Future pandemic influenza control (FPIC) related strategic management plan based on the 2009 H1N1 pandemic influenza review of health policy decisions, their practice and implications

This cross-sectional study is based on the qualitative and quantitative research design to review health policy decisions, their practice and implications during 2009 H1N1 influenza pandemic in the United States and globally. The “Future Pandemic Influenza Control (FPIC) related Strategic Management Plan” was developed based on the incorporation of the “National Strategy for Pandemic Influenza (2005)” for the United States from the U.S. Homeland Security Council and “The Canadian Pandemic Influenza Plan for the Health Sector (2006)” from the Canadian Pandemic Influenza Committee for use by the public health agencies in the United States as well as globally. The “global influenza experts’ survey” was primarily designed and administered via email through the “Survey Monkey” system to the 2009 H1N1 influenza pandemic experts as the study respondents. The effectiveness of this plan was confirmed and the approach of the study questionnaire was validated to be convenient and the excellent quality of the questions provided an efficient opportunity to the study respondents to evaluate the effectiveness of predefined strategies/interventions for future pandemic influenza control.^ The quantitative analysis of the responses to the Likert-scale based questions in the survey about predefined strategies/interventions, addressing five strategic issues to control future pandemic influenza. The effectiveness of strategies defined as pertinent interventions in this plan was evaluated by targeting five strategic issues regarding pandemic influenza control. For the first strategic issue pertaining influenza prevention and pre pandemic planning; the confirmed effectiveness (agreement) for strategy (1a) 87.5%, strategy (1b) 91.7% and strategy (1c) 83.3%. The assessment of the priority level for strategies to address the strategic issue no. (1); (1b (High Priority) > 1a (Medium Priority) > 1c (Low Priority) based on the available resources of the developing and developed countries. For the second Strategic Issue encompassing the preparedness and communication regarding pandemic influenza control; the confirmed effectiveness (agreement) for the strategy (2a) 95.6%, strategy (2b) 82.6%, strategy (2c) 91.3% and Strategy (2d) 87.0%. The assessment of the priority level for these strategies to address the strategic issue no. (2); (2a (highest priority) > 2c (high priority) >2d (medium priority) > 2b (low priority). For the third strategic issue encompassing the surveillance and detection of pandemic influenza; the confirmed effectiveness (agreement) for the strategy (3a) 90.9% and strategy (3b) 77.3%. The assessment of the priority level for theses strategies to address the strategic Issue No. (3) (3a (high priority) > 3b (medium/low priority). For the fourth strategic issue pertaining the response and containment of pandemic influenza; the confirmed effectiveness (agreement) for the strategy (4a) 63.6%, strategy (4b) 81.8%, strategy (4c) 86.3%, and strategy (4d) 86.4%. The assessment of the priority level for these strategies to address the strategic issue no. (4); (4d (highest priority) > 4c (high priority) > 4b (medium priority) > 4a (low priority). The fifth strategic issue about recovery from influenza and post pandemic planning; the confirmed effectiveness (agreement) for the strategy (5a) 68.2%, strategy (5b) 36.3% and strategy (5c) 40.9%. The assessment of the priority level for strategies to address the strategic issue no. (5); (5a (high priority) > 5c (medium priority) > 5b (low priority).^ The qualitative analysis of responses to the open-ended questions in the study questionnaire was performed by means of thematic content analysis. The following recurrent or common “themes” were determined for the future implementation of various predefined strategies to address five strategic issues from the “FPIC related Strategic Management Plan” to control future influenza pandemics. (1) Pre Pandemic Influenza Prevention, (2) Seasonal Influenza Control, (3) Cost Effectiveness of Non Pharmaceutical Interventions (NPI), (4) Raising Global Public Awareness, (5) Global Influenza Vaccination Campaigns, (6)Priority for High Risk Population, (7) Prompt Accessibility and Distribution of Influenza Vaccines and Antiviral Drugs, (8) The Vital Role of Private Sector, (9) School Based Influenza Containment, (10) Efficient Global Risk Communication, (11) Global Research Collaboration, (12) The Critical Role of Global Public Health Organizations, (13) Global Syndromic Surveillance and Surge Capacity and (14) Post Pandemic Recovery and Lessons Learned. The future implementation of these strategies with confirmed effectiveness to primarily “reduce the overall response time’ in the process of ‘early detection’, ‘strategies (interventions) formulation’ and their ‘implementation’ to eventually ensure the following health outcomes: (a) reduced influenza transmission, (b) prompt and effective influenza treatment and control, (c) reduced influenza related morbidity and mortality.^

Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^

Observations from the Balcony: Directions for Pediatric Health Disparities Research and Policy

In 2002, the Institute of Medicine released Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare, a landmark monograph documenting health disparities in the U.S. health care system. Since the publication of Unequal Treatment, the field of pediatric health disparities research has advanced significantly with a proliferation of studies examining a wide array of topics concerning inequities in child health. Advances in health care policy and legislation have also added to a heightened discourse on pediatric health disparities. While there has been substantial activity in efforts to address pediatric health disparities, questions remain regarding whether these efforts have changed the trajectory of health equity among children. The aim of this paper is to examine the practical challenges of addressing pediatric health disparities in the dynamic context of global changes in health care research, policy, and legislation relevant to children. Using the Adaptive Leadership framework, this paper outlines a conceptual model for assessing the scope of progress made in addressing pediatric health disparities, diagnoses the continued adaptive challenges of pediatric health disparities, and provides an agenda for further work and future investment.