Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection

Osei, Frank Badu; Stein, Alfred; Ofosu, Anthony

doi:10.3390/ijerph16030339

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Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection

Frank Badu Osei

^1,*

Alfred Stein

and

Anthony Ofosu

Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NB Enschede, The Netherlands

Policy, Planning, Monitoring and Evaluation (PPME)–Ghana Health Service; Accra, Ghana

Author to whom correspondence should be addressed.

Int. J. Environ. Res. Public Health 2019, 16(3), 339; https://doi.org/10.3390/ijerph16030339

Received: 13 November 2018 / Revised: 15 January 2019 / Accepted: 18 January 2019 / Published: 26 January 2019

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Abstract

Understanding the spatially varying effects of demographic factors on the spatio-temporal variation of intestinal parasites infections is important for public health intervention and monitoring. This paper presents a hierarchical Bayesian spatially varying coefficient model to evaluate the effects demographic factors on intestinal parasites morbidities in Ghana. The modeling relied on morbidity data collected by the District Health Information Management Systems. We developed Poisson and Poisson-gamma spatially varying coefficient models. We used the demographic factors, unsafe drinking water, unsafe toilet, and unsafe liquid waste disposal as model covariates. The models were fitted using the integrated nested Laplace approximations (INLA). The overall risk of intestinal parasites infection was estimated to be 10.9 per 100 people with a wide spatial variation in the district-specific posterior risk estimates. Substantial spatial variation of increasing multiplicative effects of unsafe drinking water, unsafe toilet, and unsafe liquid waste disposal occurs on the variation of intestinal parasites risk. The structured residual spatial variation widely dominates the unstructured component, suggesting that the unaccounted-for risk factors are spatially continuous in nature. The study concludes that both the spatial distribution of the posterior risk and the associated exceedance probability maps are essential for monitoring and control of intestinal parasites. View Full-Text

Keywords: intestinal parasites; spatio-temporal; Poisson-gamma; Bayesian; integrated nested Laplace approximations

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Osei, F.B.; Stein, A.; Ofosu, A. Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection. Int. J. Environ. Res. Public Health 2019, 16, 339. https://doi.org/10.3390/ijerph16030339

AMA Style

Osei FB, Stein A, Ofosu A. Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection. International Journal of Environmental Research and Public Health. 2019; 16(3):339. https://doi.org/10.3390/ijerph16030339

Chicago/Turabian Style

Osei, Frank B., Alfred Stein, and Anthony Ofosu. 2019. "Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection" International Journal of Environmental Research and Public Health 16, no. 3: 339. https://doi.org/10.3390/ijerph16030339

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Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection

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