A general contextual analysis of endemic infectious disease risk in Kenya

de Glanville, WA, Thomas, Lian, Bronsvoort, BM, Wardrop, N, Wamae, NC, Kariuki, S and Fevre, Eric (2018) A general contextual analysis of endemic infectious disease risk in Kenya. [Data Collection]

Data Catalogue DOI: 10.17638/datacat.liverpool.ac.uk/448

Description

A general contextual analysis of endemic infectious disease risk in Kenya de Glanville W.A.1,2 #, Thomas L.F.2, Cook E.A.J.1,2, Bronsvoort B.M.3, Wardrop N.4‡, Wamae N.C.5, Kariuki S.6, Fèvre E.M.2,7* 1Centre for Immunity, Infection and Evolution, Institute for Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3JT, UK 2 International Livestock Research Institute, Old Naivasha Road, PO BOX 30709, 00100-Nairobi, Kenya 3 The Epidemiology, Economics and Risk Assessment Group, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, Midlothian, EH25 9RG, UK 4 Geography and Environment, University of Southampton, Highfield Campus, University Road, Southampton, SO17 1BJ, UK 5 School of Pharmacy and Health Sciences, United States International Research University, PO Box 14634-00800, Nairobi, Kenya 6 Centre for Microbiology Research, Kenya Medical Research Institute, PO Box 19464-00200, Nairobi, Kenya 7 Institute of Infection and Global Health, University of Liverpool, Leahurst Campus, Neston, CH64 7TE, UK *Corresponding author # Current address: Boyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, United Kingdom, G12 8QQ; ‡ Current address: Department for International Development, Abercrombie House, Eaglesham Road, East Kilbride, United Kingdom, G75 8EA Abstract Quantification of the effect of context in shaping disparities in disease risk provides a simple yet underutilised method for identifying health inequalities. We derived estimates of general contextual effect on the risk of individual infection from multi-level regression models for a range of endemic pathogens in a rural population in western Kenya. Measures of within-group correlation and between-group heterogeneity were calculated for household, sublocation and constituency clusters. The importance of place-based contextual effects was further assessed using the spatial scan statistic. Individuals living in the same household showed correlation in risk of infection for all pathogens under study, and this was highest for the environmentally transmitted parasites. Heterogeneities in risk between sublocations was largest for Schistosoma mansoni and Taenia solium cysticercosis and between constituencies for S. mansoni, Trichuris trichiura, Ascaris lumbricoides and HIV. Large, overlapping spatial clusters were observed for these four pathogens, as well as for taeniasis due to T. solium and/or T. saginata. Substantial heterogeneity in individual infectious disease risk exists in this rural farming community. Interventions targeted at those groups and areas at greatest risk would be expected to reduce both the overall infectious disease prevalence and important health inequalities in this population.

Keywords:

Social epidemiology; multilevel analysis; contextual; clustering; health inequality

Divisions:

Faculty of Health and Life Sciences

Depositing User:

Eric Fevre

Date Deposited:

14 Feb 2018 14:46

Last Modified:

14 Feb 2018 14:46

DOI:

10.17638/datacat.liverpool.ac.uk/448