Quantifying the Population-Level Effect of the COVID-19 Mass Vaccination Campaign in Israel: A Modeling Study.

Background: Estimating real-world vaccine effectiveness is challenging as a variety of population factors can impact vaccine effectiveness. We aimed to assess the population-level reduction in cumulative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases, hospitalizations, and mortality due to the BNT162b2 mRNA coronavirus disease 2019 (COVID-19) vaccination campaign in Israel during January-February 2021. Methods: A susceptible-infected-recovered/removed (SIR) model and a Dynamic Survival Analysis (DSA) statistical approach were used. Daily counts of individuals who tested positive and of vaccine doses administered, obtained from the Israeli Ministry of Health, were used to calibrate the model. The model was parameterized using values derived from a previous phase of the pandemic during which similar lockdown and other preventive measures were implemented in order to take into account the effect of these prevention measures on COVID-19 spread. Results: Our model predicted for the total population a reduction of 648 585 SARS-CoV-2 cases (75% confidence interval [CI], 25 877-1 396 963) during the first 2 months of the vaccination campaign. The number of averted hospitalizations for moderate to severe conditions was 16 101 (75% CI, 2010-33 035), and reduction of death was estimated at 5123 (75% CI, 388-10 815) fatalities. Among children aged 0-19 years, we estimated a reduction of 163 436 (75% CI, 0-433 233) SARS-CoV-2 cases, which we consider to be an indirect effect of the vaccine. Conclusions: Our results suggest that the rapid vaccination campaign prevented hundreds of thousands of new cases as well as thousands of hospitalizations and fatalities and has probably averted a major health care crisis.

Thirty-five years later: Long-term effects of the Matlab maternal and child health/family planning program on older women's well-being.

Family planning programs are believed to have substantial long-term benefits for women's health and well-being, yet few studies have established either extent or direction of long-term effects. The Matlab, Bangladesh, maternal and child health/family planning (MCH/FP) program afforded a 12-y period of well-documented differential access to services. We evaluate its impacts on women's lifetime fertility, adult health, and economic outcomes 35 y after program initiation. We followed 1,820 women who were of reproductive age during the differential access period (born 1938-1973) from 1978 to 2012 using prospectively collected data from the Matlab Health and Demographic Surveillance System and the 1996 and 2012 Matlab Health and Socioeconomic Surveys. We estimated intent-to-treat single-difference models comparing treatment and comparison area women. MCH/FP significantly increased contraceptive use, reduced completed fertility, lengthened birth intervals, and reduced age at last birth, but had no significant positive impacts on health or economic outcomes. Treatment area women had modestly poorer overall health (+0.07 SD) and respiratory health (+0.12 SD), and those born 1950-1961 had significantly higher body mass index (BMI) in 1996 (0.76 kg/m2) and 2012 (0.57 kg/m2); fewer were underweight in 1996, but more were overweight or obese in 2012. Overall, there was a +2.5 kg/m2 secular increase in BMI. We found substantial changes in lifetime contraceptive and fertility behavior but no long-term health or economic benefits of the program. We observed modest negative health impacts that likely result from an accelerated nutritional transition among treated women, a transition that would, in an earlier context, have been beneficial.

Investigating the association of room features with healthcare-facility-onset Clostridioides difficile: An exploratory study.

OBJECTIVE: To investigate hospital room and patient-level risk factors associated with increased risk of healthcare-facility-onset Clostridioides difficile infection (HO-CDI). DESIGN: The study used a retrospective cohort design that included patient data from the institution's electronic health record, existing surveillance data on HO-CDI, and a walk-through survey of hospital rooms to identify potential room-level risk factors. The primary outcome was HO-CDI diagnosis. SETTING: A large academic medical center. PATIENTS AND PARTICIPANTS: All adult patients admitted between January 1, 2015, and December 31, 2016 were eligible for inclusion. Prisoners were excluded. Patients who only stayed in rooms that were not surveyed were excluded. RESULTS: The hospital room survey collected room-level data on 806 rooms. Included in the study were 17,034 patients without HO-CDI and 251 with HO-CDI nested within 535 unique rooms. In this exploratory study, room-level risk factors associated with the outcome in the multivariate model included wear on furniture and flooring and antibiotic use by the prior room occupant. Hand hygiene devices and fixed in-room computers were associated with reduced odds of a HO-CDI. Differences between hospital buildings were also detected. The only individual patient factors that were associated with increased odds of HO-CDI were antibiotic use and comorbidity score. CONCLUSION: Combining a hospital-room walk-through data collection survey, EHR data, and CDI surveillance data, we were able to develop a model to investigate room and patient-level risks for HO-CDI.

Organizations matter in local governance: evidence from health sector decentralization in Honduras.

Health systems strengthening is at the forefront of the global health agenda. Many health systems in low-resource settings face profound challenges, and robust causal evidence on the effects of health systems reforms is lacking. Decentralization has been one of the most prominent reforms, and after more than 50 years of implementation and hundreds of studies, we still know little about whether these policies improve, harm or are inconsequential for the performance of health systems in less-developed countries. A persistent problem in existing studies is the inability to isolate the effect of decentralization on health outcomes, struggling with heterogeneous meanings of decentralization and missing counterfactuals. We address these shortcomings with a quasi-experimental, longitudinal research design that takes advantage of a unique staggered reform process in Honduras. Using three waves of household survey data over 10 years for a matched sample of 65 municipalities in Honduras, we estimated difference-in-difference models comparing changes in outcomes over time between local health systems that were decentralized using one of three types of organizations [municipal governments, associations of mayors or non-governmental organization (NGOs)] and those that remained centrally administered. We find evidence of overall improvements between 2005 and 2016 in several service delivery-related outcomes, and additional improvements in decentralized municipalities governed by NGOs. NGO-led municipalities saw a 15% decrease in home delivery relative to centralized municipalities in 2016, a 12.5% increase in MCH facility delivery and a 7% increase in the use of a skilled birth attendant. There were no detectable positive treatment effects for vaccination, and a slight decline in the weight-for-length z-scores in NGO municipalities, but we find no systematic evidence of decentralization negatively impacting any maternal and child health outcomes. These findings highlight the importance of considering implementation context, namely organization type, when assessing the effects of decentralization reform.

Geovisualization and Spatial Analysis of Infant Mortality and Preterm Birth in Ohio, 2008-2015: Opportunities to Enhance Spatial Thinking.

OBJECTIVES: Geovisualization and spatial analysis are valuable tools for exploring and evaluating the complex social, economic, and environmental interactions that lead to spatial inequalities in health. The objective of this study was to describe spatial patterns of infant mortality and preterm birth in Ohio by using interactive mapping and spatial analysis. METHODS: We conducted a retrospective cohort study using Ohio vital statistics records from 2008-2015. We geocoded live births and infant deaths by using residential address at birth. We used multivariable logistic regression to adjust spatial and space-time cluster analyses that examined the geographic clustering of infant mortality and preterm birth and changes in spatial distribution over time. RESULTS: The overall infant mortality rate in Ohio during the study period was 6.55 per 1000 births; of 1 097 507 births, 10.3% (n = 112 552) were preterm. We found significant geographic clustering of both infant mortality and preterm birth centered on large urban areas. However, when known demographic risk factors were taken into account, urban clusters disappeared and, for preterm birth, new rural clusters appeared. CONCLUSIONS: Although many public health agencies have the capacity to create maps of health outcomes, complex spatial analysis and geovisualization techniques are still challenging for public health practitioners to use and understand. We found that actively engaging policymakers in reviewing results of the cluster analysis improved understanding of the processes driving spatial patterns of birth outcomes in the state.

Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population.

Consensus is growing on the need to investigate the joint impact of neighborhood-level social factors and environmental hazards on respiratory health. This study used latent profile analysis (LPA) to empirically identify distinct neighborhood subtypes according to a clustering of social factors and environmental hazards, and to examine whether those subtypes are associated with lung function. The study included 182 low-income participants who were enrolled in the Colorado Home Energy Efficiency and Respiratory Health (CHEER) study during the years 2015⁻2017. Distinct neighborhood typologies were identified based on analyses of 632 census tracts in the Denver-Metro and Front Range area of Colorado; neighborhood characteristics used to identify typologies included green space, traffic-related air pollution, violent and property crime, racial/ethnic composition, and socioeconomic status (SES). Generalized estimating equations were used to examine the association between neighborhood typology and lung function. We found four distinct neighborhood typologies and provide evidence that these social and environmental aspects of neighborhoods cluster along lines of advantage/disadvantage. We provide suggestive evidence of a double jeopardy situation where low-income populations living in disadvantaged neighborhoods may have decreased lung function. Using LPA with social and environmental characteristics may help to identify meaningful neighborhood subtypes and inform research on the mechanisms by which neighborhoods influence health.

Repurposing Geographic Information Systems for Routine Hospital Infection Control.

This chapter discusses the potential role of geographic information systems (GIS) for infection control within the hospital system. The chapter provides a brief overview of the role of GIS in public health and reviews current work applying these methods to the hospital setting. Finally, it outlines the potential opportunities and challenges for adapting GIS for use in the hospital setting for infection prevention. A targeted literature review is used to illustrate current use of GIS in the hospital setting. The discussion of complexity was compiled using the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework. Challenges and opportunities were then extracted from this exercise by the authors. There are multiple challenges to implementation of a Hospital GIS for infection prevention, mainly involving the domains of technology, organization, and adaptation. Use of a transdisciplinary approach can address many of these challenges. More research, specifically prospective, reproducible clinical trials, needs to be done to better assess the potential impact and effectiveness of a Hospital GIS in real-world settings. This chapter highlights a powerful but rarely used tool for infection prevention within the hospital. Given the importance of reducing hospital-acquired infection rates, it is vital to identify relevant methods from other fields that could be translated into the field of hospital epidemiology.

Residential Mobility Across Early Childhood and Children's Kindergarten Readiness.

Understanding residential mobility in early childhood is important for contextualizing family, school, and neighborhood influences on child well-being. We examined the consequences of residential mobility for socioemotional and cognitive kindergarten readiness using the Early Childhood Longitudinal Study-Birth Cohort, a nationally representative longitudinal survey that followed U.S. children born in 2001 from infancy to kindergarten. We described individual, household, and neighborhood characteristics associated with residential mobility for children aged 0-5. Our residential mobility indicators examined frequency of moves, nonlinearities in move frequency, quality of moves, comparisons between moving houses and moving neighborhoods, and heterogeneity in the consequences of residential mobility. Nearly three-quarters of children moved by kindergarten start. Mobility did not predict cognitive scores. More moves, particularly at relatively high frequencies, predicted lower kindergarten behavior scores. Moves from socioeconomically advantaged to disadvantaged neighborhoods were especially problematic, whereas moves within a ZIP code were not. The implications of moves were similar across socioeconomic status. The behavior findings largely support an instability perspective that highlights potential disruptions from frequent or problematic moves. Our study contributes to literature emphasizing the importance of contextualizing residential mobility. The high prevalence and distinct implications of early childhood moves support the need for further research.

Physical activity and activity space in patients with pulmonary fibrosis not prescribed supplemental oxygen.

BACKGROUND: Patients with pulmonary fibrosis (PF) have impaired quality of life, and research suggests that dyspnea and physical activity are primary drivers. As PF progresses, some patients notice the disease "shrinks their worlds". The objective of this study is to describe movement (both physical activity and activity space) in a cohort of patients with PF of various etiologies who have not been prescribed supplemental oxygen (O2). METHODS: Subjects with PF not on supplemental O2 during the day were enrolled from across the U.S. from August 2013 to October 2015. At enrollment, each subject completed questionnaires and, for seven consecutive days, wore an accelerometer and GPS tracker. RESULTS: One hundred ninety-four subjects had a confirmed diagnosis of PF and complete, analyzable GPS data. The cohort was predominantly male (56%), Caucasian (95%) and had idiopathic pulmonary fibrosis (30%) or connective tissue disease related-PF (31%). Subjects walked a median 7497 (interquartile range [IQR] 5766-9261) steps per day. Steps per day were correlated with symptoms and several quality of life domains. In a model controlling for age, body mass index, wrist- (vs. waist) worn accelerometer and percent predicted diffusing capacity (DLCO%), fatigue (beta coefficient = -51.5 ± 11.7, p < 0.0001) was an independent predictor of steps per day (model R2=0.34). CONCLUSIONS: Patients with PF, who have not been prescribed O2 for use during the day, have wide variability in their mobility. Day-to-day physical activity is related to several domains that impact quality of life, but GPS-derived activity space is not. Wearable data collection devices may be used to determine whether and how therapeutic interventions impact movement in PF patients. TRIAL REGISTRATION: NCT01961362 . Registered 9 October, 2013.

Demographic and ecological risk factors for human influenza A virus infections in rural Indonesia.

BACKGROUND: Indonesia has the world's highest reported mortality for human infections with highly pathogenic avian influenza (HPAI) A(H5N1) virus. Indonesia is an agriculturally driven country where human-animal mixing is common and provides a unique environment for zoonotic influenza A virus transmission. OBJECTIVES: To identify potential demographic and ecological risk factors for human infection with seasonal influenza A viruses in rural Indonesia, a population-based study was conducted in Cileunyi and Soreang subdistricts near Bandung in western Java from 2008 to 2011. METHODS: Passive influenza surveillance with RT-PCR confirmation of influenza A viral RNA in respiratory specimens was utilized for case ascertainment. A population census and mapping were utilized for population data collection. The presence of influenza A(H3N2) and A(H1N1)pdm09 virus infections in a household was modeled using Generalized Estimating Equations. RESULTS: Each additional child aged <5 years in a household increased the odds of H3N2 approximately 5 times (OR=4.59, 95%CI: 3.30-6.24) and H1N1pdm09 by 3.5 times (OR=3.53, 95%CI: 2.51-4.96). In addition, the presence of 16-30 birds in the house was associated with an increased odds of H3N2 (OR=5.08, 95%CI: 2.00-12.92) and H1N1pdm09 (OR=12.51 95%CI: 6.23-25.13). CONCLUSION: Our findings suggest an increase in influenza A virus infections in rural Indonesian households with young children and poultry.

Distance to health services modifies the effect of an 11-valent pneumococcal vaccine on pneumonia risk among children less than 2 years of age in Bohol, Philippines.

Background: Both vaccine trials and surveillance studies typically use passive surveillance systems to monitor study outcomes, which may lead to under-reporting of study outcomes in areas with poor access to care. This detection bias can have an adverse effect on conventional estimates of pneumonia risk derived from vaccine trials. Methods: We conducted a secondary analysis of a randomized, placebo-controlled, double-blind vaccine trial that examined the efficacy of an 11-valent pneumococcal vaccine (PCV) among children less than 2 years of age in Bohol, Philippines. Trial data were linked to the residential location of each participant using a geographical information system. The study was conducted using 11 729 children who received three doses of any study vaccine (PCV11) or placebo. Multivariate Cox proportional hazards models were used to examine major risk factors for pneumonia diagnosis and the relationship between distance to Bohol Regional Hospital (BRH) and vaccination with PCV with risk for pneumonia diagnosis. Results: There was a significant interaction effect between distance from BRH and vaccination with PCV11 on pneumonia risk. Among children living 12 km from BRH, vaccination with PCV11 was associated with a decreased hazard ratio for radiographic pneumonia, compared with vaccination with the study placebo [0.57, 95% confidence interval (CI) 0.37-0.86). However, for children living 1 km from BRH, there was little difference in risk of radiographic pneumonia diagnosis between children vaccinated with PCV11 and those given the study placebo. Conclusion: Children living close to BRH had no documented reduction in the primary study outcome from PCV11, whereas those at greater distance experienced a substantial reduction. Because of detection bias caused by distance to BRH, in spatial analysis of vaccine trial results it may be necessary to adjust estimates of pneumonia risk and vaccine efficacy. Failure to consider the geographical dimension of trials may lead to underestimates of efficacy which might influence public health planning efforts.

Effects of health intervention programs and arsenic exposure on child mortality from acute lower respiratory infections in rural Bangladesh.

BACKGROUND: Respiratory infections continue to be a public health threat, particularly to young children in developing countries. Understanding the geographic patterns of diseases and the role of potential risk factors can help improve future mitigation efforts. Toward this goal, this paper applies a spatial scan statistic combined with a zero-inflated negative-binomial regression to re-examine the impacts of a community-based treatment program on the geographic patterns of acute lower respiratory infection (ALRI) mortality in an area of rural Bangladesh. Exposure to arsenic-contaminated drinking water is also a serious threat to the health of children in this area, and the variation in exposure to arsenic must be considered when evaluating the health interventions. METHODS: ALRI mortality data were obtained for children under 2 years old from 1989 to 1996 in the Matlab Health and Demographic Surveillance System. This study period covers the years immediately following the implementation of an ALRI control program. A zero-inflated negative binomial (ZINB) regression model was first used to simultaneously estimate mortality rates and the likelihood of no deaths in groups of related households while controlling for socioeconomic status, potential arsenic exposure, and access to care. Next a spatial scan statistic was used to assess the location and magnitude of clusters of ALRI mortality. The ZINB model was used to adjust the scan statistic for multiple social and environmental risk factors. RESULTS: The results of the ZINB models and spatial scan statistic suggest that the ALRI control program was successful in reducing child mortality in the study area. Exposure to arsenic-contaminated drinking water was not associated with increased mortality. Higher socioeconomic status also significantly reduced mortality rates, even among households who were in the treatment program area. CONCLUSION: Community-based ALRI interventions can be effective at reducing child mortality, though socioeconomic factors may continue to influence mortality patterns. The combination of spatial and non-spatial methods used in this paper has not been applied previously in the literature, and this study demonstrates the importance of such approaches for evaluating and improving public health intervention programs.

Disease mapping for informing targeted health interventions: childhood pneumonia in Bohol, Philippines.

BACKGROUND: Acute lower respiratory tract infections (ALRI) are the leading cause of childhood mortality worldwide. Currently, most developing countries assign resources at a district level, and yet District Medical Officers have few tools for directing targeted interventions to high mortality or morbidity areas. Mapping of ALRI at the local level can guide more efficient allocation of resources, coordination of efforts and targeted interventions, which are particularly relevant for health management in resource-scarce settings. METHODS: An efficacy study of 11-valent pneumococcal vaccine was conducted in six municipalities in the Bohol Province of central Philippines from July 2000 to December 2004. Geocoded under-five pneumonia cases (using WHO classifications) were mapped to create spatial patterns of pneumonia at the local health unit (barangay) level. RESULTS: There were 2951 children with WHO-defined clinical pneumonia, of whom 1074 were severe or very severely ill, 278 were radiographic, and 219 were hypoxaemic. While most children with pneumonia were from urban barangays, there was a disproportionately higher distribution of severe/very severe pneumonia in rural barangays and the most severe hypoxaemic children were concentrated in the northern barangays most distant from the regional hospital. CONCLUSIONS: Mapping of ALRI at the local administrative health level can be performed relatively simply. If these principles are applied to routinely collected IMCI classification of disease at the district level in developing countries, such efforts can form the basis for directing public health and healthcare delivery efforts in a targeted manner.

Residential Mobility in Early Childhood: Household and Neighborhood Characteristics of Movers and Non-Movers.

BACKGROUND: Understanding residential mobility in early childhood is important for contextualizing influences on child health and well-being. OBJECTIVE: This study describes individual, household, and neighborhood characteristics associated with residential mobility for children aged 0-5. METHODS: We examined longitudinal data from the Early Childhood Longitudinal Study-Birth Cohort (ECLS-B), a nationally representative sample of children born in 2001. Frequencies describe the prevalence of characteristics for four waves of data and adjusted Wald tests compared means. RESULTS: Moving was common for these families with young children, as nearly three-quarters of children moved at least once. Movers transitioned to neighborhoods with residents of higher socioeconomic status but experienced no improved household socioeconomic position relative to non-movers. CONCLUSION: Both the high prevalence and unique implications of early childhood residential mobility suggest the need for further research.

Neighborhood racial composition and trajectories of child self-rated health: an application of longitudinal propensity scores.

Children function within multiple socio-environmental contexts including family, school, and neighborhood. The role each of these contexts play in determining well-being is dynamic and changes throughout early-middle childhood. Recent literature on neighborhood context and health suggests that the life-course processes involved in building trajectories of health are not adequately captured in cross-sectional analysis, which has been the empirical focus of much of the research in this area. In this study we use a nationally representative longitudinal sample of approximately 21,400 United States school children derived from the Early Childhood Longitudinal Study--Kindergarten Cohort (ECLS-K) survey to examine the impact of longitudinal measures of neighborhood racial composition on child self-rated health between kindergarten and 8th grade. We employ two-level multilevel longitudinal logistic regression models with time-varying propensity scores to examine variation in the initial status and trajectories of child self-rated health between kindergarten and 8th grade. Since the ECLS-K tracked child mobility over time, we are able to model the impact of changes in neighborhood racial composition. We find significant differences in initial poor self-rated health by child race, household socioeconomic status and parental marital status but no evidence of a change in trajectory of health over time. Using time-varying propensity scores, we find no effect of neighborhood racial composition on initial health status or health status trajectories.

Adjusting for geographic variation in observational comparative effectiveness studies: a case study of antipsychotics using state Medicaid data.

BACKGROUND: Area-level variation in treatment and outcomes may be a potential source of confounding bias in observational comparative effectiveness studies. This paper demonstrates how to use exploratory spatial data analysis (ESDA) and spatial statistical methods to investigate and control for these potential biases. The case presented compares the effectiveness of two antipsychotic treatment strategies: oral second-generation antipsychotics (SGAs) vs. long-acting paliperiodone palmitate (PP). METHODS: A new-start cohort study was conducted analyzing patient-level administrative claims data (8/1/2008-4/30/2011) from Missouri Medicaid. ESDA techniques were used to examine spatial patterns of antipsychotic prescriptions and outcomes (hospitalization and emergency department (ED) visits). Likelihood of mental health-related outcomes were compared between patients starting PP (N = 295) and oral SGAs (N = 8,626) using multilevel logistic regression models adjusting for patient composition (demographic and clinical factors) and geographic region. RESULTS: ESDA indicated significant spatial variation in antipsychotic prescription patterns and moderate variation in hospitalization and ED visits thereby indicating possible confounding by geography. In the multilevel models for this antipsychotic case example, patient composition represented a stronger source of confounding than geographic context. CONCLUSION: Because geographic variation in health care delivery is ubiquitous, it could be a comparative effectiveness research (CER) best practice to test for possible geographic confounding in observational data. Though the magnitude of the area-level geography effects were small in this case, they were still statistically significant and should therefore be examined as part of this observational CER study. More research is needed to better estimate the range of confounding due to geography across different types of observational comparative effectiveness studies and healthcare utilization outcomes.

Evidence for localised HIV related micro-epidemics associated with the decentralised provision of antiretroviral treatment in rural South Africa: a spatio-temporal analysis of changing mortality patterns (2007-2010).

BACKGROUND: In this study we analysed the spatial and temporal changes in patterns of mortality over a period when antiretroviral therapy (ART) was rolled out in a rural region of north-eastern South Africa. Previous studies have identified localised concentrated HIV related sub-epidemics and recommended that micro-level analyses be carried out in order to direct focused interventions. METHODS: Data from an ongoing health and socio-demographic surveillance study was used in the analysis. The follow-up was divided into two periods, 2007-2008 and 2009-2010, representing the times immediately before and after the effects on mortality of the decentralised ART provision from a newly established local health centre would be expected to be evident. The study population at the start of the analysis was approximately 73 000 individuals. Data were aggregated by village and also using a 2 × 2 km grid. We identified villages, grid squares and regions in the site where mortality rates within each time period or rate ratios between the periods differed significantly from the overall trends. We used clustering techniques to identify cause-specific mortality hotspots. FINDINGS: Comparing the two periods, there was a 30% decrease in age and gender standardised adult HIV-related and TB (HIV/TB) mortality with no change in mortality due to other causes. There was considerable spatial heterogeneity in the mortality patterns. Areas separated by 2 to 4 km with very different epidemic trajectories were identified. There was evidence that the impact of ART in reducing HIV/TB mortality was greatest in communities with higher mortality rates in the earlier period. CONCLUSIONS: This study shows the value of conducting high resolution spatial analyses in order to understand how local micro-epidemics contribute to changes seen over a wider area. Such analyses can support targeted interventions.

Distance to health services affects local-level vaccine efficacy for pneumococcal conjugate vaccine (PCV) among rural Filipino children.

Pneumococcal conjugate vaccines (PCVs) have demonstrated efficacy against childhood pneumococcal disease in several regions globally. We demonstrate how spatial epidemiological analysis of a PCV trial can assist in developing vaccination strategies that target specific geographic subpopulations at greater risk for pneumococcal pneumonia. We conducted a secondary analysis of a randomized, placebo-controlled, double-blind vaccine trial that examined the efficacy of an 11-valent PCV among children less than 2 y of age in Bohol, Philippines. Trial data were linked to the residential location of each participant using a geographic information system. We use spatial interpolation methods to create smoothed surface maps of vaccination rates and local-level vaccine efficacy across the study area. We then measure the relationship between distance to the main study hospital and local-level vaccine efficacy, controlling for ecological factors, using spatial autoregressive models with spatial autoregressive disturbances. We find a significant amount of spatial variation in vaccination rates across the study area. For the primary study endpoint vaccine efficacy increased with distance from the main study hospital from -14% for children living less than 1.5 km from Bohol Regional Hospital (BRH) to 55% for children living greater than 8.5 km from BRH. Spatial regression models indicated that after adjustment for ecological factors, distance to the main study hospital was positively related to vaccine efficacy, increasing at a rate of 4.5% per kilometer distance. Because areas with poor access to care have significantly higher VE, targeted vaccination of children in these areas might allow for a more effective implementation of global programs.

The impact of childhood mobility on exposure to neighborhood socioeconomic context over time.

We used the 1998-1999 Early Childhood Longitudinal Study-Kindergarten Cohort, with data collected in kindergarten, first, third, fifth, and eighth grades, in a descriptive analysis of associations between early childhood residential mobility frequency and neighborhood context changes. We found that children who move frequently appear initially to move into higher-socioeconomic-status neighborhoods but eventually move back to lower-socioeconomic-status neighborhoods, exposing frequent movers to diverse neighborhood contexts. These findings have implications for policy and research that seeks to link neighborhood context to health.