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Lead (Pb) is a prevalent environmental toxic metal that may harmfully affect the function of the thyroid gland. Our information about the effects of lead on thyroid function in lead poisoning is limited. The present study aimed to evaluate thyroid function in lead-poisoned patients compared with the healthy group. In this study, two groups of lead poisoning subjects (lead concentrations ≥ 25 μg/dL) (n = 56) (HBLC group) and randomly selected age and gender-matched healthy individuals with lower blood lead concentrations (BLC < 10 μg/dL) (n = 58) (LBLC group) were included. Thyroid function tests, including thyroxine (T4), triiodothyronine (T3), and thyroid-stimulating hormone (TSH) concentration, were measured for each patient in both groups (for the HBLC group, it was taken on admission). The linear regression model was used to investigate the effects of lead poisoning on thyroid function tests. A p-value of less than 0.05 was considered significant. Our study showed no significant difference between the two groups in terms of age and gender. The mean concentration of T3 and TSH in the HBLC group was significantly lower than the LBLC group, but the mean levels of T4 were significantly higher in the HBLC group (p < 0.05). Based on the linear regression model results, the T3 and TSH levels in the LBLC group were significantly higher by 13.86 and 0.43 units than the HBLC group, respectively. The current study results showed that lead poisoning affects thyroid function, reduces TSH, and increases T4., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background and Objectives: Due to COVID-19, various countries introduced lockdowns and limited citizen movements. These restrictions triggered an increased use of digital technologies and platforms by the public. This provides an opportunity for the authorities to capture public perceptions on COVID-19 from social media channels to make informed decisions. The use of social media analytics during pandemics for decision-making, however, is an understudied area of research. Thus, this study aims to generate insights into how social media analytics can assist authorities in pandemic-related policy decisions., Methods: This study involved a social media analysis approach-i.e., systematic geo-Twitter analysis-that contains descriptive, content, sentiment, and spatial analyses. Australian states and territories are selected as the case study context for the empirical investigation. This study collected 96,666 geotagged tweets (originated from Australia between 1 January and 4 May 2020), and analysed 35,969 of them after data cleaning., Results: The findings disclose that: (a) Social media analytics is an efficient approach to capture the attitudes and perceptions of the public during a pandemic; (b) Crowdsourced social media data can guide interventions and decisions of the authorities during a pandemic, and; (c) Effective use of government social media channels can help the public to follow the introduced measures/restrictions., Conclusion: The findings are invaluable for authorities to understand community perceptions and identify communities in needs and demands in a pandemic situation, where authorities are not in a position to conduct direct and lengthily public consultations., Competing Interests: Conflict of interestThe authors declare that they have no known competing financial interests or personal relationships (or any other conflict of interest) that could have appeared to influence the work reported in this paper., (© Springer Nature Switzerland AG 2020.)