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The COVID-19 pandemic has affected many industries, and reports indicate that this includes the illicit drug market. Recent research suggests that the homeless are particularly vulnerable during the pandemic, and the UK Government has acted to house rough sleepers. Research is scarce regarding homeless people’s experiences of the illicit drug market. This study aims to explore homeless people’s experiences of the drug supply in the UK during COVID-19.

Eight homeless people who use illicit drugs, residing in hostels for homeless people in Southampton, participated in semi-structured one-on-one telephone-based interviews.

A thematic analysis revealed five themes: availability of drugs, presence of dealers, quality of drugs, finances and personal experiences. Participants reported varying experiences of the drug supply, with lockdown measures expressed as the main reason for reduced supplies, as users found it difficult to find dealers and generate income for purchasing drugs.

The results may lack generalisability to the wider population, such as rough sleepers and drug dealers, suggesting a need for further research into people’s experiences of the drug supply during COVID-19. Research on this topic could be more in-depth through the use of research methods that are convenient for the homeless population.

Services should invest in harm reduction services and encourage homeless people who use drugs to engage in substitution treatment. Homeless services should provide psychological support for homeless people who use drugs.

The changes in homeless people’s behaviour following the pandemic may have implications for their interactions with the rest of society (e.g. begging in town centres may reduce). These changes in behaviour may also change the way society can best support homeless people.

The results are partially consistent with other research findings about the illicit drug supply; however, they also suggest that some individuals experienced minimal change in the illicit drug supply.

The continuous increase of energy demands is a critical worldwide matter. Jordan’s household sector accounts for 44% of overall electricity usage annually. This study aims to use artificial neural networks (ANNs) to assess and forecast electricity usage and demands in Jordan’s residential sector.

Four parameters are evaluated throughout the analysis, namely, population (P), income level (IL), electricity unit price (E$) and fuel unit price (F$). Data on electricity usage and independent factors are gathered from government and literature sources from 1985 to 2020. Several networks are analyzed and optimized for the ANN in terms of root mean square error, mean absolute percentage error and coefficient of determination (R²).

The predictions of this model are validated and compared with literature-reported models. The results of this investigation showed that the electricity demand of the Jordanian household sector is mainly driven by the population and the fuel price. Finally, time series analysis approach is incorporated to forecast the electricity demands in Jordan’s residential sector for the next decade.

The paper provides useful recommendations and suggestions for the decision-makers in the country for dynamic planning for future resource policies in the household sector.