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bioRxiv2018

The landscape of incident disease risk for the biomarker GlycA and its mortality stratification in angiography patients

Integration of systems-level biomolecular information with electronic health records has led to the discovery of robust blood-based biomarkers predictive of future health and disease. Of recent intense interest is the GlycA biomarker, a complex nuclear magnetic resonance (NMR) spectroscopy signal reflective of acute and chronic inflammation, which predicts long term risk of diverse outcomes including cardiovascular disease, type 2 diabetes, and all-cause mortality. To systematically explore the specificity of the disease burden indicated by GlycA we analysed the risk for 468 common incident hospitalization and mortality outcomes occurring during an 8-year follow-up of 11,861 adults from Finland. Our analyses of GlycA replicated known associations, identified associations with specific cardiovascular disease outcomes, and uncovered new associations with risk of alcoholic liver disease (meta-analysed hazard ratio 2.94 per 1-SD, P=5x10-6), chronic renal failure (HR=2.47, P=3x10-6), glomerular diseases (HR=1.95, P=1x10-6), chronic obstructive pulmonary disease (HR=1.58, P=3x10-5), inflammatory polyarthropathies (HR=1.46, P=4x10-8), and hypertension (HR=1.21, P=5x10-5). We further evaluated GlycA as a biomarker in secondary prevention of 12-year cardiovascular mortality in 900 angiography patients with suspected coronary artery disease. We observed hazard ratios of 4.87 and 5.00 for 12-year mortality in angiography patients in the fourth and fifth quintiles by GlycA levels demonstrating the prognostic potential of GlycA for identification of high mortality-risk individuals. Both GlycA and C-reactive protein had shared as well as independent contributions to mortality hazard, emphasising the importance of chronic inflammation in secondary prevention of cardiovascular disease.

epidemiology↗

bioRxiv2018

Body mass index and mortality in UK Biobank: revised estimates using Mendelian randomization

ObjectiveObtain estimates of the causal relationship between different levels of body mass index (BMI) and mortality.\n\nMethodsMendelian randomization (MR) was conducted using genotypic variation reliably associated with BMI to test the causal effect of increasing BMI on all-cause and cause-specific mortality in participants of White British ancestry in UK Biobank.\n\nResultsMR analyses supported existing evidence for a causal association between higher levels of BMI and greater risk of all-cause mortality (hazard ratio (HR) per 1kg/m2: 1.02; 95% CI: 0.97,1.06) and mortality from cardiovascular diseases (HR: 1.12; 95% CI: 1.02, 1.23), specifically coronary heart disease (HR: 1.19; 95% CI: 1.05, 1.35) and those other than stroke/aortic aneurysm (HR: 1.13; 95% CI: 0.93, 1.38), stomach cancer (HR: 1.30; 95% CI: 0.91, 1.86) and oesophageal cancer (HR: 1.08; 95% CI: 0.84, 1.38), and with decreased risk of lung cancer mortality (HR: 0.97; 95% CI: 0.84, 1.11). Sex-stratified analyses supported a causal role of higher BMI in increasing the risk of mortality from bladder cancer in males and other causes in females, but in decreasing the risk of respiratory disease mortality in males. The characteristic J-shaped observational association between BMI and mortality was visible with MR analyses but with a smaller value of BMI at which mortality risk was lowest and apparently flatter over a larger range of BMI.\n\nConclusionResults support a causal role of higher BMI in increasing the risk of all-cause mortality and mortality from other causes. However, studies with greater numbers of deaths are needed to confirm the current findings.

epidemiology↗

bioRxiv2018

Mechanisms for European Bat Lyssavirus subtype 1 persistence in non-synanthropic bats: insights from a modeling study

BackgroundLyssaviruses are pathogens of bat origin of considerable zoonotic concern being the causative agent for rabies disease, however our understanding of their persistence in bat populations remains very scarce.\n\nMethodsLeveraging existing data from an extensive ecological field survey characterizing Myotis myotis and Miniopterus schreibersii bat species in the Catalonia region, we develop a data-driven spatially explicit metapopulation model to identify the mechanisms of the empirically observed persistence of European Bat Lyssavirus subtype 1 (EBLV-1), the most common lyssavirus species found in Europe. We consider different disease progressions accounting for lethal infection, immunity waning, and potential cross-species transmission when the two populations share the same refuge along the migratory path of M. schreibersii.\n\nResultsWe find that EBLV-1 persistence relies on host spatial structure through the migratory nature of M. schreibersii bats, on cross-species mixing with M. myotis population, and on a disease progression leading to survival of infected animals followed by temporary immunity. The higher fragmentation along the northern portion of the migratory path is necessary to maintain EBLV-1 sustained circulation in both species, whereas persistence would not be ensured in the single colony of M. myotis. Our study provides first estimates for the EBLV-1 transmission potential in M. schreibersii bats and average duration of immunity in the host species, yielding values compatible with previous empirical observations in M. myotis bats.\n\nConclusionsHabitats sharing and the strong spatial component of EBLV-1 transmission dynamics identified as key drivers in this ecological context may help understanding the observed spatial diffusion of the virus at a larger scale and across a diverse range of host species, through long-range migration and seeding of local populations. Our approach can be readily adapted to other zoonotic pathogens of public health concern.

epidemiology↗

bioRxiv2018

Hierarchical modeling of the effect of pre-exposure prophylaxis on HIV in the US

1.AO_SCPLOWBSTRACTC_SCPLOWIn this paper we present a differential equation model stratified by behavioral risk and sexual activity. Some susceptible individuals have higher rates of risky behavior that increase their chance of contracting the disease. Infected individuals can be considered to be generally sexually active or inactive. The sexually active infected population is at higher risk of transmitting the disease to a susceptible individual. We further divide the sexually active population into diagnosed or undiagnosed infected individuals. We define model parameters for both the national and the urban case. These parameter sets are used to study the predicted population dynamics over the next 5 years. Our results indicate that the undiagnosed high risk infected group is the largest contributor to the epidemic. Finally, we apply a preventative medication protocol to the susceptible population and observe the effective reduction in the infected population. The simulations suggest that preventative medication effectiveness extends outside of the group that is taking the drug (herd immunity). Our models suggest that a strategy targeting the high risk undiagnosed infected group would have the largest impact in the next 5 years. We also find that such a protocol has similar effects for the national as the urban case, despite the smaller sexual network found in rural areas.

epidemiology↗

bioRxiv2018

Appraising the causal relevance of DNA methylation for risk of lung cancer

DNA methylation changes in peripheral blood have been identified in relation to lung cancer risk. However, the causal nature of these associations remains to be fully elucidated. Meta-analysis of four epigenome-wide association studies (918 cases, 918 controls) revealed differential methylation at 16 CpG sites (FDR < 0.05) in relation to lung cancer risk. A two-sample Mendelian randomization analysis, using genetic instruments for methylation at 14 of the 16 CpG sites, and 29,863 cases and 55,586 controls from the TRICL-ILCCO lung cancer consortium, was performed to appraise the causal role of methylation at these sites on lung cancer. This approach provided little evidence that DNA methylation in peripheral blood at the 14 CpG sites play a causal role in lung cancer development, including for cg05575921 AHRR, where methylation is strongly associated with lung cancer risk. Further studies are needed to investigate the causal role played by DNA methylation in lung tissue.

epidemiology↗

bioRxiv2018

The median and the mode as robust meta-analysis methods in the presence of small study effects

Meta-analyses based on systematic literature reviews are commonly used to obtain a quantitative summary of the available evidence on a given topic. Despite its attractive simplicity, and its established position at the summit of the evidence-based medicine hierarchy, the reliability of any meta-analysis is largely constrained by the quality of its constituent studies. One major limitation is small study effects, whose presence can often easily be detected, but not so easily adjusted for. Here, robust methods of estimation based on the median and mode are proposed as tools to increase the reliability of findings in a meta-analysis. By re-examining data from published meta-analyses, and by conducting a detailed simulation study, we show that these two simple methods offer notable robustness to a range of plausible bias mechanisms, without making any explicit modelling assumptions. In conclusion, when performing a meta-analysis with suspected small study effects, we recommend reporting the mean, median and modal pooled estimates as a simple but informative sensitivity analyses.

epidemiology↗

bioRxiv2018

Tendency towards being a “Morning person” increases risk of Parkinson’s disease: evidence from Mendelian randomisation

BackgroundCircadian rhythm may play a role in neurodegenerative diseases such as Parkinsons disease (PD). Chronotype is the behavioural manifestation of circadian rhythm and Mendelian randomisation (MR) involves the use of genetic variants to explore causal effects of exposures on outcomes. This study aimed to explore a causal relationship between chronotype and coffee consumption on risk of PD.\n\nMethodsTwo-sample MR was undertaken using publicly available GWAS data. Associations between genetic instrumental variables (IV) and \"morning person\" (one extreme of chronotype) were obtained from the personal genetics company 23andMe, Inc., and UK Biobank, and consisted of the per-allele odds ratio of being a \"morning person\" for 15 independent variants. The per-allele difference in log-odds of PD for each variant was estimated from a recent meta-analysis. The inverse variance weight method was used to estimate an odds ratio (OR) for the effect of being a \"morning person\" on PD. Additional MR methods were used to check for bias in the IVW estimate, arising through violation of MR assumptions. The results were compared to analyses employing a genetic instrument of coffee consumption, because coffee consumption has been previously inversely linked to PD.\n\nFindingsBeing a \"morning person\" was causally linked with risk of PD (OR 1*27; 95% confidence interval 1*06-1*51; p=0*012). Sensitivity analyses did not suggest that invalid instruments were biasing the effect estimate and there was no evidence for a reverse causal relationship between liability for PD and chronotype. There was no robust evidence for a causal effect of high coffee consumption using IV analysis, but the effect was imprecisely estimated (OR 1*12; 95% CI 0*89-1*42; p=0*22).\n\nInterpretationWe observed causal evidence to support the notion that being a \"morning person\", a phenotype driven by the circadian clock, is associated with a higher risk of PD. Further work on the mechanisms is warranted and may lead to novel therapeutic targets.\n\nFundingNo specific funding source.

epidemiology↗

bioRxiv2018

Estimating the proportion of bystander selection for antibiotic resistance in the US

Bystander selection -- the selective pressures exerted by antibiotics on microbial flora that are not the target pathogen of treatment -- is critical to understanding the total impact of broad-spectrum antibiotic use; however, to our knowledge, this effect has never been quantified. Using the 2010-2011 National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey (NAMCS/NHAMCS), the Human Microbiome Project, and additional carriage and etiological data from existing literature, we estimate the magnitude of bystander selection for a range of clinically relevant antibiotic-species pairs as the proportion of all exposures of an antibiotic experienced by a species for conditions in which that species was not the causative pathogen (\"proportion of bystander exposures\"). For outpatient prescribing in the United States, we find that this proportion over all included antibiotics is over 80% for 8 out of 9 organisms of interest. Low proportions of bystander exposure are often associated with infrequent bacterial carriage or a high proportion of antibiotic prescribing focused on conditions caused by the species of interest. Using the proportion of bystander exposures, we roughly estimate that S. aureus and E. coli may benefit from 90.7% and 99.7%, respectively, of the estimated reduction in antibiotic use due to pneumococcal conjugate vaccination, despite not being the pathogen targeted by the vaccine. These results underscore the importance of considering antibiotic exposures to bystanders, in addition to the targeted pathogen, in measuring the impact of antibiotic resistance interventions.\n\nSignificance StatementThe forces that contribute to changing population prevalence of antibiotic resistance are not well understood. Bystander selection -- the inadvertent pressures imposed by antibiotics on the microbial flora other than the pathogen targeted by treatment -- is hypothesized to be a major factor in the propagation of antibiotic resistance, but its extent has not been characterized. We estimate the proportion of bystander exposures across a range of antibiotics and organisms and describe factors driving variability of these proportions. Impact estimates for antibiotic resistance interventions, including vaccination, are often limited to effects on a target pathogen. However, the reduction of antibiotic treatment for illnesses caused by the target pathogen may have the broader potential to decrease bystander selection pressures for resistance on many other organisms.

epidemiology↗

bioRxiv2018

HERD IMMUNITY TO EBOLAVIRUSES IS NOT A REALISTIC TARGET FOR CURRENT VACCINATION STRATEGIES

The recent West African Ebola virus pandemic, which affected >28,000 individuals increased interest in anti-Ebolavirus vaccination programs. Here, we systematically analyzed the requirements for a prophylactic vaccination program based on the basic reproductive number (R0, i.e. the number of secondary cases that result from an individual infection). Published R0 values were determined by a systematic literature research and ranged from 0.37 to 20. R0s [≥]4 realistically reflected the critical early outbreak phases and superspreading events. Based on the R0, the herd immunity threshold (Ic) was calculated using the equation Ic=1-(1/R0). The critical vaccination coverage (Vc) needed to provide herd immunity was determined by including the vaccine effectiveness (E) using the equation Vc=Ic/E. At an R0 of 4, the Ic is 75% and at an E of 90%, more than 80% of a population need to be vaccinated to establish herd immunity. Such vaccination rates are currently unrealistic because of resistance against vaccinations, financial/ logistical challenges, and a lack of vaccines that provide long-term protection against all human-pathogenic Ebolaviruses. Hence, outbreak management will for the foreseeable future depend on surveillance and case isolation. Clinical vaccine candidates are only available for Ebola viruses. Their use will need to be focused on health care workers, potentially in combination with ring vaccination approaches.

epidemiology↗

bioRxiv2018

The Healthy Pregnancy Research Program: Transforming Pregnancy Research Through a ResearchKit App

Although maternal morbidity and mortality in the U.S. is among the worst of developed countries, pregnant women have been under-represented in research studies, resulting in deficiencies in evidence-based guidance for treatment. There are over two billion smartphone users worldwide, enabling researchers to easily and cheaply conduct extremely large-scale research studies through smartphone apps, especially among pregnant women in whom app use is exceptionally high, predominantly as an information conduit. We developed the first pregnancy research app that is embedded within an existing, popular pregnancy app for self-management and education of expectant mothers. Through the large-scale and simplified collection of survey and sensor generated data via the app, we aim to improve our understanding of factors that promote a healthy pregnancy for both the mother and developing fetus. From the launch of this cohort study on March 16, 2017 through December 17, 2017, we have enrolled 2,058 pregnant women from all 50 states. Our study population is diverse geographically and demographically, and fairly representative of U.S. population averages. We have collected 14,045 individual surveys and 11,669 days of sleep, activity, blood pressure and heart rate measurements during this time. On average, women stayed engaged in the study for 59 days and 45 percent who reached their due date filled out the final outcome survey. During the first nine months, we demonstrated the potential for a smartphone-based research platform to capture an ever-expanding array of longitudinal, objective and subjective participant-generated data from a continuously growing and diverse population of pregnant women.\n\nFundingSupported in part by the National Institutes of Health (NIH)/National Center for Advancing Translational Sciences grant UL1TR001114 and a grant from the Qualcomm Foundation.

epidemiology↗

bioRxiv2018

Characterizing Subpopulations with Better Response to Treatment Using Observational Data - an Epilepsy Case Study

Electronic health records and health insurance claims, providing observational data on millions of patients, offer great opportunities, and challenges, for population health studies. The objective of this study is identifying subpopulations that are likely to benefit from a given treatment using observational data. We refer to these subpopulations as \"better responders\" and focus on characterizing these using linear scores with a limited number of variables. Building upon well-established causal inference techniques for analyzing observational data, we propose two algorithms that generate such scores for identifying better responders, as well as methods for evaluating and comparing these scores. We applied our methodology to a large dataset of ~135,000 epilepsy patients derived from claims data. Out of this sample, 85,000 were used to characterize subpopulations with better response to next-generation (\"Newer\") anti-epileptic drugs (AEDs), compared to an alternative treatment by first-generation (\"Older\") AEDs. The remaining 50,000 epilepsy patients were then used to evaluate our scores. Our results demonstrate the ability of our scores to identify large subpopulations of epilepsy patients with significantly better response to newer AEDs.

epidemiology↗

bioRxiv2018

Socioeconomic status of indigenous peoples with active tuberculosis in Brazil: a principal components analysis

Indigenous people usually live in precarious conditions and suffer a disproportionally burden of tuberculosis in Brazil. To characterize the socioeconomic status of indigenous peoples with active tuberculosis in Brazil, this cross-sectional study included all Amerindians that started tuberculosis treatment between March 2011 and December 2012 in four municipalities of Mato Grosso do Sul state (Central-Western region). We tested the approach using principal components analysis (PCA) to create three socioeconomic indexes (SEI) using groups of variables: household characteristics, ownership of durable goods, and both. Cases were then classified into tertiles, with the 1st tertile representing the most disadvantaged. A total of 166 indigenous cases of tuberculosis were included. 31.9% did not have durable goods. 25.9% had family bathroom, 9.0% piped water inside the house and 53.0% electricity, with higher proportions in Miranda and Aquidauana. Houses were predominantly made using natural materials in Amambai and Caarapo. Miranda and Aquidauana had more cases in the 3rd tertile (92.3%) and Amambai, in the 1st tertile (37.7%). The indexes showed similar results and consistency for socioeconomic characterization. The percentage of people in the 3rd tertile increased with years of schooling. The majority in the 3rd tertile received Bolsa Familia, a social welfare programme. This study confirmed the applicability of the PCA using information on household characteristics and ownership of durable goods for socioeconomic characterization of indigenous groups and provided important evidence of the unfavorable living conditions of Amerindians with tuberculosis in Mato Grosso do Sul.

epidemiology↗

bioRxiv2018

Chorioamnionitis as a risk factor for retinopathy of prematurity: an updated systematic review and meta-analysis

The role of chorioamnionitis (CA) in the development of retinopathy of prematurity (ROP) is difficult to establish, because CA-exposed and CA-unexposed infants frequently present different baseline characteristics. We performed an updated systematic review and meta-analysis of studies reporting on the association between CA and ROP. We searched PubMed and EMBASE for relevant articles. Studies were included if they examined preterm or very low birth weight (VLBW, <1500g) infants and reported primary data that could be used to measure the association between exposure to CA and the presence of ROP. Of 748 potentially relevant studies, 50 studies met the inclusion criteria (38,986 infants, 9,258 CA cases). Meta-analysis showed a significant positive association between CA and any stage ROP (odds ratio [OR] 1.39, 95% confidence interval [CI] 1.11 to 1.74). CA was also associated with severe (stage [≥]3) ROP (OR 1.63, 95% CI 1.41 to 1.89). Exposure to funisitis was associated with a higher risk of ROP than exposure to CA in the absence of funisitis. Additional meta-analyses showed that infants exposed to CA had lower gestational age (GA) and lower birth weight (BW). Meta-regression showed that lower GA and BW in the CA-exposed group was significantly associated with a higher risk of ROP. In conclusion, our study confirms that CA is a risk factor for developing ROP. However, part of the effects of CA on the pathogenesis of ROP may be mediated by the role of CA as an etiological factor for very preterm birth.

epidemiology↗

bioRxiv2018

Differential human mobility and local variation in human infection attack rate

Infectious disease transmission in animals is an inherently spatial process in which a hosts home location and their social mixing patterns are important, with the mixing of infectious individuals often different to that of susceptible individuals. Although incidence data for humans have traditionally been aggregated into low-resolution data sets, modern representative surveillance systems such as electronic hospital records generate high volume case data with precise home locations. Here, we use a high resolution gridded spatial transmission model of arbitrary resolution to investigate the theoretical relationship between population density, differential population movement and local variability in incidence. We show analytically that uniform local attack rate is only possible for individual pixels in the grid if susceptible and infectious individuals move in the same way. Using a population in Guangdong, China, for which a robust quantitative description of movement is available (a movement kernel), and a natural history consistent with pandemic influenza; we show that for the estimated kernel, local cumulative incidence is positively correlated with population density when susceptible individuals are more connected in space than infectious individuals. Conversely, when infectious individuals are more connected, local cumulative incidence is negatively correlated with population density. The amplitude of correlation is substantial for the estimated kernel. However, the strength and direction of correlation changes sign for other kernel parameter values. These results describe a precise relationship between the spatio-social mixing of infectious and susceptible individuals and local variability in attack rates, and suggest a plausible mechanism for the counter-intuitive scenario in which local incidence is lower on average in less dense populations. Also, these results suggest that if spatial transmission models are implemented at high resolution to investigate local disease dynamics, including micro-tuning of interventions, the underlying detailed assumptions about the mechanisms of transmission become more important than when similar studies are conducted at larger spatial scales.\n\nAuthor SummaryWe know that some places have higher rates of infectious disease than others. However, at the moment, we usually only measure these differences for large towns and cities. With modern data, such as those we can get from mobile phones, we can measure rates of infection at much smaller scales. In this paper, we used a computer simulation of an epidemic to propose ways that rates of incidence in small local areas might be related to population density. We found that if infectious people are better connected than non-infectious people, perhaps because they receive visitors, then, on average, higher density areas would have lower rates of infection. If infectious people were less connected than non-infectious people then higher density areas would have higher rates of infection. As data get more accurate, this type of analysis will allow us to propose and test ways to optimize interventions such as the delivery of vaccines and antivirals during a pandemic.

epidemiology↗

bioRxiv2018

A systematic review of social contact surveys to inform transmission models of close contact infections

Social contact data are increasingly being used to inform models for infectious disease spread with the aim of guiding effective policies on disease prevention and control. In this paper, we undertake a systematic review of the study design, statistical analyses and outcomes of the many social contact surveys that have been published. Our primary focus is to identify the designs that have worked best and the most important determinants and to highlight the most robust [fi]ndings.\n\nTwo publicly accessible online databases were systematically searched for articles regarding social contact surveys. PRISMA guidelines were followed as closely as possible. In total, 64 social contact surveys were identi[fi]ed. These surveys were conducted in 24 countries, and more than 80% of the surveys were conducted in high-income countries. Study settings included general population (58%), schools/universities (37%) and health care/conference/research institutes (5%). The majority of studies did not focus on a speci[fi]c age group (38%), whereas others focused on adults (32%) or children (19%). Retrospective and prospective designs were used mostly (45% and 41% of the surveys, respectively) with 6% using both for comparison purposes. The de[fi]nition of a contact varied among surveys, e.g. a non-physical contact may require conversation, close proximity or both. Age, time schedule (e.g., weekday/weekend) and household size were identi[fi]ed as relevant determinants for contact pattern across a large number of studies. The surveys present a wide range of study designs. Throughout, we found that the overall contact patterns were remarkably robust for the study details. By considering the most common approach in each aspect of design (e.g., sampling schemes, data collection, de[fi]nition of contact), we could identify a common practice approach that can be used to facilitate comparison between studies and for benchmarking future studies.

epidemiology↗

bioRxiv2018

Trends in outpatient antibiotic prescribing practice among US older adults, 2011-2015: an observational study

Structured abstractO_ST_ABSObjectiveC_ST_ABSTo identify temporal trends in outpatient antibiotic use and antibiotic prescribing practice among older adults.\n\nDesignObservational study using United States Medicare administrative claims during 2011-2015. Trends in antibiotic use were estimated using multivariable regression adjusting for beneficiaries demographic and clinical covariates.\n\nSettingMedicare.\n\nParticipants4.6 million Medicare beneficiaries from a nationwide, 20% sample of fee-forservice Medicare beneficiaries [≥]65 years old.\n\nMain outcome measurementsOverall rates of antibiotic prescription claims, rates of appropriate and inappropriate prescribing, rates for each of the most frequently prescribed antibiotics, and rates of antibiotic claims associated with specific diagnoses.\n\nResultsAntibiotic claims fell from 1362.2 to 1361.6 claims per 1,000 beneficiaries per year during 2011-2015, an overall 0.2% decrease (95% CI 0.07-0.32). Inappropriate antibiotic claims fell from 552 to 533 claims per 1,000 beneficiaries, a 4.1% decrease (CI 3.9-4.3). Individual antibiotics had heterogeneous changes in use. For example, azithromycin claims per beneficiary decreased by 18.4% (CI 18.2-18.7) while levofloxacin claims increased by 28.1% (CI 27.5-28.6). Azithromycin use associated with each of the potentially appropriate and inappropriate respiratory diagnoses we considered decreased, while levofloxacin use associated with each of those diagnoses increased.\n\nConclusionAmong US Medicare beneficiaries, overall antibiotic use and inappropriate use declined modestly, but individual drugs experienced divergent changes in use. Trends in drug use across indications were stronger than trends in use for individual indications, suggesting that guidelines and concerns about antibiotic resistance were not major drivers of change in antibiotic use.

epidemiology↗

bioRxiv2018

Decline in pneumococcal disease in unimmunized adults is associated with vaccine-associated protection against colonization in toddlers and preschool-aged children

Vaccinating children with pneumococcal conjugate vaccines disrupts transmission, reducing disease rates in unvaccinated adults. When considering changes in vaccination strategies (e.g., removing doses), it is critical to understand which groups of children contribute most to transmission. We used data from Israel to evaluate how the build-up of vaccine-associated immunity in children was associated with declines in IPD due to vaccine-targeted serotypes in unimmunized adults. Data on vaccine uptake and prevalence of colonization with PCV-targeted serotypes were obtained from a unique study conducted among children visiting an emergency department in southern Israel and from surveys of colonization from central Israel. Data on invasive pneumococcal disease in adults were obtained from a nationwide surveillance study. We compared the trajectory of decline of IPD due to PCV-targeted serotypes in adults with the trajectory of decline of colonization prevalence and trajectory of increase in vaccine-derived protection against pneumococcal carriage among different age groupings of children. The declines in IPD in adults were most closely associated with the declines in colonization and increased vaccination coverage in children in the range of 36-59 months of age. This suggests that preschool-aged children, rather than infants, are responsible for maintaining the indirect benefits of PCVs.

epidemiology↗

bioRxiv2018

A Novel Household Water Insecurity Scale: Procedures and Psychometric Analysis among Postpartum Women in Western Kenya

Our ability to measure household-level food insecurity has revealed its critical role in a range of physical, psychosocial, and health outcomes. Currently, there is no analogous, standardized instrument for quantifying household-level water insecurity, which prevents us from understanding both its prevalence and consequences. Therefore, our objectives were to develop and validate a household water insecurity scale appropriate for use in our cohort in western Kenya. We used a range of qualitative techniques to develop a preliminary set of 29 household water insecurity questions, and administered those questions at 15 and 18 months postpartum, concurrent with a suite of other survey modules. These data were complemented by data on quantity of water used and stored, and microbiological quality. Inter-item and item-total correlations were performed to reduce scale items to 20. Exploratory factor and parallel analyses were used to determine the latent factor structure; a unidimensional scale was hypothesized and tested using confirmatory factor and bifactor analyses, along with multiple statistical fit indices. Reliability was assessed using Cronbachs alpha and the coefficient of stability, which produced a coefficient alpha of 0.97 at 15 and 18 months postpartum and a coefficient of stability of 0.62. Predictive, convergent and discriminant validity of the final household water insecurity scale were supported, based on relationships with food insecurity, perceived stress, per capita household water use, and time and money spent acquiring water. The resultant scale is a valid and reliable instrument. It can be used in this setting to test a range of hypotheses about the role of household water insecurity in numerous physical and psychosocial health outcomes, to identify the households most vulnerable to water insecurity, and to evaluate the effects of water-related interventions. To extend its applicability, we encourage efforts to develop a cross-culturally valid scale using robust qualitative and quantitative techniques.

epidemiology↗