Modelling and predicting the spatio-temporal spread of cOVID-19 in Italy.

BACKGROUND: The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was first detected in China at the end of 2019 and it has since spread in few months all over the World. Italy was one of the first Western countries who faced the health emergency and is one of the countries most severely affected by the pandemic. The diffusion of Coronavirus disease 2019 (COVID-19) in Italy has followed a peculiar spatial pattern, however the attention of the scientific community has so far focussed almost exclusively on the prediction of the evolution of the disease over time. METHODS: Official freely available data about the number of infected at the finest possible level of spatial areal aggregation (Italian provinces) are used to model the spatio-temporal distribution of COVID-19 infections at local level. An endemic-epidemic time-series mixed-effects generalized linear model for areal disease counts has been implemented to understand and predict spatio-temporal diffusion of the phenomenon. RESULTS: Three subcomponents characterize the fitted model. The first describes the transmission of the illness within provinces; the second accounts for the transmission between nearby provinces; the third is related to the evolution of the disease over time. At the local level, the provinces first concerned by containment measures are those that are not affected by the effects of spatial neighbours. On the other hand, the component accounting for the spatial interaction with surrounding areas is prevalent for provinces that are strongly involved by contagions. Moreover, the proposed model provides good forecasts for the number of infections at local level while controlling for delayed reporting. CONCLUSIONS: A strong evidence is found that strict control measures implemented in some provinces efficiently break contagions and limit the spread to nearby areas. While containment policies may potentially be more effective if planned considering the peculiarities of local territories, the effective and homogeneous enforcement of control measures at national level is needed to prevent the disease control being delayed or missed as a whole. This may also apply at international level where, as it is for the European Union or the United States, the internal border checks among states have largely been abolished.

Assessing the effect of containment measures on the spatio-temporal dynamic of COVID-19 in Italy.

This paper aims at investigating empirically whether and to what extent the containment measures adopted in Italy had an impact in reducing the diffusion of the COVID-19 disease across provinces. For this purpose, we extend the multivariate time-series model for infection counts proposed in Paul and Held (Stat Med 30(10):118-1136, 2011) by augmenting the model specification with B-spline regressors in order to account for complex nonlinear spatio-temporal dynamics in the propagation of the disease. The results of the model estimated on the time series of the number of infections for the Italian provinces show that the containment measures, despite being globally effective in reducing both the spread of contagion and its self-sustaining dynamics, have had nonlinear impacts across provinces. The impact has been relatively stronger in the northern local areas, where the disease occurred earlier and with a greater incidence. This evidence may be explained by the shared popular belief that the contagion was not a close-to-home problem but rather restricted to a few distant northern areas, which, in turn, might have led individuals to adhere less strictly to containment measures and lockdown rules.

Glutamate receptor ligands: synthesis, stereochemistry, and enantiopharmacology of methylated 2-aminoadipic acid analogs.

Homologation and substitution on the carbon backbone of (S)-glutamic acid [(S)-Glu, 1], as well as absolute stereochemistry, are structural parameters of key importance for the pharmacological profile of (S)-Glu receptor ligands. We describe a series of methyl-substituted 2-aminoadipic acid (AA) analogs, and the synthesis, stereochemistry, and enantiopharmacology of 3-methyl-AA (4a-d), 4-methyl-AA (5a-d), 5-methyl-AA (6a-d), and (E)-Delta(4)-5-methyl-AA (7a and 7b) are reported. The compounds were resolved using chiral HPLC and the configurational assignments of the enantiomers were based on X-ray crystallographic analyses, chemical correlation, and CD spectral analyses. The effects of the individual stereoisomers at ionotropic and metabotropic (S)-Glu receptors (iGluRs and mGluRs) were characterized. Compounds with S-configuration at the alpha-carbon generally showed mGluR2 agonist activity of similar or slightly lower potencies than (S)-AA [e.g., EC(50) = 76 microM for (2S,4S)-4-methyl-AA (5a) as compared to EC(50) = 35 microM for (S)-AA]. The position of the methyl substituent had a profound effect on the observed pharmacology, whereas the absolute stereochemistry at the methylated carbon atom had a very limited effect on pharmacology. Structure-activity relationships at iGluRs in the rat cortical wedge preparation showed a complex pattern, some compounds being NMDA receptor agonists [e.g., EC(50) =110 microM for (2S,5RS)-5-methyl-AA (6a,b)] and some compounds showing NMDA receptor antagonist effects [e.g., IC(50) = 300 microM for (2R,4S)-4-methyl-AA (5d)]. The two unsaturated analogs (S)- (7a) and (R)-(E)-Delta(4)-5-methyl-AA (7b) turned out to be a weak AMPA receptor agonist and a weak mixed NMDA/AMPA receptor antagonist, respectively.