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bioRxiv2018

Projecting social contact matrices to different demographic structures

The modeling of large-scale communicable epidemics has greatly benefited in the last years from the increasing availability of highly detailed data. Particularly, in order to achieve quantitative descriptions of the evolution of epidemics, contact networks and mixing patterns are key. These heterogeneous patterns depend on several factors such as location, socioeconomic conditions, time, and age. This last factor has been shown to encapsulate a large fraction of the observed inter-individual variation in contact patterns, an observation validated by different measurements of age-dependent contact matrices. Recently, several works have studied how to project those matrices to areas where empiric data is not available. However, the dependence of contact matrices on demographic structures and their time evolution has been largely neglected. In this work, we tackle the problem of how to transform an empirical contact matrix that has been obtained for a given demographic structure into a different contact matrix that is compatible with a different demography. The methodology discussed here allows extrapolating a contact structure measured in a particular area to any other whose demographic structure is known, as well as to obtain the time evolution of contact matrices as a function of the demographic dynamics of the populations they refer to. To quantify the effect of considering time-dynamics of contact patterns on disease modeling, we implemented a Susceptible-Exposed-Infected-Recovered (SEIR) model on 16 different countries and evaluated the impact of neglecting the temporal evolution of mixing patterns. Our results show that simulated disease incidence rates, both at the aggregated and age-specific levels, are significantly dependent on contact structures variation driven by demographic evolution. The present work opens the path to eliminate technical biases from model-based impact evaluations of future epidemic threats and warns against the use of contact matrices to model diseases without correcting for demographic evolution or geographic variations.\n\nAuthor summaryLarge scale epidemic outbreaks represent an ever increasing threat to humankind. In order to anticipate eventual pandemics, mathematical modeling should not only have the capacity to model in real time an ongoing disease, but also to predict the evolution of potential outbreaks in different locations and times. To this end, computational frameworks need to incorporate, among other ingredients, realistic contact patterns into the models. This not only implies anticipating the demographic structure of the populations under study, but also understanding how demographic evolution reshapes social mixing patterns along time. Here we present a mathematical framework to solve this problem and test our modeling approach on 16 different empirical contact matrices. We also evaluate the impact of an eventual future outbreak by simulating a SEIR scenario in the countries analyzed. Our results show that using outdated or imported contact matrices that do not take into account demographic structure or its evolution can lead to largely misleading conclusions.

epidemiology↗

bioRxiv2018

Comparative sensitivity of the test with tuberculosis recombinant allergen, containing ESAT6-CFP10 protein, and Mantoux test with 2 TU PPD-L in newly diagnosed tuberculosis children and adolescents in Moscow

Background. A group of Russian scientists has developed Diaskintest, which comprises Mycobacterium tuberculosis-specific recombinant proteins CFP10-ESAT6, for skin testing (0.2 {micro}g/0.1 ml).\n\nStudy purpose: to evaluate the comparative sensitivity of TST with 2 TU PPD-L and a skin test with tuberculous recombinant allergen (Diaskintest) containing the ESAT6-CFP10 protein in children and adolescents with newly diagnosed respiratory tuberculosis during mass screening in the primary medical service in Moscow, 2013-2016.\n\nMaterials and methods. The trial was a comprehensive retrospective group study of children and adolescents diagnosed in Moscow with respiratory tuberculosis in 2013-2016, aged 0 to 17 years inclusive. From 441 patients selected for analysis 408 patients had both tests (TST with 2 TU PPD-L and Diaskintest) performed, in 193 patients both tests were given simultaneously, of them 162 patients were BCG-vaccinated.\n\nResults. Comparative results of both tests in 408 patients with tuberculosis: at cut-off 5 mm, both tests has similar sensitivity: Diaskintest 98.3 % (95 % CI 97.0-99.6 %), TST 98.0 % (95 % CI 96.7-99.4 %), at cut-off 10 mm, the sensitivity decreases for both tests: Diaskintest 90.0 % (95 % CI 87.0-93.0 %), TST 88.7 % (95 % CI 85.6-91.9 %), but at cut-off 15 mm, the decrease in sensitivity is statistically significant: for Diaskintest 61.5 % (95 % CI 56.7-66.3 %), and for TST 46.3 % (95 % CI 41.4-51.3 %), p <0.0001.\n\nThe results of simultaneous setting of tests on different hands in 193 people (including 162 BCG-vaccinated), do not differ from the results for 408 people.\n\nThe correlation between the results of Diaskintest and TST was significant in all groups.\n\nConclusion. In children and adolescents with respiratory tuberculosis, Diaskintest of 0.2 {micro}g/ml and the Mantoux test with 2 TU PPD-L have high sensitivity (98%) at a cut-off of 5 mm; however, at cut-off 15 mm sensitivity is significantly reduced, and the decrease is more pronounced in the Mantoux test. The advantage of Diaskintest is that, unlike the Mantoux test, it has high specificity under the conditions of mass BCG vaccination. The test is cost-effective, simple to carry out, and can be used in mass screening.

epidemiology↗

bioRxiv2018

Repetition of deliberate self-poisoning in rural Sri Lanka

Repetition of deliberate self harm is an important predictor of subsequent suicide. Repetition rates in Asian countries appear to be significantly lower than in western high income countries. The reason for these reported differences is not clear and has been suggested to due methodological differences or the impact of access to more lethal means of self harm. This prospective study determines the rates and demographic pattern of deliberate self-poisoning, suicide and fatal and non fatal repeated deliberate self-poisoning in rural Sri Lanka.\n\nDetails of deliberate self poisoning admission in all hospitals (n=46) and suicides reported to all the police stations (n=28) of a rural district were collected for 3 years, 2011-2013. Demographic details of the cohort of deliberate self-poisoning patients admitted to all hospitals in 2011 (N=4022), were screened to link with patient records and police reports of successive two years with high sensitivity using a computer program and manual matching was performed with higher specificity. Life time repetition was assessed in a randomly selected subset of DSP patients (n=438).\n\nThere were 15,914 DSP admissions and 1078 suicides during the study period. Within the study area the deliberate self poisoning and suicide population incidences were, 248.3/100,000 and 20.7/100,000 in 2012. Repetition rate for four weeks, one-year and two-years were 1.9% (95% CI 1.5-2.3%), 5.7% (95% CI 5.0 to 6.4) and 7.9% (95% CI 7.1 to 8.8) respectively. The median interval between two attempts were 92 (IQR 10 - 238) and 191 (IQR 29 - 419.5) days for the one and two-year repetition groups. The majority of patients used the same poison in the repeat attempt. Age and hospital stay of individuals with repetitive events were not significantly different from those who had no repetitive events. The two-year rate for suicide following DSP was 0.7% (95% CI 0.4-0.9%). Reported life time history of deliberate self harm attempts was 9.5% (95% CI 6.7-12.2%).\n\nThe low comparative repetition rates in rural Sri Lanka was not explained by higher rates of suicide or access to more lethal means or differences in methodology.

epidemiology↗

bioRxiv2018

Improved state-level influenza activity nowcasting in the United States leveraging Internet-based data sources and network approaches via ARGONet

In the presence of population-level health threats, precision public health approaches seek to provide the right intervention to the right population at the right time. Accurate real-time surveillance methodologies that can estimate infectious disease activity ahead of official healthcare-based reports, in relevant spatial resolutions, are critical to eventually achieve this goal. We introduce a novel methodological framework for this task which dynamically combines two distinct flu tracking techniques, using ensemble machine learning approaches, to achieve improved flu activity estimates at the state level in the US. The two predictive techniques behind the proposed ensemble methodology, named ARGONet, utilize (1) a dynamic and self-correcting statistical approach to combine flu-related Google search frequencies, information from electronic health records, and historical trends within a given state, as well as (2) a data-driven network-based approach that leverages spatial and temporal synchronicities observed in historical flu activity across states to improve state-level flu activity estimates. The proposed ensemble approach considerably outperforms each individual method and any previously proposed state-specific method for flu tracking, with higher correlations and lower prediction errors.

epidemiology↗

bioRxiv2018

Birth attendance in rural Bangladesh: practices and correlates

IntroductionThe maternal mortality ratio (MMR) and neonatal mortality rate (NMR) are higher in the rural regions of Bangladesh compared to the urban areas or the national average. These two rates could be reduced by increasing use of skilled birth attendance in rural regions of this country. Although the majority of Bangladeshi population lives in rural areas, there has been a little investigation of the practices and determinants of delivery attendance in this region of Bangladesh. This study investigated the practices and determinants of attendance during child-births in rural Bangladesh.\n\nMethodsData were collected by the 2014 Bangladesh Demographic and Health Survey (BDHS 2014). After reporting the distribution of deliveries by types of attendance and distribution of selected factors, logistic regression was applied to calculate the crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs), and p-values.\n\nResultsMore than half of the deliveries (53.1%) were conducted by traditional attendants; community skilled attendants were present in only a small number of deliveries. The following factors were positively associated with deliveries by skilled attendants: 25-34 years age group of women (adjusted odds ratio (AOR): 1.4; 95% CI: 1.1-1.8), a higher education level of women (AOR: 2.9; 95% CI: 1.7-4.9), or their husbands (AOR: 2.4; 95% CI: 1.6-3.7), receiving antenatal care (AOR: 2.1; 95% CI: 1.6-2.7), and higher wealth quintiles (AOR of the richest wealth quintile vs the poorest: 3.5; 95% CI: 2.3-5.3). On the other hand, women having a higher parity (i.e., number of pregnancy, [≥]2) led to a lower likelihood of delivery by skilled birth attendants. The proportion of deliveries attended by skilled attendants was significantly lower in the other six divisions compared to Khulna.\n\nConclusionsSocioeconomic factors should be considered to design future interventions to increase the proportion of deliveries attended by skilled delivery attendants. Awareness programs are required in rural areas to highlight the importance of skilled attendants. Further re-evaluation of the community skilled birth attendants program is required.

epidemiology↗

bioRxiv2018

How Public Transport affected the Propagation of Zika and Microcephaly within Rio de Janeiro early in 2015

From mid-2015 to the end of January 2016, 47 cases of microcephaly were observed in the city of Rio de Janeiro, that were not due to other viral infections (syphilis, toxoplasmosis, herpes & cytomegalovirus). These children were conceived from Dec 2014 to April 2015, far too early to be explained by the officially recorded cases from October 2015 onward. Zika must have been rampant in the city from late 2014 onward. In the first half of the paper we study how the geographic spread of microcephaly cases evolved from mid-2015 to January 2016 (and hence Zika 6-9 months earlier). Cases were not evenly spread in proportion to the number of births; they were preferentially located in the northern suburbs apparently following the public transport routes, with virtually no cases in favelas and none in the southern suburbs (Zona Sul). One key difference between the transport systems in the northern and southern suburbs is that the metro & rail system in the north is above ground in the north whereas in the southern part the metro is underground with air-conditioning in carriages and forced ventilation on the platforms. The train system does not extend to Zona Sul.\n\nIn the second half of the paper we postulate that the air-conditioning and ventilation prevent mosquitos from biting people who are waiting on platforms in Zona Sul. Agent-based simulations are used to test this hypothesis. After confirming this, we postulate that providing air-conditioning and/or forced ventilation on the rail-metro transport hub in the city center (Centro) would significantly delay the propagation of arboviruses in the city, possibly preventing epidemics. One advantage of this proposal is that it does not require the use of insecticides.

epidemiology↗

bioRxiv2018

Getting more from heterogeneous HIV-1 surveillance data in a high immigration country: estimation of incidence and undiagnosed population size using multiple biomarkers

BackgroundMost HIV infections originate from individuals who are undiagnosed and unaware of their infection. Estimation of this quantity from surveillance data is hard because there is incomplete knowledge about i) the time between infection and diagnosis (TI) for the general population and ii) the time between immigration and diagnosis for foreign-born persons.\n\nDevelopmentWe developed a new statistical method for estimating the number of undiagnosed people living with HIV (PLHIV) and the incidence of HIV-1 based on dynamic modeling of heterogenous HIV-1 surveillance data. We formulated a Bayesian non-linear mixed effects model using multiple biomarkers to estimate TI accounting for biomarker correlation and individual heterogeneities. We explicitly model the probability that an HIV-1 infected foreign-born person was infected either before or after immigration to distinguish between endogenous and exogeneous incidence. The incidence estimator allows for direct calculation of the number of undiagnosed persons.\n\nApplicationThe model was applied to surveillance data in Sweden. The dynamic biomarker model was trained on longitudinal data from 31 treatment-naive patients with well-defined TI, using CD4 counts, BED serology, polymorphisms in HIV-1 pol sequences, and testing history. The multiple-biomarker model was more accurate than single biomarkers (mean absolute error 1.01 vs [≥] 1.95). We estimate that 813 (95% CI 780-862) PLHIV were undiagnosed in 2015, representing a proportion of 10.8% (95% CI 10.4-11.3%) of all PLHIV.\n\nConclusionsThe proposed methodology will enhance the utility of standard surveillance data streams and will be useful to monitor progress towards and compliance with the 90-90-90 UNAIDS target.\n\nKey messagesO_LICombined heterogeneous HIV-1 surveillance data and biomarker data can be used to estimate both local incidence and the number of undiagnosed people living with HIV.\nC_LIO_LIExplicit modeling of the dynamics, heterogeneity, and correlation of multiple biomarkers over time improved estimation of time between infection and diagnosis.\nC_LIO_LIExplicit modeling of the probability that foreign-born persons were infected before or after immigration improves accuracy of estimates of endogenous incidence and undiagnosed persons living with HIV.\nC_LIO_LIThe endogenous incidence of HIV-1 in Sweden is declining, despite continued immigration of HIV-1 infected persons.\nC_LIO_LIThe proportion of undiagnosed PLHIV decreased over 2010-2015 and was estimated to be 10.8% (95% CI, 10.4-11.3%) in 2015.\nC_LI

epidemiology↗

bioRxiv2018

Whole genome sequencing of Neisseria meningitidis W isolates from the Czech Republic recovered in 1984 - 2017

IntroductionThe study presents the analysis of whole genome sequence (WGS) data for Neisseria meningitidis serogroup W isolates recovered in the Czech Republic in 1984 - 2017 and their comparison with WGS data from other countries.\n\nMaterial and MethodsThirty-one Czech N. meningitidis W isolates, 22 from invasive meningococcal disease (IMD) and nine from healthy carriers were analysed. The 33-year study period was divided into three periods: 1984-1999, 2000-2009, and 2010-2017.\n\nResultsMost study isolates from IMD and healthy carriers were assigned to clonal complex cc22 (n = 10) in all study periods. The second leading clonal complex was cc865 (n = 8) presented by IMD (n = 7) and carriage (n = 1) isolates that emerged in the last study period, 2010 - 2017. The third clonal complex was cc11 (n = 4) including IMD isolates from the first (1984 - 1999) and third (2010 - 2017) study periods. The following clonal complex was cc174 (n = 3) presented by IMD isolates from the first two study periods, i.e. 1984 - 1999 and 2000 - 2009. One isolate of each cc41/44 and cc1136 originated from healthy carriers from the second study period, 2000 - 2009. The comparison of WGS data for N. meningitidis W isolates recovered in the Czech Republic in the study period 1984 - 2017 and for isolates from other countries recovered in the same period showed that clonal complex cc865, ST-3342 is unique to the Czech Republic since 2010. Moreover, the comparison shows that cc11 in the Czech Republic does not comprise novel hypervirulent lineages reported from both European and non-European countries. WGS data for Czech serogroup W meningococci point to the presence of MenB vaccine antigen genes and confirm the hypothesis about the MenB vaccine potential against N. meningitidis serogroup W. All 31 study isolates were assigned to Bexsero(R) Antigen Sequence Types (BAST), and seven of them were of newly described BASTs.\n\nConclusionsWGS analysis contributed considerably to a more detailed molecular characterization of N. meningitidis W isolates recovered in the Czech Republic over a 33-year period and allowed for a spatial and temporal comparison of these characteristics between isolates from the Czech Republic and other countries. In addition, the WGS data precised the base for the update of the recommendation for vaccination in the Czech Republic.

epidemiology↗

bioRxiv2018

Knowledge and attitudes of Ebola among the general public of Trinidad and Tobago during the 2014-15 West Africa outbreak

ObjectiveHealth system resilience and resilience of a country include the capacity of health personnel, institutions, and populations to prepare for and effectively respond to crises. This study investigates the knowledge and attitudes of the public concerning Ebola Virus Disease in Trinidad and Tobago.\n\nDesign and MethodsA cross sectional study whereby respondents (n = 920) were sampled from public places. Data were collected via interviewer administered questionnaires. Data were analysed using SPSS version 23.\n\nResultsThe response rate was 67.6 % (622/920). The main age category of responders was the 20 to 30 year age category (40.5%); responders were mostly female (58.0 %). Regarding knowledge, there were significant differences among occupational categories (F = 2.811, df1 = 6, df2 = 571, p-value = 0.011). Tukeys HSD post hoc test revealed that the mean knowledge scores for professional and sales occupations differed significantly (p-value = 0.003). There was a significant association between being afraid to go for treatment and age (p-value = 0.001). Significant associations were also found between occupational grouping and education attainment with opinion about the preparedness of private medical facilities, likelihood to shun family members with Ebola, being afraid to go for treatment and preference for traditional medicine (p-value <0.05).\n\nConclusionThis study highlights opportunities for community engagement to enhance health system resilience during outbreaks which would maximise national and global health security.

epidemiology↗

bioRxiv2018

Evaluating predictive biomarkers for a binary outcome with linear versus logistic regression - Practical recommendations for the choice of the model

A predictive biomarker can forecast whether a patient benefits from a specific treatment under study. To establish predictiveness of a biomarker, a statistical interaction between the biomarker status and the treatment group concerning the clinical outcome needs to be shown. In clinical trials looking at a binary outcome, linear or logistic regression models may be used to evaluate the interaction, but the effects in the two models are different and differently interpreted. Specifically, the effects are estimated as absolute risk reductions (ARRs) and odds ratios (ORs) in the linear and logistic model, thus measuring the effect on an additive and multiplicative scale, respectively.\n\nWe derived the relationship between the effects of the linear and the logistic regression model allowing for translations between the effect estimates between both models. In addition, we performed a comprehensive simulation study to compare the power of the two models under a variety of scenarios in different study designs. In general, the differences in power to detect interaction were minor, and visible differences were detected in rather unrealistic scenarios of effect size combinations and were usually in favor of the logistic model.\n\nBased on our results and theoretical considerations, we recommend to 1) estimate logistic regression models because of their statistical properties, 2) test for interaction effects and 3) calculate and report both ARRs and ORs from these using the formulae provided.

epidemiology↗

bioRxiv2018

Impact of Sexual Transmission to Sex-specific Attack Rates in Zika Epidemics

In 2015 and 2016 South America went through the largest Zika epidemic in recorded history. One important aspect of this epidemic was the impact on newborns due to the effect of Zika on development of the central nervous system leading to severe malformations. Another aspect of the Zika epidemic which became evident from the data was the importance of the sexual route of transmission leading to increased risk for women. Here propose a mathematical model for the transmission of the Zika virus including sexual transmission via all forms of sexual contact, as well as simplified vector transmission, assuming a constant availability of mosquitoes. From this model we derive an expression for[R] 0 which can be used to study and analyze the relative contributions of the different routes of Zika transmission and the male to female sexual transmission route vis-a-vis vectorial transmission. We also fit the model to data from the 2016 Zika epidemic in Rio de Janeiro, to estimate the values of key parameters of the model.

epidemiology↗

bioRxiv2018

Facility delivery and postnatal care services use among mothers who attended four or more antenatal care visits in Ethiopia: further analysis of the 2016 Demographic and Health Survey

IntroductionIn Ethiopia, many mothers who attend the recommended number of antenatal care visits fail to use facility delivery and postnatal care services. This study identifies factors associated with facility delivery and use of postnatal care among mothers who had four or more antenatal care visits, using data from the 2016 Ethiopian Demographic and Health Survey (EDHS).\n\nMethodsTo identify factors associated with facility delivery, we studied background and service-related characteristics among 2,415 mothers who attended four or more antenatal care visits for the most recent birth. In analyzing factors associated with postnatal care within 42 days after delivery, the study included 1,055 mothers who attended four or more antenatal care visits and delivered at home. We focused on women who delivered at home because women who deliver at a health facility are more likely also to receive postnatal care as well. A multivariable logistic regression model was fitted for each outcome to find significant associations between facility delivery and use of postnatal care.\n\nResultsFifty-six percent of women who had four or more antenatal care visits delivered at a health facility, while 44% delivered at home. Mothers with secondary or above level of education, urban residents, women in the richest wealth quintile, and women who were working at the time of interview had higher odds of delivering in a health facility. High birth order was associated with a lower likelihood of health facility delivery. Among women who delivered at home, only 8% received postnatal care within 42 days after delivery. Quality of antenatal care as measured by the content of care received during antenatal care visits stood out as an important factor that influences both facility delivery and postnatal care. Among mothers who attended four or more antenatal care visits and delivered at home, the content of care received during ANC visits was the only factor that showed a statistically significant association with receiving postnatal care.\n\nConclusionsThe more antenatal care components a mother receives, the higher her probability of delivering at a health facility and of receiving postnatal care. The health care system needs to increase the quality of antenatal care provided to mothers because receiving more components of antenatal care is associated with increased health facility delivery and postnatal care. Further research is recommended to identify other reasons why many women do not use facility delivery and postnatal care services even after attending four or more antenatal care visits.

epidemiology↗

bioRxiv2018

Bleeding, Cramping, and Satisfaction Among New Copper IUD Users: A Prospective Study

ObjectiveWe assess change in bleeding, cramping, and satisfaction among new copper (Cu) IUD users during the first six months of use, and evaluate the impact of bleeding and cramping on method satisfaction.\n\nMethodsWe recruited 77 women ages 18-45 for this prospective longitudinal observational cohort study. Eligible women reported regular menses, had no exposure to hormonal contraception in the last three months, and desired a Cu IUD for contraception. We collected data prospectively for 180 days following IUD insertion. Monthly, Participants reported bleeding scores using the validated pictorial blood loss assessment chart (PBAC), IUD satisfaction using a five-point Likert scale, and cramping using a seven-level ordinal scale. We used multiple imputation to address nonrandom attrition. Structural equation models for count and ordered outcomes modeled bleeding, cramping, and satisfaction growth curves over the six monthly repeated assessments.\n\nResultsBleeding significantly decreased (approximately 25%) over the course of the study from an estimated PBAC=195 at one month post-insertion to PBAC=151 at six months (t=-2.38, p<0.05). Additionally, IUD satisfaction improved over time (t=2.65, p<0.01), increasing from between \"Neutral\" and \"Satisfied\" to \"Satisfied\", over the six month study. Cramping decreased sharply over the six-month study from between biweekly and weekly, to once or twice a month (t=-4.38, p<0.001). Finally, bleeding, but not cramping, was associated with IUD satisfaction (study mean: t=-2.31, p<0.05; study end: t=-2.81, p<0.01).\n\nConclusionsNew Cu IUD users reported decreasing bleeding and cramping, and increasing IUD satisfaction, over the first six months. Method satisfaction was negatively associated with bleeding.

epidemiology↗

bioRxiv2018

Detecting spatiotemporal pattern of tuberculosis and the relationship between ecological environment and tuberculosis, a spatial panel data analysis in Guangxi, China

Guangxi is one of the provinces having the highest reported incidence of tuberculosis (TB) in China. However, spatial and temporal pattern and causation of the situation are still unclear. In order to detect the spatiotemporal pattern of TB and the association with ecological environment factors in Guangxi Zhuang autonomous region, China, We performed a spatiotemporal analysis with prediction using time series analysis, Morans I global and local spatial autocorrelation statistics, and space-time scan statistics, to detect temporal and spatial clusters. Spatial panel models were employed to identify the influence factors. The time series analysis shows that the number of reported cases peaked in spring and summer and decreased in autumn and winter with the annual reported incidence of 113.1/100,000 population. Morans I global statistics were greater than 0 (0.363 - 0.536) during the study period. The most significant hot spots were mainly located in the central part. The east part exhibited a low-low relation. By spacetime scanning, the clusters identified were similar to that of the local autocorrelation statistics, and were clustered toward the early of 2016. Duration of sunshine, per capita gross domestic product (PGDP), the recovery rate of TB and participation rate of new cooperative medical care insurance in rural areas had a significant negative association with TB. In conclusion, the reported incidence of TB in Guangxi remains high. The main cluster was located in the central part of Guangxi, a region where promoting the productivity, improving TB treatment pathway and strengthening environmental protective measures (increasing sunshine exposure) are urgently needed.

epidemiology↗

bioRxiv2018

The global burden of trichiasis in 2016

BackgroundTrichiasis is present when one or more eyelashes touches the eye. Uncorrected, it can cause blindness. Accurate estimates of numbers affected, and their geographical distribution, help guide resource allocation.\n\nMethodsWe obtained district-level trichiasis prevalence estimates for 44 endemic and previously-endemic countries. We used (1) the most recent data for a district, if more than one estimate was available; (2) age- and sex-standardized corrections of historic estimates, where raw data were available; (3) historic estimates adjusted using a mean adjustment factor for districts where raw data were unavailable; and (4) expert assessment of available data for districts for which no prevalence estimates were available.\n\nFindingsInternally age- and sex-standardized data represented 1,355 districts and contributed 662 thousand cases (95% confidence interval [CI] 324 thousand-1.1 million) to the global total. age- and sex-standardized district-level prevalence estimates differed from raw estimates by a mean factor of 0.45 (range 0.03-2.28). Previously non-standardized estimates for 398 districts, adjusted by x0.45, contributed a further 411 thousand cases (95% CI 283-557 thousand). Eight countries retained previous estimates, contributing 848 thousand cases (95% CI 225 thousand-1.7 million). New expert assessments in 14 countries contributed 862 thousand cases (95% CI 228 thousand-1.7 million). The global trichiasis burden in 2016 was 2.8 million cases (95% CI 1.1-5.2 million).\n\nInterpretationThe 2016 estimate is lower than previous estimates, probably due to more and better data; scale-up of trichiasis management services; and reductions in incidence due to lower active trachoma prevalence.\n\nAuthor SummaryAs an individual with trichiasis blinks, the eyelashes abrade the cornea, which can lead to corneal opacity and blindness. Through high quality surgery, which involves correcting the position of the in-turned eyelid, it is possible to reduce the number of people with trichiasis. An accurate estimate of the number of persons with trichiasis and their geographical distribution are needed in order to effectively align resources for surgery and other necessary services. We obtained district-level trichiasis prevalence estimates for 44 endemic and previously-endemic countries. We used the most recently available data and expert assessments to estimate the global burden of trichiasis. We estimated that in 2016 the global burden was 2.8 million cases (95% CI 1.1-5.2 million).\n\nThe 2016 estimate is lower than previous estimates, probably due to more and better data; scale-up of trichiasis management services; and reductions in incidence due to lower active trachoma prevalence.

epidemiology↗

bioRxiv2018

Statin treatment and the risk of depression

The effect of statin treatment on the risk of developing depression remains unclear. Therefore, we aimed to assess the association between statin treatment and depression in a nationwide register-based cohort study with up to 20 years of follow up. We identified all statin users among all individuals born in Denmark between 1920 and 1983. One non-user was matched to each statin user based on age, sex and a propensity score taking several potential confounders into account. Using Cox regression we investigated the association between statin use and: I) redemption of prescriptions for antidepressants, II) redemption of prescriptions for any other drug, III) depression diagnosed at psychiatric hospitals, IV) cardiovascular mortality and V) all-cause mortality. A total of 193,977 statin users and 193,977 non-users were followed for 2,621,282 person-years. Statin use was associated with I) increased risk of antidepressant use (hazard rate ratio (HRR)=1.33; 95% confidence interval (95%-CI)=1.31-1.36), II) increased risk of any other prescription drug use (HRR=1.33; 95%-CI=1.31-1.35), III) increased risk of receiving a depression diagnosis (HRR=1.22, 95%-CI=1.12-1.32) - but not after adjusting for antidepressant use (HRR=1.07, 95%-CI=0.99- 1.15), IV) reduced cardiovascular mortality (HRR=0.92, 95%-CI=0.87-0.97) and V) reduced all-cause mortality (HRR=0.90, 95%-CI=0.88-0.92). These results suggest that the association between statin treatment and antidepressant use was unspecific (equivalent association between statins and other drugs) and that the association between statin use and depression diagnoses was mediated by antidepressant use. Thus, statin users and non-users appear to be equally likely to develop depression, but the depression is more often detected/treated among statin users.

epidemiology↗

bioRxiv2018

Systematic biases in disease forecasting - the role of behavior change

In a simple susceptible-infected-recovered (SIR) model, the initial speed at which infected cases increase is indicative of the long-term trajectory of the outbreak. Yet during real-world outbreaks, individuals may modify their behavior and take preventative steps to reduce infection risk. As a consequence, the relationship between the initial rate of spread and the final case count may become tenuous. Here, we evaluate this hypothesis by comparing the dynamics arising from a simple SIR epidemic model with those from a modified SIR model in which individuals reduce contacts as a function of the current or cumulative number of cases. Dynamics with behavior change exhibit significantly reduced final case counts even though the initial speed of disease spread is nearly identical for both of the models. We show that this difference in final size projections depends critically in the behavior change of individuals. These results also provide a rationale for integrating behavior change into iterative forecast models. Hence, we propose to use a Kalman filter to update models with and without behavior change as part of iterative forecasts. When the ground truth outbreak includes behavior change, sequential predictions using a simple SIR model perform poorly despite repeated observations while predictions using the modified SIR model are able to correct for initial forecast errors. These findings highlight the value of incorporating behavior change into baseline epidemic and dynamic forecast models.

epidemiology↗

bioRxiv2018

Environmental and Socioeconomic Factors Associated with West Nile Virus

Environmental and socioeconomic risk factors associated with West Nile Virus cases were investigated in the Northern San Joaquin Valley region of California, a largely rural area. The study included human West Nile Virus (WNV) cases from the years 2011-2015 in the three county area of San Joaquin, Stanislaus and Merced Counties, and examined whether factors were associated with WNV using census tracts as the unit of analysis. Environmental factors included temperature, precipitation, mosquitoes positive for WNV, and habitat. Socioeconomic variables included age, education, housing age, home vacancies, median income, population density, ethnicity, and language spoken. Chi-squared independence tests were used to examine whether each variable was associated with WNV in each county, and then also used for the three counties combined. Logistic regression was used for a three-county combined analysis, to examine which environmental and socioeconomic variables were most likely associated with WNV cases. The chi-squared tests found that the variables associated with WNV varied in each of the three counties. The chi-squared tests for data combined from the three counties found that WNV cases were significantly associated with mosquitoes positive for WNV, urban habitat, higher home vacancies, higher population density, higher education, and ethnicity. Logistic regression analysis revealed that overall, the environmental factors precipitation, mean temperature, and WNV positive mosquitoes were the strongest predictors of WNV cases. Results support efforts of mosquito control districts, which aim for source reduction of mosquito breeding sites. In addition, findings suggest that residents with higher income and education may be more aware of WNV and its symptoms, and more likely to request testing from physicians. Lower income and education residents may not be aware of WNV. Public health education might increase its prevention messages about vector-borne disease in the various languages of the region, which would contribute overall to public health in the region.

epidemiology↗