New publication: An urban-to-rural continuum of malaria risk: new analytic approaches characterize patterns in Malawi
12 years in the making! Our new paper from partners at the University of Michigan and the #Malawi College of Medicine on new approaches to defining urban and rural environments in the context of malaria risk is now out in #Malaria Journal.
It was the last chapter in my dissertation to be published (all the rest were published when I was still in grad school.)Short version: malaria is complicated and really local. Malaria transmits poorly in urban and environments and well in rural environments. There’s urban like spaces in “rural” areas and rural-like spaces in “urban” areas, demanding a more nuanced view of what those terms really mean.
We know that malaria is a “rural” problem, but not all “rural” spaces are the same. Even in the country, there are “urban like” spaces and in “rural like” spaces even in the largest cities in Sub-Saharan Africa. Could those spaces impact malaria risk? If so, shouldn’t we redefine what we mean by urban vs. rural to inform intervention strategies to better target resources?
Here, we combine GIS and statistical methods with a house to house malaria survey in Malawi to create and test a new composite index of urbanicity and apply that to create a more nuanced risk map.
The urban–rural designation has been an important risk factor in infectious disease epidemiology. Many studies rely on a politically determined dichotomization of rural versus urban spaces, which fails to capture the complex mosaic of infrastructural, social and environmental factors driving risk. Such evaluation is especially important for Plasmodium transmission and malaria disease. To improve targeting of anti-malarial interventions, a continuous composite measure of urbanicity using spatially-referenced data was developed to evaluate household-level malaria risk from a house-to-house survey of children in Malawi.
Children from 7564 households from 8 districts in Malawi were tested for presence of Plasmodium parasites through finger-prick blood sampling and slide microscopy. A survey questionnaire was administered and latitude and longitude coordinates were recorded for each household. Distances from households to features associated with high and low levels of development (health facilities, roads, rivers, lakes) and population density were used to produce a principal component analysis (PCA)-based composite measure for all centroid locations of a fine geo-spatial grid covering Malawi. Regression methods were used to test associations of the urbanicity measure against Plasmodium infection status and to predict parasitaemia risk for all locations in Malawi.
Infection probability declined with increasing urbanicity. The new urbanicity metric was more predictive than either a governmentally defined rural/urban dichotomous variable or a population density variable. One reason for this was that 23% of cells within politically defined rural areas exhibited lower risk, more like those normally associated with “urban” locations.
Mark WilsonDon MathangaVeronica Berrocal#malaria#globalhealth#publichealth#GIS#spatialanalysis#maps#Malawi#Africa#Plasmodium#surveys#health#medicine#environmental#data