Statistical Methods for Linking Health, Exposure, and Hazards

The Environmental Public Health Tracking Network (EPHTN) proposes to link environmental hazards and exposures to health outcomes. Statistical methods used in case–control and cohort studies to link health outcomes to individual exposure estimates are well developed. However, reliable exposure estimates for many contaminants are not available at the individual level. In these cases, exposure/hazard data are often aggregated over a geographic area, and ecologic models are used to relate health outcome and exposure/hazard. Ecologic models are not without limitations in interpretation. EPHTN data are characteristic of much information currently being collected—they are multivariate, with many predictors and response variables, often aggregated over geographic regions (small and large) and correlated in space and/or time. The methods to model trends in space and time, handle correlation structures in the data, estimate effects, test hypotheses, and predict future outcomes are relatively new and without extensive application in environmental public health. In this article we outline a tiered approach to data analysis for EPHTN and review the use of standard methods for relating exposure/hazards, disease mapping and clustering techniques, Bayesian approaches, Markov chain Monte Carlo methods for estimation of posterior parameters, and geostatistical methods. The advantages and limitations of these methods are discussed

Improving malaria control in West Africa: interruption of transmission as a paradigm shift.

With the paradigm shift from the reduction of morbidity and mortality to the interruption of transmission, the focus of malaria control broadens from symptomatic infections in children ≤5 years of age to include asymptomatic infections in older children and adults. In addition, as control efforts intensify and the number of interventions increases, there will be decreases in prevalence, incidence and transmission with additional decreases in morbidity and mortality. Expected secondary consequences of these changes include upward shifts in the peak ages for infection (parasitemia) and disease, increases in the ages for acquisition of antiparasite humoral and cellular immune responses and increases in false-negative blood smears and rapid diagnostic tests. Strategies to monitor these changes must include: (1) studies of the entire population (that are not restricted to children ≤5 or ≤10 years of age), (2) study sites in both cities and rural areas (because of increasing urbanization across sub-Saharan Africa) and (3) innovative strategies for surveillance as the prevalence of infection decreases and the frequency of false-negative smears and rapid diagnostic tests increases