From Taxonomic Accuracy to Toxin Naming: A Welcome Dialogue in Toxicon

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  From Taxonomic Accuracy to Toxin Naming: A Welcome Dialogue in Toxicon By Luis A. Roque | Arácnido Taxonomy When I submitted my correspondence, “When tarantula venom comes from a misnamed spider: The importance of taxonomic accuracy in theraphosid toxinology,” to Toxicon , I hoped it would encourage a broader conversation. The purpose was to draw attention to a problem that benefits from the experience of people working across taxonomy, venom research, and biological databases. Dr. Volker Herzig’s response, “The need for a unified toxin nomenclature for consistent toxin naming,” is precisely the kind of engagement I hoped to see. His contribution acknowledges the importance of identifying venom-source organisms accurately while bringing another essential question into focus: How do we maintain continuity in toxin names when taxonomy and our understanding of toxin function change? Two connected challenges My original correspondence focused on the biological source of venom. In t...

A Hybrid Approach Based on Seasonal Autoregressive Integrated Moving Average and Neural Network Autoregressive Models to Predict Scorpion Sting Incidence in El Oued Province, Algeria, From 2005 to 2020

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A Hybrid Approach Based on Seasonal Autoregressive Integrated Moving Average and Neural Network Autoregressive Models to Predict Scorpion Sting Incidence in El Oued Province, Algeria, From 2005 to 2020

In general, 96909 scorpion stings were recorded in El Oued province from 2005-2020. The incidence rate experienced a gradual decrease until 2012 and since then slight fluctuations have been noted. Scorpion stings occurred throughout the year with peaks in September followed by July and August and troughs in December and January. Sting cases were not evenly distributed across demographic groups; the most affected age group was 15-49 years, and males were more likely to be stung. Of the reported deaths, more than half were in children 15 and younger. Scorpion’s activity was conditioned by climate factors, and temperature had the highest effect. The SARIMA(2,0,2)(1,1,1)12, NNAR(1,1,2)12, and SARIMA(2,0,2)(1,1,1)12-NNAR(1,1,2)12 were selected as the best-fitting models. The RMSE, MAE, and MAPE of the SARIMA and SARIMA-NNAR models were lower than those of the NNAR model in fitting and forecasting; however, the NNAR model could produce better predictive accuracy.

Zenia S, L’Hadj M, Selmane S. A hybrid approach based on seasonal autoregressive integrated moving average and neural network autoregressive models to predict scorpion sting incidence in El Oued province, algeria, from 2005 to 2020. J Res Health Sci. 2023; 23(3):e00586. doi:10.34172/jrhs.2023.121