Mapping Soil Transmitted Helminths and Schistosomiasis under Uncertainty: A Systematic Review and Critical Appraisal of Evidence

Andrea L Araujo Navas, Nicholas A S Hamm, Ricardo J Soares Magalhães and Alfred Stein

PLOS Neglected Tropical Diseases, 2016, vol. 10, issue 12, 1-28

Abstract: Background: Spatial modelling of STH and schistosomiasis epidemiology is now commonplace. Spatial epidemiological studies help inform decisions regarding the number of people at risk as well as the geographic areas that need to be targeted with mass drug administration; however, limited attention has been given to propagated uncertainties, their interpretation, and consequences for the mapped values. Using currently published literature on the spatial epidemiology of helminth infections we identified: (1) the main uncertainty sources, their definition and quantification and (2) how uncertainty is informative for STH programme managers and scientists working in this domain. Methodology/Principal Findings: We performed a systematic literature search using the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol. We searched Web of Knowledge and PubMed using a combination of uncertainty, geographic and disease terms. A total of 73 papers fulfilled the inclusion criteria for the systematic review. Only 9% of the studies did not address any element of uncertainty, while 91% of studies quantified uncertainty in the predicted morbidity indicators and 23% of studies mapped it. In addition, 57% of the studies quantified uncertainty in the regression coefficients but only 7% incorporated it in the regression response variable (morbidity indicator). Fifty percent of the studies discussed uncertainty in the covariates but did not quantify it. Uncertainty was mostly defined as precision, and quantified using credible intervals by means of Bayesian approaches. Conclusion/Significance: None of the studies considered adequately all sources of uncertainties. We highlighted the need for uncertainty in the morbidity indicator and predictor variable to be incorporated into the modelling framework. Study design and spatial support require further attention and uncertainty associated with Earth observation data should be quantified. Finally, more attention should be given to mapping and interpreting uncertainty, since they are relevant to inform decisions regarding the number of people at risk as well as the geographic areas that need to be targeted with mass drug administration. Author Summary: In recent years spatial modelling studies of schistosome and soil-transmitted helminth infections have become commonplace; however there is no standard framework for uncertainty evaluation and reporting. In this study we aim to identify faults in existing studies and propose a framework for evaluation and reporting. We conducted a systematic review of the literature to identify the gaps in knowledge in relation to how uncertainty is dealt with in existing studies addressing the spatial modelling of helminth infections. It was found that none of the studies considered adequately all sources of uncertainty. Uncertainty in the response variables and covariates should be incorporated into the modelling framework. More attention should be given to mapping and interpreting uncertainty, and to quantify the different sources of uncertainty present in the observed covariates (environmental variables), measured response variable (morbidity indicators), used model and uncertainty representation and interpretation of the predicted morbidity indicators.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pntd00:0005208

DOI: 10.1371/journal.pntd.0005208

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