SEARCH · bioRxiv Science

Results for “epidemiology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,225 records · Page 68Linked to original sources

bioRxiv2017

The impact of regular school closure on seasonal influenza epidemics: a data-driven spatial transmission model for Belgium

School closure is often considered as an option to mitigate influenza epidemics because of its potential to reduce transmission in children and then in the community. The policy is still however highly debated because of controversial evidence. Moreover, the specific mechanisms leading to mitigation are not clearly identified.\n\nWe introduced a stochastic spatial age-specific metapopulation model to assess the role of holiday-associated behavioral changes and how they affect seasonal influenza dynamics. The model is applied to Belgium, parameterized with country-specific data on social mixing and travel, and calibrated to the 2008/2009 influenza season. It includes behavioral changes occurring during weekend vs. weekday, and holiday vs. school-term. Several experimental scenarios are explored to identify the relevant social and behavioral mechanisms.\n\nStochastic numerical simulations show that holidays considerably delay the peak of the season and mitigate its impact. Changes in mixing patterns are responsible for the observed effects, whereas changes in travel behavior do not alter the epidemic. Weekends are important in slowing down the season by periodically dampening transmission. Christmas holidays have the largest impact on the epidemic, however later school breaks may help in reducing the epidemic size, stressing the importance of considering the full calendar. An extension of the Christmas holiday of 1 week may further mitigate the epidemic.\n\nChanges in the way individuals establish contacts during holidays are the key ingredient explaining the mitigating effect of regular school closure. Our findings highlight the need to quantify these changes in different demographic and epidemic contexts in order to provide accurate and reliable evaluations of closure effectiveness. They also suggest strategic policies in the distribution of holiday periods to minimize the epidemic impact.

epidemiology↗

bioRxiv2017

Systemic Inflammation Mediates the Relationship between Obesity and Health Related Quality of Life

BackgroundAt the population level, obesity has been reported to be positively associated with low-level chronic inflammation, and negatively associated with several indices of health-related quality of life (HRQOL). It is however not clear if obesity-associated inflammation is partly responsible for the observed negative associations between obesity and HRQOL. The present study investigates this question by testing the hypothesis that systemic inflammation is a mediator of the observed association between obesity and a specific HRQOL index called \"healthy days\", as measured via a subset of the CDC HRQOL-4 questionnaire.\n\nMethodsDemographic, body mass index (BMI), C-reactive protein (CRP), inflammatory disease status, medication use, smoking, and HRQOL data were obtained from NHANES (2005-2008) and analyzed using sampling-weighted generalized linear models. Both main effects and interaction effects were analyzed to evaluate possible mediator-outcome confounding. Model robustness was tested via sensitivity analysis. Prior to model development, data was subjected to multiple imputation in order to mitigate information loss from survey non-response. Averaged results from the imputed datasets were reported in the form of odds ratios (OR) and confidence intervals (CI).\n\nResultsObesity (BMI >30kg/m2) was positively associated with poor physical healthy days (OR: 1.59, 95% CI: 1.15-2.21) in unadjusted models. Elevated and clinically raised levels of the inflammation marker CRP were also positively associated with poor physical healthy days (OR= 1.61, 95% CI: 1.23-2.12, and OR= 2.45, 95% CI: 1.84-3.26, respectively); additionally clinically raised CRP was positively associated with mental unhealthy days (OR= 1.66, 95% CI: 1.26-2.19). The association between obesity and physical HRQOL was rendered non-significant in models including CRP. Association between elevated and clinically raised CRP and physical unhealthy days remained significant even after adjustment for obesity or inflammation-modulating covariates (OR= 1.36, 95% CI :1.02-1.82, and OR= 1.75, 95% CI: 1.21-2.54, respectively).\n\nConclusionsSystemic inflammation is a significant mediator of the association between obesity and physical unhealthy days. and is also an independent determinant of physical and mental unhealthy days. Importantly, elevated inflammation below the clinical threshold is also negatively associated with physical healthy days and may warrant more attention from a population health perspective than currently appreciated.

epidemiology↗

bioRxiv2017

Conditioning on a collider may induce spurious associations: Do the results of Gale et al. (2017) support a protective effect of neuroticism in population sub-groups?

Introduction Introduction Methods Results Discussion References Gale and colleagues (Gale et al., 2017) examined the association between neuroticism and mortality in a large sample (N > 300,000) drawn from the UK Biobank study (Sudlow et al., 2015). They observed that neuroticism was associated with an increase in all-cause mortality, but that following adjustment for self-rated health neuroticism was associated with a reduction in all-cause mortality. Further analyses stratified on self-rated health suggested that higher neuroticism was associated with reduced mortality only among those with fair or poor self-rated health. The authors conclude that neuroticism may have protective effects among certain sub-groups, and finding that generated substantial interest (TIME, 2017).\n\nThe availability ...

epidemiology↗

bioRxiv2017

Close encounters between infants and household members measured through wearable proximity sensors

Describing and understanding close proximity interactions between infant and family members can provide key information on transmission opportunities of respiratory infections within households. Among respiratory infections, pertussis represents a public health priority. Pertussis infection can be particularly harmful to young, unvaccinated infants and for these patients, family members represent the main sources of transmission. Here, we report on the use of wearable proximity sensors based on RFID technology to measure face-to-face proximity between family members within 16 households with infants younger than 6 months for 2-5 consecutive days of data collection. The sensors were deployed over the course of approximately 1 year, in the context of a national research project aimed at the improvement of infant pertussis prevention strategies. We recorded 5,958 contact events between 55 individuals: 16 infants, 4 siblings, 31 parents and 4 grandparents. The contact networks showed a heterogeneous distribution of the cumulative time spent in proximity with the infant by family members. Most of the contacts occurred between the infant and other family members (70%), and many contacts were observed between infants and adults, in particular between infant and mother, followed by father, siblings and grandparents. A larger number of contacts and longer contact durations between infant and other family members were observed in families adopting exclusive breastfeeding, compared to families in which the infant receives artificial or mixed feeding.\n\nOur results demonstrate how a high-resolution measurement of contact matrices within infants households is feasible using wearable proximity sensing devices. Moreover, our findings suggest the mother is responsible for the large majority of the infants contact pattern, thus being the main potential source of infection for a transmissible disease. As the contribution to the infants contact pattern by other family members is very variable, vaccination against pertussis during pregnancy is probably the best strategy to protect young, unvaccinated infants.

epidemiology↗

bioRxiv2017

Using an agent-based sexual-network model to guide mitigation efforts for controlling chlamydia

We create and analyze a stochastic heterosexual agent-based bipartite network model to help understand the spread of chlamydia trachomatis. Chlamydia is the most common sexually transmitted infection in the United States and is major cause of infertility, pelvic inflammatory disease, and ectopic pregnancy among women. We use an agent-based network model to capture the complex heterogeneous assortative sexual mixing network of men and women. Both long-term and casual partnerships are modeled with different sexual contact frequencies and condom use. We use simulations to compare the effectiveness of intervention strategies based on randomly screening people for infection, treating the partners of infected people, and rescreening for infection after treatment. We compare the difference between treating the partners of an infected person both with, and without, testing them first for infection. The highest prevalence is among young sexually active individuals. We calibrate the model parameters to agree with recent survey data showing chlamydia prevalence of 14% of the women and 9% of the men in the 15 - 25 year-old African American residents of New Orleans, Louisiana. We observed that although increased chlamydia screening and treating most of the partners of infected people will reduce the incidence, these mitigations alone are not sufficient to control the epidemic. The model predicts that the current epidemic can brought under control once over half of the partners of infected people are tested and treated.

epidemiology↗

bioRxiv2017

A frailty index for UK Biobank participants

BackgroundFrailty indices (FIs) measure variation in health between aging individuals. Researching FIs in resources with large-scale genetic and phenotypic data will provide insights into the causes and consequences of frailty. Thus, we aimed to develop an FI using UK Biobank data, a cohort study of 500,000 middle-aged and older adults.\n\nMethodsAn FI was calculated using 49 self-reported questionnaire items on traits covering health, presence of diseases and disabilities, and mental wellbeing, according to standard protocol. We used multiple imputation to derive FI values for the entire eligible sample in the presence of missing item data (N =500,336). To validate the measure, we assessed associations of the FI with age, sex, and risk of all-cause mortality (follow-up [≤] 9.7 years) using linear and Cox proportional hazards regression models.\n\nResultsMean FI in the cohort was 0.125 (standard deviation = 0.075), and there was a curvilinear trend towards higher values in older participants. FI values were also marginally higher on average in women than men. In survival models, 10% higher baseline frailty (i.e. a 0.1 FI increment) was associated with higher risk of death (hazard ratio (HR) = 1.65; 95% confidence interval: 1.62, 1.68). Associations were stronger in younger participants than in old, and in men compared to women (HRs: 1.72 vs. 1.56, respectively).\n\nConclusionsThe FI is a valid measure of frailty in UK Biobank. The cohorts data are open-access for researchers to use, and we provide script for deriving this tool to facilitate future studies on frailty.

epidemiology↗

bioRxiv2017

Disentangling reporting and disease transmission using second order statistics

Second order statistics such as the variance and autocorrelation can be useful indicators of the stability of randomly perturbed systems, in some cases providing early warning of an impending, dramatic change in the systems dynamics. One specific application area of interest is the surveillance of infectious diseases. In the context of disease (re-)emergence, a goal could be to have an indicator that is informative of whether the system is approaching the epidemic threshold, a point beyond which a major outbreak becomes possible. Prior work in this area has provided some proof of this principle but has not analytically treated the effect of imperfect observation on the behavior of indicators. This work provides expected values for several moments of the number of reported cases, where reported cases follow a binomial or negative binomial distribution with a mean based on the number of deaths in a birth-death-immigration process over some reporting interval. The normalized second factorial moment and the decay time of the number of case reports are two indicators that are insensitive to the reporting probability. Simulation is used to show how this insensitivity could be used to distinguish a trend of increased reporting from a trend of increased transmission. The simulation study also illustrates both the high variance of estimates and the possibility of reducing the variance by avE. ODea eraging over an ensemble of estimates from multiple time series.

epidemiology↗

bioRxiv2017

Performance of serological antibody tests for bovine tuberculosis in cattle from infected herds in Northern Ireland

The ability to accurately identify infected hosts is the cornerstone of effective disease control and eradication programs. In the case of bovine tuberculosis, caused by infection with the pathogen Mycobacterium bovis, accurately identifying infected individual animals has been challenging as all available tests exhibit less than 100% discriminatory ability. Here we assess the utility of three serological tests and assess their performance relative to skin test (Single Intradermal Comparative Cervical Tuberculin; SICCT), gamma-interferon (IFN{gamma}) and post-mortem results in a Northern Ireland setting. Furthermore, we describe a case-study where one test was used in conjunction with statutory testing.\n\nSerological tests using samples taken prior to SICCT disclosed low proportions of animals as test positive (mean 3% positive), despite the cohort having high proportions with positive SICCT test under standard interpretation (121/921; 13%) or IFN{gamma} (365/922; 40%) results. Furthermore, for animals with a post-mortem record (n=286), there was a high proportion with TB visible lesions (27%) or with laboratory confirmed infection (25%). As a result, apparent sensitivities within this cohort was very low ([≤]15%), however the tests succeeded in achieving very high specificities (96-100%). During the case-study, 7/670 (1.04%) samples from SICCT negative animals from a large chronically infected herd were serology positive, with a further 10 animals being borderline positive (17/670; 2.54%). 9/17 of these animals were voluntarily removed, none of which were found to be infected (-lesions/-bacteriology) post-mortem; 1 serology test negative animal was subsequently lesion+ and M bovis confirmed at slaughter.\n\nImportanceEradication of bovine tuberculosis (bTB; caused by Mycobacterium bovis) has remained elusive in a number of countries despite long-term coordinated test and cull programs. This can partially be explained by the limitations of available statutory tests; therefore supplementary test platforms that identify additional infected animals would be of significant utility. Overall, during our study three serological tests did not disclose a high proportion of animals as infected in high-risk cattle herds, and exhibited limited ability to disclose animals that were positive to the statutory skin test, the gamma interferon test (IFN{gamma}), or were post-mortem confirmed with M. bovis. These serological tests could be used in a supplementary fashion to the statutory tests in particular circumstances; but may be of limited advantage where parallel use of IFN{gamma} and skin testing is performed, as these tests together tended to disclose the majority of animals with post-mortem evidence of infection in our study cohort.

epidemiology↗

bioRxiv2017

Sex-specific gene and pathway modeling of inherited glioma risk

BackgroundGenome-wide association studies (GWAS) have identified 25 risk variants for glioma, which explain ~30% of heritable risk. Most glioma histologies occur with significantly higher incidence in males. A sex-stratified analysis ide7ntified sex-specific glioma risk variants, and further analyses using gene- and pathway-based approaches may further elucidate risk variation by sex.\n\nMethodsResults from the Glioma International Case-Control Study were used as a testing set, and results from three GWAS were combined via meta-analysis and used as a validation set. Using summary statistics for autosomal SNPs found to be nominally significant (p<0.01) in a previous meta-analysis and X chromosome SNPs with nominally significant association (p<0.01), three algorithms (Pascal, BimBam, and GATES) were used to generate gene-scores, and Pascal was used to generate pathway scores. Results were considered significant when p<3.3x10-6 in [2/3] algorithms.\n\nResults25 genes within five regions and 19 genes within six regions reached the set significance threshold in at least 2/3 algorithms in males and females, respectively. EGFR and RTEL1-TNFRSF6B were significantly associated with all glioma and glioblastoma in males only, and a female-specific association in TERT, all of which remained nominally significant after conditioning on known risk loci. There were nominal associations with the Telomeres, Telomerase, Cellular Aging, and Immortality pathway in both males and females.\n\nConclusionsThese results suggest that there may be biologically relevant significant differences by sex in genetic risk for glioma. Additional gene- and pathway-based analyses may further elucidate the biological processes through which this risk is conferred.

epidemiology↗

bioRxiv2017

Searching for the causal effects of BMI in over 300 000 individuals, using Mendelian randomization

Mendelian randomization (MR) has been used to estimate the causal effect of body mass index (BMI) on particular traits thought to be affected by BMI. However, BMI may also be a modifiable, causal risk factor for outcomes where there is no prior reason to suggest that a causal effect exists. We perform a MR phenome-wide association study (MR-pheWAS) to search for the causal effects of BMI in UK Biobank (n=334 968), using the PHESANT open-source phenome scan tool. Of the 20 461 tests performed, our MR-pheWAS identified 519 associations below a stringent P value threshold corresponding to a 5% estimated false discovery rate, including many previously identified causal effects. We also identified several novel effects, including protective effects of higher BMI on a set of psychosocial traits, identified initially in our preliminary MR-pheWAS and replicated in an independent subset of UK Biobank. Such associations need replicating in an independent sample.

epidemiology↗

bioRxiv2017

Effect of antimicrobial treatment for acute otitis media on carriage of Streptococcus pneumoniae with reduced susceptibility to penicillin in a randomized, double-blind, placebo-controlled trial

BackgroundConcerns that antimicrobial treatment may foster selection and transmission of resistant bacterial lineages have led to conflicting guidelines for clinical management of common non-severe infections. However, the impact of antimicrobial treatment on colonization dynamics is poorly understood. We used data from a previously-conducted trial of amoxicillin-clavulanate therapy for acute otitis media (AOM) to understand how antimicrobial treatment impacts the acquisition and clearance of Streptococcus pneumoniae lineages with varying susceptibility to penicillin.\n\nMethods and findingsWe measured impacts of antimicrobial treatment on nasopharyngeal carriage of penicillin-susceptible S. pneumoniae (PSSP) and penicillin-non-susceptible S. pneumoniae (PNSP) lineages at end-of-treatment and 15d, 30d, and 60d after treatment in a previously-conducted randomized, double-blind, placebo-controlled trial. Analyses were not specified in the original protocol. Among children 6-35 months of age with stringently-defined AOM, 162 were assigned amoxicillin-clavulanate, and 160 were assigned placebo. Children who did not show clinical improvement received open-label antimicrobial rescue treatment with amoxicillin-clavulanate irrespective of the randomized treatment assignment, to which both patients and physicians were blinded. The intention-to-treat populations of the intervention and placebo arms thus received care resembling immediate antimicrobial therapy and watchful waiting, respectively. Immediate amoxicillin-clavulanate reduced PSSP carriage prevalence by 88% (95%CI: 76-96%) at end-of-treatment and by 27% (-3-49%) after 60d, but did not measurably alter PNSP carriage prevalence throughout follow-up. By end-of-treatment, 7% of children who carried PSSP at enrollment remained colonized in the amoxicillin-clavulanate arm, compared to 61% of PSSP carriers who received placebo; differences in carriage prevalence persisted at least 60d after treatment among children who carried PSSP at enrollment. Among children not carrying pneumococci at enrollment, amoxicillin-clavulanate reduced PSSP acquisition by >80% over 15d. Among children who carried PNSP at enrollment, no differences in carriage prevalence of S. pneumoniae, PSSP, or PNSP were detected at follow-up visits.\n\nConclusionsIn a setting with low PNSP prevalence, antimicrobial therapy for AOM conferred a selective impact on colonizing S. pneumoniae by accelerating clearance, and delaying acquisition, of penicillin-susceptible lineages. Absolute risk of carrying PNSP was unaffected by treatment (ClinicalTrials.gov: NCT00299455; Funding: NIH/NIGMS).

epidemiology↗

bioRxiv2017

Quantifying biases in test-negative studies of vaccine effectiveness

Test-negative designs have become commonplace in assessments of seasonal influenza vaccine effectiveness. Vaccine effectiveness is measured from the exposure odds ratio (OR) of vaccination among individuals seeking treatment for acute respiratory illness and receiving a laboratory test for influenza infection. This approach is widely believed to correct for differential healthcare-seeking behavior among vaccinated and unvaccinated persons. However, the relation of the measured OR to true vaccine effectiveness is poorly understood. We derive the OR under circumstances of real-world test-negative studies. The OR recovers the true vaccine direct effect when two conditions are met: (1) that individuals vaccination decisions are uncorrelated with exposure or susceptibility to infection, and (2) that vaccination confers \"all-or-nothing\" protection (whereby certain individuals have no protection while others are perfectly protected). Biased effect size estimates arise if either condition is unmet. Such bias may suggest misleading associations of the OR with time since vaccination or the force of infection of influenza. The test-negative design may also fail to correct for differential healthcare-seeking behavior among vaccinated and unvaccinated persons without stringent criteria for enrollment and testing. Our findings demonstrate a need to reassess how data from test-negative studies are interpreted for policy decisions conventionally based on causal inferences.

epidemiology↗

bioRxiv2018

Predictors of emergency department attendance following NHS 111 calls for children and young people: analysis of linked data

ObjectivesTo assess whether clinical input during calls to the NHS 111 telephone-based advice service is associated with lower rates of subsequent emergency department attendance and hospital admission.\n\nDesignAlthough NHS 111 largely employs non-clinical call handling staff to triage calls using computerised clinical decision support software, some support is available from clinical supervisors, and additionally some calls are referred to out-of-hours General Practitioners (GP). We used linked data sets to examine GP and secondary care activity following calls to NHS 111, adjusting for the patient characteristics, signs and symptoms recorded during the NHS 111 call.\n\nSettingOut-of-hours care in three areas of North West London that have an integrated approach to delivering NHS 111 and out-of-hours GP care.\n\nParticipantsNHS 111 calls for children and young people aged 15 years or under. We excluded calls that were diverted to the emergency ( 999) service or where patients were advised to go to an emergency department. This left callers who were either referred to a GP or advised to manage their health needs at home.\n\nPrimary and secondary outcome measuresThe percentage of callers attending any emergency departments, major emergency department, or minor injury unit within ten hours of the NHS 111 call, and the percentage admitted to hospital following visits to emergency departments.\n\nResultsOf the 10,356 callers, 2,898 (28.0%) were advised by NHS 111 to manage their health needs at home, with an appointment with an out-of-hours GP made for the remaining 7,458 (72.0%). 14.9% (432/2,898) of the callers who were advised by NHS 111 to manage their health needs at home attended an emergency department with ten hours, compared with 16% (1,207/7,458) of callers who had an out-of-hours appointment with an out-of-hours GP. After adjusting for patient characteristics, GP out-of-hours appointment was associated with lower rates of emergency department attendance (adjusted odds ratio, 0.86, 95% CI, 0.75-0.99),). When we subset emergency department types, a GP out-of-hours appointment was associated with lower rates of minor injury unit attendance (adjusted odds ratio, 0.32, 95% CI, 0.23 - 0.44) but not major emergency department attendance (adjusted odds ratio 1.06, 95% CI 0.90-1.24). There was no association with hospital admission. Review by an NHS 111 clinical supervisor was associated with fewer emergency department attendances (adjusted OR 0.77, 95% CI, 0.62-0.97).\n\nConclusionsClinical input during or following out-of-hours calls to NHS 111 was associated with lower rates of emergency department utilisation for children and young people, though the reduction may be concentrated in lower intensity care settings. Thus, there may be potential to reduce the use of emergency care by providing access to clinical advice or out-of-hour services in other settings through the NHS 111 telephone service.

epidemiology↗

bioRxiv2017

Breast cancer incidence as a function of the number of previous mammograms: analysis of the NHS screening programme

The discrepancy between the protective effect of early surgery of breast cancer and the poor benefits of mammography screening programs in the long term can be explained if mammography induces breast cancer at a much higher rate than anticipated. Mammography screening is associated in most countries with a higher incidence of breast cancer, attributed to overdiagnosis. X-ray-induced cancers can be distinguished from overdiagnosed cancers by the fact that their incidence depends on the number of previous mammograms, whereas overdiagnosis solely depends on the last screening mammogram, leading to diagnosis. The unbiased relationship between the number of mammograms and breast cancer incidence was evaluated from the data of the NHS Breast Cancer screening programme in women aged from 50 to 64 years in the United Kingdom. The delay between mammography and increased breast cancer incidence was confirmed from the data of the \"Age\" trial, a randomized trial of annual screening starting at age 40 in the UK. In women aged 50-64 attending screening at the NHS Breast Cancer programme, in situ breast cancer incidence increased linearly from 1993 to 2005 as a function of the number of mammograms. Incidence did not increase anymore after 2005 when the number of mammograms and the delay after screening was stable. Invasive breast cancer incidence increased more specifically in the 60-69 age group. The risk of breast cancer almost doubled after 15 years of screening. Additional cancers began to occur less than 6 years after mammography. These results are evidence that X-ray-induced carcinogenesis, rather than overdiagnosis, is the cause of the increase in breast cancer incidence.

epidemiology↗

bioRxiv2017

Catching up to a fast-moving target: Evaluation of a health system strengthening intervention in rural Rwanda 2005-2010 using data from repeated cross-sectional surveys

IntroductionAlthough Rwandas health system underwent major reforms and improvements after the 1994 Genocide, the health system and population health in the southeast lagged behind other areas. In 2005 Partners In Health and the Rwandan Ministry of Health began a health system strengthening intervention in this region.\n\nMethodsCombining results from the 2005 and 2010 Demographic and Health Surveys with those from a supplemental 2010 survey, we compared changes in health system output indicators and population health outcomes between 2005 and 2010 as reported by 21,338 women living in the intervention area and similar rural areas, controlling for potential confounding by economic and demographic variables.\n\nResultsOverall health system coverage improved similarly in both regions between 2005 and 2010, with an indicator of composite coverage of child health interventions increasing from 57.9% to 75.0% in the intervention area and from 58.7% to 73.8% in other rural areas. Despite experiencing poorer health outcomes in 2005, the intervention area caught up to or exceeded other rural areas on 23 of 25 indicators. Most notably, under-five mortality declined by an annual rate of 12.8% in the intervention area, from 229.8 to 83.2 deaths per 1000 live births, and by 8.9% in other rural areas, from 157.7 to 75.8 deaths per 1000 live births. Improvements were most dramatic among the poorest households.\n\nConclusionWe observed dramatic improvements in population health outcomes including under-five mortality between 2005 and 2010 in rural Rwanda generally, and in the intervention area specifically.\n\nSUMMARY BOXO_ST_ABSWhat is already known about this topic?C_ST_ABSO_LIMuch of the evidence that health system strengthening in rural Africa has improved health outcomes comes from studies of targeted regional interventions such as performance based financing or community health worker programs, rather than integrated interventions that encompass multiple components including infrastructure and supply chain investments, health management information system, workforce training and incentives at all levels, community health workers, and free services for poor patients.\nC_LIO_LIIn addition to these experimental or quasi-experimental studies, a series of case studies have documented individual nations, pathways to achieving millennium development goal 4 target, the reduction of under-five mortality by two thirds between 1990 and 2015.\nC_LIO_LIThese reports suggest that improvements in coverage of reproductive, maternal and child health indicators explain some, but not all, of the decline in child mortality and that these successes occurred in the context of national gains in health, nutrition and food security, sanitation, poverty reduction, and access to clean water.\nC_LI\n\nWhat are the new findings?O_LICoverage of most maternal and child health care interventions improved at a similar pace in our rural intervention area and other rural areas.\nC_LIO_LIDespite experiencing poorer health outcomes in 2005, our rural intervention area caught up to or exceeded other rural areas on 23 of 25 population health indicators by 2010.\nC_LIO_LIInfant and under-5 mortality declined in our rural intervention area even more precipitously than in other rural areas of Rwanda between 2005 and 2010.\nC_LI\n\nHow might this influence practice?O_LIThe process of strengthening national health systems often involves trade-offs between a focus on first testing individual programs that distributed widely, as is often practiced by pilot programs with multilateral institutions, or implementing multiple simultaneous programs locally. Our results show that integrated health system strengthening interventions can be locally adapted to enable the rapid expansion of health care coverage as well as dramatic improvements in population health outcomes.\nC_LIO_LIIntegrated multi-level interventions can also help narrow the health care coverage and outcome gap between richer and poorer members of a society.\nC_LIO_LINational governments can leverage nongovernmental partners to achieve the health related sustainable development goals through joint implementation of national health policy.\nC_LI

epidemiology↗

bioRxiv2017

Is a large eye size a risk factor for myopia? A Mendelian randomization study

Myopia (nearsightedness) is an increasingly common cause of irreversible visual impairment. The ocular structures with greatest impact on refractive error are corneal curvature and axial length. Emmetropic eyes range in size within and across species, yet possess a balance between corneal curvature and axial length that is under genetic control. This scaling goes awry in myopia: 1 mm axial elongation is associated with ~3 Dioptres (D) myopia. Evidence that eye size prior to onset is a risk factor for myopia is conflicting. We applied Mendelian randomisation to test for a causal effect of eye size on refractive error. Genetic variants associated with corneal curvature identified in emmetropic eyes (22,180 individuals) were used as instrumental variables and tested for association with refractive error (139,697 individuals). A genetic risk score for the variants was tested for association with corneal curvature and axial length in an independent sample (315 emmetropes). The genetic risk score explained 2.3% (P=0.007) and 2.7% (P=0.002) of the variance in corneal curvature and axial length, respectively, in the independent sample, confirming these variants are predictive of eye size in emmetropes. The estimated causal effect of eye size on refractive error was + 1.41 D (95% CI. 0.65 to 2.16) less myopic refractive error per mm flatter cornea (P<0.001), corresponding to +0.48 D (95% CI. 0.22 to 0.73) more hypermetropic refractive error for an eye with a 1mm longer axial length. These results do not support the hypothesis that a larger eye size is a risk factor for myopia. We conclude the genetic determinants of normal eye size are not shared with those influencing susceptibility to myopia.

epidemiology↗

bioRxiv2018

Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji

Dengue is a major health burden, but it can be challenging to examine transmission dynamics and evaluate control measures because outbreaks depend on multiple factors, including human population structure, prior immunity and climate. We combined population-representative paired sera collected before and after the major 2013/14 dengue-3 outbreak in Fiji with surveillance data to determine how such factors influence dengue virus transmission and control in island settings. Our results suggested the 10-19 year-old age group had the highest risk of acquiring infection, but we did not find strong evidence that other demographic or environmental risk factors were linked to seroconversion. Mathematical modelling showed that temperature-driven variation in transmission and herd immunity could not fully explain observed dynamics. However, there was evidence of an additional reduction in transmission coinciding with a vector clean-up campaign, which may have contributed to the decline in cases and prevented transmission continuing into the following season.

epidemiology↗

bioRxiv2018

Cigarette smoking and personality: Investigating causality using Mendelian randomization

BackgroundDespite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop more targeted smoking cessation programmes that could lead to both improved uptake and efficacy.\n\nMethodsRecent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to data from UK Biobank to investigate the link between smoking and personality. We first estimated genetic overlap between traits using LD score regression and then applied both one- and two-sample Mendelian randomization methods to unpick the nature of this relationship.\n\nResultsWe found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion, suggesting shared genetic aetiology. We found some evidence to suggest an association between neuroticism and increased smoking initiation. We also found some evidence that personality traits appear to be causally linked to certain smoking phenotypes: higher neuroticism and heavier cigarette consumption, and higher extraversion and increased odds of smoking initiation. The latter finding could lead to more targeted smoking prevention programmes.\n\nConclusionThe association between neuroticism and cigarette consumption lends support to the self-medication hypothesis, while the association between extraversion and smoking initiation could lead to more targeted smoking prevention programmes.

epidemiology↗