Percentile Method Research Articles

Study on early warning threshold values for 7 common communicable diseases in Gansu province, 2016

Objective: To optimize the warning threshold values of common communicable diseases in Gansu province, and improve the early warning effect. Method: An early warning model was set up for influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, viral hepatitis type E and hand foot and mouth disease (HFMD) respectively in Gansu by using the moving percentile method and cumulative sum method. By calculating the sensitivity, specificity, predictive value of positive test, predictive value of negative test, Youden' index and receiver-operating characteristic curve, the optimum early warning threshold values for communicable diseases in Gansu were selected. Results: The optimum early warning boundary values of influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, and viral hepatitis type E were P(90), P(80), P(95), P(90), P(80) and P(90) respectively. The optimum early warning parameters of HFMD were k=1.2, H=5σ. Under the optimum early warning boundary values/parameters, the early warning sensitivities of influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, viral hepatitis type E and HFMD were 86.67%, 100.00%, 91.67%, 100.00%, 100.00%, 100.00% and 100.00%, the specificities were 86.49%, 62.22%, 75.00%, 100.00%, 97.92%, 89.13% and 74.47%. The predictive values of positive test were 72.22%, 29.17%, 52.38%, 100.00%, 80.00%, 54.55% and 29.41%, and the predictive values of negative test were 94.12%, 100.00%, 96.77%, 100.00%, 100.00%, 100.00% and 100.00%, and the Youden' indexes were 0.73, 0.62, 0.67, 1.00, 0.98,0.89 and 0.74. Receiver-operating characteristic curve showed that the values/parameters of this warning boundary were the points closest to the upper left of the coordinate diagram. Conclusion: The early warning thresholds of influenza, other infectious diarrheal diseases, dysentery and hepatitis E in Gansu may be raised appropriately and the early warning parameters of HFMD need to be adjusted to improve the effectiveness of early warning.

Confidence Interval Width for Pearson’s Correlation Coefficient: A Gaussian‐Independent Estimator Based on Sample Size and Strength of Association

Core Ideas The confidence interval (CI) of Pearson’s correlation coefficient (r) was investigated.Confidence interval width is inversely proportional to r and sample size (n).It is recommended to use 1000 or more bootstrap replicates in order to not underestimate CI width (CIw).A model to estimate CIw as a function of n and r is proposed. The nonparametric bootstrap percentile method has been widely used to estimate confidence intervals (CI) for Pearson’s product‐moment correlation coefficient (r). However, because most studies provide results for specific crops and pre‐stablished CIs, an innovative approach to CI estimation is needed. The aim of this study was to propose a model that predicts CI width (CIw) as a function of the sample size (n) and the strength of association among traits. Additionally, we also investigated the extent to which the number of bootstrap replicates (BRs) influences CI estimation. Seventy‐eight different r magnitudes from a maize field experiment were used. The 95% CI half‐width for each trait combination was estimated based on 991 different sample sizes and seven different numbers of BRs. A simple nonlinear model with n and r as predictors is proposed for estimating the CIw: , where δ, β0, and β1 are the model coefficients. Based on our data, the fitted model was: . This model exhibited excellent goodness of fit (R2 = 0.988; root mean square error [RMSE] = 0.011). Considering an assumed magnitude of association (r), the n for a desired CIw can then be calculated as: . We also recommend using ≥1000 BRs, to prevent underestimating CIw. Finally, we present an intuitive table that provides previously estimated n for 9 levels of half‐widths for 95% CIs (0.05, 0.1,... 0.45) and 19 magnitudes for r (0.05, 0.10,..., 0.95).

Reference interval for immature platelet fraction on Sysmex XN haematology analyser in adult population.

IntroductionThe Sysmex XN-series haematology analyser has newly adopted a fluorescent channel to measure immature platelet fraction (IPF). To promote the clinical utility of this promising parameter, establishing a reliable reference interval is mandatory. According to previous studies, IPF values may be affected by the employed analyser and the ethnic background of the individual, but no differences seem to be found between individuals’ genders. Therefore, this study aimed to define the reference interval for IPF in a Spanish population following Clinical and Laboratory Standard Institute (CLSI) guidelines.Materials and methodsA total of 153 healthy Caucasian adults from Spain met the inclusion criteria. IPF measurement was performed by means of a Sysmex XN-2000 haematology analyser. A non-parametric percentile method was used to calculate the reference intervals in accordance with CLSI guidelines.ResultsThe obtained reference interval for IPF on the Sysmex XN-2000 was 1.6–9.6% (90% confidence intervals (CIs) were 1.5–1.8 and 9.3–11.5, respectively). No significant gender difference in IPF reference intervals was observed (P = 0.101).ConclusionsThis study provides, for the first time, a reference interval for IPF using a Sysmex XN-2000 in a Spanish population, ranging from 1.6 to 9.6%. These data are needed to evaluate platelet production in several conditions such as thrombocytopenia, inflammatory states and cardiovascular diseases, as well as for future research.

Percentile Estimators for Two-Component Mixture Distribution Models

The percentile estimators have a widespread usage in the estimation of distribution parameters because of simplicity and ease of computation. In this study, we investigate the percentile method for two-component mixture distribution models which are commonly used in modeling of heterogeneous univariate data sets. We have proposed percentile estimator for two-component mixture Weibull and two-component mixture Rayleigh distributions according to two different approaches. Performances of the defined percentile estimators were compared with maximum likelihood estimators using simulation. For this purpose, we used several criteria which are bias, mean squared error, mean absolute deviation, mean relative total error and running time of the algorithm. The benefits of the proposed methods have been illustrated by three different real data sets.

Maternal thyroid-stimulating hormone reference ranges for first trimester screening from 11 to 14weeks of gestation.

To establish maternal thyroid-stimulating hormone (TSH) reference ranges for first trimester screening from 11+0 to 13+6weeks of gestation. A total of 10592 singleton and 201 twin consecutive Caucasian pregnant women who underwent simultaneously prenatal first trimester Down's syndrome screening and thyroid function screening from January 2010 to November 2017 were included in the study. Women with positive antithyroid peroxidase antibody (TPOAb) and positive personal history of thyroid disease were previously excluded. TSH was measured by immunochemiluminescent assay on ci 16200 Abbott Architect analyzer. Nonparametric percentile method (also known as CLSI C28.A3) was used for the determination of reference ranges. We established reference ranges of TSH for the period of gestation from 11+0 to 13+6weeks of pregnancy as 0.16-3.43 mU/L for singleton Caucasian pregnancies and 0.02-2.95 mU/L for twin Caucasian pregnancies. The median (IQR) of TSH for singleton pregnancies was higher than that for twin pregnancies (1.25 mU/L (0.83-1.81) vs 0.84 (0.37-1.47), respectively; P<.0001). Each first trimester screening center should be aware of which type of immunoassay their laboratory uses. TSH reference ranges in women during the first trimester of pregnancy are lower than those for general population. Twin pregnancies have lower TSH than singleton pregnancies.

The effect of temperature on the developmental rates of seedling emergence and leaf-unfolding in two dwarf bamboo species

The mean and variance of developmental rates of bamboos at different temperatures follow a power law. The rate isomorphy hypothesis, demonstrated in insects and mites, does not hold in bamboos. The developmental time of plants and poikilotherms can be significantly affected by temperature. Developmental rate (i.e. the reciprocal of developmental time) of arthropods and germination rate of some plant seeds have been demonstrated to follow a linear function with temperature. The rate isomorphy hypothesis in entomology suggests a lower developmental threshold below which development of all life stages terminates. If this hypothesis also holds for plants, the estimated lower threshold for one development stage could be used for predicting thresholds of other stages. Here, we tested this hypothesis to compare the developmental time of seedling emergence and the time from seedling emergence to the unfolding of the third leaf in two bamboo species. We used five constant thermal environments from 18.5 to 28.5 °C with an increment of 2.5 °C. Both species showed a linear relationship between temperature and developmental rate, with the mean and variance of developmental rates following a power law. Using the bootstrap percentile method, we showed that the isomorphy hypothesis does not hold for both species. The effect of temperature on the survival rate at the time of seedling emergence differed significantly between the two species.

IMAGE THRESHOLDING BASED ON HIERARCHICAL CLUSTERING ANALYSIS AND PERCENTILE METHOD FOR TUNA IMAGE SEGMENTATION

Automatic classification of tuna image needs a good segmentation as a main process. Tuna image is taken with textural background and the tuna’s shadow behind the object. This paper proposed a new weighted thresholding method for tuna image segmentation which adapts hierarchical clustering analysisand percentile method. The proposed method considering all part of the image and the several part of the image. It will be used to estimate the object which the proportion has been known. To detect the edge of tuna images, 2D Gabor filter has been implemented to the image. The result image then threshold which the value has been calculated by using HCA and percentile method. The mathematical morphologies are applied into threshold image. In the experimental result, the proposed method can improve the accuracy value up to 20.04%, sensitivity value up to 29.94%, and specificity value up to 17,23% compared to HCA. The result shows that the proposed method cansegment tuna images well and more accurate than hierarchical cluster analysis method.

New approach for the identification of implausible values and outliers in longitudinal childhood anthropometric data

PurposeWe aimed to demonstrate the use of jackknife residuals to take advantage of the longitudinal nature of available growth data in assessing potential biologically implausible values and outliers. MethodsArtificial errors were induced in 5% of length, weight, and head circumference measurements, measured on 1211 participants from the Maternal Vitamin D for Infant Growth (MDIG) trial from birth to 24 months of age. Each child's sex- and age-standardized z-score or raw measurements were regressed as a function of age in child-specific models. Each error responsible for a biologically implausible decrease between a consecutive pair of measurements was identified based on the higher of the two absolute values of jackknife residuals in each pair. In further analyses, outliers were identified as those values beyond fixed cutoffs of the jackknife residuals (e.g., greater than +5 or less than −5 in primary analyses). Kappa, sensitivity, and specificity were calculated over 1000 simulations to assess the ability of the jackknife residual method to detect induced errors and to compare these methods with the use of conditional growth percentiles and conventional cross-sectional methods. ResultsAmong the induced errors that resulted in a biologically implausible decrease in measurement between two consecutive values, the jackknife residual method identified the correct value in 84.3%–91.5% of these instances when applied to the sex- and age-standardized z-scores, with kappa values ranging from 0.685 to 0.795. Sensitivity and specificity of the jackknife method were higher than those of the conditional growth percentile method, but specificity was lower than for conventional cross-sectional methods. ConclusionsUsing jackknife residuals provides a simple method to identify biologically implausible values and outliers in longitudinal child growth data sets in which each child contributes at least 4 serial measurements.

Temporal and spatial change of climate resources and meteorological disasters under climate change during winter crop growing season in Guangdong Province, China.

Trend analysis method was applied to analyze the general variation characteristics of the climate resources and meteorological disasters of growing season of the winter planting in Guangdong before (1961-1996) and after climate warming (1997-2015). Percentile method was employed to determine thresholds for extreme cold and drought in major planting regions, and the characteristics of extreme disasters since climate warming were analyzed. The results showed that, by comparing 1997-2015 with 1961-1996, the heat value in winter growing season increased significantly. The belt with a higher heat value, where the average temperature was ≥15 ℃ and accumulated temperature was ≥2200 ℃·d, covered the main winter production regions as Shaoguan, Zhanjiang, Maoming, Huizhou, Meizhou and Guangzhou. Meanwhile, the precipitation witnessed a slight increase. The regions with precipitations of 250-350 mm included Zhanjiang, Maoming, Huizhou, Guangzhou and Meizhou. Chilling injury in the winter planting season in the regions decreased, the belt with an accumulated chilling of <2 ℃·d covered the major geographic parts of the involved regions as Zhanjiang, Maoming, Guangzhou and Huizhou; and the belt with an accumulated chilling of 8-16 ℃·d covered the major geographic parts of Shaoguan and Meizhou. Meanwhile, the drought days decreased, the belt with drought days ≥50 included the major geographic parts of Zhanjiang, Maoming, Huizhou, Guangzhou and the belt with drought days <50 included the major geographic parts of Shaoguan. The typical case of the extreme disasters showed that the extreme chilling injury and drought in the main producing regions should not be overlooked. Maoming, Huizhou and Meizhou were at higher risk of extreme chilling injury, followed by Shaoguan and Guangzhou. Zhanjiang and Maoming faced the highest risk of extreme drought, Huizhou and Guangzhou took the second place, Shaoguan and Meizhou went last. During 1997-2015, the heat of winter season increased significantly, the trend of chilling and drought decreased, however, the extreme disasters occurred frequently and the risks were higher in winter production areas. It was suggested that the winter planting should be closely integrated with climate resources and the occurrence law of meteorological disasters in growing season.

Awareness Towards Impact of Festivals on Ecology: Need for Social Work Intervention

Festivities are considered as series of event conducted by people for the fulfillment of cultural needs. Irrespective of region, religion, castes we could see celebration of festivities with joy and prosperity. People do celebrate festivities because get together of family member, to come away from monotonous lifestyle and have some delicious food. Apart from these positive things festivities are the way to pollute environment in all sphere, like air, water, soil, noise pollution. From this study researcher has assessed the awareness level among people about ecological pollution during festivities and Explored Social work intervention to bring awareness about celebrating festivities without harming ecology. Descriptive research design was adopted for this study. Non probability sampling method was used with purposeful sample technique. 50 samples were drawn from universal for this study. The study found, that Indian cultural influence and low awareness about ecological protection among people are leading towards pollution (Environment foot print) in the name of festivities. Researcher has came up with Social Work intervention to bringing awareness among people regarding environment protection. Simple percentile and central tendency methods were used for statistical analysis and SPSS 20 was used to compute data.

Reference values for serum folate and vitamin B12 in a Spanish population using an electrochemiluminiscent method

BackgroundDespite being the most widely used medical decision-making tool, reference intervals are not usually determined by clinical laboratories, due to the highly demanding activities and costly process it involves. However, scientific societies encourage individual clinical laboratories to establish their own reference values. This is especially important in the cases of folate and vitamin B12, due to strong differences in vitamin status among different populations. ObjectiveOur aim is to establish reference intervals for folate and vitamin B12 levels in a healthy blood donor population using an electrochemiluminiscent method (ROCHE DIAGNOSTICS). MethodFolate and vitamin B12 levels were measured in 141 healthy blood donors aged between 18 and 65 years. Biochemical analyses were performed using a Modular E170 analyzer (ROCHE DIAGNOSTICS) and an electrochemiluminiscent method. Reference intervals were calculated with a non-parametric percentile method following the CLSI guidelines. ResultsThere were not significant differences in folate or cobalamin levels between age or sex subgroups. The limits of the reference interval for folate were 2.2 and 18ng/mL (5–40.7nmol/L), and 213.8 and 763.3pg/mL (158.2–564.8pmol/L) for vitamin B12. These intervals differed from those claimed by the manufacturer. ConclusionsOur results emphasize the convenience of building reference values based on the population served by the laboratory, in order to unequivocally rule out deficiencies of folate or vitamin B12.

A dynamic system for Gompertz model

ABSTRACTTwo-parameter Gompertz distribution has been introduced as a lifetime model for reliability inference recently. In this paper, the Gompertz distribution is proposed for the baseline lifetimes of components in a composite system. In this composite system, failure of a component induces increased load on the surviving components and thus increases component hazard rate via a power-trend process. Point estimates of the composite system parameters are obtained by the method of maximum likelihood. Interval estimates of the baseline survival function are obtained by using the maximum-likelihood estimator via a bootstrap percentile method. Two parametric bootstrap procedures are proposed to test whether the hazard rate function changes with the number of failed components. Intensive simulations are carried out to evaluate the performance of the proposed estimation procedure.

Reference intervals for absolute and percentage immature platelet fraction using the Sysmex XN-10 automated haematology analyser in a UK population

Background: Immature platelet fraction (IPF) estimation is a non-invasive and sensitive test that is available on recently introduced Sysmex XN-series of automated haematology analysers. It is a direct cellular indicator of thrombopoiesis. The aim of this study was to establish reference intervals for IPF, for both absolute (A-IPF) and percentage (%-IPF) measurements.Material and methods: A total of 2366 samples that met the inclusion criteria were assayed for full blood count on the Sysmex XN-10 and a non-parametric percentile method was used for calculating the reference intervals.Results: After the outliers were excluded, the reference interval for %-IPF and A-IPF on Sysmex XN-10 were 1.6–10.1% and 4.37–23.21 × 109/L in total individuals, respectively. There was a statistical significance noted between the sexes (p = .004) for %-IPF, therefore a sex-specific reference interval was established, which was 1.8–10.0% for the males and 1.5–10.1% for females. No significant difference in sex status for A-IPF and age status for both %-IPF and A-IPF was observed. A very poor correlation was estimated between age versus %-IPF, ρ = 0.0156, and age versus A-IPF, ρ = −0.0023, indicating that there is no overall biological relationship between age and these parameters. As expected, a strong correlation between %-IPF and A-IPF was noted which could be attributed to their inter-relatedness.Conclusions: This large-scale study showed comparable reference intervals with the previous studies for %-IPF and A-IPF in a UK population. It found the need to establish sex-specific reference intervals for %-IPF, but not for A-IPF, whereas reference intervals were found to be stable across the age range.

Testing autocorrelation and partial autocorrelation: Asymptotic methods versus resampling techniques.

Autocorrelation and partial autocorrelation, which provide a mathematical tool to understand repeating patterns in time series data, are often used to facilitate the identification of model orders of time series models (e.g., moving average and autoregressive models). Asymptotic methods for testing autocorrelation and partial autocorrelation such as the 1/T approximation method and the Bartlett's formula method may fail in finite samples and are vulnerable to non-normality. Resampling techniques such as the moving block bootstrap and the surrogate data method are competitive alternatives. In this study, we use a Monte Carlo simulation study and a real data example to compare asymptotic methods with the aforementioned resampling techniques. For each resampling technique, we consider both the percentile method and the bias-corrected and accelerated method for interval construction. Simulation results show that the surrogate data method with percentile intervals yields better performance than the other methods. An R package pautocorr is used to carry out tests evaluated in this study.

Associations Between Five Important Domains of Health and the Patient Acceptable Symptom State in Rheumatoid Arthritis and Psoriatic Arthritis: A Cross‐Sectional Study of 977 Patients

To explore the link between a patient acceptable symptom state (PASS) and patient-perceived impact in rheumatoid arthritis (RA) and psoriatic arthritis (PsA). This was a cross-sectional study of unselected patients with definite RA or PsA. Pain, functional capacity, fatigue, coping, and sleep disturbance were assessed using a numeric rating scale (0-10) and compared between patients in PASS or not (Cohen's effect sizes). The domains of health associated with PASS status were assessed by multivariate forward logistic regression, and PASS thresholds were determined using the 75th percentile method and receiver operating characteristic analyses. Among 977 patients (531 with RA, 446 with PsA), the mean ± SD age was 53.4 ± 13.2 years, mean ± SD disease duration was 11.2 ± 10.0 years, and 637 (65.8%) were women. In all, 595 patients (60.9%) were in PASS; they had lower symptom levels, and all domains of health except sleep disturbance discriminated clearly between patients in PASS or not (effect sizes 0.73-1.45 in RA and 0.82-1.52 in PsA). In multivariate analysis, less pain and better coping were predictive of being in PASS. Odds ratios were: RA pain 0.80 (95% confidence interval [95% CI] 0.67-0.96), PsA pain 0.63 (95% CI 0.52-0.75), RA coping 0.84 (95% CI 0.74-0.96), and PsA coping 0.83 (95% CI 0.71-0.97). The cutoffs of symptom intensity (range 0-10), corresponding to PASS for the 5 domains of health and the 2 diseases were similar, i.e., approximately 4-5. In RA and PsA, PASS was associated with the 5 domains of health analyzed, and in particular with less pain and better coping.

Procedural Justice, Job Satisfaction and Organizational Citizenship Behaviour: Mediating Role of Organizational Trust—Indian Tourism Industry Study

This study attempts to understand job satisfaction (JS) and organizational citizenship behaviour (OCB) in relation to procedural justice (PJ). It also studies the mechanism through which PJ is likely to influence the dependent variables. On the basis of existing literature, organizational trust is identified as the mediating instrument through which PJ may affect JS and OCB. A survey-based design was used to collect data from 204 employees in the National Capital Region of Delhi. The respondents were working in organizations that broadly encompass the tourism industry. Correlation, regression and hierarchical multiple regression were used to test the model in the study. The mediation model was also tested using the bias-corrected percentile method with 5000 bootstrap samples. The results of the study corroborated with the previous findings and the stated hypotheses, with the exception that organizational trust was found not to mediate the relation between PJ and OCB. Some significant implications for managers and organizations can be gauged from this study. Managers must work towards establishing fair procedures in all aspects of organizational functioning. They should also decipher the attributes of organizational trust which are perceived as valuable by the employees.

Assessment of the status of injury knowledge prevention and management at various levels of sports persons

In the present scenario of sports injury has been identified as major adolescent health problem. The purpose of this study was to investigate the current level of knowledge of sports injury prevention and management and its present status among different level of sportspersons. For accomplish the study a total 100 sportspersons were randomly selected as sample. The age of the sample were ranged from 17 to 35. To assess the knowledge of sports injury prevention and management a self-structured knowledge questionnaire was used which consists of 25 questions related to injury prevention, injury type, injury management, dressing and extremity fixation, hot and cold padding, CPR, traumatic bleeding management, and shock management respectively. For analysis demographic information mean, standard deviation, were used as descriptive statistics, percentage & percentile method were used to access the status of injury knowledge. The SPSS version 21 was used to perform the statistical equations.

Hearing Preservation: Does Electrode Choice Matter?

Objective Evaluate if electrode design affects hearing preservation (HP) following cochlear implantation (CI) with full-length electrodes. Study Design Case series with chart review. Setting Tertiary referral academic center. Subjects and Methods Forty-five adults with low-frequency hearing (≤85 dB at 250 and 500 Hz) who underwent unilateral CI with full-length electrode arrays made by 1 manufacturer were included. HP was calculated with (1) mean low-frequency pure-tone average (LFPTA) at 250 and 500 Hz (MEAN method), (2) a percentile method across the audiometric frequency spectrum generating an S-value (HEARRING method), and (3) functional if hearing remained ≤85 dB at 250 and 500 Hz. Audiometric testing was performed approximately 1 month and 1 year postoperatively, yielding short-term and long-term results, respectively. Results Of 45 patients who underwent CI, 46.7% received lateral wall (LW) and 53.3% received perimodiolar (PM) electrodes. At short-term follow-up, LW electrodes were associated with significantly better HP than PM (LFPTA method: 27.7 vs 39.3 dB, P < .05; S-value method: 48.2 vs 21.8%, P < .05). In multivariate regression of short-term outcomes, LW electrode use was a significant predictor of better HP ( P < .05). At long-term follow-up, electrode type was not associated with HP. Younger patient age was the only significant predictor of long-term HP on multivariate analysis ( P < .05). Conclusion The LW electrode is associated with short-term HP, suggesting its design is favorable for limiting trauma to the cochlea during and directly following CI. Other factors, including age, are relevant for maintaining HP over the long term. The data support further investigation into what modifiable factors may promote long-term HP.

Potential impacts of climate change on extreme precipitation over four African coastal cities

This study examines the impacts of climate change on characteristics of extreme precipitation events over four African coastal cities (Cape Town, Maputo, Lagos and Port Said) under two future climate scenarios (RCP4.5 and RCP8.5). Fourteen indices were used to characterise extreme precipitation and 16 multi-model simulation datasets from the Coordinated Regional Climate Downscaling Experiment (CORDEX) were analysed. The capability of the models to reproduce past characteristics of extreme precipitation over the cities was evaluated against four satellite datasets after quantifying the observation uncertainties over the cities. The models give realistic simulation of extreme precipitation characteristics over the cities, and in most cases, the magnitudes of the simulation biases are within the observation uncertainties. For both the RCP4.5 and RCP8.5 scenarios, the models project a decrease in wet days and an increase in dry spells over the four cities in the future. More intense daily precipitation is projected over Maputo, Lagos and Port Said. The intensity and frequency of extreme precipitation events are projected to increase over Lagos, but decrease over the other cities. A decrease in annual precipitation is projected over Cape Town, Maputo and Port Said, whilst an increase is projected over Lagos, where the water surplus from the more extreme precipitation events exceeds the deficit from the less wet days. A decrease in the number of widespread extreme events is indicated over all the cities. Wet-day percentile and all-day percentile methods signal opposite future changes in the extreme precipitation thresholds over the cities (except over Lagos). The results of this study may have application in managing the vulnerabilities of these coastal cities to extreme precipitation events under climate change.

How to select a proper early warning threshold to detect infectious disease outbreaks based on the China infectious disease automated alert and response system (CIDARS)

BackgroundChina Centre for Diseases Control and Prevention (CDC) developed the China Infectious Disease Automated Alert and Response System (CIDARS) in 2005. The CIDARS was used to strengthen infectious disease surveillance and aid in the early warning of outbreak. The CIDARS has been integrated into the routine outbreak monitoring efforts of the CDC at all levels in China. Early warning threshold is crucial for outbreak detection in the CIDARS, but CDCs at all level are currently using thresholds recommended by the China CDC, and these recommended thresholds have recognized limitations. Our study therefore seeks to explore an operational method to select the proper early warning threshold according to the epidemic features of local infectious diseases.MethodsThe data used in this study were extracted from the web-based Nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS), and data for infectious disease cases were organized by calendar week (1–52) and year (2009–2015) in Excel format; Px was calculated using a percentile-based moving window (moving window [5 week*5 year], x), where x represents one of 12 centiles (0.40, 0.45, 0.50….0.95). Outbreak signals for the 12 Px were calculated using the moving percentile method (MPM) based on data from the CIDARS. When the outbreak signals generated by the ‘mean + 2SD’ gold standard were in line with a Px generated outbreak signal for each week during the year of 2014, this Px was then defined as the proper threshold for the infectious disease. Finally, the performance of new selected thresholds for each infectious disease was evaluated by simulated outbreak signals based on 2015 data.ResultsSix infectious diseases were selected in this study (chickenpox, mumps, hand foot and mouth diseases (HFMD), scarlet fever, influenza and rubella). Proper thresholds for chickenpox (P75), mumps (P80), influenza (P75), rubella (P45), HFMD (P75), and scarlet fever (P80) were identified. The selected proper thresholds for these 6 infectious diseases could detect almost all simulated outbreaks within a shorter time period compared to thresholds recommended by the China CDC.ConclusionsIt is beneficial to select the proper early warning threshold to detect infectious disease aberrations based on characteristics and epidemic features of local diseases in the CIDARS.