Performance of bovine genital campylobacteriosis diagnostic tests in bulls from Uruguay: a Bayesian latent class model approach

Background: Central to the successful elimination of Plasmodium falciparum malaria, are tests with superior capability of diagnosing low-density parasitaemias. Empirical evidence on the performance of the commonly available diagnostics (light microscopy (LM), rapid diagnostic tests (RDT) and polymerase chain reaction (PCR)) is needed to better inform case management and surveillance activities within primary health care settings where elimination of falciparum malaria is targeted. The objective of this study was to estimate the sensitivity (Se) and specificity (Sp) and predictive values of LM, RDT and PCR tests for P. falciparum infection in children, while evaluating the effect of specific covariates on the accuracy of the tests. Methods: The study enrolled 1,563 children presenting with fever (axillary temperature ≥ 37.50C) to the Ngerenya dispensary, Kilifi County between March and December 2014. A Bayesian latent class model (BLCM) was fitted to the participants’ diagnostic data obtained from blood samples that were screened for the presence of P. falciparum using the three tests. Results: The PCR assay registered a higher Se (97.6% [92.0; 99.7]) than LM (84.0% [74.8; 91.0]) but similar to RDT (92.2% [84.4; 97.0]). However, the assay showed a similar Sp (98.9% [98.2; 99.4]) to both RDT (99.4% [98.9; 99.7]) and LM (99.5% [99.0; 99.8]). Regarding predictive values, the tests yielded statistically similar estimates of positive and negative predictive values (PPV and NPV). A serial interpretation of the results of RDT and LM raised the PPVs and NPVs to >98%. Conclusions: LM and RDT afford high Se and Sp in symptomatic care-seeking children in this low P. falciparum prevalence setting. A serial combination of the tests assures high PPV and NPV estimates. These elements, coupled with the wide deployment and affordability of the tests, lend the tests useful for guiding clinical care and surveillance activities for P. falciparum within elimination settings.

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Heterogeneity in flood risk awareness: a longitudinal, Latent Class model approach

Journal of Hydrology ◽

10.1016/j.jhydrol.2021.126255 ◽

2021 ◽

pp. 126255

Author(s):

Cristiano Franceschinis ◽

Mara Thiene ◽

Giuliano Di Baldassarre ◽

Elena Mondino ◽

Anna Scolobig ◽

...

Keyword(s):

Flood Risk ◽

Latent Class ◽

Latent Class Model ◽

Risk Awareness ◽

Class Model ◽

Model Approach

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Bayesian evaluation of the performance of three diagnostic tests for Plasmodium falciparum infection in a low-transmission setting in Kilifi County, Kenya

Wellcome Open Research ◽

10.12688/wellcomeopenres.15204.2 ◽

2019 ◽

Vol 4 ◽

pp. 67

Author(s):

Marshal M. Mweu ◽

Juliana Wambua ◽

Fixtan Njuga ◽

Philip Bejon ◽

Daniel Mwanga

Keyword(s):

Plasmodium Falciparum ◽

Diagnostic Tests ◽

Latent Class ◽

Clinical Care ◽

Latent Class Model ◽

Axillary Temperature ◽

Class Model ◽

Predictive Values ◽

Polymerase Chain ◽

Primary Health Care Settings

Background: Central to the successful elimination of Plasmodium falciparum malaria, are tests with superior capability of diagnosing low-density parasitaemias. Empirical evidence on the performance of the commonly available diagnostics (light microscopy (LM), rapid diagnostic tests (RDT) and polymerase chain reaction (PCR)) is needed to better inform case management and surveillance activities within primary health care settings where elimination of falciparum malaria is targeted. The objective of this study was to estimate the sensitivity (Se) and specificity (Sp) and predictive values of LM, RDT and PCR tests for P. falciparum infection in children, while evaluating the effect of specific covariates on the accuracy of the tests. Methods: The study enrolled 1,563 children presenting with fever (axillary temperature ≥ 37.50C) to the Ngerenya dispensary, Kilifi County between March and December 2014. A Bayesian latent class model (BLCM) was fitted to the participants’ diagnostic data obtained from blood samples that were screened for the presence of P. falciparum using the three tests. Results: The PCR assay registered a higher Se (97.6% [92.0; 99.7]) than LM (84.0% [74.8; 91.0]) but similar to RDT (92.2% [84.4; 97.0]). However, the assay showed a similar Sp (98.9% [98.2; 99.4]) to both RDT (99.4% [98.9; 99.7]) and LM (99.5% [99.0; 99.8]). Regarding predictive values, the tests yielded statistically similar estimates of positive and negative predictive values (PPV and NPV). A serial interpretation of the results of RDT and LM raised the PPVs and NPVs to >98%. Conclusions: LM and RDT afford high Se and Sp in a low P. falciparum prevalence setting. A serial combination of the tests assures high PPV and NPV estimates. These elements, coupled with the wide deployment and affordability of the tests, lend the tests useful for guiding clinical care and surveillance activities for P. falciparum within elimination settings.

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Demand for value-added pork in Sweden: a latent class model approach

Agribusiness ◽

10.1002/agr.20262 ◽

2010 ◽

Vol 27 (2) ◽

pp. 129-146 ◽

Cited By ~ 14

Author(s):

Carolina Liljenstolpe

Keyword(s):

Latent Class ◽

Latent Class Model ◽

Value Added ◽

Class Model ◽

Model Approach

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Type Choice Behavior of Alternative Fuel Vehicles: A Latent Class Model Approach

Transportation Research Procedia ◽

10.1016/j.trpro.2017.05.188 ◽

2017 ◽

Vol 25 ◽

pp. 3299-3313 ◽

Cited By ~ 3

Author(s):

Nazmul Arefin Khan ◽

Mahmudur Rahman Fatmi ◽

Muhammad Ahsanul Habib

Keyword(s):

Choice Behavior ◽

Latent Class ◽

Latent Class Model ◽

Alternative Fuel ◽

Class Model ◽

Alternative Fuel Vehicles ◽

Model Approach

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A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

Computational and Mathematical Methods in Medicine ◽

10.1155/2012/487502 ◽

2012 ◽

Vol 2012 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Gilberto de Araujo Pereira ◽

Francisco Louzada ◽

Valdirene de Fátima Barbosa ◽

Márcia Maria Ferreira-Silva ◽

Helio Moraes-Souza

Keyword(s):

Chagas Disease ◽

General Model ◽

Gold Standard ◽

Diagnostic Tests ◽

Latent Class ◽

Latent Class Model ◽

False Negative ◽

Screening Tests ◽

Class Model ◽

Suitable Alternative

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

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