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Insights from quantitative and mathematical modelling on the proposed WHO 2030 goal for schistosomiasis [version 2; peer review: 3 approved]

Abstract:
Schistosomiasis remains one of the neglected tropical diseases (NTDs) impacting millions of people around the world. The World Health Organization (WHO) recently proposed a goal of elimination as a public health problem (EPHP) for schistosomiasis to be reached by 2030. Current WHO treatment guidelines for achieving EPHP focus on targeting school-aged children. The NTD Modelling Consortium has developed mathematical models to study schistosomiasis transmission dynamics and the impact of control measures. Our modelling insights on Schistosoma mansoni have shown that EPHP is likely to be attainable in low to moderate prevalence settings using the current guidelines. However, as prevalence rises within high prevalence settings, EPHP is less likely to be achieved unless both school-aged children and adults are treated (with coverage levels increasing with the adult burden of infection). We highlight the challenges that are faced by treatment programmes, such as non-adherence to treatment and resurgence, which can hinder progress towards achieving and maintaining EPHP. Additionally, even though EPHP may be reached, prevalence can still be high due to persisting infections. Therefore, without interruption of transmission, treatment will likely have to continue to maintain EPHP. Further modelling work is being carried out, including extending our results to S. haematobium. By providing these modelling insights, we aim to inform discussions on the goals and treatment guidelines for schistosomiasis.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.12688/gatesopenres.13052.2

Authors

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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Big Data Institute
Role:
Author

Contributors


Publisher:
F1000Research
Journal:
Gates Open Research More from this journal
Volume:
3
Article number:
1517
Publication date:
2019-08-16
Acceptance date:
2019-08-16
DOI:
EISSN:
2572-4754


Language:
English
Keywords:
Pubs id:
1076613
Local pid:
pubs:1076613
Deposit date:
2020-04-29
ARK identifier:

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