The joint determination of morbidity and vaccination in the spatiotemporal epidemiology of COVID-19.

This paper examines the mutual dependence between COVID-19 morbidity and vaccination rollout. A theory of endogenous immunization is proposed in which the decision to become vaccinated varies directly with the risks of contagion, and the public self-selects into self-protection. Hence, COVID-19 morbidity varies inversely with vaccination rollout, and vaccination rollout varies directly with COVID-19 morbidity. The paper leverages the natural sequencing between morbidity and immunization to identify the causal order in the dynamics of this relationship. A modified SIR model is estimated using spatial econometric methods for weekly panel data for Israel at a high level of spatial granularity. Connectivity between spatial units is measured using physical proximity and a unique mobility-based measure. Spatiotemporal models for morbidity and vaccination rollout show that not only does morbidity vary inversely with vaccination rollout, vaccination rollout varies directly with morbidity. The utility of the model for public health policy targeting, is highlighted.

Predicting the stability and growth of acoustic neuromas.

HYPOTHESIS: Acoustic neuroma (AN) growth can be predicted using information gathered at the time the AN is initially diagnosed. BACKGROUND: Knowledge of AN growth is essential for treatment planning. Previous studies have not been able to identify predictors of AN growth. METHODS: A multivariate statistical analysis was carried out using two independent sets of secondary data from the natural histories of ANs. Logit, probit, and censored regression techniques were used to test alternative hypotheses of AN growth between the initial and second measurements, as well as between subsequent measurements. RESULTS: In one data set, AN growth between the first and second measurements varied significantly and inversely with age. It was much greater if the AN was on the left side and if there were more symptoms. It did not depend on initial tumor size or the measurement interval. In the other data set, AN growth was also greater for left-sided tumors and depended on symptoms. However, it varied inversely with tumor size and directly with the measurement interval. There was also some evidence that tumors that were more stable between the initial two measurements were more likely to remain stable between the second and third measurements. However, this did not apply to AN growth between the third and fourth measurements. CONCLUSIONS: AN growth is predictable but the prediction model is not apparently independent of the policy for selecting ANs for conservative management.

Testing Gateway Theory: do cigarette prices affect illicit drug use?

We test the causal Gateway Theory of drug use dynamics by way of a natural experiment. We randomize cigarette smoking by birth cohort and cigarette prices. We use data for Israel to show that while cigarette smoking causes cannabis use, the evidence that cannabis use causes hard drug use is much weaker. These results are based on various econometric methodologies including two-stage logit (2SL), bivariate probit, and frailty analysis for survival data.