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Algorithm for diagnosis of early Schistosoma haematobium using prodromal signs and symptoms in pre-s...

Algorithm for diagnosis of early Schistosoma haematobium using prodromal signs and symptoms in pre-s...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2573455042

Algorithm for diagnosis of early Schistosoma haematobium using prodromal signs and symptoms in pre-school age children in an endemic district in Zimbabwe

About this item

Full title

Algorithm for diagnosis of early Schistosoma haematobium using prodromal signs and symptoms in pre-school age children in an endemic district in Zimbabwe

Publisher

San Francisco: Public Library of Science

Journal title

PLoS neglected tropical diseases, 2021-08, Vol.15 (8), p.e0009599-e0009599

Language

English

Formats

Publication information

Publisher

San Francisco: Public Library of Science

More information

Scope and Contents

Contents

Introduction Prompt diagnosis of acute schistosomiasis benefits the individual and provides opportunities for early public health intervention. In endemic areas schistosomiasis is usually contracted during the first 5 years of life, thus it is critical to look at how the infection manifests in this age group. The aim of this study was to describe t...

Alternative Titles

Full title

Algorithm for diagnosis of early Schistosoma haematobium using prodromal signs and symptoms in pre-school age children in an endemic district in Zimbabwe

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_plos_journals_2573455042

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2573455042

Other Identifiers

ISSN

1935-2735,1935-2727

E-ISSN

1935-2735

DOI

10.1371/journal.pntd.0009599

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