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

Quirine ten Bosch (1, 2) , Voahangy Andrianaivoarimanana (3) , Beza Ramasindrazana (3) , Guillain Mikaty (4, 5) , Rado J L Rakotonanahary (3) , Birgit Nikolay (1) , Soloandry Rahajandraibe (3) , Maxence Feher (4, 5) , Quentin Grassin (4, 5) , Juliette Paireau (1) , Soanandrasana Rahelinirina (3) , Rindra Randremanana (6) , Feno Rakotoarimanana (6) , Marie Melocco (6) , Voahangy Rasolofo (7) , Javier Pizarro-Cerdá (8, 9, 10) , Anne-Sophie Le Guern (8, 9, 10) , Eric Bertherat (11) , Maherisoa Ratsitorahina (7) , André Spiegel (7) , Laurence Baril (6) , Minoarisoa Rajerison (3) , Simon Cauchemez (1)

1 Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases
2 WUR - Wageningen University and Research [Wageningen]
3 Unité Peste - Plague Unit [Antananarivo, Madagascar]
4 ERI - Environnement et Risques infectieux - Environment and Infectious Risks
5 CIBU - Cellule d'Intervention Biologique d'Urgence (Centre National de Référence) - Laboratory for Urgent Response to Biological Threats (National Reference Center)
6 Unité d’Épidémiologie et de Recherche clinique [Antananarivo, Madagascar]
7 Institut Pasteur de Madagascar
8 Yersinia
9 CNR - Centre National de Référence de la Peste et autres Yersinioses - National Reference Center Plague and Yersinioses
10 CC-OMS / WHO-CC - Centre collaborateur de l'OMS Yersinia - WHO Collaborating Center Yersinia
11 OMS / WHO - Organisation Mondiale de la Santé / World Health Organization Office

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.

Domaines: Sciences du Vivant [q-bio]

Quirine ten Bosch, Voahangy Andrianaivoarimanana, Beza Ramasindrazana, Guillain Mikaty, Rado J L Rakotonanahary, et al.. Analytical framework to evaluate and optimize the use of imperfect diagnostics to inform outbreak response: Application to the 2017 plague epidemic in Madagascar. PLoS Biology, 2022, 20 (8), pp.e3001736. ⟨10.1371/journal.pbio.3001736⟩. ⟨pasteur-04094929⟩