Currently set to Index
Currently set to Follow
Skip to main content

Publication | Analytical framework to evaluate and optimize the use of imperfect diagnostics to inform outbreak response: Application to the 2017 plague epidemic in Madagascar

Written by OneHealthPact on . Posted in Publications.

publication

This publication is part of the project ‘Preparing for vector-borne virus outbreaks in a changing world: a One Health Approach’ (NWA.1160.1S.210) which is (partly) financed by the Dutch Research Council (NWO).

Authors: Quirine ten Bosch, Voahangy Andrianaivoarimanana, Beza Ramasindrazana, Guillain Mikaty, Rado J. L. Rakotonanahary, Birgit Nikolay, Soloandry Rahajandraibe, Maxence Feher, Quentin Grassin, Juliette Paireau, Soanandrasana Rahelinirina, Rindra Randremanana, Feno Rakotoarimanana, Marie Melocco, Voahangy Rasolofo, Javier Pizarro-Cerdá, Anne-Sophie Le Guern, Eric Bertherat, Maherisoa Ratsitorahina, André Spiegel, Laurence Baril, Minoarisoa Rajerison, Simon Cauchemez 

Abstract

During outbreaks, the lack of diagnostic “gold standard” can mask the true burden of infection in the population and hamper the allocation of resources required for control. Here, we present an analytical framework to evaluate and optimize the use of diagnostics when multiple yet imperfect diagnostic tests are available. We apply it to laboratory results of 2,136 samples, analyzed with 3 diagnostic tests (based on up to 7 diagnostic outcomes), collected during the 2017 pneumonic (PP) and bubonic plague (BP) outbreak in Madagascar, which was unprecedented both in the number of notified cases, clinical presentation, and spatial distribution. The extent of these outbreaks has however remained unclear due to nonoptimal assays. Using latent class methods, we estimate that 7% to 15% of notified cases were Yersinia pestis-infected. Overreporting was highest during the peak of the outbreak and lowest in the rural settings endemic to Y. pestis. Molecular biology methods offered the best compromise between sensitivity and specificity. The specificity of the rapid diagnostic test was relatively low (PP: 82%, BP: 85%), particularly for use in contexts with large quantities of misclassified cases. Comparison with data from a subsequent seasonal Y. pestis outbreak in 2018 reveal better test performance (BP: specificity 99%, sensitivity: 91%), indicating that factors related to the response to a large, explosive outbreak may well have affected test performance. We used our framework to optimize the case classification and derive consolidated epidemic trends. Our approach may help reduce uncertainties in other outbreaks where diagnostics are imperfect.

Fig 1. Diagnostics and case classification during the plague outbreak in Madagascar in 2017. (A, B) Weekly number of notified cases for PP (A) and BP (B) by case classification. (C–E) Proportion of notified cases classified as confirmed (conf) or probable (prob) (C), with a positive test result for RDT, culture, or MB (NB, only cases on whom the respective test was performed are considered in the denominator. No restrictions were put on the use of MB and RDT. Culture was only performed if RDT was positive, apart from PP samples from nonendemic regions. On those samples, culture was performed irrespective of RDT result) (D) and with a certain combination of diagnostic outcomes (E), presenting outcomes that were performed on all samples (RDT, qPCR on pla and caf1 genes). Model fits to these proportions are provided with black dots and lines indicating model predictions and 95% credible intervals, respectively. The underlying data and code to reproduce this figure are available on Open Science Framework (https://osf.io/nbc4t/). BP, bubonic plague; MB, molecular biology; PP, pneumonic plague; qPCR, quantitative polymerase chain reaction; RDT, rapid diagnostic test.
Fig 2. Case classification algorithm. Confirmed cases include cases with positive results for both RDT and MB and/or positive culture, probable have either RDT or MB positive, and suspected have no confirmatory laboratory results. MB, molecular biology; RDT, rapid diagnostic test.
Fig 3. Model estimates of test performance and prevalence. (A) Specificity of each test, with RDT denoting rapid diagnostic test and MB denoting molecular biology. (B) Sensitivity of each test. (C) Prevalence of Y. pestis infection among notified cases, under the assumption of perfect sample quality. (D) Relationship between sample quality (i.e., the proportion of samples from infected individuals that contain detectable bacterial material) and estimated prevalence of infection among notified cases. Results are presented by clinical form: pneumonic (PP: blue) and bubonic (BP: orange). The circle/triangle shows the posterior median of the parameter while the lines show the 95% credible interval. The underlying data and code to reproduce this figure are available on Open Science Framework (https://osf.io/nbc4t/). BP, bubonic plague; MB, molecular biology; PP, pneumonic plague; RDT, rapid diagnostic test.
Fig 4. Performance of the case classification system. (A, B) Expected proportion of notified cases classified as confirmed (dark blue or orange), probable (light blue or orange), and suspected (white), as a function of prevalence of infection for PP (A) and BP (B). The dashed vertical line indicates the prevalence among notified cases estimated during the 2017 Madagascar outbreak. The dashed diagonal line corresponds to perfect classification (C, D). Expected proportion of Y. pestis infections among cases in the category confirmed, confirmed or probable, and suspected as a function of prevalence of infection for PP (C) and BP (D). (E, F) ROC plots presenting sensitivity versus (1-specificity) for a range of possible classification criteria for PP (E) and BP (F) and for simplifications of the MB algorithm for PP (inset of E) and BP (inset of F). MB is considered here due to its potential for being considered as a classifier by itself. Here, conf denotes confirmed and prob denotes probable. Classifications ≥1 qpcr and 2 qpcr represent results based on qPCR solely, i.e., in the absence of confirmatory cPCR, with ≥1 qpcr denoting “at least 1 gene positive” and 2 qpcr “both genes positive.” The underlying data and code to reproduce this figure are available on Open Science Framework (https://osf.io/nbc4t/). BP, bubonic plague; cPCR, classical polymerase chain reaction; MB, molecular biology; PP, pneumonic plague; qPCR, quantitative polymerase chain reaction; ROC, Receiver operating characteristic.
Fig 5. Reconstruction of the outbreak by place and time. (A, B) Estimated prevalence of infection among notified cases by time period for PP (A) and BP (B). Here, the initial phase spans weeks 34–38, outbreak phase 39–43, and the end phase 44–48. (C, D) Prevalence estimates by zone for PP (C) and BP (D). No BP cases were notified from Toamasina. (E, F) Prevalence estimates by age for PP (E) and BP (F). (G, H) Observed notifications (bars) vs. estimated infections (solid lines with shading denoting 95% credible intervals) among notified cases for PP (G) and BP (H). The stacked bar plots denote the percentage (A–F) and absolute numbers (G–H) by case classification. The underlying data and code to reproduce this figure are available on Open Science Framework (https://osf.io/nbc4t/). BP, bubonic plague; PP, pneumonic plague.

Citation: ten Bosch Q, Andrianaivoarimanana V, Ramasindrazana B, Mikaty G, Rakotonanahary RJL, Nikolay B, et al. (2022) Analytical framework to evaluate and optimize the use of imperfect diagnostics to inform outbreak response: Application to the 2017 plague epidemic in Madagascar. PLoS Biol 20(8): e3001736. https://doi.org/10.1371/journal.pbio.3001736

Academic Editor: James Lloyd-Smith, University of California, Los Angeles, UNITED STATES

Received: November 15, 2021; Accepted: June 30, 2022; Published: August 15, 2022

Copyright: © 2022 ten Bosch et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data and code required to reproduce the analysis in this manuscript are available on Open Science Framework: https://osf.io/nbc4t/.

Funding: This work was supported by Wellcome Trust/ Department of International Development (Grant 211309/Z/18/Z; https://wellcome.org/ supporting MM, RR, and FMR), AXA Research Fund (https://www.axa-research.org/ supporting QTB, BN, JP and SC), and the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (Grant ANR-10-LABX-62-IBEID; https://anr.fr/ supporting JPC, QTB, BN, JP and SC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations:: BP, bubonic plague; CFR, case fatality ratio; CLP, central laboratory for plague; cPCR, classical polymerase chain reaction; IPM, Institut Pasteur de Madagascar; MB, molecular biology; MCMC, Markov chain Monte Carlo; PP, pneumonic plague; PPV, positive predictive value; qPCR, quantitative polymerase chain reaction; RDT, rapid diagnostic test.

Read more

Bron: PLOS BIOLOGY

Datum: August 15th 2022