Fine resolution mapping of population age-structures for health and development applications

The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings

How do risk preferences relate to malaria care-seeking behavior and the acceptability of a new health technology in Nigeria?

BACKGROUND: To reduce the burden of disease from malaria, innovative approaches are needed to engender behavior change. One unobservable, but fundamental trait—preferences for risk—may influence individuals’ willingness to adopt new health technologies. We explore the association of risk preferences with malaria care-seeking behavior and the acceptability of malaria rapid diagnostic tests (RDTs) to inform RDT scale-up plans. METHODS: In Oyo State, Nigeria, adult customers purchasing anti-malarial medications at selected drug shops took surveys and received an RDT as they exited. After an initial risk preference assessment via a simple lottery game choice, individuals were given their RDT result and treatment advice, and called four days later to assess treatment adherence. We used bivariable and multivariable regression analysis to assess the association of risk game choices with malaria care-seeking behaviors and RDT acceptability. RESULTS: Of 448 respondents, 63.2% chose the lottery game with zero variance in expected payout, 27.9% chose the game with low variance, and 8.9% chose the game with high variance. Compared to participants who chose lower variance games, individuals choosing higher variance games were older, less educated, more likely to be male, and were more likely to patronize lower quality drug shops, seek care immediately, and report complete disability due to their illness. In contrast, individuals choosing lower variance games were more likely to follow the correct treatment directions and were more likely to report an increase in their willingness to pay for an RDT compared to other risk groups, our two measures of RDT acceptability. Differences in estimated associations between risk game choices and selected care-seeking behaviors remained after controlling sociodemographic confounders. CONCLUSIONS: The uptake of health diagnostic information in terms of translating the RDT experience into willingness to pay for an RDT and treatment adherence to test results may vary according to risk preferences. Hence, health promotion communications may want to be crafted bearing in mind differences in uptake among people of different risk preferences to encourage wider RDT adoption and more rational malaria treatment. Estimates will serve as the basis for power calculations for an expanded study