The Effect of Incomplete Death Certificates on Estimates of Unintentional Opioid-Related Overdose Deaths in the United States, 1999-2015.

OBJECTIVES: A complete and accurate count of the number of opioid-related overdose deaths is essential to properly allocate resources. We determined the rate of unintentional overdose deaths (non-opioid-related, opioid-related, or unspecified) in the United States and by state from 1999 to 2015 and the possible effects of underreporting on national estimates of opioid abuse. METHODS: We abstracted unintentional drug overdose deaths ( International Classification of Diseases, 10th Revision, codes X40-X44) with contributory drug-specific T codes (T36.0-T50.9) from the Mortality Multiple Cause Micro-Data Files. We assumed that the proportion of unspecified overdose deaths that might be attributed to opioids would be the same as the proportion of opioid-related overdose deaths among all overdose deaths and calculated the number of deaths that could be reallocated as opioid-related for each state and year. We then added these reallocated deaths to the reported deaths to determine their potential effect on total opioid-related deaths. RESULTS: From 1999 to 2015, a total of 438 607 people died from unintentional drug overdoses. Opioid-related overdose deaths rose 401% (from 5868 to 29 383), non-opioid-related overdose deaths rose 150% (from 3005 to 7505), and unspecified overdose deaths rose 220% (from 2255 to 29 383). In 5 states (Alabama, Indiana, Louisiana, Mississippi, and Pennsylvania), more than 35% of unintentional overdose deaths were coded as unspecified. Our reallocation resulted in classifying more than 70 000 unspecified overdose deaths as potential additional opioid-related overdose deaths. CONCLUSIONS: States may be greatly underestimating the effect of opioid-related overdose deaths because of incomplete cause-of-death reporting, indicating that the current opioid overdose epidemic may be worse than it appears.

Improvement in racial disparities in years of life lost in the USA since 1990.

OBJECTIVE: To examine changes in cause-specific Years of Life Lost (YLL) by age, race, and sex group in the USA from 1990 to 2014. METHODS: 60 million death reports from the National Center for Health Statistics (NCHS) were categorized by age group, sex, race, and cause of death. YLL were calculated using age-specific life expectancies. Age groups were: infants <1, children 1-19, adults 20-64, and older adults 65+. RESULTS: Blacks have historically experienced more years of life lost than whites or other racial groups in the USA. In the year 1990 the YLL per 100,000 population was 21,103 for blacks, 14,160 for whites, and 7,417 for others. Between 1990 and 2014 overall YLL in the USA improved by 10%, but with marked variations in the rate of change across age, race, and sex groups. Blacks (all ages, both sexes) showed substantial improvement with a 28% reduction in YLL, compared to whites (all ages, both sexes) who showed a 4% reduction. Among blacks, improvements were seen in all age groups: reductions of 43%, 48%, 28%, and 25% among infants, children, adults, and older adults, respectively. Among whites, reductions of 33%, 44%, and 18% were seen in infants, children, and older adults, but there was a 6% increase in YLL among white adults. YLL increased by 18% in white adult females and declined 1% in white adult males. American Indian/Alaska Native women also had worsening in YLL, with an 8% increase. Asian Pacific Islanders consistently had the lowest YLL across all ages. Whites had a higher proportion of YLL due to overdose; blacks had a higher proportion due to homicide at younger ages and to heart disease at older ages. CONCLUSIONS: Race-based disparities in YLL in the USA since 1990 have narrowed considerably, largely as a result of improvements among blacks compared to whites. Adult white and American Indian / Alaskan Native females have experienced worsening YLL, while white males have experienced essentially no change. If recent trajectories continue, adult black/white disparities in YLL will continue to narrow.

Assessment of serosurveys for H5N1.

BACKGROUND: It has been suggested that the true case-fatality rate of human H5N1 influenza infection is appreciably less than the figure of approximately 60% that is based on official World Health Organization (WHO)-confirmed case reports because asymptomatic cases may have been missed. A number of seroepidemiologic studies have been conducted in an attempt to identify such missed cases. METHODS: We conducted a comprehensive literature review of all English-language H5N1 human serology surveys with detailed attention to laboratory methodology used (including whether investigators used criteria set by the WHO to define positive cases), laboratory controls used, and the clades/genotypes involved. RESULTS: Twenty-nine studies were included in the analysis. Few reported using unexposed control groups and one-third did not apply WHO criteria. Of studies that used WHO criteria, only 4 found any seropositive results to clades/genotypes of H5N1 that are currently circulating. No studies reported seropositive results to the clade 2/genotype Z viruses that have spread throughout Eurasia and Africa. CONCLUSIONS: This review suggests that the frequency of positive H5 serology results is likely to be low; therefore, it is essential that future studies adhere to WHO criteria and include unexposed controls in their laboratory assays to limit the likelihood of false-positive results.

A game dynamic model for vaccine skeptics and vaccine believers: measles as an example.

Widespread avoidance of Measles-Mumps-Rubella vaccination (MMR), with a consequent increase in the incidence of major measles outbreaks, demonstrates that the effectiveness of vaccination programs can be thwarted by the public misperceptions of vaccine risk. By coupling game theory and epidemic models, we examine vaccination choice among populations stratified into two behavioral groups: vaccine skeptics and vaccine believers. The two behavioral groups are assumed to be heterogeneous with respect to their perceptions of vaccine and infection risks. We demonstrate that the pursuit of self-interest among vaccine skeptics often leads to vaccination levels that are suboptimal for a population, even if complete coverage is achieved among vaccine believers. The demand for measles vaccine across populations driven by individual self-interest was found to be more sensitive to the proportion of vaccine skeptics than to the extent to which vaccine skeptics misperceive the risk of vaccine. Furthermore, as the number of vaccine skeptics increases, the probability of infection among vaccine skeptics increases initially, but it decreases once the vaccine skeptics begin receiving the vaccination, if both behavioral groups are vaccinated according to individual self-interest. Our results show that the discrepancy between the coverages of measles vaccine that are driven by self-interest and those driven by population interest becomes larger when the cost of vaccination increases. This research illustrates the importance of public education on vaccine safety and infection risk in order to maintain vaccination levels that are sufficient to maintain herd immunity.

Impact of changing the measles vaccine vial size on Niger's vaccine supply chain: a computational model.

BACKGROUND: Many countries, such as Niger, are considering changing their vaccine vial size presentation and may want to evaluate the subsequent impact on their supply chains, the series of steps required to get vaccines from their manufacturers to patients. The measles vaccine is particularly important in Niger, a country prone to measles outbreaks. METHODS: We developed a detailed discrete event simulation model of the vaccine supply chain representing every vaccine, storage location, refrigerator, freezer, and transport device (e.g., cold trucks, 4 × 4 trucks, and vaccine carriers) in the Niger Expanded Programme on Immunization (EPI). Experiments simulated the impact of replacing the 10-dose measles vial size with 5-dose, 2-dose and 1-dose vial sizes. RESULTS: Switching from the 10-dose to the 5-dose, 2-dose and 1-dose vial sizes decreased the average availability of EPI vaccines for arriving patients from 83% to 82%, 81% and 78%, respectively for a 100% target population size. The switches also changed transport vehicle's utilization from a mean of 58% (range: 4-164%) to means of 59% (range: 4-164%), 62% (range: 4-175%), and 67% (range: 5-192%), respectively, between the regional and district stores, and from a mean of 160% (range: 83-300%) to means of 161% (range: 82-322%), 175% (range: 78-344%), and 198% (range: 88-402%), respectively, between the district to integrated health centres (IHC). The switch also changed district level storage utilization from a mean of 65% to means of 64%, 66% and 68% (range for all scenarios: 3-100%). Finally, accounting for vaccine administration, wastage, and disposal, replacing the 10-dose vial with the 5 or 1-dose vials would increase the cost per immunized patient from $0.47US to $0.71US and $1.26US, respectively. CONCLUSIONS: The switch from the 10-dose measles vaccines to smaller vial sizes could overwhelm the capacities of many storage facilities and transport vehicles as well as increase the cost per vaccinated child.

Would school closure for the 2009 H1N1 influenza epidemic have been worth the cost?: a computational simulation of Pennsylvania.

BACKGROUND: During the 2009 H1N1 influenza epidemic, policy makers debated over whether, when, and how long to close schools. While closing schools could have reduced influenza transmission thereby preventing cases, deaths, and health care costs, it may also have incurred substantial costs from increased childcare needs and lost productivity by teachers and other school employees. METHODS: A combination of agent-based and Monte Carlo economic simulation modeling was used to determine the cost-benefit of closing schools (vs. not closing schools) for different durations (range: 1 to 8 weeks) and symptomatic case incidence triggers (range: 1 to 30) for the state of Pennsylvania during the 2009 H1N1 epidemic. Different scenarios varied the basic reproductive rate (R(0)) from 1.2, 1.6, to 2.0 and used case-hospitalization and case-fatality rates from the 2009 epidemic. Additional analyses determined the cost per influenza case averted of implementing school closure. RESULTS: For all scenarios explored, closing schools resulted in substantially higher net costs than not closing schools. For R(0) = 1.2, 1.6, and 2.0 epidemics, closing schools for 8 weeks would have resulted in median net costs of $21.0 billion (95% Range: $8.0 - $45.3 billion). The median cost per influenza case averted would have been $14,185 ($5,423 - $30,565) for R(0) = 1.2, $25,253 ($9,501 - $53,461) for R(0) = 1.6, and $23,483 ($8,870 - $50,926) for R(0) = 2.0. CONCLUSIONS: Our study suggests that closing schools during the 2009 H1N1 epidemic could have resulted in substantial costs to society as the potential costs of lost productivity and childcare could have far outweighed the cost savings in preventing influenza cases.

Economic value of dengue vaccine in Thailand.

With several candidate dengue vaccines under development, this is an important time to help stakeholders (e.g., policy makers, scientists, clinicians, and manufacturers) better understand the potential economic value (cost-effectiveness) of a dengue vaccine, especially while vaccine characteristics and strategies might be readily altered. We developed a decision analytic Markov simulation model to evaluate the potential health and economic value of administering a dengue vaccine to an individual (≤ 1 year of age) in Thailand from the societal perspective. Sensitivity analyses evaluated the effects of ranging various vaccine (e.g., cost, efficacy, side effect), epidemiological (dengue risk), and disease (treatment-seeking behavior) characteristics. A ≥ 50% efficacious vaccine was highly cost-effective [< 1× per capita gross domestic product (GDP) ($4,289)] up to a total vaccination cost of $60 and cost-effective [< 3× per capita GDP ($12,868)] up to a total vaccination cost of $200. When the total vaccine series was $1.50, many scenarios were cost saving.

Replacing the measles ten-dose vaccine presentation with the single-dose presentation in Thailand.

Introduced to minimize open vial wastage, single-dose vaccine vials require more storage space and therefore may affect vaccine supply chains (i.e., the series of steps and processes involved in distributing vaccines from manufacturers to patients). We developed a computational model of Thailand's Trang province vaccine supply chain to analyze the effects of switching from a ten-dose measles vaccine presentation to each of the following: a single-dose measles-mumps-rubella vaccine (which Thailand is currently considering) or a single-dose measles vaccine. While the Trang province vaccine supply chain would generally have enough storage and transport capacity to accommodate the switches, the added volume could push some locations' storage and transport space utilization close to their limits. Single-dose vaccines would allow for more precise ordering and decrease open vial waste, but decrease reserves for unanticipated demand. Moreover, the added disposal and administration costs could far outweigh the costs saved from preventing open vial wastage.

Single versus multi-dose vaccine vials: an economic computational model.

Single-dose vaccine formats can prevent clinic-level vaccine wastage but may incur higher production, medical waste disposal, and storage costs than multi-dose formats. To help guide vaccine developers, manufacturers, distributors, and purchasers, we developed a computational model to predict the potential economic impact of various single-dose versus multi-dose measles (MEA), hemophilus influenzae type B (Hib), Bacille Calmette-Guérin (BCG), yellow fever (YF), and pentavalent (DTP-HepB-Hib) vaccine formats. Lower patient demand favors fewer dose formats. The mean daily patient arrival thresholds for each vaccine format are as follows: for the MEA vaccine, 2 patients/day (below which the single-dose vial and above which the 10-dose vial are least costly); BCG vaccine, 6 patients/day (below, 10-dose vial; above, 20-dose vial); Hib vaccine, 5 patients/day (below, single-dose vial; above, 10-dose vial); YF vaccine, 33 patients/day (below, 5-dose vials; above 50-dose vial); and DTP-HepB-Hib vaccine, 5 patients/day (below, single-dose vial; above, 10-dose vial).

A computer simulation of vaccine prioritization, allocation, and rationing during the 2009 H1N1 influenza pandemic.

In the fall 2009, the University of Pittsburgh Models of Infectious Disease Agent Study (MIDAS) team employed an agent-based computer simulation model (ABM) of the greater Washington, DC, metropolitan region to assist the Office of the Assistant Secretary of Public Preparedness and Response, Department of Health and Human Services, to address several key questions regarding vaccine allocation during the 2009 H1N1 influenza pandemic, including comparing a vaccinating children (i.e., highest transmitters)-first policy versus the Advisory Committee on Immunization Practices (ACIP)-recommended vaccinating at-risk individuals-first policy. Our study supported adherence to the ACIP (instead of a children-first policy) prioritization recommendations for the H1N1 influenza vaccine when vaccine is in limited supply and that within the ACIP groups, children should receive highest priority.

Spatial and multidimensional visualization of Indonesia's village health statistics.

BACKGROUND: A community health assessment (CHA) is used to identify and address health issues in a given population. Effective CHA requires timely and comprehensive information from a wide variety of sources, such as: socio-economic data, disease surveillance, healthcare utilization, environmental data, and health resource allocation. Indonesia is a developing country with 235 million inhabitants over 13,000 islands. There are significant barriers to conducting CHA in developing countries like Indonesia, such as the high cost of computing resources and the lack of computing skills necessary to support such an assessment. At the University of Pittsburgh, we have developed the Spatial OLAP (On-Line Analytical Processing) Visualization and Analysis Tool (SOVAT) for performing CHA. SOVAT combines Geographic Information System (GIS) technology along with an advanced multidimensional data warehouse structure to facilitate analysis of large, disparate health, environmental, population, and spatial data. The objective of this paper is to demonstrate the potential of SOVAT for facilitating CHA among developing countries by using health, population, healthcare resources, and spatial data from Indonesia for use in two CHA cases studies. RESULTS: Bureau of Statistics administered data sets from the Indonesian Census, and the Indonesian village statistics, were used in the case studies. The data consisted of: healthcare resources (number of healthcare professionals and facilities), population (census), morbidity and mortality, and spatial (GIS-formatted) information. The data was formatted, combined, and populated into SOVAT for CHA use. Case study 1 involves the distribution of healthcare professionals in Indonesia, while case study 2 involves malaria mortality. Screen shots are shown for both cases. The results for the CHA were retrieved in seconds and presented through the geospatial and numerical SOVAT interface. CONCLUSION: The case studies show the potential of spatial and multidimensional analysis using SOVAT for community health assessment in developing countries. Since SOVAT is based primarily on open-source components and can be deployed using small personal computers, it is cost-effective for developing countries. Also, combining the strength in analysis and the ease of use makes tools like SOVAT ideal for healthcare professionals without extensive computer skills.

Strategies for mitigating an influenza pandemic.

Development of strategies for mitigating the severity of a new influenza pandemic is now a top global public health priority. Influenza prevention and containment strategies can be considered under the broad categories of antiviral, vaccine and non-pharmaceutical (case isolation, household quarantine, school or workplace closure, restrictions on travel) measures. Mathematical models are powerful tools for exploring this complex landscape of intervention strategies and quantifying the potential costs and benefits of different options. Here we use a large-scale epidemic simulation to examine intervention options should initial containment of a novel influenza outbreak fail, using Great Britain and the United States as examples. We find that border restrictions and/or internal travel restrictions are unlikely to delay spread by more than 2-3 weeks unless more than 99% effective. School closure during the peak of a pandemic can reduce peak attack rates by up to 40%, but has little impact on overall attack rates, whereas case isolation or household quarantine could have a significant impact, if feasible. Treatment of clinical cases can reduce transmission, but only if antivirals are given within a day of symptoms starting. Given enough drugs for 50% of the population, household-based prophylaxis coupled with reactive school closure could reduce clinical attack rates by 40-50%. More widespread prophylaxis would be even more logistically challenging but might reduce attack rates by over 75%. Vaccine stockpiled in advance of a pandemic could significantly reduce attack rates even if of low efficacy. Estimates of policy effectiveness will change if the characteristics of a future pandemic strain differ substantially from those seen in past pandemics.

Bushmeat hunting, deforestation, and prediction of zoonoses emergence.

Understanding the emergence of new zoonotic agents requires knowledge of pathogen biodiversity in wildlife, human-wildlife interactions, anthropogenic pressures on wildlife populations, and changes in society and human behavior. We discuss an interdisciplinary approach combining virology, wildlife biology, disease ecology, and anthropology that enables better understanding of how deforestation and associated hunting leads to the emergence of novel zoonotic pathogens.

Coverage and costs of childhood immunizations in Cameroon.

OBJECTIVE: To quantify the association between household-level and provider-level determinants and childhood immunization rates in Cameroon while also calculating the cost of childhood immunizations. METHODS: This study uses multilevel regression analysis to calculate these relationships. The 1998 Cameroon Demographic and Health Survey and the 2000 Multiple Indicator Cluster Survey are the main sources of household-level data. These surveys are supplemented by data from a 2002 survey of health facilities conducted in three provinces. At the national level, immunization financing data were collected from the Ministry of Health and donors that support the national Expanded Programme on Immunization. FINDINGS: The 1998 survey found that nationally 37% of children were fully immunized; the 2000 survey found that nationally 34% were fully immunized. These results are strongly correlated with both the mother's level of education and the household's economic status. Multilevel logistic regression shows that maternal education level is a stronger predictor of positive immunization status than is relative economic status. Children of mothers with secondary education or higher education were 3 times more likely to be fully vaccinated than children whose mothers had not completed primary education. At the health-facility level, both having art immunization plan and regular supervisory visits from someone at the health-district level are strongly positively associated with immunization rates. The cost of routine vaccinations for each fully immunized child is 12.73 U.S. dollars when donors' contributions are included but not the costs of immunization campaigns. CONCLUSION: Studies conducted in the 1980s and 1990s found that costs per fully immunized child varied from 2.19 U.S. dollars to 26.59 U.S. dollars (not adjusted for inflation) in a range of low-income and middle-income countries. The relatively low rates of immunization coverage in Cameroon, and the strong influence of the household's socioeconomic status--particularly the mother's level of education--on immunization rates suggest that the effectiveness of the Cameroon programme could be increased by promoting immunization and directing such programmes towards households with limited resources.