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Defining the relationship between Plasmodium vivax parasite rate and clinical disease

Battle, Katherine E., Cameron, Ewan, Guerra, Carlos A., Golding, Nick, Duda, Kirsten A., Howes, Rosalind E., Elyazar, Iqbal RF, Price, Ric N., Baird, J. Kevin, Reiner, Robert C. Jr., Smith, David L., Gething, Peter W. and Hay, Simon I. (2015). Defining the relationship between Plasmodium vivax parasite rate and clinical disease. Malaria Journal,14(Article No. 191).

Document type: Journal Article
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IRMA ID 75039815xPUB864
Title Defining the relationship between Plasmodium vivax parasite rate and clinical disease
Author Battle, Katherine E.
Cameron, Ewan
Guerra, Carlos A.
Golding, Nick
Duda, Kirsten A.
Howes, Rosalind E.
Elyazar, Iqbal RF
Price, Ric N.
Baird, J. Kevin
Reiner, Robert C. Jr.
Smith, David L.
Gething, Peter W.
Hay, Simon I.
Journal Name Malaria Journal
Publication Date 2015
Volume Number 14
Issue Number Article No. 191
ISSN 1475-2875   (check CDU catalogue open catalogue search in new window)
Scopus ID 2-s2.0-84929000693
Total Pages 14
Place of Publication United Kingdom
Publisher BioMed Central Ltd.
HERDC Category C1 - Journal Article (DIISR)
Abstract Background
Though essential to the development and evaluation of national malaria control programmes, precise enumeration of the clinical illness burden of malaria in endemic countries remains challenging where local surveillance systems are incomplete. Strategies to infer annual incidence rates from parasite prevalence survey compilations have proven effective in the specific case of Plasmodium falciparum, but have yet to be developed for Plasmodium vivax. Moreover, defining the relationship between P. vivax prevalence and clinical incidence may also allow levels of endemicity to be inferred for areas where the information balance is reversed, that is, incident case numbers are more widely gathered than parasite surveys; both applications ultimately facilitating cartographic estimates of P. vivax transmission intensity and its ensuring disease burden.

Methods
A search for active case detection surveys was conducted and the recorded incidence values were matched to local, contemporary parasite rate measures and classified to geographic zones of differing relapse phenotypes. A hierarchical Bayesian model was fitted to these data to quantify the relationship between prevalence and incidence while accounting for variation among relapse zones.

Results
The model, fitted with 176 concurrently measured P. vivax incidence and prevalence records, was a linear regression of the logarithm of incidence against the logarithm of age-standardized prevalence. Specific relationships for the six relapse zones where data were available were drawn, as well as a pooled overall relationship. The slope of the curves varied among relapse zones; zones with short predicted time to relapse had steeper slopes than those observed to contain long-latency relapse phenotypes.

Conclusions

The fitted relationships, along with appropriate uncertainty metrics, allow for estimates of clinical incidence of known confidence to be made from wherever P. vivax prevalence data are available. This is a prerequisite for cartographic-based inferences about the global burden of morbidity due to P. vivax, which will be used to inform control efforts.
Keywords Malaria
Plasmodim vivax
Epidemiology
Incidence
Prevalance
Model
DOI http://dx.doi.org/10.1186/s12936-015-0706-3   (check subscription with CDU E-Gateway service for CDU Staff and Students  check subscription with CDU E-Gateway in new window)
Additional Notes This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Description for Link Link to CC Attribution 4.0 License
URL https://creativecommons.org/licenses/by/4.0/au


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