IJERPH, Vol. 15, Pages 259: Converging Human and Malaria Vector Diagnostics with Data Management towards an Integrated Holistic One Health Approach

IJERPH, Vol. 15, Pages 259: Converging Human and Malaria Vector Diagnostics with Data Management towards an Integrated Holistic One Health Approach

International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020259

Authors: Konstantinos Mitsakakis Sebastian Hin Pie Müller Nadja Wipf Edward Thomsen Michael Coleman Roland Zengerle John Vontas Konstantinos Mavridis

Monitoring malaria prevalence in humans, as well as vector populations, for the presence of Plasmodium, is an integral component of effective malaria control, and eventually, elimination. In the field of human diagnostics, a major challenge is the ability to define, precisely, the causative agent of fever, thereby differentiating among several candidate (also non-malaria) febrile diseases. This requires genetic-based pathogen identification and multiplexed analysis, which, in combination, are hardly provided by the current gold standard diagnostic tools. In the field of vectors, an essential component of control programs is the detection of Plasmodium species within its mosquito vectors, particularly in the salivary glands, where the infective sporozoites reside. In addition, the identification of species composition and insecticide resistance alleles within vector populations is a primary task in routine monitoring activities, aiming to support control efforts. In this context, the use of converging diagnostics is highly desirable for providing comprehensive information, including differential fever diagnosis in humans, and mosquito species composition, infection status, and resistance to insecticides of vectors. Nevertheless, the two fields of human diagnostics and vector control are rarely combined, both at the diagnostic and at the data management end, resulting in fragmented data and mis- or non-communication between various stakeholders. To this direction, molecular technologies, their integration in automated platforms, and the co-assessment of data from multiple diagnostic sources through information and communication technologies are possible pathways towards a unified human vector approach.

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