title: Geography and social distribution of malaria in Indonesian Papua: a cross-sectional study.
abstract: BACKGROUND
  Despite being one of the world's most affected regions, only little is known about the social and spatial distributions of malaria in Indonesian Papua. Existing studies tend to be descriptive in nature; their inferences are prone to confounding and selection biases. At the same time, there remains limited malaria-cartographic activity in the region. Analysing a subset (N = 22,643) of the National Basic Health Research 2007 dataset (N = 987,205), this paper aims to quantify the district-specific risk of malaria in Papua and to understand how socio-demographic/economic factors measured at individual and district levels are associated with individual's probability of contracting the disease.
  
  
  METHODS
  We adopt a Bayesian hierarchical logistic regression model that accommodates not only the nesting of individuals within the island's 27 administrative units but also the spatial autocorrelation among these locations. Both individual and contextual characteristics are included as predictors in the model; a normal conditional autoregressive prior and an exchangeable one are assigned to the random effects. Robustness is then assessed through sensitivity analyses using alternative hyperpriors.
  
  
  RESULTS
  We find that rural Papuans as well as those who live in poor, densely forested, lowland districts are at a higher risk of infection than their counterparts. We also find age and gender differentials in malaria prevalence, if only to a small degree. Nine districts are estimated to have higher-than-expected malaria risks; the extent of spatial variation on the island remains notable even after accounting for socio-demographic/economic risk factors.
  
  
  CONCLUSIONS
  Although we show that malaria is geography-dependent in Indonesian Papua, it is also a disease of poverty. This means that malaria eradication requires not only biological (proximal) interventions but also social (distal) ones.
authors.affiliation: Cathie Marsh Institute for Social Research (CMIST), University Manchester, Oxford Road, Manchester, M13 9PL, UK. wulung.hanandita@postgrad.manchester.ac.uk.
authors.forename: Wulung
authors.initials: W
authors.lastname: Hanandita
authors.affiliation: Cathie Marsh Institute for Social Research (CMIST), University Manchester, Oxford Road, Manchester, M13 9PL, UK.
authors.forename: Gindo
authors.initials: G
authors.lastname: Tampubolon
mesh_terms: D000293:Adolescent; D000328:Adult; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D062305:Geographic Mapping; D006801:Humans; D007214:Indonesia / Q000453:epidemiology; D007223:Infant; D007231:Infant, Newborn; D008288:Malaria / Q000175:diagnosis / Q000191:economics* / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D011203:Poverty / Q000191:economics* / Q000706:statistics & numerical data*; D012424:Rural Population / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D055815:Young Adult
keywords: Bayesian; Indonesia; Malaria; Map; Multilevel; Papua; Spatial