scholarly journals The Early Warning And Response System (EWARS-TDR) For Dengue Outbreaks: Can It Also Be Applied To Chikungunya And Zika Outbreak Warning?

2021 ◽  
Author(s):  
Rocio Cardenas ◽  
Laith Hussain-Alkhateeb ◽  
David Benitez-Valladares ◽  
Gustavo Sanchez-Tejeda ◽  
Axel Kroeger
Keyword(s):  
Positive Predictive Value ◽  
Early Warning ◽  
Predictive Value ◽  
Large City ◽  
High Sensitivity ◽  
Surveillance Systems ◽  
Insect Vector ◽  
Alarm Signals ◽  
Response System ◽  
Dengue Outbreaks

Abstract Background. In the Americas, endemic countries for Aedes-borne diseases such as dengue, chikungunya, and Zika face great challenges particularly since the recent outbreaks of CHIKV and ZIKV, all transmitted by the same insect vector Aedes aegypti and Ae. albopictus. The Special Program for Research and Training in Tropical Diseases (TDR- WHO) has developed together with partners an early warning and Response System (EWARS) for dengue outbreaks based on a variety of alarm signals with a high sensitivity and positive predictive value (PPV). The question is if this tool can also be used for the prediction of Zika and chikungunya outbreaks.Methodology. We conducted in nine districts of Mexico and one large city in Colombia a retrospective analysis of epidemiological data (for the outbreak definition) and of climate and entomological data (as potential alarm indicators) produced by the national surveillance systems for dengue, chikungunya and Zika outbreak prediction covering the following outbreak years: for dengue 2012-2016, for Zika 2015-2017, for chikungunya 2014-2016. This period was divided into a “run in period” (to establish the “historical” pattern of the disease) and an “analysis period” (to identify sensitivity and PPV of outbreak prediction). Results. In Mexico, the sensitivity of alarm signals for correctly predicting an outbreak was 92% for dengue, and 97% for Zika (chikungunya data could not be obtained in Mexico); the PPV was 68% for dengue and 100% for Zika. The time period between alarm and start of the outbreak (i.e. the time available for early response activities) was for dengue 6-8 weeks and for Zika 3-5 weeks. In Colombia the sensitivity of the outbreak prediction was 92% for dengue, 93% for chikungunya and 100% for Zika; the PPV was 68% for dengue, 92% for chikungunya and 54% for Zika; the prediction distance was for dengue 3-5 weeks, for chikungunya 10-13 weeks and for Zika 6-10 weeks. Conclusion. The implementation of an early warning and response system (EWARS) could predict outbreaks of three Aedes borne diseases with a high sensitivity and positive predictive value and with a lag time long enough for preparing an adequate outbreak response in order to reduce the magnitude or avert the occurrence of outbreaks with their elevated social and economic tolls.

scholarly journals Early Warning and Response System (EWARS) for chikungunya, zika and dengue outbreaks: The innovated WHO-TDR tool.

2019 ◽  
Author(s):  
Rocio Cardenas ◽  
Laith Hussain-Alkhateeb ◽  
David Benitez-Valladares ◽  
Gustavo Sanchez Tejeda ◽  
Axel Kroeger
Keyword(s):  
Early Warning ◽  
Urban Areas ◽  
High Sensitivity ◽  
Early Response ◽  
Surveillance Systems ◽  
Insect Vector ◽  
Predictive Values ◽  
Alarm Signals ◽  
Response System ◽  
Dengue Outbreaks

Abstract Background. In the Americas, endemic cities for Aedes-borne diseases such as chikungunya, Zika and dengue face great challenges particularly since the recent outbreaks of CHIKV and ZIKV, all transmitted by the same insect vector Aedes aegypti and albopictus. Areas, such as Colombia and Mexico with the highest incidence and most frequent outbreaks of the three diseases are located in tropical environments due to their favorable eco-epidemiological conditions for vector breeding. In Colombia, the city of Cúcuta on the border with Venezuela is one of such highly endemic areas. Likewise, in Mexico a number of municipalities has very similar environmental conditions. This is why these urban areas provide the opportunity to test the Early Warning and Response System (EWARS), developed originally for dengue outbreaks, also for the other two diseases (Chikungunya and Zika). Methodology. Through the retrospective analysis of epidemiological, climate and entomological data produced by the national surveillance systems in Colombia and Mexico, we intended to predict outbreaks with a high sensitivity and positive predictive value (PPV) through alarm signals by using the EWARS tool. The registered outbreaks of DENV 2012-2016, CHIKV 2014-2016 and ZIKV 2015-2016 were analyzed for 2 years retrospectively (“run in period”) and one year of analysis (“evaluation period”). Outbreak prediction for dengue and Zika was for both countries but for Chikungunya in Colombia only due to the availability of surveillance data. Results. In Mexico, the sensitivity of different alarm signals for correctly predicting an outbreak ranged between 74-92% for dengue, 77–93% for chikungunya and 78-97% for Zika. Their Positive Predictive Values ranged between 51-68% for dengue, 48-92% for chikungunya and 11-100% for Zika. The lag time between predictions and start of the outbreak (i.e. the time available for early response activities) was for dengue 3-5 weeks, for chikungunya 10-13 weeks and for Zika 3-5 weeks. Conclusion. The implementation of an early warning and response system (EWARS) could substantially reduce the magnitude and occurrence of outbreaks and the elevated social and economic toll.

scholarly journals Validation of the Early Warning and Response System (EWARS) for dengue outbreaks: Evidence from the national vector control program in Mexico

2021 ◽  
Vol 15 (12) ◽  
pp. e0009261
Author(s):  
David Benitez-Valladares ◽  
Axel Kroeger ◽  
Gustavo Sánchez Tejeda ◽  
Laith Hussain-Alkhateeb
Keyword(s):  
Vector Control ◽  
Early Warning ◽  
Disease Transmission ◽  
Indoor Residual Spraying ◽  
Alarm Signals ◽  
Dengue Outbreak ◽  
Response System ◽  
Adequate Response ◽  
Dengue Outbreaks ◽  
The Impact

Background During 2017, twenty health districts (locations) implemented a dengue outbreak Early Warning and Response System (EWARS) in Mexico, which processes epidemiological, meteorological and entomological alarm indicators to predict dengue outbreaks and triggers early response activities. Out of the 20 priority districts where more than one fifth of all national disease transmission in Mexico occur, eleven districts were purposely selected and analyzed. Nine districts presented outbreak alarms by EWARS but without subsequent outbreaks (“non-outbreak districts”) and two presented alarms with subsequent dengue outbreaks (“outbreak districts”). This evaluation study assesses and compares the impact of alarm-informed response activities and the consequences of failing a timely and adequate response across the outbreak groups. Methods Five indicators of dengue outbreak response (larval control, entomological studies with water container interventions, focal spraying and indoor residual spraying) were quantitatively analyzed across two groups (”outbreak districts” and “non-outbreak districts”). However, for quality control purposes, only qualitative concluding remarks were derived from the fifth response indicator (fogging). Results The average coverage of vector control responses was significantly higher in non-outbreak districts and across all four indicators. In the “outbreak districts” the response activities started late and were of much lower intensity compared to “non-outbreak districts”. Vector control teams at districts-level demonstrated diverse levels of compliance with local guidelines for ‘initial’, ‘early’ and ‘late’ responses to outbreak alarms, which could potentially explain the different outcomes observed following the outbreak alarms. Conclusion Failing timely and adequate response of alarm signals generated by EWARS showed to negatively impact the disease outbreak control process. On the other hand, districts with adequate and timely response guided by alarm signals demonstrated successful records of outbreak prevention. This study presents important operational scenarios when failing or successding EWARS but warrants investigating the effectiveness and cost-effectiveness of EWARS using a more robust designs.

scholarly journals Evaluating Specivity, Sensitivity, Positive and Negative Predictive Values of CA125 for Diagnosing Ovarian Cancer

2021 ◽  
Vol 24 (2) ◽  
pp. 196-203
Author(s):  
Elahe Fini ◽  
◽  
Neda Nasirian ◽  
Bahram Hosein Beigy ◽  
◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Positive Predictive Value ◽  
Tumor Marker ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Screening Test ◽  
High Sensitivity ◽  
Medical Community ◽  
Cross Sectional ◽  
Predictive Values

Background and Aim: Ovarian cancer is among the most common cancers in women worldwide. CA125 is the most frequent biomarker used in the screening for ovarian cancer. CA125 has no high sensitivity and specificity as a screening test in the medical community; however, because of being simple and noninvasive, it is almost always requested for evaluation and ruling out cancer. It plays an important role in the treatment and post-treatment process, the prediction of prognosis, and the relapse of the disease. The present study aimed to determine the relationship between a high level of CA125 tumor marker and ovarian cancer by detecting spesivity, sensivity, positive and negative predictive values. Methods & Materials: In this cross-sectional study, all cases undergoing CA125 test in Velayat Hospital in 2017-1028 were evaluated for having ovarian cancer. In addition, the CA125 level was compared between healthy individuals and patients with ovarian cancer. Finally, the obtained data were analyzed using SPSS. Ethical Considerations: The present study was approved by the Qazvin University of Medical Sciences (Ethics Code: IR.QUMS.REC.1396.316). Results: In this study, 35.3% of the study participants received a definite diagnosis of ovarian cancer. Generally, CA125 values were negative in 41.8% and positive in.58.2% of the study subjects. The sensitivity of the test was measured as 80.1%, the specivity as 53.6%, the positive predictive value equaled 48.4%, and the negative predictive value was measured as 83%. There was a significant relationship between age and the presence of ovarian cancer, and serum CA125 levels. Conclusion: The present study suggested that age and the serum level of CA125 were statistically significant. Finally, CA125 levels were significantly related to ovarian cancer. It provided moderate specivity and specivity as well as low positive predictive value and high negative predictive value as a tumor marker; it is valuable for ruling out of tumor but not appropriate as a screening test.

Abstract 3426: Approximate Volume Using "XYZ/2" Is Equivalent to Planimetric Volume Mismatch Evaluation

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Marie Luby ◽  
Jennifer Hong ◽  
José G Merino ◽  
John K Lynch ◽  
Amie W Hsia ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
Gold Standard ◽  
Correlation Coefficients ◽  
High Sensitivity ◽  
Evaluation Methods ◽  
Slice Thickness ◽  
Linear Measurements ◽  
Visual Evaluation ◽  
Volume Measurements

Objectives: In the clinical setting, the extent of mismatch on MRI is frequently assessed with an approximate “XYZ/2” method but the agreement with the “gold standard” planimetric volume and the “visual evaluation” methods are not known. In a published study, we established that the visual evaluation and planimetric methods are equivalent as far as mismatch classification. The objectives of this study were to quantify the agreement of the approximate method with the “gold standard” and “visual evaluation” methods and to compare the mismatch classification results. Methods: Patients were selected from the Lesion Evolution of Stroke and Ischemia On Neuroimaging (LESION) database if they: had an acute ischemic stroke, were treated with intravenous rt-PA only, and had a pre-treatment MRI with evaluable maps including trace or isotropic b1000 DWI and MTT images. A trained rater viewed the images on the PACS, placed the two perpendicular linear measurements, “X” and “Y”, on the slices with the largest DWI and MTT lesion areas, and then used a “XYZ/2” formula where “Z” was the product of the slice thickness and the total number of slices containing the lesion. A separate expert rater measured the planimetric volumes on a slice-by-slice basis with a semiautomated segmentation tool followed by manual editing. Expert readers evaluated the MRI scans for the presence of qualitative mismatch. The expert readers were not the trained reader that performed the approximate volume measurements. Quantitative mismatch was considered present if MTT volume - DWI volume ≥50 ml. Mismatch classifications using the ≥ 50 ml definition were compared by constructing contingency tables. Results: A total of 194 patients met the study criteria and had median DWI and MTT planimetric volumes of 13.06 ml and 99.27 ml respectively. For both the DWI (n=170) and MTT (n=164), 94% of the measurements were within two standard deviations of the difference between the planimetric and approximate volume measurements. Comparing the planimetric and approximate volume measurements, the Spearman correlation coefficients were 0.855 and 0.886 for the DWI and MTT measurements respectively (p<0.01). Compared to the planimetric method, the approximate “XYZ/2” method had a high sensitivity (0.91), specificity (0.80), accuracy (0.86) and positive predictive value (0.85) to detect mismatch using the ≥ 50 ml definition. Compared to the qualitative method, the approximate “XYZ/2” method had a sensitivity (0.77), specificity (0.76), accuracy (0.77) and positive predictive value (0.87) to detect mismatch using the ≥ 50 ml definition. Conclusions: The approximate “XYZ/2” method is sufficient for classifying the presence of MRI determined mismatch in acute stroke patients and therefore is a potential tool when using MRI determined mismatch as an inclusion criteria for clinical trials.

Isolated demyelinating syndromes: comparison of CSF oligoclonal bands and different MR imaging criteria to predict conversion to CDMS

2001 ◽  
Vol 7 (6) ◽  
pp. 359-363 ◽  
Author(s):  
M Tintoré ◽  
A Rovira ◽  
L Brieva ◽  
E Grivé ◽  
R Jardí ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
High Sensitivity ◽  
Oligoclonal Bands ◽  
High Negative Predictive Value ◽  
Csf Oligoclonal Bands ◽  
Sensitivity Specificity

Aim of the study: To evaluate and compare the capacity of oligoclonal bands (OB) and three sets of MR imaging criteria to predict the conversion of clinically isolated syndromes (CIS) to clinically definite multiple sclerosis (CDMS). Patients and methods: One hundred and twelve patients with CIS were prospectively studied with MR imaging and determination of OB. Based on the clinical follow-up (conversion or not conversion to CDMS), we calculated the sensitivity, specificity accuracy, positive and negative predictive value of the OB, and MR imaging criteria proposed by Paty et al, Fazekas et al and Barkhof et al. Results: CDMS developed in 26 (23.2%) patients after a mean follow-up of 31 months (range 12-62). OB were positive in 70 (62.5%) patients and were associated with a higher risk of developing CDMS. OB showed a sensitivity of 81%, specificity of 43%, accuracy of 52%, positive predictive value (PPV) of 30% and negative predictive value (NPV) of 88%. Paty and Fazekas criteria showed the same results with a sensitivity of 77%, specificity of 51%, accuracy of 57%, positive predictive value of 32% and negative predictive value of 88%. Barkhof criteria showed a sensitivity of 65%, specificity of 70%, accuracy of 69%, PPV of 40% and NPV of 87%. The greatest accuracy was achieved when patients with positive OB and three or four Barkhof's criteria were selected. Conclusions: We observed a high prevalence of OB in CIS. OB and MR imaging (Paty's and Fazekas' criteria) have high sensitivity. Barkhof's criteria have a higher specificity. Both OB and MR imaging criteria have a high negative predictive value.

Sensitivity, Specificity, and Positive Predictive Value of Technetium 99-HMPAO SPECT in Discriminating Alzheimer's Disease from other Dementias

1997 ◽  
Vol 10 (1) ◽  
pp. 15-21 ◽  
Author(s):  
Donna L. Masterman ◽  
Mario F. Mendez ◽  
Lynn A. Fairbanks ◽  
Jeffrey L. Cummings
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
Single Photon ◽  
Photon Emission ◽  
High Sensitivity ◽  
Hmpao Spect ◽  
Clinical Diagnoses ◽  
Sensitivity Specificity

Investigators have reported high sensitivity and specificity values for single photon emission computerized tomography (SPECT) when distinguishing Alzheimer's disease (AD) patients from normal elderly controls or from selected patient groups. The role of SPECT in identifying AD among unselected patients with memory complaints requires investigation. We examined 139 consecutive patients with 99Tc-HMPAO SPECT. NINCDS-ADRDA diagnoses were determined blind to SPECT results, and scans were read and classified by visual inspection blind to clinical diagnoses. Bilateral temporoparietal hypoperfusion (TP) occurred in 75% of probable, 65% of possible, and 45% of unlikely AD patients, yielding a sensitivity of 75% and a specificity of 52% when comparing probable AD versus unlikely AD groups. A positive predictive value of 78% was obtained based on a 69% prevalence of AD in our total clinic population. Patients with false-positive results included a variety of dementing illnesses; all patients with bilateral hypoperfusion had dementia. A pattern of TP on SPECT scans is seen in most patients with AD, but could be found in other dementias as well and cannot be regarded as specific to AD. Reduced TP perfusion discriminated between demented and nondemented individuals. Further strategies for SPECT interpretation that improve diagnostic specificity should be sought.

A pharmacogenetic model predicting low paclitaxel clearance based on the DMET platform.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 2597-2597
Author(s):  
Annemieke J.M. Nieuweboer ◽  
Anne-Joy M. de Graan ◽  
Laure Elens ◽  
Marcel Smid ◽  
John W. M. Martens ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Prediction Model ◽  
Predictive Value ◽  
Plasma Concentrations ◽  
Sampling Strategy ◽  
High Sensitivity ◽  
Cancer Drug ◽  
Drug Metabolizing Enzyme ◽  
Validation Set ◽  
Metabolizing Enzyme

2597 Background: Paclitaxel (PTX) is a commonly used cytotoxic agent. It is metabolized by P450 cytochrome iso-enzymes CYP3A4 and CYP2C8 and has high interindividual variability in pharmacokinetics (PK) and toxicity. Here, we present a genetic prediction model to identify patients with low PTX clearance (CL) using the new Drug-Metabolizing Enzyme and Transporter (DMET; Affymetrix) platform, capable of detecting 1,936 genetic variants (SNPs) in 225 genes. Methods: In a PK study, 270 Caucasian cancer patients were treated with PTX. PK parameters were determined using a limited sampling strategy. HPLC or LC-MS/MS were used to determine PTX plasma concentrations and non-linear mixed effects modelling (NONMEM) was used to estimate individual unbound CL from previously developed PK population models. Subsequently, the cohort of patients was randomly split into a training and validation set. In all patients, the presence of SNPs in metabolic enzymes and transporters was determined using the DMET platform. Selected SNPs were subsequently validated in the validation set. Results: Baseline characteristics were comparable in both sets. The mean CL of the total cohort was 488 ± 149 L/h and the threshold for low CL was set at 339 L/h (1 SD < total mean CL). 14 SNPs were selected to be included in the prediction model and validated in the validation set. For none of these 14 SNPs, evidence for a biological plausible link to taxane metabolism exists. The developed prediction model had a sensitivity of 95% to identify low PTX CL, a positive predictive value of 22% and remained significantly associated with low CL after multivariate analysis correcting for age, gender and Hb levels at start of therapy (P=0.024). Conclusions: This is the first considerably-sized application of the DMET platform to explain PK variability of a widely used anti-cancer drug. Although this validated prediction model for PTX CL had a high sensitivity, its positive predictive value is too low to be of direct clinical use. Likely, genetic variability in DMET genes alone does not sufficiently explain PTX CL, as for example environmental factors may also influence PTX metabolism.

scholarly journals Validation of the Early Warning and Response System (EWARS) for dengue outbreaks: Evidence from the national vector control program in Mexico

2021 ◽  
Author(s):  
David Benitez-Valladares ◽  
Axel Kroeger ◽  
Gustavo Sánchez Tejeda ◽  
Laith Hussain-Alkhateeb
Keyword(s):  
Vector Control ◽  
Early Warning ◽  
National Level ◽  
Indoor Residual Spraying ◽  
False Alarms ◽  
Outbreak Response ◽  
Effective Response ◽  
Dengue Outbreak ◽  
Response System ◽  
Dengue Outbreaks

AbstractBackgroundDuring 2017, twenty health districts (locations) in Mexico implemented a dengue outbreak early warning and response system (EWARS) that uses epidemiological, meteorological and entomological variables (alarm indicators) to predict dengue outbreaks and triggers early response activities.Eleven of these districts were analyzed as they presented reliable information. Nine districts presented outbreak alarms but without subsequent outbreaks (“non-outbreak districts”) and two presented after the alarms dengue outbreaks (“outbreak districts”). This study is concerned with i) if the alarms without outbreaks were false alarms or if the control services had established effective response activities averting an outbreak and ii) if vector control activities can mitigate or even avert dengue outbreaks.MethodsFive components of dengue outbreak response (larval control, entomological studies with water container interventions, focal spraying, indoor residual spraying, space spraying) were quantitatively analyzed across two groups (”outbreak districts” and “non-outbreak districts”).ResultsThe average coverage of vector control and responses were higher in non-outbreak districts and across all five components. In the “outbreak districts” the response activities started late and were of much lower intensity compared to “non-outbreak districts”. District vector control teams demonstrated diverse compliance with local guidlines for ‘initial’, ‘early’ and ‘late’ responses to outbreak alarms which could explain the different outcomes observed following the outbreak alarms.Conclusionfindings from this study plausibly demonstrates important operational scenarios when succeeding or failing alarms signals generated by EWARS at national level. This study presents evidence warranting for further investigation into the effectiveness and cost-effectiveness of EWARS using gold-standard designs.

scholarly journals Comparison of early warning scores for sepsis early identification and prediction in the general ward setting

JAMIA Open ◽  
2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Sean C Yu ◽  
Nirmala Shivakumar ◽  
Kevin Betthauser ◽  
Aditi Gupta ◽  
Albert M Lai ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Early Warning ◽  
Predictive Value ◽  
Early Identification ◽  
Academic Medical Center ◽  
Scoring Systems ◽  
General Ward ◽  
Early Warning Score ◽  
Patient Acuity ◽  
Early Warning Scores

Abstract The objective of this study was to directly compare the ability of commonly used early warning scores (EWS) for early identification and prediction of sepsis in the general ward setting. For general ward patients at a large, academic medical center between early-2012 and mid-2018, common EWS and patient acuity scoring systems were calculated from electronic health records (EHR) data for patients that both met and did not meet Sepsis-3 criteria. For identification of sepsis at index time, National Early Warning Score 2 (NEWS 2) had the highest performance (area under the receiver operating characteristic curve: 0.803 [95% confidence interval [CI]: 0.795–0.811], area under the precision recall curves: 0.130 [95% CI: 0.121–0.140]) followed NEWS, Modified Early Warning Score, and quick Sequential Organ Failure Assessment (qSOFA). Using validated thresholds, NEWS 2 also had the highest recall (0.758 [95% CI: 0.736–0.778]) but qSOFA had the highest specificity (0.950 [95% CI: 0.948–0.952]), positive predictive value (0.184 [95% CI: 0.169–0.198]), and F1 score (0.236 [95% CI: 0.220–0.253]). While NEWS 2 outperformed all other compared EWS and patient acuity scores, due to the low prevalence of sepsis, all scoring systems were prone to false positives (low positive predictive value without drastic sacrifices in sensitivity), thus leaving room for more computationally advanced approaches.

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