Background and aims: Wastewater-based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to (i) assess spatial and temporal trends of population-normalized mass loads of benzoylecgonine, amphetamine, methamphetamine, and 3,4-methylenedioxymethamphetamine (MDMA) in raw wastewater over seven years (2011-2017); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city. Design: Analysis of daily composite raw wastewater samples collected over one week per year from 2011 to 2017. Setting: Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries. Methods: Parent substances (amphetamine, methamphetamine, and MDMA) and the metabolites of cocaine (benzoylecgonine) and of Δ9-tetrahydrocannabinol (11-nor-9-carboxy-Δ9-tetrahydrocannabinol) were measured in wastewater using liquid chromatography-tandem mass spectrometry. Daily mass loads (mg/day) were normalized to catchment population (mg/1000 people/day) and converted to the number of combined doses consumed per day. Spatial differences were assessed worldwide, and temporal trends were discerned at European level by comparing 2011-2013 drug loads versus 2014-2017 loads. Findings: Benzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA, and methamphetamine in the east and the north-centre of Europe. In other continents methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. Over the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge. Conclusions: The analysis of wastewater to quantify drug loads provides updated and objective estimates of drug use that globally correspond to prevalence and seizure data. Additional strengths of this approach are its flexibility for application at different spatial and temporal scales, and the identification of consumption trends nearly in real time.