to increase immunization coverage and to introduce new vaccines. Here, we analyze the disease and financial burden alleviated across India's population (by wealth quintile, rural or urban area, and state) through increasing vaccination rates and introducing a rotavirus vaccine. We use IndiaSim, a simulated agent-based model (ABM) of the Indian population (including socio-economic characteristics and immunization status) and the health system to model three interventions. In the first intervention, a rotavirus vaccine is introduced at the current DPT3 immunization coverage level in India. In the second intervention, coverage of three doses of rotavirus and DPT and one dose of the measles vaccine are increased to 90% randomly across the population. In the third, we evaluate an increase in immunization coverage to 90% through targeted increases in rural and urban regions (across all states) that are below that level at baseline. For each intervention, we evaluate the disease and financial burden alleviated, costs incurred, and the cost per disability-adjusted life-year (DALY) averted. Baseline immunization coverage is low and has a large variance across population segments and regions. Targeting specific regions can approximately equate the rural and urban immunization rates. Introducing a rotavirus vaccine at the current DPT3 level (intervention one) averts 34.7 (95% uncertainty range [UR], 31.7–37.7) deaths and $215,569 (95$207,846–$223,292) out-of-pocket (OOP) expenditure per 100,000 under-five children. Increasing all immunization rates to 90$45,914 (95% UR, $37,909–$53,920) OOP expenditure. Scaling up immunization by targeting regions with low coverage (intervention three) averts a slightly higher number of deaths and OOP expenditure. The reduced burden of rotavirus diarrhea is the primary driver of the estimated health and economic benefits in all intervention scenarios. All three interventions are cost saving. Improving immunization coverage and the introduction of a rotavirus vaccine significantly alleviates disease and financial burden in Indian households. Population subgroups or regions with low existing immunization coverage benefit the most from the intervention. Increasing coverage by targeting those subgroups alleviates the burden more than simply increasing coverage in the population at large

Bringing together emerging and endemic zoonoses surveillance: shared challenges and a common solution

Early detection of disease outbreaks in human and animal populations is crucial to the effective surveillance of emerging infectious diseases. However, there are marked geographical disparities in capacity for early detection of outbreaks, which limit the effectiveness of global surveillance strategies. Linking surveillance approaches for emerging and neglected endemic zoonoses, with a renewed focus on existing disease problems in developing countries, has the potential to overcome several limitations and to achieve additional health benefits. Poor reporting is a major constraint to the surveillance of both emerging and endemic zoonoses, and several important barriers to reporting can be identified: (i) a lack of tangible benefits when reports are made; (ii) a lack of capacity to enforce regulations; (iii) poor communication among communities, institutions and sectors; and (iv) complexities of the international regulatory environment. Redirecting surveillance efforts to focus on endemic zoonoses in developing countries offers a pragmatic approach that overcomes some of these barriers and provides support in regions where surveillance capacity is currently weakest. In addition, this approach addresses immediate health and development problems, and provides an equitable and sustainable mechanism for building the culture of surveillance and the core capacities that are needed for all zoonotic pathogens, including emerging disease threats

Estimating the effect of vaccination on antimicrobial-resistant typhoid fever in 73 countries supported by Gavi: a mathematical modelling study

BACKGROUND: Multidrug resistance and fluoroquinolone non-susceptibility (FQNS) are major concerns for the epidemiology and treatment of typhoid fever. The 2018 prequalification of the first typhoid conjugate vaccine (TCV) by WHO provides an opportunity to limit the transmission and burden of antimicrobial-resistant typhoid fever. METHODS: We combined output from mathematical models of typhoid transmission with estimates of antimicrobial resistance from meta-analyses to predict the burden of antimicrobial-resistant typhoid fever across 73 lower-income countries eligible for support from Gavi, the Vaccine Alliance. We considered FQNS and multidrug resistance separately. The effect of vaccination was predicted on the basis of forecasts of vaccine coverage. We explored how the potential effect of vaccination on the prevalence of antimicrobial resistance varied depending on key model parameters. FINDINGS: The introduction of routine immunisation with TCV at age 9 months with a catch-up campaign up to age 15 years was predicted to avert 46-74% of all typhoid fever cases in 73 countries eligible for Gavi support. Vaccination was predicted to reduce the relative prevalence of antimicrobial-resistant typhoid fever by 16% (95% prediction interval [PI] 0-49). TCV introduction with a catch-up campaign was predicted to avert 42.5 million (95% PI 24.8-62.8 million) cases and 506 000 (95% PI 187 000-1.9 million) deaths caused by FQNS typhoid fever, and 21.2 million (95% PI 16.4-26.5 million) cases and 342 000 (95% PI 135 000-1.5 million) deaths from multidrug-resistant typhoid fever over 10 years following introduction. INTERPRETATION: Our results indicate the benefits of prioritising TCV introduction for countries with a high avertable burden of antimicrobial-resistant typhoid fever. FUNDING: The Bill & Melinda Gates Foundation