Diane K. Wagener

Modeling targeted layered containment of an influenza pandemic in the United States

Planning a response to an outbreak of a pandemic strain of influenza is a high public health priority. Three research groups using different individual-based, stochastic simulation models have examined the consequences of intervention strategies chosen in consultation with U.S. public health workers. The first goal is to simulate the effectiveness of a set of potentially feasible intervention strategies. Combinations called targeted layered containment (TLC) of influenza antiviral treatment and prophylaxis and nonpharmaceutical interventions of quarantine, isolation, school closure, community social distancing, and workplace social distancing are considered. The second goal is to examine the robustness of the results to model assumptions. The comparisons focus on a pandemic outbreak in a population similar to that of Chicago, with ≈8.6 million people. The simulations suggest that at the expected transmissibility of a pandemic strain, timely implementation of a combination of targeted household antiviral prophylaxis, and social distancing measures could substantially lower the illness attack rate before a highly efficacious vaccine could become available. Timely initiation of measures and school closure play important roles. Because of the current lack of data on which to base such models, further field research is recommended to learn more about the sources of transmission and the effectiveness of social distancing measures in reducing influenza transmission.

The PhenX Toolkit: Get the Most From Your Measures

The potential for genome-wide association studies to relate phenotypes to specific genetic variation is greatly increased when data can be combined or compared across multiple studies. To facilitate replication and validation across studies, RTI International (Research Triangle Park, North Carolina) and the National Human Genome Research Institute (Bethesda, Maryland) are collaborating on the consensus measures for Phenotypes and eXposures (PhenX) project. The goal of PhenX is to identify 15 high-priority, well-established, and broadly applicable measures for each of 21 research domains. PhenX measures are selected by working groups of domain experts using a consensus process that includes input from the scientific community. The selected measures are then made freely available to the scientific community via the PhenX Toolkit. Thus, the PhenX Toolkit provides the research community with a core set of high-quality, well-established, low-burden measures intended for use in large-scale genomic studies. PhenX measures will have the most impact when included at the experimental design stage. The PhenX Toolkit also includes links to standards and resources in an effort to facilitate data harmonization to legacy data. Broad acceptance and use of PhenX measures will promote cross-study comparisons to increase statistical power for identifying and replicating variants associated with complex diseases and with gene-gene and gene-environment interactions.

Controlling Pandemic Flu: The Value of International Air Travel Restrictions

Background Planning for a possible influenza pandemic is an extremely high priority, as social and economic effects of an unmitigated pandemic would be devastating. Mathematical models can be used to explore different scenarios and provide insight into potential costs, benefits, and effectiveness of prevention and control strategies under consideration. Methods and Findings A stochastic, equation-based epidemic model is used to study global transmission of pandemic flu, including the effects of travel restrictions and vaccination. Economic costs of intervention are also considered. The distribution of First Passage Times (FPT) to the United States and the numbers of infected persons in metropolitan areas worldwide are studied assuming various times and locations of the initial outbreak. International air travel restrictions alone provide a small delay in FPT to the U.S. When other containment measures are applied at the source in conjunction with travel restrictions, delays could be much longer. If in addition, control measures are instituted worldwide, there is a significant reduction in cases worldwide and specifically in the U.S. However, if travel restrictions are not combined with other measures, local epidemic severity may increase, because restriction-induced delays can push local outbreaks into high epidemic season. The per annum cost to the U.S. economy of international and major domestic air passenger travel restrictions is minimal: on the order of 0.8% of Gross National Product. Conclusions International air travel restrictions may provide a small but important delay in the spread of a pandemic, especially if other disease control measures are implemented during the afforded time. However, if other measures are not instituted, delays may worsen regional epidemics by pushing the outbreak into high epidemic season. This important interaction between policy and seasonality is only evident with a global-scale model. Since the benefit of travel restrictions can be substantial while their costs are minimal, dismissal of travel restrictions as an aid in dealing with a global pandemic seems premature.

Simulating School Closure Strategies to Mitigate an Influenza Epidemic

BACKGROUND There remains substantial debate over the impact of school closure as a mitigation strategy during an influenza pandemic. The ongoing 2009 H1N1 influenza pandemic has provided an unparalleled opportunity to test interventions with the most up-to-date simulations. METHODS To assist the Allegheny County Health Department during the 2009 H1N1 influenza pandemic, the University of Pittsburgh Models of Infectious Disease Agents Study group employed an agent-based computer simulation model (ABM) of Allegheny County, Pennsylvania, to explore the effects of various school closure strategies on mitigating influenza epidemics of different reproductive rates (R0). RESULTS Entire school system closures were not more effective than individual school closures. Any type of school closure may need to be maintained throughout most of the epidemic (ie, at least 8 weeks) to have any significant effect on the overall serologic attack rate. In fact, relatively short school closures (ie, 2 weeks or less) may actually slightly increase the overall attack rate by returning susceptible students back into schools in the middle of the epidemic. Varying the illness threshold at which school closures are triggered did not seem to have substantial impact on the effectiveness of school closures, suggesting that short delays in closing schools should not cause concern. CONCLUSIONS School closures alone may not be able to quell an epidemic but, when maintained for at least 8 weeks, could delay the epidemic peak for up to a week, providing additional time to implement a second more effective intervention such as vaccination.

Signatures of natural selection are not uniform across genes of innate immune system, but purifying selection is the dominant signature.

We tested the opposing views concerning evolution of genes of the innate immune system that (i) being evolutionary ancient, the system may have been highly optimized by natural selection and therefore should be under purifying selection, and (ii) the system may be plastic and continuing to evolve under balancing selection. We have resequenced 12 important innate-immunity genes (CAMP, DEFA4, DEFA5, DEFA6, DEFB1, MBL2, and TLRs 1, 2, 4, 5, 6, and 9) in healthy volunteers (n = 171) recruited from a region of India with high microbial load. We have compared these data with those of European-Americans (EUR) and African-Americans (AFR). We have found that most of the human haplotypes are many mutational steps away from the ancestral (chimpanzee) haplotypes, indicating that humans may have had to adapt to new pathogens. The haplotype structures in India are significantly different from those of EUR and AFR populations, indicating local adaptation to pathogens. In these genes, there is (i) generally an excess of rare variants, (ii) high, but variable, degrees of extended haplotype homozygosity, (iii) low tolerance to nonsynonymous changes, (iv) essentially one or a few high-frequency haplotypes, with star-like phylogenies of other infrequent haplotypes radiating from the modal haplotypes. Purifying selection is the most parsimonious explanation operating on these innate immunity genes. This genetic surveillance system recognizes motifs in pathogens that are perhaps conserved across a broad range of pathogens. Hence, functional constraints are imposed on mutations that diminish the ablility of these proteins to detect pathogens.

Temporal trends in the socioeconomic gradient for breast cancer mortality among US women.

Temporal trends in breast cancer mortality among US women were examined for 1969 through 1989 by age, race, and county-level socioeconomic status (SES). The mortality ratio for high- relative to low-SES counties declined significantly among women 25 to 44, 45 to 64, and more than 65 years of age, respectively, from 1.13 to 0.96, 1.32 to 1.19, and 1.48 to 1.26. The narrowing of mortality occurred among Whites and, to a lesser extent, Blacks. A relative increase in either breast cancer incidence among women in lower SES counties or improved survival among women in higher SES counties (reflecting greater use of screening and treatment) could account for this relative worsening of breast cancer mortality among lower SES women in lower SES counties.

Social Network Analysis of Patient Sharing Among Hospitals in Orange County, California

OBJECTIVES We applied social network analyses to determine how hospitals within Orange County, California, are interconnected by patient sharing, a system which may have numerous public health implications. METHODS Our analyses considered 2 general patient-sharing networks: uninterrupted patient sharing (UPS; i.e., direct interhospital transfers) and total patient sharing (TPS; i.e., all interhospital patient sharing, including patients with intervening nonhospital stays). We considered these networks at 3 thresholds of patient sharing: at least 1, at least 10, and at least 100 patients shared. RESULTS Geographically proximate hospitals were somewhat more likely to share patients, but many hospitals shared patients with distant hospitals. Number of patient admissions and percentage of cancer patients were associated with greater connectivity across the system. The TPS network revealed numerous connections not seen in the UPS network, meaning that direct transfers only accounted for a fraction of total patient sharing. CONCLUSIONS Our analysis demonstrated that Orange Countys 32 hospitals were highly and heterogeneously interconnected by patient sharing. Different hospital populations had different levels of influence over the patient-sharing network.

Socioeconomic Status and Breast Cancer Mortality, 1989 through 1993: An Analysis of Education Data from Death Certificates

OBJECTIVES This study examined whether more highly educated women were at greater risk of dying of breast cancer during 1989 through 1993. METHODS Breast cancer mortality rates were calculated through death certificates and Current Population Survey data. RESULTS Breast cancer mortality rates were highest among women with 12 and with 16 or more years of education. Non-Hispanic Black women had the highest mortality rates and Asian women the lowest. Positive relationships between mortality and education were found for Hispanic women as well as non-Hispanic Black and Asian women. CONCLUSIONS The previously seen positive relationship between breast cancer mortality and education was found among US women of color but not non-Hispanic White women.

Protecting health care workers: a pandemic simulation based on Allegheny County

Please cite this paper as: Cooley et al. (2010) Protecting health care workers: a pandemic simulation based on Allegheny County. Influenza and Other Respiratory Viruses 4(2), 61–72.

Achieving National Health Objectives: The Impact on Life Expectancy and on Healthy Life Expectancy

Our study quantifies the impact of achieving specific Healthy People 2010 targets and of eliminating racial/ethnic health disparities on summary measures of health. We used life table methods to calculate gains in life expectancy and healthy life expectancy that would result from achievement of Healthy People 2010 objectives or of current mortality rates in the Asian/Pacific Islander (API) population. Attainment of Healthy People 2010 mortality targets would increase life expectancy by 2.8 years, and reduction of population wide mortality rates to current API rates would add 4.1 years. Healthy life expectancy would increase by 5.8 years if Healthy People 2010 mortality and assumed morbidity targets were attained and by 8.1 years if API mortality and activity limitation rates were attained. Achievement of specific Healthy People 2010 targets would produce significant increases in longevity and health, and elimination of racial/ethnic health disparities could result in even larger gains.