Public Health Policy Decisions Research Articles

Improving the measurement of the Korean emergency medical System's spatial accessibility

Measuring spatial accessibility for healthcare service is an important prerequisite for public health policy decision. While existing literature offers spatial accessibility measures, applying those measures to healthcare services reveals some weaknesses for improvement. In this study, we propose an improved accessibility measure. The proposed measure is based on the floating catchment area method but improved in some aspects. We use two distance decay functions to distinguish their respective effects in measuring accessibility. A local distance decay function, expressed as a logistic cumulative density function, accounts for region-specific patient visit patterns. A global distance decay function, also defined as a logistic density function, incorporates patients’ inherent resistance to travel in the measure. To address the problem of potential demand estimation, which distorts the resulting accessibility values, we introduce effective potential demand which is defined as the ratio of potential demand to total nearby capacity by care providers as an adjustment factor. To examine the effectiveness, we apply the measure to identify the medically underserved areas in Korea for emergency medical services. Compared with the existing floating catchment area measure, the proposed measure provides more proper spatial accessibility information.

Systems Thinking as a Framework for Analyzing Commercial Determinants of Health.

Policy Points: Worldwide, more than 70% of all deaths are attributable to noncommunicable diseases (NCDs), nearly half of which are premature and apply to individuals of working age. Although such deaths are largely preventable, effective solutions continue to elude the public health community.One reason is the considerable influence of the “commercial determinants of health”: NCDs are the product of a system that includes powerful corporate actors, who are often involved in public health policymaking.This article shows how a complex systems perspective may be used to analyze the commercial determinants of NCDs, and it explains how this can help with (1) conceptualizing the problem of NCDs and (2) developing effective policy interventions. ContextThe high burden of noncommunicable diseases (NCDs) is politically salient and eminently preventable. However, effective solutions largely continue to elude the public health community. Two pressing issues heighten this challenge: the first is the public health community's narrow approach to addressing NCDs, and the second is the involvement of corporate actors in policymaking. While NCDs are often conceptualized in terms of individual‐level risk factors, we argue that they should be reframed as products of a complex system. This article explores the value of a systems approach to understanding NCDs as an emergent property of a complex system, with a focus on commercial actors.MethodsDrawing on Donella Meadows's systems thinking framework, this article examines how a systems perspective may be used to analyze the commercial determinants of NCDs and, specifically, how unhealthy commodity industries influence public health policy.FindingsUnhealthy commodity industries actively design and shape the NCD policy system, intervene at different levels of the system to gain agency over policy and politics, and legitimize their presence in public health policy decisions.ConclusionsIt should be possible to apply the principles of systems thinking to other complex public health issues, not just NCDs. Such an approach should be tested and refined for other complex public health challenges.

Cost-Effectiveness of Interventions to Prevent and Manage Diabetes—A Systematic Review and Update

Many interventions are available for preventing type 2 diabetes (DM) and managing DM, but their cost-effectiveness (CE) varies greatly. Previously, we conducted a systematic cost-effectiveness (CE) review of all DM interventions covering studies between 1985 and 2007. Here, we update the study for Jan 20to July 2017. We used the same search strategies (databases, MeSH terms and keywords, exclusion criteria and study quality assessment tool) to select studies. We grouped interventions by CE ratios (CER) in cost per quality-adjusted life years (QALY) or life year gained (LYG)—cost saving (CER ≤ 0); very cost-effective (0 < CER ≤ $25,000); cost-effective ($25,000 < CER ≤ $50,000); marginally cost-effective ($50,000 < ICER ≤ $100,000); or not cost-effective (>$100,000)—and whether evidence was strong, supportive, or uncertain. We used the median CER to represent the CE of an intervention if multiple evaluations exist. Costs and CER were expressed as 2015 U.S. dollars. The initial search yielded 18,195 titles; 46 prevention and 110 management papers were included in the review. Interventions that were cost-saving or very cost-effective with strong evidence included: for preventing type 2 DM, 1) imposing taxes on sweetened beverages and 2) structured lifestyle intervention and metformin in people at high risk; for management of DM and its complications, 1) ACE inhibitor therapy for intensive hypertension (HTN) control, 2) self-monitoring of blood glucose, 3) comprehensive foot care to prevent ulcers, 4) multi-component coordinated care with peer support for managing HTN, hyperglycemia, hyperlipidemia, and chronic kidney disease, and early detection of DM complications. The CERs of other interventions ranged from $30,000 to $4,817,000 per QALY or <$25,000 per QALY with a high degree of uncertainty. Our results provide critical information for making evidence-based clinical and public health policy decisions. Disclosure K.R. Siegel: None. X. Zhou: None. B. Ng: None. S. Jawanda: None. K. Proia: None. X. Zhang: None. P. Zhang: None.

Prescription opioid dispensing in New South Wales, Australia: spatial and temporal variation

BackgroundPatterns of opioid dispensing often exhibit substantial temporal and geographical variability, which has implications for public health policy decisions and interventions. The study examined recent trends in prescription opioid dispensing and identified high dispensing areas and factors associated with the doses dispensed.MethodsThree years (1 January 2013–31 December 2015) of dispensing data of prescription opioids in local government areas (LGAs) for New South Wales (NSW), Australia’s most populous state, were analyzed. The proportion of individuals who were dispensed opioids was computed for four age-groups. A Chi-square test was used to examine trends over time in proportions of the population who were dispensed opioids in four age-groups. The number of prescriptions over time and quantities in daily defined dose/1000 people/day (denoted DDD) were also examined. LGAs with relatively high levels of dispensing were identified and mapped. A multivariate regression model was used to identify factors associated with DDD.ResultsOverall, codeine, oxycodone and tramadol were the main opioids in terms of DDD, number of prescriptions and number of individuals who were dispensed these medications. Quantity (in DDD), and population dispensed to were consistently higher for women than men over time. Proportions of individuals who were dispensed opioids increased significantly over time in all four age-groups. In the multivariate model, age, urbanization, sex and socio-economic indexes for areas were significantly associated with doses dispensed among opioid users. All areas with very high dispensing were outside major metropolitan areas.ConclusionsGiven that over-use of opioids is a major public health problem and that long-term use has substantial side effects including dependence, it is important to understand spatial patterns of opioid prescribing to enable targeted interventions. Nationwide implementation of real-time drug-monitoring programs and access to monitoring databases from both doctor and pharmacy point-of-care sources may potentially reduce excessive and undue use of opioid.

Light me up: power and expertise in risk communication and policy-making in the e-cigarette health debates

This paper presents a detailed account of policy-making in a contemporary risk communication arena, where strong power dynamics are at play that have hitherto lacked theoretical analysis and empirical validation. Specifically, it expands on the understanding of how public health policy decisions are made when there is a weak evidential base and where multiple interpretations, power dynamics and values are brought to bear on issues of risk and uncertainty. The aim of the paper is to understand the role that power and expertise play in shaping public health risk communication within policy-related debates. By drawing on insight from a range of literatures, the paper argues that there several interacting factors that shape how a particular narrative gains prominence within a wider set of perspectives and how the arguments and findings associated with that perspective become amplified within the context of policy choices. These findings are conceptualised into a new model – a policy evaluation risk communication (PERC) framework – and are then tested using the Electronic cigarette debate as a case study.

Evaluating oral flavorant effects on nicotine self-administration behavior and phasic dopamine signaling

Understanding how tobacco product flavor additives, such as flavorants in electronic cigarettes, influence smoking behavior and addiction is critical for informing public health policy decisions regarding tobacco product regulation. Here, we developed a combined intraoral (i.o.) and intravenous (i.v.) self-administration paradigm in rats to determine how flavorants influence self-administration behavior. By combining i.o. flavorant delivery with fast scan cyclic voltammetry (FSCV) or i.v. nicotine self-administration in adult, male rats, we examined whether flavors alter phasic dopamine (DA) signaling and nicotine self-administration. Oral administration of 10% sucrose or 0.32% saccharin, but not 0.005% menthol, increased phasic DA release in the nucleus accumbens (NAc). Oral sucrose or saccharin, when combined with i.v. nicotine delivery, also led to increased self-administration behavior. Specifically, combined i.o. sucrose and i.v. nicotine decreased responding compared to sucrose alone, and increased responding compared to nicotine alone. In contrast, i.o. flavorants did not alter motivational breakpoint in a progressive ratio task. Oral menthol, which did not alter i.v. nicotine administration, reversed oral nicotine aversion (50 and 100 mg/L) in a two-bottle choice test. Here, we demonstrate that i.o. appetitive flavorants that increase phasic DA signaling also increase self-administration behavior when combined with i.v. nicotine delivery. Additionally, oral menthol effects were specific to oral nicotine, and were not observed with i.v. nicotine-mediated reinforcement. Together, these preclinical findings have important implications regarding menthol and sweet flavorant additive effects on tobacco product use and can be used to inform policy decisions on tobacco product flavorant regulation.

Smoothed Temporal Atlases of Age-Gender All-Cause Mortality in South Africa.

Most mortality maps in South Africa and most contried of the sub-Saharan region are static, showing aggregated count data over years or at specific years. Lack of space and temporral dynamanics in these maps may adversely impact on their use and application for vigorous public health policy decisions and interventions. This study aims at describing and modeling sub-national distributions of age–gender specific all-cause mortality and their temporal evolutions from 1997 to 2013 in South Africa. Mortality information that included year, age, gender, and municipality administrative division were obtained from Statistics South Africa for the period. Individual mortality level data were grouped by three ages groups (0–14, 15–64, and 65 and over) and gender (male, female) and aggregated at each of the 234 municipalities in the country. The six age-gender all-cause mortality rates may be related due to shared common social deprivation, health and demographic risk factors. We undertake a joint analysis of the spatial-temporal variation of the six age-gender mortality risks. This is done within a shared component spatial model construction where age-gender common and specific spatial and temporal trends are estiamted using a hierarchical Bayesian spatial model. The results show municipal and temporal differentials in mortality risk profiles between age and gender groupings. High rates were seen in 2005, especially for the 15–64 years age group for both males and females. The dynamic geographical and time distributions of subnational age-gender all-cause mortality contribute to a better understanding of the temporal evolvement and geographical variations in the relationship between demographic composition and burden of diseases in South Africa. This provides useful information for effective monitoring and evaluation of public health policies and programmes targeting mortality reduction across time and sub-populations in the country.

Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage

Objectives: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a defence against pandemic influenza is a significant public health policy decision that must be made despite a lack of conclusive evidence from randomised controlled trials regarding the effectiveness of NAIs on important clinical end points such as mortality. The objective of this study was to determine whether NAIs should be stockpiled for treatment of pandemic influenza on the basis of current evidence. Methods: A decision model for stockpiling was designed. Data on previous pandemic influenza epidemiology was combined with data on the effectiveness of NAIs in reducing mortality obtained from a recent individual participant meta-analysis using observational data. Evidence synthesis techniques and a bias modelling method for observational data were used to incorporate the evidence into the model. The stockpiling decision was modelled for adults (≥16 years old) and the United Kingdom was used as an example. The main outcome was the expected net benefits of stockpiling in monetary terms. Health benefits were estimated from deaths averted through stockpiling. Results: After adjusting for biases in the estimated effectiveness of NAIs, the expected net benefit of stockpiling in the baseline analysis was £444 million, assuming a willingness to pay of £20,000/QALY ($31,000/QALY). The decision would therefore be to stockpile NAIs. There was a greater probability that the stockpile would not be utilised than utilised. However, the rare but catastrophic losses from a severe pandemic justified the decision to stockpile. Conclusions: Taking into account the available epidemiological data and evidence of effectiveness of NAIs in reducing mortality, including potential biases, a decision maker should stockpile anti-influenza medication in keeping with the postulated decision rule.

Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage

Objectives: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a defence against pandemic influenza is a significant public health policy decision that must be made despite a lack of conclusive evidence from randomised controlled trials regarding the effectiveness of NAIs on important clinical end points such as mortality. The objective of this study was to determine whether NAIs should be stockpiled for treatment of pandemic influenza on the basis of current evidence. Methods: A decision model for stockpiling was designed. Data on previous pandemic influenza epidemiology was combined with data on the effectiveness of NAIs in reducing mortality obtained from a recent individual participant meta-analysis using observational data. Evidence synthesis techniques and a bias modelling method for observational data were used to incorporate the evidence into the model. The stockpiling decision was modelled for adults (≥16 years old) and the United Kingdom was used as an example. The main outcome was the expected net benefits of stockpiling in monetary terms. Health benefits were estimated from deaths averted through stockpiling. Results: After adjusting for biases in the estimated effectiveness of NAIs, the expected net benefit of stockpiling in the baseline analysis was £444 million, assuming a willingness to pay of £20,000/QALY ($31,000/QALY). The decision would therefore be to stockpile NAIs. There was a greater probability that the stockpile would not be utilised than utilised. However, the rare but catastrophic losses from a severe pandemic justified the decision to stockpile. Conclusions: Taking into account the available epidemiological data and evidence of effectiveness of NAIs in reducing mortality, including potential biases, a decision maker should stockpile anti-influenza medication in keeping with the postulated decision rule.

Climate Change Influences Potential Distribution of Infected Aedes aegypti Co-Occurrence with Dengue Epidemics Risk Areas in Tanzania.

BackgroundDengue is the second most important vector-borne disease of humans globally after malaria. Incidence of dengue infections has dramatically increased recently, potentially due to changing climate. Climate projections models predict increases in average annual temperature, precipitation and extreme events in the future. The objective of this study was to assess the effect of changing climate on distribution of dengue vectors in relation to epidemic risk areas in Tanzania.Methods/FindingsWe used ecological niche models that incorporated presence-only infected Aedes aegypti data co-occurrence with dengue virus to estimate potential distribution of epidemic risk areas. Model input data on infected Ae. aegypti was collected during the May to June 2014 epidemic in Dar es Salaam. Bioclimatic predictors for current and future projections were also used as model inputs. Model predictions indicated that habitat suitability for infected Ae. aegypti co-occurrence with dengue virus in current scenarios is highly localized in the coastal areas, including Dar es Salaam, Pwani, Morogoro, Tanga and Zanzibar. Models indicate that areas of Kigoma, Ruvuma, Lindi, and those around Lake Victoria are also at risk. Projecting to 2020, we show that risk emerges in Mara, Arusha, Kagera and Manyara regions, but disappears in parts of Morogoro, Ruvuma and near Lake Nyasa. In 2050 climate scenario, the predicted habitat suitability of infected Ae. aegypti co-occurrence with dengue shifted towards the central and north-eastern parts with intensification in areas around all major lakes. Generally, model findings indicated that the coastal regions would remain at high risk for dengue epidemic through 2050.Conclusion/SignificanceModels incorporating climate change scenarios to predict emerging risk areas for dengue epidemics in Tanzania show that the anticipated risk is immense and results help guiding public health policy decisions on surveillance and control of dengue epidemics. A collaborative approach is recommended to develop and adapt control and prevention strategies.

Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage.

Objectives: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a defence against pandemic influenza is a significant public health policy decision that must be made despite a lack of conclusive evidence from randomised controlled trials regarding the effectiveness of NAIs on important clinical end points such as mortality. The objective of this study was to determine whether NAIs should be stockpiled for treatment of pandemic influenza on the basis of current evidence. Methods: A decision model for stockpiling was designed. Data on previous pandemic influenza epidemiology was combined with data on the effectiveness of NAIs in reducing mortality obtained from a recent individual participant meta-analysis using observational data. Evidence synthesis techniques and a bias modelling method for observational data were used to incorporate the evidence into the model. The stockpiling decision was modelled for adults (≥16 years old) and the United Kingdom was used as an example. The main outcome was the expected net benefits of stockpiling in monetary terms. Health benefits were estimated from deaths averted through stockpiling. Results: After adjusting for biases in the estimated effectiveness of NAIs, the expected net benefit of stockpiling in the baseline analysis was £444 million, assuming a willingness to pay of £20,000/QALY ($31,000/QALY). The decision would therefore be to stockpile NAIs. There was a greater probability that the stockpile would not be utilised than utilised. However, the rare but catastrophic losses from a severe pandemic justified the decision to stockpile. Conclusions: Taking into account the available epidemiological data and evidence of effectiveness of NAIs in reducing mortality, including potential biases, a decision maker should stockpile anti-influenza medication in keeping with the postulated decision rule.

Achieving population-level violence declines: implications of the international crime drop for prevention programming.

The Sustainable Development Goals (SDGs) adopted by the United Nations for the period 2016-2030 aim to achieve a substantial reduction of interpersonal violence. An increasing body of evidence of what works, emerging from randomized controlled trials, can inform public health policy decisions. However, there is very limited evidence on the kinds of mechanisms that lead to sustained declines in interpersonal violence at the population level. We discuss the implications of what is known about recent major declines in violence to guide violence-reduction policies.

Prevalence of Hepatitis B Virus Infection in Kenya, 2007.

Current estimates put the prevalence of hepatitis B virus (HBV) infection in Kenya at 5-8%. We determined the HBV infection prevalence in the human immunodeficiency virus (HIV)-negative Kenyan adult and adolescent population based on samples collected from a national survey. We analyzed data from HIV-negative participants in the 2007 Kenya AIDS Indicator Survey to estimate the HBV infection prevalence. We defined past or present HBV infection as presence of total hepatitis B core antibody (HBcAb), and chronic HBV infection (CHBI) as presence of both total HBcAb and hepatitis B surface antigen (HBsAg). We calculated crude and adjusted odds of HBV infection by demographic characteristics and risk factors using logistic regression analyses. Of 1,091 participants aged 15-64 years, approximately 31.5% (95% confidence interval [CI] = 28.0-35.3%) had exposure to HBV, corresponding to approximately 6.1 million (CI = 5.4-6.8 million) with past or present HBV infection. The estimated prevalence of CHBI was 2.1% (95% CI = 1.4-3.1%), corresponding to approximately 398,000 (CI = 261,000-602,000) with CHBI. CHBI is a major public health problem in Kenya, affecting approximately 400,000 persons. Knowing the HBV infection prevalence at baseline is important for planning and public health policy decision making and for monitoring the impact of viral hepatitis prevention programs.

Disease Burden of 32 Infectious Diseases in the Netherlands, 2007-2011.

BackgroundInfectious disease burden estimates provided by a composite health measure give a balanced view of the true impact of a disease on a population, allowing the relative impact of diseases that differ in severity and mortality to be monitored over time. This article presents the first national disease burden estimates for a comprehensive set of 32 infectious diseases in the Netherlands.Methods and FindingsThe average annual disease burden was computed for the period 2007–2011 for selected infectious diseases in the Netherlands using the disability-adjusted life years (DALY) measure. The pathogen- and incidence-based approach was adopted to quantify the burden due to both morbidity and premature mortality associated with all short and long-term consequences of infection. Natural history models, disease progression probabilities, disability weights, and other parameters were adapted from previous research. Annual incidence was obtained from statutory notification and other surveillance systems, which was corrected for under-ascertainment and under-reporting. The highest average annual disease burden was estimated for invasive pneumococcal disease (9444 DALYs/year; 95% uncertainty interval [UI]: 8911–9961) and influenza (8670 DALYs/year; 95% UI: 8468–8874), which represents 16% and 15% of the total burden of all 32 diseases, respectively. The remaining 30 diseases ranked by number of DALYs/year from high to low were: HIV infection, legionellosis, toxoplasmosis, chlamydia, campylobacteriosis, pertussis, tuberculosis, hepatitis C infection, Q fever, norovirus infection, salmonellosis, gonorrhoea, invasive meningococcal disease, hepatitis B infection, invasive Haemophilus influenzae infection, shigellosis, listeriosis, giardiasis, hepatitis A infection, infection with STEC O157, measles, cryptosporidiosis, syphilis, rabies, variant Creutzfeldt-Jakob disease, tetanus, mumps, rubella, diphtheria, and poliomyelitis. The very low burden for the latter five diseases can be attributed to the National Immunisation Programme. The average disease burden per individual varied from 0.2 (95% UI: 0.1–0.4) DALYs per 100 infections for giardiasis, to 5081 and 3581 (95% UI: 3540–3611) DALYs per 100 infections for rabies and variant Creutzfeldt-Jakob disease, respectively.ConclusionsFor guiding and supporting public health policy decisions regarding the prioritisation of interventions and preventive measures, estimates of disease burden and the comparison of burden between diseases can be informative. Although the collection of disease-specific parameters and estimation of incidence is a process subject to continuous improvement, the current study established a baseline for assessing the impact of future public health initiatives.

Mercury bioaccumulation in an estuarine predator: Biotic factors, abiotic factors, and assessments of fish health

Estuarine wetlands are major contributors to mercury (Hg) transformation into its more toxic form, methylmercury (MeHg). Although these complex habitats are important, estuarine Hg bioaccumulation is not well understood. The longnose gar Lepisosteus osseus (L. 1758), an estuarine predator in the eastern United States, was selected to examine Hg processes due to its abundance, estuarine residence, and top predator status. This study examined variability in Hg concentrations within longnose gar muscle tissue spatially and temporally, the influence of biological factors, potential maternal transfer, and potential negative health effects on these fish. Smaller, immature fish had the highest Hg concentrations and were predominantly located in low salinity waters. Sex and diet were also important factors and Hg levels peaked in the spring. Although maternal transfer occurred in small amounts, the potential negative health effects to young gar remain unknown. Fish health as measured by fecundity and growth rate appeared to be relatively unaffected by Hg at concentrations in the present study (less than 1.3 ppm wet weight). The analysis of biotic and abiotic factors relative to tissue Hg concentrations in a single estuarine fish species provided valuable insight in Hg bioaccumulation, biomagnification, and elimination. Insights such as these can improve public health policy and environmental management decisions related to Hg pollution.

Burden of type 2 diabetes in Mexico: past, current and future prevalence and incidence rates

IntroductionMexico diabetes prevalence has increased dramatically in recent years. However, no national incidence estimates exist, hampering the assessment of diabetes trends and precluding the development of burden of disease analyses to inform public health policy decision-making. Here we provide evidence regarding current magnitude of diabetes in Mexico and its future trends. MethodsWe used data from the Mexico National Health and Nutrition Survey, and age-period-cohort models to estimate prevalence and incidence of self-reported diagnosed diabetes by age, sex, calendar-year (1960–2012), and birth-cohort (1920–1980). We project future rates under three alternative incidence scenarios using demographic projections of the Mexican population from 2010–2050 and a Multi-cohort Diabetes Markov Model. ResultsAdult (ages 20+) diagnosed diabetes prevalence in Mexico increased from 7% to 8.9% from 2006 to 2012. Diabetes prevalence increases with age, peaking around ages 65–68 to then decrease. Age-specific incidence follows similar patterns, but peaks around ages 57–59. We estimate that diagnosed diabetes incidence increased exponentially during 1960–2012, roughly doubling every 10years. Projected rates under three age-specific incidence scenarios suggest diabetes prevalence among adults (ages 20+) may reach 13.7–22.5% by 2050, affecting 15–25 million individuals, with a lifetime risk of 1 in 3 to 1 in 2. ConclusionsDiabetes prevalence in Mexico will continue to increase even if current incidence rates remain unchanged. Continued implementation of policies to reduce obesity rates, increase physical activity, and improve population diet, in tandem with diabetes surveillance and other risk control measures is paramount to substantially reduce the burden of diabetes in Mexico.

Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making

SUMMARYThe dominant approach to decision-making in public health policy for infectious diseases relies heavily on expert opinion, which often applies empirical evidence to policy questions in a manner that is neither systematic nor transparent. Although systematic reviews are frequently commissioned to inform specific components of policy (such as efficacy), the same process is rarely applied to the full decision-making process. Mathematical models provide a mechanism through which empirical evidence can be methodically and transparently integrated to address such questions. However, such models are often considered difficult to interpret. In addition, models provide estimates that need to be iteratively reevaluated as new data or considerations arise. Using the case study of a novel diagnostic for tuberculosis, a framework for improved collaboration between public health decision-makers and mathematical modellers that could lead to more transparent and evidence-driven policy decisions for infectious diseases in the future is proposed. The framework proposes that policymakers should establish long-term collaborations with modellers to address key questions, and that modellers should strive to provide clear explanations of the uncertainty of model structure and outputs. Doing so will improve the applicability of models and clarify their limitations when used to inform real-world public health policy decisions.

The cost of acute respiratory infections in Northern India: a multi-site study.

BackgroundDespite the high mortality and morbidity resulting from acute respiratory infections (ARI) globally, there are few data from low-income countries on costs of ARI to inform public health policy decisions We conducted a prospective survey to assess costs of ARI episodes in selected primary, secondary, and tertiary healthcare facilities in north India where no respiratory pathogen vaccine is routinely recommended.MethodsFace-to-face interviews were conducted among a purposive sample of patients with ARI from healthcare facilities. Data were collected on out-of-pocket costs of hospitalization, medical consultations, medications, diagnostics, transportation, lodging, and missed work days. Telephone surveys were conducted two weeks after medical encounters to ask about subsequent missed work and costs incurred. Costs of prescriptions and diagnostics in public facilities were supplemented with WHO-CHOICE estimates of hospital bed costs. Missed work days were assigned cost based on the national annual per capita income (US$1,104). Non-medically attended ARI cases were identified from an ongoing community-based ARI surveillance project in Faridabad.ResultsDuring September 2012-March 2013, 1766 patients with ARI were enrolled, including 451 hospitalized patients, 1056 outpatients, and 259 non-medically attended patients. The total direct cost of an ARI episode requiring outpatient care was US$4- $6 for public and $3-$10 for private institutions based on age groups. The total direct cost of an ARI episode requiring hospitalized care was $54-$120 in public and $135-$355 in private institutions. The cost of ARI among those hospitalized was highest among persons aged > = 65 years and lowest among children aged < 5 years. Indirect costs due to missed work days were 16-25% of total costs. The direct out-of-pocket cost of hospitalized ARI was 34% of annual per capita income.ConclusionsThe cost of hospitalized ARI episodes in India is high relative to median per capita income. Data from this study can inform evaluations of the cost effectiveness of proven ARI prevention strategies such as vaccination.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-1685-6) contains supplementary material, which is available to authorized users.

Stakeholder engagement in policy development: challenges and opportunities for human genomics.

Along with rapid advances in human genomics, policies governing genomic data and clinical technologies have proliferated. Stakeholder engagement is widely lauded as an important methodology for improving clinical, scientific, and public health policy decision making. The purpose of this paper is to examine how stakeholder engagement is used to develop policies in genomics research and public health areas, as well as to identify future priorities for conducting evidence-based stakeholder engagements. We focus on exemplars in biobanking and newborn screening to illustrate a variety of current stakeholder engagement in policy-making efforts. Each setting provides an important context for examining the methods of obtaining and integrating informed stakeholder voices into the policy-making process. While many organizations have an interest in engaging stakeholders with regard to genomic policy issues, there is broad divergence with respect to the stakeholders involved, the purpose of engagements, when stakeholders are engaged during policy development, methods of engagement, and the outcomes reported. Stakeholder engagement in genomics policy development is still at a nascent stage. Several challenges of using stakeholder engagement as a tool for genomics policy development remain, and little evidence regarding how to best incorporate stakeholder feedback into policy-making processes is currently available.

Short Communication on “MATS: Global Coverage Estimates for 4CMenB, a Novel Multicomponent Meningococcal B Vaccine”

Meningococcal antigen typing system (MATS) - the golden standard in many reference labs worldwide–for rapid, reproducible and accurate (conservative nonetheless) prediction of Bexsero strain coverage, can pave the way towards a data-driven decision making of national immunization technical advisory groups (NITAGs), allowing indirect comparison of immunization policies across countries and regions leading to rapid adaptation of public health policy decisions based on worldwide datasets. Нe recent milestone of the UK national infant routine recommendation and reimbursement, paves the way for other nations to follow, bringing closer the pediatric community to the vision of a meningitis free world.