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01.12.2018 | Research | Ausgabe 1/2018 Open Access

Malaria Journal 1/2018

Plasmodium species differentiation by non-expert on-line volunteers for remote malaria field diagnosis

Zeitschrift:
Malaria Journal > Ausgabe 1/2018
Autoren:
Alejandra Ortiz-Ruiz, María Postigo, Sara Gil-Casanova, Daniel Cuadrado, José M. Bautista, José Miguel Rubio, Miguel Luengo-Oroz, María Linares
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12936-018-2194-8) contains supplementary material, which is available to authorized users.
Miguel Luengo-Oroz and María Linares contributed equally to this work

Abstract

Background

Routine field diagnosis of malaria is a considerable challenge in rural and low resources endemic areas mainly due to lack of personnel, training and sample processing capacity. In addition, differential diagnosis of Plasmodium species has a high level of misdiagnosis. Real time remote microscopical diagnosis through on-line crowdsourcing platforms could be converted into an agile network to support diagnosis-based treatment and malaria control in low resources areas. This study explores whether accurate Plasmodium species identification—a critical step during the diagnosis protocol in order to choose the appropriate medication—is possible through the information provided by non-trained on-line volunteers.

Methods

88 volunteers have performed a series of questionnaires over 110 images to differentiate species (Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax, Plasmodium malariae, Plasmodium knowlesi) and parasite staging from thin blood smear images digitalized with a smartphone camera adapted to the ocular of a conventional light microscope. Visual cues evaluated in the surveys include texture and colour, parasite shape and red blood size.

Results

On-line volunteers are able to discriminate Plasmodium species (P. falciparum, P. malariae, P. vivax, P. ovale, P. knowlesi) and stages in thin-blood smears according to visual cues observed on digitalized images of parasitized red blood cells. Friendly textual descriptions of the visual cues and specialized malaria terminology is key for volunteers learning and efficiency.

Conclusions

On-line volunteers with short-training are able to differentiate malaria parasite species and parasite stages from digitalized thin smears based on simple visual cues (shape, size, texture and colour). While the accuracy of a single on-line expert is far from perfect, a single parasite classification obtained by combining the opinions of multiple on-line volunteers over the same smear, could improve accuracy and reliability of Plasmodium species identification in remote malaria diagnosis.
Zusatzmaterial
Additional file 1. Example of supporting example images used in the query. (a) : young trophozoites, (b) mature trophozoites, (c) schizonts and (d) gametocytes of Plasmodium knowlesi. (e) Percentage of correct answers when support images were used (+) or not (−). Values given are the mean ± SEM calculated for the different images shown in a total of 32 volunteers. Asterisk indicates a significant difference between the percentage of response of the correct answer and each other two possibilities. * P < 0.05.
Literatur
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